AppWrap September 2026

16.09 One NZ has slashed mobile service provisioning times from a 10 day process to under 10 minutes, using an orchestration layer combining AI, automation and human decision-making. The telco says the system has enabled it to streamline workflows across multiple disconnected systems while maintaining governance, visibility and control.

14.09 ’Significantly flawed assumptions’ saw Immigration NZ overestimate the benefits from its $336m Our Future Services transformation project by $134m. Savings of $453m had been touted. The updated figures mean the project, which has been paused, would cost more than it would save RNZ reports.

11.09 Kiwi restaurant booking platform First Table has raised $12m to fund ‘going deeper’ in New Zealand alongside international expansion. The round was backed by existing investors including Altered Capital and Invest South, alongside new investors K1W1 and Icehouse ventures, the company says.

10.09 Police are investigating after sample material purported to be Zenith Technology company data was published online. Sensitive data relating to clinical trials run by the Contract Research Organisation are among the data allegedly stolen. ZenTech says it is responding to the cyber incident, and has engaged independent cyber security experts. Health NZ says there  is no impact to its digital systems.

10.09 Police are investigating after files relating to clinical trials, and including sensitive health data, were allegedly taken from ZenTech about a week ago. Stuff reports a ransomware group has  publicly claimed responsibility and gave ZenTech and alleged victims in other countries a deadline to negotiate, saying it wants ‘nothing but financial rewards’.

09.09 Labour has released a wide-ranging technology policy that would establish an Office of AI, introduce copyright protections for creators and create new rules for data centres and online safety. RNZ reports the election promises also see the regulator having a wider mandate than overseeing a social media ban for under-16s and the public service being given ‘clear expectations’ around AI.

09.09 Cyber attackers are beginning to use AI systems capable of automatically scanning for vulnerabilities, troubleshooting problems and harvesting credentials with minimal human input, the Google Threat Intelligence Group says. It says AI is accelerating the speed and scale of cyber attacks, potentially reducing the time organisations have to detect and respond to threats.

08.09 Non-profit security organisation Shadowserver Foundation says 56 Exchange servers in New Zealand remained exposed to CVE-2026-62911 as of August 31, three weeks after Microsoft issued a fix. The Australian Signals Directorate has issued warnings urging organisations to running the outdated Exchange versions to take action or segment their networks if they cannot replace them, TechBest reports.

07.09 More than half of New Zealand’s government agencies have failed to implement DMARC email security standards. Proofpoint says its analysis of mor ethna 200 primary organisations found 97 percent have adopted DMARC but only 50 percent have implemented the required ‘Reject’ policy – the strongest level of DMARC protection. Agencies are required to implement DMARC at the reject level from October.

07.09 The personal data of more than one million students, parents, guardians and school staff in Australia and New Zealand has been exposed through an attack on online learning platform Mathspace. 7News reports names, email addresses and user IDs were among the information affected, along with Mathspace staff records. Mathspace says customer passwords, single sign-on tokens and other customer authentication credentials were not exposed.

AppWrap August 2026

29.08 Datacom’s 2026 State of AI Index shows AI adoption has hit 91 percent in New Zealand – but most organisations are yet to scale beyond the exploratory and implementation stages. In bad news the report shows those using AI to transform core operations has fallen from 8% in 2025 to just 4% with widespread use not translating into organisation-wide change.

27.08 One NZ and 2degrees have proposed combining radio access networks into a new, jointly-owned wholesale business, currently dubbed RanCo. The proposal, which is subject to approvals, including from the NZ Commerce Commission and OIO, would avoid duplication and enable more efficient use of existing infrastructure, One NZ says. The two companies would continue to separately own and invest in the parts of their businesses that drive competition and differentiation.

27.08 Xero investors have voted against adopting the board’s decision to give CEO Sukhinder Singh Cassidy a 22 percent pay rise – lifting her target remuneration to US$18 million, the majority through long-term equity awards split between performance and service, Forbes Australia reports.  The move comes amid ongoing struggles for Xero’s stock prices, which have been halved in the past year. Under NZ law the board does not require shareholder approval, but put it forward to an advisory vote as ‘a matter of good governance’.

27.08 Meta has agreed to a landmark US$18 billion settlement in a US federal case accusing it of endangering children, with a slew of new safety features now required to its platforms including Instagram and Facebook. Al Jazeera reports those changes range from night curfews to two-hour usage limits for US users under the age of 18. Other countries are also taking regulatory action against Meta and other social media platforms.

26.08 An RFI shows Health New Zealand is lacking a consistent consolidated view of the health and performance of its critical digital systems, limiting its ability to detect and respond to service disruptions early. eHealth News reports the RFI is seeking information on how it can improve visibility of critical digital services, enable earlier detection of issues and support faster diagnosis and resolution of service disruptions. The agency has experienced a number of outages this year.

21.08 New MBIE figures show open banking is gaining traction with the number of monthly payments made using regulated open banking technologies increasing from 294,000 transactions worth $92 million in May to more than 408,000 transactions worth $130m in July, the agency says. MBIE is taking over responsibility from Payments NZ for maintaining and developing regulated open banking standards.

20.08 The National Cyber Security Centre says 92 cyber security incidents in the quarter to June 2026 were triaged for specialist technical support because of their potential national significance – up from 77 the previous quarter. The agency responded to 1,129 incident reports in the quarter, up from 1,164 in the first quarter of the year. NCSC says while overall reporting volumes remained steady, the number of incidents with potential to cause wider harm has increased. Reported direct financial losses were down 52 percent to $2.7m, with scams and fraud returning to the top as the most commonly reported incident.

20.08 Spark’s IT services revenue dropped 10.3 percent to $104m on lower project activity in the subdued economic environment and the ongoing migration of legacy services in FY26. Cloud revenue remained flat at $233m, with a 20 percent growth in public cloud offset by the transition away from higher margin private cloud. Broadband was also down with business connectivity down 9.9 percent. In July the company announced a strategic review into its Digital Services division which it says has been identified as ‘outside core operations’. Mobile revenue as up and the company reported a six percent increase in overall revenue to $3.9 billion.

18.08 Datagrid has begun ‘horizontal works’ on its Makarewa site which will be home to the country’s largest data centre. HEB Construction is handling the works, which include creating a six-metre-high bund to reduce the campus’ visual and noise footprint. The foundation platform for the data centre, cable landing station and power substation are expected to be completed by the end of the year, Datagrid says.

18.08 The Reserve Bank of New Zealand has launched public consultation on ‘issues’ it has identified in the payments system, which it says is outdated and does not meet international best practice for modern, faster, retail payment systems. “Given the scale of payments systems, even small improvements in their efficiency can lift national productivity, enhance the global competitiveness of local businesses and strengthen economic resilience’ the RBNZ says. It has been charged with leading the delivery of a strategy for payments modernisation. Consultation is open until 27 October 2026.

13.08 The NZSIS is warning that geopolitical uncertainty has intensified national security challenges for New Zealand, with both the public and private sector being targeted by foreign states and their proxies to gain access to critical assets including IP and innovative technology. The annual New Zealand Security Threat Environment report says rapid advances in technology are constantly changing the nature of security threats, with hostile states and violent extremist actors using GenAI capabilities to create and spread content advancing their ideological interests, and AI amplifying polarising narratives and hiding the source of content.

12.08 Halter has logged a significant jump in revenue in the nine months to 31 December 2025 to hit $98.1 million – up from $71.0 million for the year ended 31 March 2025. The company, which is transitioning to a December financial year end in keeping with its US parent, reported an after-tax profit of $2.6 million for the nine-month period according to Companies Office records. Earlier this year it reached a US$2b valuation following a $220m Series E funding round. The records show subscription and instalment income accounted for around half of total revenue with the remainder coming from services to the US parent.

10.08 Contact Energy and CDC Data Centres are ‘exploring’ a potential 250MW data centre at Stratford in Taranaki, near the site of Contact’s gas power plant which was retired earlier this year, the companies say. Electricity would be supplied under long-term contract, supported by new generation from Contact’s 11 TWh pipeline of options. A joint venture between Contact and Lightsource bp is also progressing an option for a 150MW solar farm near the site.

AppWrap July 2026

29 Hawke’s Bay manufacturer Hawke Technology has seen a surge in global demand for its robotics for the apple industry. Fifty apple packers have already been installed in Washington, with another 250 on order, RNZ reports.

28.07 TikTok apparently generated $1.2 billion in GDP and supported over 9,700 jobs in New Zealand last year, making it the latest foreign tech company to discover it is personally responsible for a surprisingly large chunk of the economy. The figures come from a TikTok sponsored report by Infometrics.

27.07 Spark is restructuring its business, splitting into two divisions – Connectivity (core) which will focus on consumer mobile, broadband, business connectivity, including managed services, and Digital Services covering IT services and cloud. Spark says the new structure enhances end-to-end accountability and is designed to sharpen execution and accelerate progress towards Spark’s FY30 ambitions. Analysts have speculated that the restructure and a strategic review of its digital services division now underway could signal plans for a sale of the IT services business.

23.07 Hospitals across the Waikato were knocked offline for 11 hours this week after a connection problem with the data centre, resulting in some appointments and theatre cases being deferred. RNZ reports health experts blame years of underinvestment in health IT and say the problem will not be a quick fix.

16.07 Australian neocloud SharonAI has inked a US$1.32 billion deal  to deploy its first AI factory in New Zealand, for an unnamed ‘global AI lab’. The five year deal will see SharonAI deploying cloud computing capacity across data centre infrastructure in New Zealand, with revenue from the contract expected to commence in the first half of 2027 the company says.

14.07 New Zealand’s National Cyber Security Centre and other five eyes agencies have issued a joint warning that Russian state-sponsored actors continue to exploit poorly configured and vulnerable routers, targeting sectors including communications, energy, financial services, government and healthcare. Organisations are being urged to tighten router security, upgrade to SNMPv3 and disable insecure legacy configurations to reduce risk of compromise.

13.07 Kiwi AI spatial intelligence platform company Hyades has raised $1.5m in seed capital from investors including Allbirds co-founder Tim Brown, Stephen Tindall and Icehouse Ventures. The $1.5m includes a $400,000 MBIE R&D grant. Hyades’ platform converts geospatial data from disparate sources into a single machine learning ready format, with use cases including insurance risk modelling, B2Bnews reports.

11.07 Meta has abruptly pulled a controversial AI tool which enabled people to create fake images from user content on Instagram. The feature, part of the Muse Image rollout, quickly sparked blowback due to privacy concerns as anyone with a public account could have their likeness used without their permission or knowledge, the BBC reports.

09.07 The government has withdrawn plans to ban cryptocurrency ATMs and will instead establish regulation making powers enabling the government to cap or restrict cash transactions for virtual assets, 1news reports.

08.07 Datacom Group has recorded revenue of $1.58 billion for the year ending 31 March 2026, up from $1.48b a year earlier. Company records show net profit dropped from $37 million to $20 million.

08.07 CDC Data Centres NZ saw significant increases in revenue and gross profit in the year to 31 March 2026, but logged a $87.7 million loss on the back of higher financing costs and property write-downs. The company’s financial records show revenue jumped 52 percent to $134.5 million.

07.07 ACC has completed a migration of its core claims, payments and provider functions to a cloud-based platform. ACC says the program took two years but was completed on schedule.

07.07 A hacker is selling what they claim is live Teletrac Navman telemetry data from almost 3,000 Australian and New Zealand organisations. CyberDaily reports the hacker claims to have exfiltrated continuous real-time GPS tracking data for 2,988 customer companies across A/NZ, over a 48 hour period, with the data including emails and mobile phone details for drivers, driver’s licenses and vehicle registration details.

07.07 The Tech Users Association of New Zealand (Tuanz) is advocating for a shift to ‘active agency’ in data use, pushing organisations to move away from passive consent models such as long – unread – privacy policies. The initiative is part of Tuanz’ 2026 policy program. It’s calling for the government and industry to adopt a standard for explainable AI, adopt standardised ‘data nutrition labels’ allowing consumers to compare data practices at a glance and enable true individual control though expansion of the Consumer Data Right, while also upholding Māori data sovereignty.

03.07 Immigration NZ’s $336m Our Future Services visa processing rebuild, which began last year, has failed to meet its first stage goals, RNZ reports.

02.07 A review of the digital revamp of government services says investment is fragmented with duplication and limited coordination, and the key Digital Delivery Agency has ‘limited influence’ over key decision on funding design and procurement, RNZ reports. A reset has been signalled.

02.07 Google Maps has gained a Kiwi voice – complete with Kiwi accent and the ability to accurately pronounce Māori place names. Google says it partnered with the Māori Language Commission to ensure the voice, which starts rolling out today, uses correct pronunciation.

AppWrap June 2026

29.06 Rocket Lab is buying satellite operator Iridium in a US$8b deal in a move designed to create a fully integrated space powerhouse and take on SpaceX with its Starlink service. The move takes Rocket Lab towards becoming a satellite comms and services company as well as a launch provider and manufacturer. Rocket Lab founder Peter Beck says marrying Iridium’s infrastructure and highly sought-after spectrum with Rocket Lab’s launch and manufacturing capabilities provides capability to unlock ‘entirely new markets’.

23.06 The National Cyber Security Centre has joined other Five Eyes partners in warning government and corporate leaders that swift action is required to remain ahead of the increased risk from AI. The agencies are warning leaders to understand and assess risk, readiness and accountability, prioritise foundational cyber security practices and controls, empower cyber leaders with authority and resources and stay actively engaged. Their warning includes practical actions which while not new are now deemed ‘urgent’ by the agencies including reducing attack surfaces, accelerating patching and limiting who can access critical systems.

23.06 The Tech Users Association of NZ is calling for urgent, coordinated investment in home-grown digital capability, including mandating tech upskilling in the core curriculum – alongside reading and mathematics – incentivising home grown capability and digital apprenticeships and encouraging diverse pathways. The industry body’s Education to Employment policy statement also calls for government-backed financial incentives to lower the barrier to entry for SMEs to improve their digital skills and cyber security defences.

22.06 Kiwi customer service chatbot maker Ambit AI has been placed in liquidation, with Grant Thornton appointed as liquidators. The company defaulted on a Callaghan Innovation load. ChatGPT has been blamed.

19.06 Business agents are big tech’s next battleground, with companies pouring billions of dollars into agents – with Meta among those placing big bets. But University of Auckland teaching fellow Guy Bate warns in The Conversation that convenience for businesses will come with a tradeoff: The more useful an agent becomes, the more influence it gains over the interaction itself.

18.06 AI world-model developer Odyssey, cofounded by Kiwi Jeff Hawke, has secured US$310 million in Series B funding at a US$1.45 billion valuation. The round was led by Natural Capital, with investors including Amazon, AMD Ventures and Google Ventures, Crunchbase reports. The startup, which is building models that understand the physical world, has now raised US$337m in funding.

17.06 NZ Police’s high-tech crime grew is now using Whisper AI in investigations after an earlier genAI trial was abandoned after significant misuse, only to be restarted again when officers used unapproved AI models, RNZ reports.

18.06 The Immigration Minister has slammed her ministry accusing officials of deliberately withholding information about the failed Biometric Capability Upgrade upgrade and using ‘creative accounting’ to avoid scrutiny. The Public Service Commissioner is to investigate ‘integrity concerns’ highlighted in a damning review of the project which has been written off at a cost of more than $30m, RNZ reports.

17.06 Dawn Aerospace has closed a US$25m (NZ$42.8m) series B capital raise to accelerate the global expansion of its reusable Aurora UAV spaceplane. The company says the funding will directly finance its global rollout, scaling commercial and operational teams in the US and Europe. The raise, backed by investors including Mana Ventures, Icehouse Ventures, and individual investors including Tim Ferriss, gives the company a $195m post-money valuation.

17.06 A new Microsoft Teams feature enabling Teams to detect activity on a user’s device even when they are not actively using Teams has raised privacy concerns. Auckland University lecturer Alex Baird warns companies that the Privacy Act is clear on being thoughtful about why data is collected and using it only for that purpose. If used for checking teammates know where you are, that’s great he told RNZ. Collecting data for performance tracking however would be ‘a very different thing’.

16.06 Anthropic has disabled its new Claude Fable 5 and Mythos 5 models after a US Export Control order. Forbes reports the US Commerce Department mandated the suspension of access for all foreign nationals citing security and export control powers. The move followed reports of a jailbreak bypassing safety guardrails.

12.06 SpaceX has made the biggest stock market debut in history, making Elon Musk the world’s first trillionaire. Early trading saw share prices jump from the opening $150 a share by a double digit percentage, sending the company’s valuation above US$2tn, the Guardian reports.

10.07 The NZ government is contributing up to $51m to an Early Adoption Accelerator to roll out emission reduction farm technologies. The government will match dollar-for-dollar every commercial dollar invested through AgriZeroNZ to help scale up practical on-farm innovation. AgriZeroNZ will administer the funds and says it is seeking expressions of interest from farming businesses.

09.07 Scott Technology has secured $12 million in contracts across Europe and North America for its automation offerings. The company says the deals come as the automation of global food production accelerates.

08.07 Kiwi ‘localscaler’ data storage company Exaba has secured almost $12m in seed funding to develop sovereign hosted cloud storage, the NZHerald reports [paywalled].

02.06 Auckland startup DataMasque, which builds data de-identification and masking tools, has raised $7m in a Series A round. The company’s premise is simple: Large enterprises want to leverage sensitive data, but feeding it into AI systems risks catastrophic breaches and regulatory exposure. The platform enables organisations to use their sensitive data for AI innovation without it leaving their own infrastructure, DataMasque says.

02.06 NZTA is pausing use of billboard cameras to detect WoF fraud, despite a trial proving successful. RNZ reports while the use of other organisations’ camera and automated number plate recognition technology resulted in ‘usable and valuable evidence for investigations’ the agency is not rolling out more of the surveillance because it can’t afford to.Use of the vGrid surveillance platform ended in mid-2025.

02.06 Inland Revenue’s myIR website has been overwhelmed by a surge in people trying to check their tax review online. Delays with two-step verification – with some codes arriving too late to be used – left users frustrated, the NZHerald reports.

02.06 Wellington’s deputy mayor Ben McNulty has slammed a $600,000 spend on a website for the capital’s new library, labelling it an ‘atrocious amount of money’. RNZ reports the cost of designing and building the site was $595,801, with a $72,000/year bill for hosting and maintenance.

02.06 Florida has become the first US state to sue OpenAI, over the design and safety of its ChatGPT chatbot. The state is suing both OpenAI and CEO Sam Altman, alleging they know ChatGPT is not safe, especially for minors, CNN reports.

AppWrap May 2026

28.05 Today’s budget includes more than $450m for digital health. The funding includes $153.6m over four years for Health NZ to expand national cybersecurity for health systems, and $300m to deliver the first three years of the Health Digital Investment Plan, upgrading core IT platforms, replacing aging devices and modernising radiology systems, eHealthNews reports.

28.05 NZQA has received $31m for technology upgrades, including work on machine learning for marking, in today’s Budget. RNZ reports funding has also be reprioritised for the Te Rito IT project – a cloud-based national system to connect and share student data.

28.05 Kiwibank has rolled out open banking for both individual and business customers across all digital channels. The bank says it is the first to do so, with customers now able to access open-banking enabled payments and data sharing directly through internet banking and the Kiwibank app.

27.05 The government has released new guidance to regulators on how to utilise AI to raise productivity, saying the technology can enable regulators to do more, faster. Regulation Minister David Seymour says the guidance shows regulators how to utilise AI in lower risk areas. It comes a week after the government announced plans to slash around 8,700 public service jobs and use AI to help fill the gaps.

18.05 Gentrack has acquired Wellington energy tech startup Factor for $24m. The deal, which includes a potential $10m earn-out, will see the AI-powered pricing intelligence embedded into the g2 platform to create an end-to-end retail operations platform, Gentrack says.

17.05 EY has withdrawn a study on cyber threats and fraud in loyalty rewards programs after the report was found to be ‘stuffed’ with fake citations and inaccurate claims. GPTzero researchers found the 44-page document was a ‘collage of vibe citations, misattributions, fake statistics and AI-written text’.

15.05 Dawn Aerospace, the University of Canterbury and the University of Auckland have been awarded a total of $1.48 million in the first round of the Kiwi Space Activator pilot program, which aims to move ‘more novel’ space tech from the lab to the skies. Dawn’s project will see it building and flying a small satellite, space minister Chris Penk says.

14.05 A group of academics has slammed the government’s leadership on AI, calling it lacklustre and ignoring anything that doesn’t include the words productivity or efficiency. The trio, writing on RNZ, say the latest missed opportunity was the decision not to send an observer to this year’s Responsible AI in the Military Domain summit.

13.05 The parent company of the Canvas educational tool involved in a major global hack last week has struck a deal with the hackers to secure stolen student and school data, Reuters reports. All data was returned to the company, it says, and digital confirmation of data destruction along with a promise no Instructure customers will be extorted were received Instructure says.

12.05 The upcoming Medical Products Bill will provide a modern regulatory framework for software used in healthcare, targeting therapeutic applications such as diagnosis, treatment guidance or disease monitoring, rather than administrative tools, eHealthNews reports.

12.05 Anti-money laundering reform bills have passed their final readings in Parliament with the government promising faster, less duplicative AML requirements once the bills receive Royal Assent in the next couple of days, InsideGovernment reports.

12.05 Xero CEO Sukhinder Singh Cassidy has apologised to customers after the accounting platform was hit with five days of outages. The outages were caused by Xero’s own systems and integrations with third-party platforms, SmartCompany reports.

10.05 The government has asked for 10 ‘no-cost, low-effort’ options to protect undersea internet and power cables amid concerns, with eight of the initiatives already completed or underway, RNZ reports. Among the 10 were an exercise simulating a cable break, a biannual threat assessment, and setting up a national surveillance warning capability. The moves follow sabotage and accidental damage of cables in Europe and Asia.

07.05 Rocket Lab has won a US$30 million contract with US defence tech company Anduril Industries. The deal will see three hypersonic test flights using Rocket Lab’s Haste launch vehicle to advance the US Department of War’s scaled hypersonics that deliver Mach 5 and beyond capabilities for future defence missions, Rocket Lab says.

06.05 Kiwi universities are among those caught in a worldwide cyber security attack after they Canvas learning management system, developed by US company Instructure, was subjected to a hack. The NZHerald reports Victoria University of Wellington, Auckland University of Technology and University of Auckland are among those using Canvas in New Zealand. Instructure says it doesn’t believe birthdates, passwords, government identifiers or financial information have been impacted. Names, locations of study, email addresses and messages between users are however believed to have been compromised.

04.05 Kiwi utility software developer Gentrack is acquiring Dubai Technology Partners in a US$10m deal. The company says DTP will add a portfolio of highly complementary AI-enable products which will integrate into Veovo’s Intelligent Airport Platform.

01.05 Trade compliance platform GingerControl has raised US$2.1m in seed funding. Backed VC says more than 90 companies are already using GingerControl to simplify workflows. The company was founded by Chen Cui and Sean Yu, who both grew up in West Auckland.

01.05 A ‘bug’ in a technology partner’s software saw widespread outages across One NZ and 2degree’s networks. Internet and calls were unavailable for many customers. RNZ reports that One NZ took responsibility for the issue.

AppWrap April 2026

28.04 Halter has launched a direct-to-satellite technology enabling cattle farmers to manage stock without the long range radio towers previously required. The company estimates the capability will expand access to Kiwi beef farms by as much as 20 percent, while also enabling expansion into more remote markets globally, including South America and parts of Africa.

23.04 A Public Service Commission performance improvement review of NZ police says New Zealand’s 111 platform ‘presents a fundamental risk to emergency response’ with police lacking end-to-end control over the emergency call process, limiting their ability to modernise, integrate and manage the system. RNZ reports the PIR notes a modern, integrated platform is needed, along with better tools to counter violent crime and ensure officer safety, with the report recommending continuation of an initiative to adopt body-worn cameras.

23.04 The NZ Government has launched a national Survey of Business Operations, which will provide a ‘comprehensive, up-to-date picture of how New Zealand businesses use AI and respond to economic and tech changes’. Insights from the survey, which builds on existing business data gathered by Stats NZ, will shape government policy. Around 20,000 businesses with six or more employees will be surveyed through May and June in what the government says will be one of the largest and most detailed business surveys undertaken in NZ. Invitations will be sent to ‘selected’ businesses in early May.

23.04 An Otago University expert says New Zealand needs a Reserve Bank-backed central bank digital currency (CBDC) in order to ensure it retains monetary sovereignty. Dr Murat Ungor says for the first time in history private companies and foreign governments can offer digital currencies that compete directly with the national currency, and without monetary sovereignty the country could be more vulnerable to economic shocks, reports RNZ.

23.04 Rocket Lab has successfully deployed its 87th launch, to deploy eight satellites for the Japan Aerospace Exploration Agency’s Innovative Satellite Technology Demonstration program providing opportunities for Japanese universities, researchers and companies to carry out tech demos in space. The company says the launch is its eighth for 2026.

21.04 Microsoft CEO and chairman Satya Nadella’s flying visit to NZ has been accompanied by an announcement that the compny will double its existing AI and digital skilling commitment to NZ, ‘opening access for a further 200,000 people to skilling’ by the end of 2028.

20.04 Kiwi shoe company Allbirds has announced its selling its footwear business to American Exchange Group for $39 million, and rebranding as NewBird AI, leasing GPUs. The company is now describing itself as a ‘fully integrated GPU-as-a-service and AI-native cloud solutions provider in what Forbes says is ‘the clearest picture you will get of where the actual AI bubble lives’. The company surged 600% in a single session on the back of the news.

20.04 Inland Revenue is warning 355,000 crypto-asset users in New Zealand that if they’re making money from those assets they need to think about their tax obligations. It says those crypto users have undertaken around 57 million transactions with a value of $36 billion.

16.04 Kiwi founded edtech company Storypark has acquired Australian childcare software provider Xap for an undisclosed sum. Storypark says the deal nearly doubles the size of the combined business and is a meaningful milestone in its international growth. Storypark was acquired by Potentia Capital in 2024.

15.04 Scott Technology’s half year results show EBITDA of $13.0 million up seven percent on the prior period, on revenue of $128m. The company says it expects further uplift in H2. New contract wins included a meat processor in Australia and automated guided vehicle contracts with a US aerospace manufacturer and a global leader in wine and spirits.

15.04 Travel giant Booking.com has notified an unknown number of customers about a data breach which has seen hackers steal customer data. BBC reports some customers have contacted it saying they have already started receiving suspicious messages. Booking.com has declined to say how many people are affected or in what regions.

14.04 Eight primary health organisations have joined forces in a joint procurement process for a shared, AI-capable tech platform for primary health organisations. The procurement covers claims and payments, provider portal, case management and referrals, eHealthNews reports.

13.04 Health NZ says it has saved $21.4m in one off savings from not having to upgrade platforms and ongoing savings from lower hosting and support costs, reduced duplication and improved productivity as it moves to cut hundreds of old websites. RNZ reports the agency inherited 344 websites about specific conditions or places such as the sites of the 20 DHBs. Many were no longer fit for purpose or did not meet government standards and posed technical and security risks.

13.04 New Plymouth District Court has issued a RFP for an enterprise-grade digital redaction solution capable of accurate and permanent redaction of sensitive information across a range of documents. The GETs document says implementation will begin as a service targeting high-volume or high-risk use cases.

09.04 The government says it has no existing plans to use Palantir’s emerging technologies, despite meeting with the company in February. RNZ reports Defence Minister Judith Collins met with Palantir’s international president for an information discussion.

07.04 MYOB has signed a five-year ‘strategic partnership’ with Microsoft to jointly fund, build and scale AI across its business management solutions to accelerate SME’s use of AI in day-to-day workflows. MYOB says the collaboration is focused on delivering practical, AI-powered tools, with Microsoft providing dedicated engineering support to work alongside MYOB’s teams to co-design and build the solutions. First up will be ‘AI teammates’ to reduce admin load.

03.04 Artemis II astronauts experienced Microsoft Outlook failures shortly after launch, with Mission Control called in to remotely troubleshoot the issue. Commander Reid Wiseman reported that two instances of Outlook were running simultaneously on his Surface Pro, leaving both unresponsive, Mashable reports.

02.04 Inland Revenue says 300 myIR accounts which did not have two-step verification have been accessed following a significant increase in malicious log-on attempts. IR says two-factor authentication prevented access to another 900 accounts which are now being monitored by IR, with the 300 compromised accounts closed and IR contacting affected customers.

02.04 The government is reallocating $122m of science, innovation and tech spend to focus more investment on emerging and advanced technologies, such as robotics, quantum technology and genomics. RNZ reports the funding – about 15 percent of the total $839m available – will be allocated to support four ‘pillars’ of primary industry and bioeconomy, technology for prosperity, environmental sustainability, and healthy people and a thriving society.

01.04 Datacom has acquired T4’s Auckland data centre in a move that gives Datacom five sovereign data centres in New Zealand and a second Auckland facility. The company did not disclose how much it paid in the deal, but says the acquisition– and planned investment in the site – means it has committed more than $200m to building out local data centre capability.

01.04 SpaceX has filed confidentially for an IPO according to reports, which say the company is committed to debuting in June, with Elon Musk aiming to raise US$50b-$75b. The NYTimes reports SpaceX values itself at more than $1 trillion and would be one of the most valuable companies to reach the stock market.

01.04 NZ Police aren’t receiving promised government funding for technology needed to carry out new powers. RNZ says police need two new or improved tech systems – one to handle photos of people and other data generated by enhanced intelligence gathering and one to issue new infringements under a new Bill currently before parliament.

AppWrap March 2026

30.03 New Zealand’s Dexibit has been acquired by UK-listed Accesso Technology Group for $21m. Dexibit is a AI and analytics platform for the visitor attractions market. Accesso says the acquisition launches Accesso Intelligence, a new AI-powered cross-platform capability.

26.03 Health NZ has reminded staff not to use tools like ChatGPT, Claude or Gemini in their work after staff were caught using the free versions to write clinical notes. RNZ reports staff have been told using the tools could result in formal disciplinary action.

26.03 Meta and Google have lost a landmark US case, with a Los Angeles jury finding the two companies negligent for designing social media platforms that are harmful to young people. Reuters reports the jury found Meta liable for damages of US$4.2 million, with Google liable for $1.8m in the case of a US woman who sued Meta and YouTube over her childhood addiction to social media.

23.03 NZ Tech has launched a cybertech community, CyberTech New Zealand. The industry body says the group will bring together New Zealand’s cyber tech companies, leaders and advocates to strengthen the sector, promote its capabilities and achievements and help advance national policy and investment in cyber. It has launched with 22 founding member companies, including KPMG, Deloitte, Microsoft, Service Now, University of Auckland, CyberCX and CyberCure.

23.03 One NZ has completed its 2G and 3G network switch off, with both networks now fully retired. The company says by switching off the old tech and reusing radio spectrum on 4G and 5G, it can boost speeds and increase capacity.

20.03 Govt.nz app users will be able to see their digital wallet in the app by the end of the month, with the Government Credential Issuance Platform also going live this month allowing people to store and present accredited digital credentials in the app. Hospitality NZ is working to be the first accredited digital credential in the wallet, pending changes to the Sale and Supply of Alcohol Act, Digitising Government and Public Service Minister Judith Collins says.

19.03 Xero co-founder Rod Drury has been named 2026 New Zealander of the Year, with Halter’s Craig Piggot named Innovator of the Year at the Kiwibank New Zealanders of the Year Awards.

19.03 The X Money payments service, Elon Musk’s attempt to build a ‘everything app’ will enter early public access in April. Musk’s ambitions for the embedding payments into X are broader than most Western tech companies, notes PaymentsIndustryIntelligence, with Musk talking about a system that could eventually encompass savings, payments, securities and other financial activity, reducing reliance on traditional banking channels. At launch X Money is expected to offer core wallet and payment functions, including the ability to move funds within the platform.

19.03 Rocket Lab has won a US$190m contract with the United States’ Department of War for a series of 20 hypersonic test flights over four years. RNZ reports the deal is the single largest contract for the Kiwi-founded company and lifts its total order backlog to more than US$2 billion.

16.03 The Financial Markets Authority has ruled that Easy Crypto’s NZDD stablecoin, which is linked to the NZ dollar, isn’t a financial product and can be treated like cash, rather than an investment. Newsroom reports the finding means the coin can be operated without the strict disclosure standards overseen by the FMA.

13.03 A Health NZ report says the loss of digital services jobs within the organisation will increase risks to patient care and will hit rural hospitals hardest, eHealthNews reports. More than 600 roles were vacant and not being filled when the organisation announced last year that it was reducing digital and data roles from around 2000 to 1460. It is now actively recruiting for 200 vacancies and has contracted Datacom to support its help desk through to May.

11.03 Professional body CA ANZ says it will investigate the failure of an external exam delivery platform after more than 1,300 students were locked out of one exam and another 60 experienced delays of up to 40 minutes on a second exam. CA ANZ blamed a failure in an external exam platform operated by a third-party provider.

11.03 Datagrid has been granted resource consent for a planned 280MW, 78,000m2 data centre in Makarewa in Southland. The company says the landing of the Tasman Ring Network subsea cable at Oreti Beach has also been approved. Datagrid, founded by Hawaikii Cable founder Remi Galasso and Callplus founder Malcolm Dick, could be live by 2028 with the University of Otago as an anchor tenant, DatacentreDynamics reports.

11.03 US medtech giant Stryker has been hit by a major cyberattack, with an Iran-linked hacking group claiming responsibility, saying it is in retaliation for the killing of more than 170 people – mainly schoolgirls – in a strike on a school, and warning it marks the beginning of a new chapter in cyber warfare, Al Jazeera reports. The group says it has seized 50TB of Stryker data in the attack which it says has erased data from 200,000 devices.

10.03 Anthropic is opening a Sydney office as it expands its presence in Australia and New Zealand. The company says New Zealand ranks 8th globally in Claude.ai usage, relative to population, with strong demand from local business. Anthropic says it is also exploring opportunities to expand compute capacity in Australia ‘given our longstanding belief that democracies should lead in AI development’. The company is currently suing the US government over its claims that Anthropic is a ‘supply chain risk’. The row erupted after Anthropic refused to all US military to have unfettered use to its AI tools.

07.03 Bunnings will begin using facial recognition technology in two Hamilton stores from mid-April, with a nationwide rollout to follow. The remainder of the North Island will be covered in phase two, with the South Island rollout coming in phase three, with timings yet to be confirmed, Bunnings says. The company says the system will help protect staff and customers from increasing threatening incidents.

05.03 The GCSB has warned government that cyber security around some of New Zealand’s critical infrastructure is ‘barely meeting that foundational level we would expect’. RNZ reports that GCSB director-general Andrew Clark told a select committee that supply chains, including digital ones from private companies into public agencies, were increasingly a weak point and they had to make sure private ones are hardened up like public ones.

04.03 Recruitment company Younity is reporting an 80 percent jump in open IT roles year-on-year in January, continuing a trend seen in December. It says demand is being driven largely by business transformation roles such as business analysis, project management and delivery focused positions, however, demand is healthy across critical IT disciplines including software development, data engineering and analytics, cloud computing and cybersecurity.

02.03 Andrew Bridgman has been appointed establishment chief executive of the New Zealand Institute for Advanced Technology. MBIE says he will oversee the critical foundation phase, putting in place governance, operational capability and systems required to deliver on NZIAT’s mission of ensuring advanced tech delivers meaningful, measurable benefits for New Zealanders.

02.03 Syos Aerospace has won a contract to supply drones to the New Zealand Defence force. Air, land and sea drones will be delivered as part of the deal, Syos says.

01.03 Kiwi managed services company Securecom has been acquired by the New Zeaand subsidiary of Japan’s Sharp. Shap says there will be no structural or operational changes, for the Auckland-headquartered operations and 24/7  integrated operations centre, which will continue under the leadership of Greg Mikkelsen. The deal provides Sharp with an IT services business as it moves from being a traditional print and copier business to ‘a more unified tech partner’, Sharp says.

AppWrap February 2026

27.02 The government has released New Zealand’s Cyber Security Strategy 2026-2030 and an accompanying action plan, providing a national framework for responding to cyber threats and strengthening cyber security practices. The strategy is focused around four objectives of understand, prevent and prepare, respond and partner, while the action plan translates the objectives into specific initiatives including strengthening critical infrastructure cyber resilience and quantum readiness.

26.02 Tauranga robotics company Syos Aerospace’s uncrewed autonomous helicopter has completed a series of fully autonomous mission trials clearing the uncrewed aerial vehicle for serial production, the company says.

26.02 Nvidia has posted blockbuster quarterly results of US$68.1 billion – up 73 percent year on year and well above analysts’ forecasts. Revenue from the data centre division, which sells the chips used to train and run AI models was up 75 percent yoy to $62.3 billion, the company says.

25.02 MediMap is seeking an urgent injunction to stop any sharing of stolen data after sensitive patient data was distributed to media outlets. The injunction being sought would prohibit anyone from accessing, using, copying, sharing or publishing any MediMap data that may have been unlawfully obtained and would seek to limit further spread of the information online, Stuff reports.

24.02 Pharmacists have implemented manual systems after medication management platform MediMap was hacked on Sunday. Records for some patients have been altered, including labelling some live patients as deceased, and changing names. Patient data for over 120,000 users was put at risk by the hack, the NZ Herald reports.

23.02 New Zealand’s Privacy Commissioner has joined other countries in signing a joint statement voicing concerns about use of AI-generated imagery, and reiterating expectations for organisations developing and using AI content generation to ensure systems are developed and used in accordance with legal frameworks, including data protection and privacy rules.

20.02 Fintech Dosh’s bid to become a bank has been turned down by the Reserve Bank, which says it does not meet the legal definition of a bank. Dosh told a Parliamentary banking inquiry follow-up that the Reserve Bank says it must make loans as well as offering other banking services to be deemed a bank – something Dosh says is a restrictive and narrow interpretation of the legislation, GoodReturns reports.

18.02 Xero is restructuring with 250 jobs on the line – including in New Zealand. The company is creating around 280 roles in Canada as part of the restructure, BusinessDesk reports [paywalled].

18.02 YouTube suffered an outage from around 1.50pm NZT, with a spokesperson for Google saying an issue with the recommendations system prevented videos appearing.

18.02 Spark has reported an 83 percent rise in net profit after tax, to $64m, for the first half of FY26. Revenue was down 1.2 percent to $1.8 billion in the interim results for the six months to December. It says use of agentic AI is reducing set up time by around 60 percent on some business products with AI now identifying customers with more complex needs so they can be escalated to the care team for faster resolution.

17.02 Mastercard has completed its first Agent Pay – agentic – transactions in New Zealand, with Mastercard’s country manager using a bot to purchase cinema tickets, then booking Queenstown accommodation. Stuff reports Mastercard plans to launch the offering fully in New Zealand within six to nine months. It has currently launched in the US and is in pilot in Australia, the UAE and Latin America.

16.02 Labour says it supports the principle of long-term investment in digital health, but wants more detail before committing to supporting the Government’s 10-year Health Digital Investment Plan. Labour health spokesperson Ayesha Verrall says she wants more detail about how the plan will invest in cybersecurity, eHealthNews reports.

16.02 An American computer scientist is heading to New Zealand’s Court of Appeal next week to test whether AI really can be an inventor. In the global test case, Stephen Thaler is challenging the Patent Office’s declining of an application for a patent for a new type of food container he says was named by an AI system, RNZ reports. The Patent Office and High Court say an inventor has to be human.

16.02 The Department of Corrections has warned staff about use of AI tools outside approved use, after some staff were found using it to draft formal reports. RNZ reports Corrections’ policy for Microsoft Copilot – the only AI used by the agency – is that Chat must not be used under any circumstances for reports or assessments containing personal information, but in a ‘small number of incidents’ inappropriate use has occurred.

13.02 Kiwi Chris Liddell has been appointed to the Anthropic board of directors. CNBC reports the appointment, which comes as Anthropic announces it closed a US$30 billion funding round at a US$380 billion post-money valuation, could help the company foster some goodwill with the Trump administration which has accused Anthropic of supporting ‘woke AI’. Liddell was deputy White House chief of staff during Trump’s first term.

11.02 Christchurch start-up Contented AI, which turns meeting notes into documents, has raised $4.1m in a seed funding round. The company says it will use the funding to scale into Australia and the UK, triple its team, invest in core technology and build out new integrations and templates. The funding round was led by Altered Capital, with backing from K1W1, Icehouse Ventures, Aspire NZ Seed Fund and others.

11.02 Wellington medtech Wellumio has raised $7.28 million in a pre-Series A funding round. The company is developing a portal AI-enhanced brain scan technology designed to rapidly detect acute stroke and unlock treatment within the ‘golden hour’, Voice of Healthcare reports. The funding will be used to build the team and accelerate clinical development.

09.02 New Zealand is adopting 57 digital technology international standards as part of a trans-Tasman standards agreement. The agreement aims to align standards and adopt trusted international rules across areas including AI, data management and cybersecurity. Commerce and Consumer Affairs Minister Scott Simpson says the agreement will also strengthen digital trade, and reduce fees and red tape. The national standards bodies on both sides of the Tasman will also support 33 additional joint A/NZ standards projects to progress in fields including telecommunications, while 24 standards across areas including building and construction and consumer protection will be ‘re-aligned’.

09.02 Computer simulations, based on climate models, are being used to predict future ocean temperatures and currents – and future marine heatwaves and ocean-driven weather patterns – in an $8.9m project examining how offshore ocean changes are driving extreme weather in New Zealand and impacting coastal waters. The five-year project will see self-driven ocean gliders mapping the ‘heatscape’ along New Zealand’s coastline University of Auckland says.

09.02 Early-stage investment in start-up businesses attracted 8.6 percent more capital, with nearly twice as many new businesses receiving investment in last year, according to Angel Association. RNZ reports deal activity rebounded with a 34 percent increase in the number of deals completed, to 167, but the capital increase was a more conservative 2.7 percent, to $13.9m.

04.02 The Warehouse Group is cutting 270 head office roles and upping its ‘co-sourcing’ with Tata Consultancy Services as part of a push for a ‘leaner operating structure’. TCS will support delivery of corporate and admin functions, including parts of technology, accounting, call centres and payroll, TWG says. Last year the company announced it was using TCS to simplify its tech stack and lower costs, saying the partnership would reduce licensing and managed services costs by up to $40m over five years and free tech teams to focus on delivering more value for customers, communities and shareholders.

03.02 Kiwi software quality consultancy Assurity Consulting has been acquired by global technology services firm Aspire Systems. Assurity says the deal will provide global scale and deep technical capability, unlocking a pipeline of AI tools for New Zealand and Australian clients.

03.02 A new ‘digital medical assistant’, aka chatbot, to provide pre-and post-surgical advice is being rolled out to some New Zealand and US clinics. The AI agent, developed by Fios Health and operating via SMS, is customised to each surgeon’s protocols and proactively sends information and answers patient questions. Early trials showed some patients felt more comfortable directing certain questions to an AI assistant rather than their surgeon, Fios says.

03.02 Xero says more than two million subscribers are using its full AI features, with more than 300,000 using its newer GenAI features. In a market update today the company claimed customers are saving around 22 hours a month using bank feeds and automated actions, with more than 12 percent using AI Insights.

03.02 Kiwi AI startup Teacher’s Buddy has raised $2.3m in trans-Tasman seed funding. The offering aims to reduce teacher workloads, helping with marking and student report writing and producing customised, differentiated curriculum-aligned teaching and assessment materials  The company says the funding was led by Auckland’s Soul Capital and Australia’s Giant Leap.

03.02 2degrees has completed the shutdown of its 3G services with finals shutdown completed last night. The telco says the shutdown enables it to focus on strengthening and expanding its 4G and 5G networks which already carry the vast majority of mobile traffic, while also looking to satellite.

AppWrap January 2026

31.01 Spectral Defence has been crowned the national winner of the ActInSpace New Zealand 2026 hackathon and will represent New Zealand at the international ActInSpace finals in France in April. The event sees teams tackle space-related challenges, applying satellite data, earth observation and space-enabled technologies to problems spanning sustainability, infrastructure, resilience and ‘everyday life applications’, SpaceBase, who delivered the NZ event, says.

30.01 The NZ government has launched its Public Service AI Work Program designed to accelerate the safe and responsible adoption of AI across government agencies. The two-year ‘action plan’ is designed to connect agencies’ efforts with the resources, guidance and support needed to accelerate AI adoption, while modelling best practice, Digital.govt.nz says. The program includes an AI marketplace, an AI hub with registries and tools, a dedicated AI Innovation and Accelerator Lab and a public service AI Sandbox.

30.01 Thirty-eight percent of Kiwis received unwanted digital communication in the last 12 months, with 14 percent reporting the experience negatively impacted their life, Netsafe reports. Ten percent admitted having sent or shared at least one form of unwanted communication themselves in the past year.

29.01 A system error with the Ministry of Social Development’s IT system resulted in around 200 pensioners who get overseas pensions receiving incorrect NZ Super payments. RNZ reports the ministry is working ‘urgently’ to fix the fault in the IT system which updates overseas pension rates.

29.01 Hospital administration systems across the top half of the North Island shut down for 12 hours in a major IT failure affecting clinical and operational systems. All emergency department, laboratory and inpatient systems were affected with clinicians resorting to paper-based systems, whiteboards and phones, Stuff reports.

27.01 Nema is warning people about AI images circulating on TikTok claiming to capture the fallout of the Mt Maunganui slip. The scenes depict exaggerated scenes of destruction including a raging waterfall and emergency workers digging through wreckage. A Victoria University senior lecturer says he believes it is the first time AI images of a New Zealand disaster have circulated online, RNZ reports.

26.01 Client data has been breached in a cyberattack on Napier law firm Langley Twigg Law. The company says security monitoring software alerted to unauthorised activity on the network on 11 January, after the network was targeted by ‘a sophisticated malicious attack using a new strain of virus’ not recognised by antivirus programs at the time. Client data has been copied from the file server, the company says.

27.01 Airwallex boss Jack Zhang says the fintech is at least two years away from a public listing, despite regular references to an IPO in 2026. Zhang’s comments, reported in StartupDaily, follow news last week that Austrac has ordered an audit of the company over AML/CTF concerns.

26.01 A digital twin simulating New Zealand’s entire population, has been used to study resilience to measles. eHealthnews reports the digital twin creates ‘virtual kiwis’ built from aggregated census and government data, enabling researchers to model public health scenarios to inform public policy decision and emergency planning, without tracking real people.

23.01 Manage My Health has warned that secondary actors may be impersonating the company and sending spam or phishing emails in the wake of the high profile hack of the online patient portal. The company says it has been granted an interim injunction from the High Court to prevent access, dissemination or publication of the impacted data by any third parties and says it is monitoring data leak websites and ready to issue takedown notices.

23.01 TikTok has finalised agreements with backers including Oracle, Silver Lake and Emirati company MGX to establish a US joint venture. Each of the three backers will hold a 15 percent stake in the company. ByteDance keeps a 19.9 percent share. The BBC reports the content recommendation algorithm has been licensed to Oracle – headed by Trump ally Larry Ellison – which already oversees US user data under a previous arrangement set up over security concerns. The deal will enable TikTok to continue operating in the US, but is likely to continue to be scrutinised, with some Democrats voicing concerns about the ties between Trump and TikTok’s new investor group could limit what gets shared on the platform.

22.01 Australia’s financial intelligence unit, Austrac has ordered an external auditor be appointed to assess whether fintech – and unicorn – Airwallex is complying with anti-money laundering and counter terrorism financing. Austrac says it has ‘concerns’ about potential non-compliance including that Airwallex’s transaction monitoring program has not been ‘attuned to the full range of risks it faces’ and the company hasn’t demonstrated an acceptable understanding of who its customers are and what reporting may be required. The auditor must report findings within 180 days of appointment.

22.01 Hamilton’s Cloudland has acquired professional services tech provider CommArc for an undisclosed sum, in its fourth acquisition in as many years.

20.01 Kiwi legal tech startup Ivo has raised US$55m in a Series B funding round led by existing investor Blackbird. The company’s platform helps in-house legal teams review contracts. Ivo says customers include Uber, Shopify, Canva, Atlassian, Reddit and Pinterest, and the capital will support product development and scaling the company.

15.01 Kiwi email signature provider Crossware has bought Germany’s largest email signature provider, CI Solutions, in a multimillion-dollar deal. Crossware says the deal significantly scales its presence in the European union and establishes it as one of the leading email signature providers globally, processing more than five million emails every day.

13.01 Advertising is hitting the AI chatbots with ads starting to show up in Google’s ‘AI Mode’ in what the Washington Post says is likely to be just the beginning of more trial-and-error attempts this year. Google has been pushing a new type of ad in AI Mode to advertisers, OpenAI has also been looking at introducing advertising in ChatGPT and Perplexity attempted ads but pulled back last year – but has left the doors open to try again.

11.01 Around 70 percent of those impacted by the ManageMyHealth breach are based in Northland. Ransomware group Kazu has demanded US$60,000 after stealing hundreds of thousands of medical files. RNZ reports around 120,000 patients have had data stolen, with 80,000 of those based in Northland.

01.01 ManageMyHealth has been hacked, with ‘six to seven per cent’ of its approximately 1.8 million registered users potentially affected. The company says it has begun to identify users affected and will start notifying them within the next 48 hours.

The post AppWrap: Flawed assumptions, breaches and booking platform raise appeared first on iStart leading the way to smarter technology investment..

As the capability moves into Auckland Council ownership as part of its council-controlled organisation reforms, Cohen, who is AT CTO, says the platform could be extended into new civic use cases and be monetised and sold to other agencies globally.

“It has provided significant value across different areas from enforcement to safety scenarios, and given us a bit of an operational edge to our business.”

Theia, which won the Cloud-native Development and Hybrid Cloud Infrastructure category at the recent Red Hat APAC Innovation Awards for Australia and New Zealand, has been under development for about a decade and today processes feeds from around 8,000 cameras across Auckland’s transport network, including road, rail and ferry. Created to help monitor roads, public transport infrastructure and other network assets, the platform is capable of automatic detection, tracking, data collection, identifying incidents and events and has evolved into a platform used for safety monitoring, enforcement, operational analytics and service management.

But Cohen believes its future could stretch well beyond buses, trains and traffic management. He told iStart he can see ‘millions’ of use cases for the technology in helping organisations identify problems earlier and respond before they escalate. One possible example: Identifying swimmers in trouble at public pools.

“With this moving to council, there will be even more opportunity and even more need because it will be across a much wider range of scenarios and use cases,” he says.

The CCO reforms will see the team responsible for the system moving under Auckland Council from October, leaving it up to the council what happens in future. Cohen though, is clear: “I personally think monetising the service would be a good idea as it would reduce rates for Aucklanders as a whole.”

Councils and public transport organisations around the world face similar operational challenges and need the capability of the system.

“It’s provided significant value across different areas from enforcement to safety scenarios, and given us a bit of an operational edge to our business,” he says. “From identifying traffic cones and where they might be sitting to identifying people who might be jumping on a rail network or scenarios where we’re currently working on aggressive behaviour detection to identify when aggressive behaviour occurs so we can send the right authorities.”

Building AI for Auckland 

Theia’s origins date back to a challenge many organisations continue to face today: How to monitor and keep track of all the assets and turn vast quantities of operational data into actionable insight.

Derek Zhang, Auckland Transport Computer Vision delivery manager, says the organisation initially relied heavily on manual monitoring of CCTV systems to oversee roads, public transport networks, parking facilities and other assets across the city. The approach was labour intensive, reactive and generated little usable data for decision-making.

After an early attempt to address the problem using a third-party platform didn’t work ‘for many different reasons’, Zhang says, and the decision was made to bring the capability in-house.

“We wanted to stand on the shoulders of giants like Google, Intel etc – I won’t mention too many names – and utilise what they have built, then modify and adjust it for what we need as a transport organisation.

The platform uses Red Hat OpenShift to provide the containerisation platform so ‘we don’t need to worry about the underlying technology that keeps the applications running’, Zhang says.

“It’s not just the AI component in it, but also how this system can be seamlessly integrated with our existing systems upstream and downstream.”

The project faced the unique challenge of operating in a real world and real time environment, requiring the technology to be reliable, scalable and available around the clock.

“That requires the technology to be able to cater for those requirements, how we design the infrastructure, how we design the product, how we link things together, without losing the requirement for real-time basically, and then it has to be maintainable as well,” Zhang says.

“We need to process those large volumes of data using the infrastructure and platform and then also need to maintain the trust, privacy, security and reliability, expected from a public sector organisation.”

Today, Zhang says the platform is used across multiple departments, including safety, compliance, network performance and asset protection teams. The system supports applications ranging from parking and bus lane enforcement to dynamic lane management, pedestrian analytics and rail safety monitoring. It is also being used in a pilot focused on detecting aggressive behaviour across the transport network.

The City Rail Link has further expanded the platform’s reach even further, with additional cameras and LiDAR systems being integrated into network operations. The technology is being used to monitor passenger numbers, assess platform occupancy  and identify people entering restricted rail areas or safety zones.

It’s also been used to enable ‘dynamic lanes’ – lanes which move between being bus only or open lanes depending on whether buses are running late or general traffic is building in order to keep transport flowing as smoothly as possible.

Going multimodal 

Cohen notes technology, whether AI, CCTV, machine learning or other mainstream offerings and even drones, underpins much of Auckland Transport’s KPI delivery.

The scale of the operation helps explain why AT is continuing to invest in the platform.

“We are talking about thousands of thousands of CCTVs that need to be monitored automatically by the system,” Zhang says, noting that reliability, scalability, privacy and real-time performance have become critical design considerations.

Those requirements are also driving the platform’s next phase of development.

While much of the current technology conversation has centred on generative AI, Zhang says Auckland Transport is preparing to incorporate both generative and multimodal AI capabilities into its roadmap.

Zhang says multimodal AI will help increase the accuracy level of the computer vision results while also improving interactions for transport operators and providing a better experience using the computer vision offering.

Theia complements a broader generative AI push underway within Auckland Transport. Cohen says the organisation is a significant user of Microsoft Copilot and is exploring ways large language models can be used to interrogate analytics systems and generate reports using natural language prompts.

 “We’re looking even at things like analytics that will be done through generative AI so that you can use an LLM to then generate a report to give you information you’re looking for, such as how many patrons did we have in the last 24 hours considering it was raining? How did that compare to last week when it was raining?”, Cohen says.

For Zhang and his 20-strong computer vision team, the bigger opportunity may be creating a reusable platform capable of serving an entire city. The environment that has been built is very scalable, and Zhang says expanding to new models would be ‘a lightweight piece of work because we have already developed the core product, which is going to run continuously as an end-to-end process.”

What began as an effort to automate CCTV monitoring is increasingly being viewed as a broader civic technology capability, one that could eventually support a growing range of council services while generating value beyond well Auckland’s transport network. And as Cohen says: “Anything that will reduce our rates, I encourage!”

The post AT’s AI ambitions go city-wide – and beyond appeared first on iStart leading the way to smarter technology investment..

That’s the contradiction at the heart of new Gartner research, which predicts AI inference costs per agentic workflow will increase more than fivefold by 2028 as organisations move from simple chatbots to more sophisticated AI agents capable of reasoning, planning and executing multistep tasks. The analyst company calls it the ‘inference paradox’ with improving model economics being overwhelmed by increasingly complex AI workloads.

While model prices might be falling, that’s luring users to build ever more complex workflows – and the greater token consumption of those workflows can outweigh savings from reducing model prices and escalating inference costs.

“The harsh economics of the Inference Paradox are exemplified by the differences between a simple chatbot and an AI agent,” Gartner senior director analyst Will Sommer says. “Where a simple chatbot must read and interpret a query and quickly respond with a probabilistically reasonable answer, an AI agent must constantly reason, negotiate and question itself.”

All of that processing comes at a cost.

Gartner says routing a task to an agentic reasoning model increases inference costs by at least five times compared with a basic chatbot interaction, and often much more as complexity grows. At the same time, organisations are discovering that increasingly capable AI systems consume vastly more tokens than traditional conversational AI.

Gartner argues many organisations are making matters worse by allowing inefficient agent behaviour to creep into systems as they scale.

“There is an enormous pool of waste in any agentic system,” Gartner says in a research note. “Most of the bill in agentic systems is redundancy.”

Among the issues identified in 50% of Token Costs Can Be Cut for AI Agents With Zero Quality Loss are repeated queries, redundant processing, oversized context windows and agent loops that repeatedly consume tokens without adding value. Gartner estimates roughly 31 percent of production queries repeat work organisations have already paid for. Agents consume around 100 input tokens for every output token generated, while 40 percent to 60 percent of agent tool output tokens can often be removed without any loss of quality.

This is where Gartner believes the next AI battleground is emerging as companies move beyond the first phase of experimentation and the second of governance, trust and responsible deployment and into AI engineering efficiency, or building systems that deliver the same outcomes using fewer resources.

That starts with model selection.

“Most tasks do not require frontier intelligence,” the report notes, warning that defaulting every workload to the largest and most capable models is ‘immensely wasteful’. Instead, Gartner recommends routing requests to the cheapest model capable of completing a particular task and escalating only when more sophisticated reasoning is genuinely required.

The report report estimates organisations can reduce costs by up to 60 percent through routing and workload optimisation alone.

Gartner argues that visibility becomes increasingly important as organisations scale AI into production. It recommends tracking metrics including cost per completed task, token consumption by model, spend by customer segment and the relationship between AI expenditure and customer outcomes. Without detailed measurement, organisations often fail to identify expensive models performing basic work or AI features generating little business value.

At the centre of Gartner’s recommendations is a concept that will sound familiar to cloud veterans: AI FinOps.

The company recommends introducing AI gateways, workload routing, caching, attribution and budget controls to actively manage AI consumption rather than simply paying whatever bill arrives at the end of the month. It describes routing, caching and orchestration as critical to preventing costs from spiralling as agent complexity increases.

“Hold agents to high-value tasks and delegate the rest down a tier,” the report says.

“Product leaders cannot rely on more efficient token economics to rationalise AI costs,” Sommer says. “Each successive generation of AI capability will necessitate more, and often more expensive, tokens.” He says there is ‘no reliable, economical one-size-fits-all model on the horizon’ and that organisations will increasingly need to manage complex multimodel environments.

The move by some AI providers to usage-based billing – as previously reported by iStart – has exacerbated issues.

Gartner’s report also identifies opportunities inside the architecture of agentic systems themselves.

Rather than feeding large volumes of information into models, the report recommends retrieval-based approaches that selectively surface only relevant content. Using retrieval-augmented generation (Rag), for example, can reduce token consumption by up to 75 percent while maintaining accuracy. Context compression approaches can reduce token volumes by 60 percent to 95 percent, while redesigning agent loops can remove 40 percent to 60 percent of redundant processing.

The broader message is that AI economics are changing.

For the past two years, the primary question has been whether AI could perform useful work. Gartner suggests the more important question now may be whether organisations can afford to run increasingly sophisticated AI systems at scale – and how to control what that intelligence costs.

The post AI’s new paradox: Cheaper models, bigger bills appeared first on iStart leading the way to smarter technology investment..

Every document uploaded, process automated and workflow handed to AI is helping build systems that could eventually outperform the very businesses feeding them. Productivity gains are real, he told iStart, but so are the unintended consequences, particularly for companies deploying AI without fully understanding where their data, knowledge and intellectual property end up.

“Everyone disregards the unintended consequences until it bites.”

A recent report found 40 percent of Australian office professionals have entered customer data or information into public AI tools, with 28 percent admitting inputting financial information or disclosing confidential company documents or strategies. Shadow AI Survey also noted that 70 percent of those surveyed have used AI tools or services at work despite not being allowed under company policies – and over half (53 percent) have faced formal consequences, such as a warning or disciplinary action, due to unauthorised AI use.

But Robb argues the issue isn’t simply whether staff are using AI. It’s how organisations are using it, what information is being shared with AI systems and whether anyone has thought through the consequences.

“Everyone disregards the unintended consequences until it bites,” he says.

Robb believes most employees are acting with good intentions. They’re looking for faster ways to complete tasks, improve reports and eliminate repetitive work. In many cases, they’re right: AI can dramatically improve productivity.

The problem is that productivity gains can obscure risk.

One of Robb’s biggest concerns is the amount of organisational knowledge being fed into public AI platforms. As staff upload documents, workflows and business information to improve outputs, organisations may be unintentionally giving away IP and expertise.

“[The foundation model providers] own the IP and you are training them to be better than you are,” he says.

Last month, Microsoft CEO Satya Nadella warned about the unintended consequences of AI, including the ‘reverse information paradox’ where enterprises unknowingly give away their proprietary institutional knowledge and competitive advantage simply by utilising third-party AI systems to boost productivity.

That’s just one unintended consequence Robb says companies need to consider as AI adoption accelerates. Another is the ease with which well-intentioned employees can create data exposure risks while trying to be more productive.

That, however, isn’t a new phenomenon. He recalls regularly dealing with incidents at a major bank where staff moved documents outside secure environments in order to work faster – sending a PDF to their home PC to convert it and send back to the work PC, for example. The intention was never malicious. Employees were simply trying to get the job done. But once sensitive information left the bank’s systems, a security breach had occurred and it was a summarily dismissible offence.

Robb sees similar behaviour emerging around AI tools today.

“Now, if I’ve loaded company data in to get that, that company’s got a genuine exposure,” he says.

For tech leaders, that means the challenge is no longer just identifying unauthorised AI use. It is understanding what information employees are putting into AI systems and whether appropriate guardrails exist around that behaviour.

Robb says regulated organisations, particularly financial institutions, have already invested heavily in governance and controls. “Banks have already stopped their people sending data to their iPads. It’s really hard to get data out of a bank or an insurance company.

“But when you’re a smaller business, the data’s everywhere.”

At the same time, companies are moving beyond AI experimentation.

Many of the early AI projects focused on incremental improvements – better reports, improved customer service or small efficiency gains. Robb says the next phase is different as businesses start to redesign entire processes around AI.

“It’s moved from incrementalism to step changes in processes.”

That shift creates new opportunities but also new risks. He cites the example of a plumbing business that has automated significant amounts of administrative work using AI. Compliance documentation and other repetitive tasks that once required multiple staff are now largely automated. The business gains efficiency, reduces effort and lowers its cost to serve customers.

The broader question, however, is what happens when competitors follow.

“If you have a lower cost to serve, you will kill your competition. Ai is a lower cost to serve.”

For business leaders, that’s a reminder that AI governance isn’t just about risk management. It is also becoming a competitive issue. Organisations that fail to adopt AI may find themselves at a disadvantage. Organisations that adopt it recklessly may create security, compliance or intellectual-property problems they don’t yet understand.

So what should companies be doing now?

Robb’s answer, unsurprisingly given he runs an AI governance consultancy, is governance. Not governance as a brake on innovation, but governance as a way of avoiding the ‘we’ll deal with that later’ approach that has accompanied many AI deployments. The question, he says, isn’t whether organisations should use AI. It’s whether they’ve thought through what happens when productivity gains collide with compliance obligations, security risks or unexpected business outcomes.

He says every organisation deploying AI into production should have a governance plan appropriate to its size and risk profile. For larger organisations, that means asking practical questions:

Does the AI initiative have board approval and a defined business outcome?

Is a human accountable for customer-impacting decisions?

If you lost control of your AI model, could you regenerate using using paper and pen, the data and the answers to get to the same position within 24 hours?

Does the business understand what data is being shared with AI tools?

An AI governance pack Robb’s company developed for banks and listed companies warns that AI governance is no longer optional and ‘we have a policy’ is no longer an answer – and ‘we are not doing anything yet’ is not a defence.

The pack outlines six guardrails:

• Strategic alignment – is AI use tied to risk appetite and corporate strategy),
• Accountability – who owns each AI system end-to-end?
• Explainability – can you explain a decision to a regulator or customer?
• Human oversight
• Monitoring and adaption – are models monitored for drift, bias and performance, and
• Organisational ethics

“If your board cannot score itself against these six, you do not yet have AI governance,” the pack says.

Smaller businesses? They’re exempt to some degree, he says. “If you’re say a five person plumbing business and you’re using AI to do training or something, honestly, congratulations, you’re curious, you’re using the tools. You don’t need a governance plan because you’re aware of the boundaries of what you’re doing.”

Putting in the wrong parts won’t be the end of the world – and it’s probably something you sometimes did pre-AI anyway.

Robb isn’t advocating caution at the expense of innovation. In fact, he believes many organisations across Australia and New Zealand have been too slow to realise AI’s potential.

Instead, his message is to stay curious, move quickly and prepare for the downsides, rather than ignoring them.

“AI is more valuable than it is detrimental,” he says. But organisations also need a plan for what happens when something goes wrong.

The post Unintended consequences: Are you training AI to eat your lunch? appeared first on iStart leading the way to smarter technology investment..

The initiative marks the global financial messaging network’s first production use of a blockchain-based ledger and is being positioned as a way to enable funds to move overnight and on weekends while remaining within the regulated banking system – and compete with the emerging stablecoin market.

“We see strong potential to help customers move funds in real-time and manage liquidity more flexibly.”

Banks from six continents are taking part, including ANZ, Citi, HSBC, Lloyds Banking Group, UBS, Wells Fargo and Standard Chartered. Swift (the Society for Worldwide Interbank Financial Telecommunications) says participating banks will use the shared ledger as an orchestration layer for bank-issued tokenised deposits on their own infrastructure, allowing institutions to move value before final settlement is completed through existing banking systems.

For ANZ, the trial expands a digital assets strategy the bank has been pursuing for several years, including work with tokenised assets and blockchain-based settlement technologies.

Lisa Vasic, ANZ managing director transaction banking, says the bank is working with Swift and global partners to ‘securely scale next-generation payments infrastructure’ and deliver ‘more efficient, always-on payment capabilities’.

“By combining Swift’s trusted network with this new infrastructure, we see strong potential to help customers move funds in real-time and manage liquidity more flexibly,” Vasic says.

Beyond crypto and speculation

Blockchain has struggled to find a use case within business. For much of the past decade, the technology, initially hyped as the foundational technology for Bitcoin and decentralised digital currency, has been associated more with cryptocurrencies, speculative trading and fraud than practical enterprise applications. Despite billions of dollars invested globally, and plenty of attempts, relatively few large-scale business deployments have emerged outside digital asset markets.

The distributed ledgers have been trialled for everything from smart contracts that automatically execute when predetermined conditions are met, to supply chain tracking systems designed to create tamper-resistant records of product governance and movement. But while some have delivered niche benefits, few have achieved widespread adoption at scale – and there have been several high profile failures. Maersk and IBM shuttered the TradeLens blockchain-enabled global trade platform in 2022 after five years work, blaming an apparent lack of interest and trust from the industry. The ASX’s blockchain-powered Chess settlement and clearing system project meanwhile went down in a ball of flames – labelled a ‘profound failure’ by the chair of a parliamentary joint committee on corporations and financial services, and leading to an AU$250 million writedown.

The payments difference

The Swift initiative sees some of the world’s largest banks using the technology to tackle an issue that has frustrated businesses for decades: The limitations of cross-border payments.

International transfers remain constrained by time zones, banking hours and fragmented settlement processes. While businesses have become increasingly digital and globally connected, moving money internationally often remains slower than moving information.

Swift believes tokenised deposits operating over a blockchain-based ledger could help bridge that gap. The organisations says the new capability would allow banks to support 24/7 cross-border payments while maintaining the compliance, risk management and control frameworks already embedded into the global financial system.

“It allows tokenised value to move across borders with the velocity and flexibility modern commerce expects, while maintaining the same high levels of resiliency, security and compliance global finance requires,” says Thierry Chilosi, Swift chief business officer.

The approach differs significantly from public cryptocurrency networks.

Rather than creating an alternative financial system, Swift’s ledger is designed to sit alongside existing banking infrastructure. Participating banks continue issuing and managing deposits, while the ledger provides a common mechanism for coordinating transactions between institutions. Final settlement still occurs through established banking channels.

That distinction may prove critical.

Many organisations have shown little appetite for holding cryptocurrencies or exposing core treasury processes to public blockchain networks. The involvement of the 17 banks suggests growing interest from major financial institutions in tokenised deposits as a way to improve payment availability and liquidity while remaining within established regulatory and banking frameworks.

Swift says banks will be able to move tokenised funds around the clock, including outside normal business hours, helping businesses access capital more quickly and manage liquidity more efficiently.

Testing blockchain’s real value

The launch also appears to reflect a broader shift taking place within the banking sector, with many major financial institutions increasingly focused on determining where exactly blockchain can deliver measurable value. Cross-border payments have emerged as one of the strongest candidates because they involve multiple organisations, multiple jurisdictions and significant coordination requirements – all characteristics that align naturally with distributed ledger designs.

In effect, the trial represents blockchain being used for what it was arguably always designed to do: Maintain a trusted and shared record between parties that do not directly control the same systems.

Swift says the shared ledger, first announced last year, was designed and built with feedback from international financial institutions.

“The strong support from banks shows the practical value of this approach,” Chilosi says, adding that it will help scale benefits globally while creating a foundation for future innovation in areas like programmable money and agentic commerce, where automated systems execute transactions and payments on behalf of users.

The scale of the network involved also gives the initiative significance. Belgium-based Swift underpins the vast majority of international bank messaging and says its infrastructure connects more than 200 markets worldwide.

While enterprise blockchain initiatives have often generated considerable hype before falling short of expectations, Swift’s initiative targets a clearly defined operational problem and is backed by institutions already responsible for moving trillions of dollars through the global financial system.

For ANZ and its banking peers, that may ultimately prove blockchain’s most natural home: Not replacing banks, but helping them move money faster.

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The prediction reflects one of the less discussed consequences of the generative AI boom. While early conversations focused on productivity gains, code generation speeds and developer efficiency, software engineering leaders (and indeed, all IT leaders) are now facing a new challenge: Controlling the cost of AI itself.

“Token discipline will not emerge through developer choice alone.”

At the same time, vendors are increasingly moving away from traditional seat-based licensing models towards consumption-based pricing, where organisations pay for the tokens consumed by AI models. As AI deployments scale, token consumption is emerging as a growing cost consideration across the industry. The combination of higher usage and metered billing is creating a cost trajectory that Gartner believes many organisations are underestimating.

On the coding front, Gartner says 40 percent of software engineering leaders are reporting that more than half of their teams are using AI tools to augment software development processes. As adoption grows, token consumption – the units increasingly used to measure and bill AI model usage – is rising rapidly.

Early signs of the cost impact are already emerging with Gartner Peer Insights data showing 23 percent of software engineering leaders are reporting costs of US$200 to US$500 per developer per month in token costs for AI coding agents such as Claude Code, Cursor and OpenAI Codex. For five percent of organisations, that figure has already soared to more than US$2,000 per developer per month.

“Organisations are rapidly moving from experimentation to scaled deployment of AI coding agents, but many are underestimating the financial impact of rising token consumption,” Nitish Tyagi, Gartner senior principal advisor, says.

““AI coding costs will continue to rise as infrastructure investment and profitability challenges push model pricing higher,” Tyagi says. “At the same time, as more developers adopt AI tools, light users are expected to rapidly become mainstream users as familiarity and reliance increase, driving further growth in token consumption and overall spend.”

The concern isn’t simply the price of large language models. Gartner argues that three common behaviours are driving much of the overspending: Giving AI agents too much autonomy, providing excessive amounts of context, and failing to establish feedback mechanisms to identify and prevent wasteful usage patterns.

“Token discipline will not emerge through developer choice alone,” Tyagi says, noting that developers will naturally optimise for speed and convenience, rather than token efficiency. Instead, organisations should treat token consumption as a governed part of their engineering operating model, the analyst company says in its How to Optimise Token Consumption for AI Coding Agents report.

That recommendation may be particularly relevant as organisations race to adopt increasingly capable AI coding agents. Unlike traditional coding assistants that suggest code snippets or provide developer support, agentic platforms can take on broader development tasks autonomously. Gartner points to increases of 100x over coding assistants experienced by software engineering leaders.  

Gartner says organisations need to establish clear rules around when AI agents should be used and how much autonomy they should be granted.

The report recommends categorising software development activities into three tiers: Developer-only work for sensitive, operationally risky work or work not worth the token cost; AI-assisted development where humans remain in control, and fully autonomous agent-led development. AI-assisted development should be the default zone for most day-to-day engineering because it improves throughput while maintaining human oversight and avoiding some of the introducing costly agentic loops which can occur when autonomous systems repeatedly call models and tools without adequate controls, Gartner says. Those with lower software engineering maturity and limited governance frameworks are also advised to prioritise assistive AI over autonomous development.

Governance is another area Gartner says requires urgent attention.

Less than one in three engineering organisations currently has formal AI governance policies in place. Gartner says engineering leaders should assess both the maturity of their software development practices and existing AI controls before expanding the use of autonomous coding agents.

“Organisations should introduce mechanisms such as token thresholds, escalation policies and automated monitoring to manage growth. Embedding these controls into engineering workflows ensures consistency and prevents uncontrolled costs.”

The report also highlights what Gartner calls context engineering as a critical discipline for controlling costs.

Every file, document, code repository extract or tool output included in an AI prompt increases token consumption. Gartner advises development teams to treat context as both a quality input and a cost driver, requiring developers to evaluate what information is essential, what can be summarised and what can be removed altogether.

“A mature context engineering practice should teach developers how to structure context so that it is not merely comprehensive, but optimised.”

Another recommendation is to avoid defaulting to premium AI models for every task. Instead, Gartner advocates model-routing approaches where smaller, lower-cost models handle routine work, with tasks escalated to more powerful and expensive models only when complexity or risk justifies the additional spending.

“AI coding agents are most cost‑effective when work is broken into smaller tasks that can be handled by smaller models, with escalation only when complexity demands it. Model choice should be driven by task complexity, context size, application criticality, and developer maturity.”

Also recommended is better visibility into how AI coding tools are being consumed, with regular reviews of high-token-consuming workflows as part of sprint retrospectives to identify inefficiencies, refine practices and promote knowledge sharing across engineering teams.

“Most organisations still lack the maturity and frameworks to effectively measure cost versus business impact,” says Tyagi.

The report stresses that higher costs aren’t necessarily bad if they bring measurable business benefits, such as profit, reduced risk, improved growth or support strategic goals.

“The goal is to use AI coding agents efficiently but not to restrict the use of them.”

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One Gartner client began with more than 600 potential AI use cases competing for investment. Unsurprisingly, Gartner’s Luke Ellery recommends companies don’t pursue everything. Instead, he recommends creating a ‘AI funding funnel’ that ranks initiatives based on business value and technical feasibility before significant budgets are committed.

“It’s a great way of helping CFOs understand AI investments.”

For CIOs facing pressure to ‘do more with AI’ the message at Gartner’s recent Data and Analytics conference in Sydney, the message was surprisingly simple: Stop launching pilots and start managing AI investments like a portfolio.

Ellery, Sydney-based Gartner VP analyst, says while organisations have been spending billions on AI, ‘you could say there is no R in ROI, only investment’. A Gartner survey showed 80-95 percent of Gartner clients saw limited financial returns from their AI investments and only 11 percent of CFOs were able to concretely measure financial returns from big AI investments.

Ellery’s assessment? Based on other Gartner surveys, he says the number one thing is picking the wrong use cases. Deploying Microsoft Copilot might help employees save time and feel happier and more productive, but that’s not financial value.

Value vs feasibility

Gartner’s funding funnel requires ideas to be vetted and prioritised across two dimensions – business value and feasibility.

Business value focuses on the outcomes executives care about – higher revenue, lower costs, reduced risk or improved service delivery. It’s an area that will vary for each organisation, Ellery notes. Time horizon is also an important factor here, he says. While last year CFOs were very focused on getting AI returns within the year, that stance has softened somewhat with the realisation achieving AI goals, and returns, will be harder than anticipated and returns will come on a longer time frame.

Feasibility, meanwhile, looks at the practical realities of implementation, including data readiness, technology requirements, skills availability, security controls and governance obligations.

The sweet spot, of course, is funding initiatives that score highly on both measures and will provide easy wins.

But Ellery notes: “Often organisations won’t have many.” All, however, is not lost. Ellery says leaders need to think about how projects work together, evaluating AI initiatives as a portfolio, rather than in isolation.

“In some scenarios it is very hard to get any of the individual projects off the ground by themselves, but if we collect a number of projects together, we can combine the cost and value and risks.

“It’s a great way of helping CFOs understand investments so we can actually create those larger returns.”

Why boring projects matter

He used customer personalisation as an example of an initiative with potentially high business value. The ability to tailor products, offers and interactions to individual customers has long been viewed as an AI holy grail, with obvious implications for revenue growth and customer retention.

The challenge, however, is that many organisations lack the foundations required to make personalisation work. Customer data may be fragmented across multiple systems. Governance controls may be immature. Data quality may be poor. Technology platforms may not be integrated.

As a result, what appears to be a high-value opportunity often scores poorly on feasibility.

By contrast, a much less glamorous project – such as automated client call summarisation – may deliver only modest business value on its own. It is unlikely to transform an organisation’s growth prospects or dramatically improve profitability, yet it may be significantly easier to implement.

More importantly, the project may capture and structure customer information essential for more advanced personalisation initiatives later.

Seen that way, the lower-value project becomes a stepping stone to something much bigger.

“We need to look at all these initiatives as a group in a broader view,” Ellery says. “The problem is that a lack of consistency prohibits us from actually achieving differentiation,” he says, arguing that organisations often need to fix underlying operational and data problems before they can use AI to create competitive advantage.

Building foundations before differentiation

Many AI projects fail not because the models are inadequate, but because organisations do not have accessible, well-governed data available for those models to use.

Technical debt presents a similar challenge. Legacy systems often store valuable information in formats that are difficult to access, integrate or analyse. Organisations may also need to invest in security, governance and compliance frameworks before deploying AI more broadly.

These investments can be difficult to sell with boards and executive teams naturally attracted to customer-facing use cases and ambitious transformation projects. Few get excited about data architecture, governance frameworks or system modernisation. Yet those investments can determine whether more ambitious AI initiatives succeed or stall.

Ellery pointed to the banking sector to illustrate that, noting years of core banking modernisation efforts as an example of organisations improving consistency across technology environments.

“That’s probably why some of the banks are more ahead in the AI race than others, in terms of realising the value of AI.”

In some cases capability-building projects lacking immediate business impact may be the highest-value investments an organisation can make.

Making the financial case

After vetting and prioritising – providing the litmus test for funding – Gartner’s funding funnel focuses on the crux of the issue – the funding. He noted there are different types of value for organisations. ‘Green money’ provides direct, measurable financial outcomes that appear in profit and loss statements, such as increased revenue or reduced budgeted costs. These are the benefits CFOs tend to care most about because the cause-and-effect relationship is clear.

‘Blue money’ by contrast, includes measures such as customer satisfaction, employee experience and Net Promoter Score. While these metrics may contribute to future financial performance, they don’t guarantee a return and can be difficult to directly link to revenue or profit with less direct correlation.

Ellery also warned against relying heavily on ‘cost avoidance’ arguments, such as delaying a system upgrade, noting that financial leaders often place less weight on savings that have never formally appeared in a budget.

“What we’re doing is putting all this information together on a slide so we can make a determination with the CFO.”

When cumulative costs are higher than the benefit – as with the earlier customer personalisation example – there’s a chance to flip the conversation and argue it as a cost leader to enable you to do other projects – or to bring it into a wider program.

Ellery noted the success of a multinational DIY and home improvement goods company. “They used a system dynamics model and did scenario simulations over three and five years to actually figure out how to order, how to do promotions with feedback loops.”

Targeting 10 percent revenue growth, they nearly got it, coming in at nine percent.

“But they also stabilised their supply chain, which unleashed about $120 million in working capital, and they also deferred the expansion of their processing facilities, which saved them about $25 million in capital costs.”

A courier company increased on-time deliveries by 25 percent, cut idle time by 20 percent and reduced fleet expansion to three percent through use of ‘a very interesting agent-based model, where they had agents represented for vehicles, drivers, customers as autonomous agents’ and micro-hubs.

And a hospital, aiming to reduce emergency department wait times by 15 percent in three, months used AI in its demand forecasting and rostering. Their wait times dropped 77 percent and – as a side benefit – they also saved $100,000 in overtime through data-driven staffing.

“If we can target the value that we’re trying to optimise, it makes it so much easier for us to build these AI systems to actually realise those outcomes and to optimise them.”

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The deployment, built on Amazon Connect, has shaved more than two-and-a-half minutes off average calls for the 150+ year old company, one of New Zealand’s largest publicly listed general insurance companies, removing more than 796,000 minutes of customer time across sales, service and claims interactions.

“By bringing interactions into a single platform and integrating customer data, we’ve enabled real-time meaningful AI support for our frontline teams.”

But the more telling detail sits behind those numbers.

Paul Johnston, Tower CEO, told iStart the project centred on consolidating customer interactions into a single platform and combining that with integrating customer data to deliver AI support as conversations unfold.

“By bringing interactions into a single platform and integrated customer data, we’ve enabled real-time meaningful AI support for our frontline teams,” Johnston says.

That support is delivered during live calls, with real-time transcription across every call and AI-assisted guidance removing the need for agents to pause interactions to take notes or search for information, and there’s less chance of missing important details.

Rather than building bespoke AI capability, Tower leaned on what was already available within its platform, with Johnston saying most of the capabilities were delivered out-of-the box, with effort focused not on customisation, but integrating those tools into day-to-day operations.

The core of that work sat in data and knowledge.

“Our focus has been on strengthening our core knowledge base and integrating this seamlessly with the platform, ensuring agents receive accurate, up-to-date guidance,” Johnston says.

That meant ensuring information feeding AI responses was well-governed and current, so it could be surfaced in real-time to support customer conversations.

The deployment was designed to sit inside existing workflows rather than alongside them. Johnston says embedding AI into how work was already done reduced friction during rollout and allowed the system to evolve based on frontline use.

Real-time feedback loops

“We’ve been able to continually refine the platform based on what actually works best for our teams,” he says. Real-time feedback loops ensure continual improvements in responses. Involving frontline ‘change champions’ throughout also aided the process, he says.

As a result, Johnston says teams quickly saw benefits, with AI supporting conversations, reducing complexity and improving consistency in responses.

“Our ability to adapt and adopt has been a real strength, supported by a strong culture of innovation and a focus on bringing our people on the journey from day one.”

Alongside the reduction in handling times, he says employee and customer net promoter scores (NPS) have improved, while quality assurance coverage has increased.

The system is also generating a richer data set to inform future product and service decisions.

Monitoring is built into the deployment. Johnston says quality is assessed – and improved – using automated evaluation alongside agent feedback, providing real-time visibility and enabling issues to be identified and addressed as they emerge.

Across the project, Johnston points to a combination of strong data, well-governed knowledge and workforce engagement and empowerment as underpinning the outcome.

“A big part of our success has come from getting those foundations right, while continuing to build and improve over time.”

Johnston describes the work as part of a broader digital transformation, with further opportunities to expand how AI supports both customers and frontline teams.

“We see this as part of our ongoing digital transformation, with continued opportunities to scale and evolve how AI supports both out people and our customers,” he says.

“Looking ahead, we’re poised to invest further in technology and AI-enablement throughout FY26. This is a critical part of our strategy that will drive greater efficiencies and continue to enhance our customer experience over the medium- and long-term.”

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Within two weeks of launching the feature in the realestate.co.nz app, more than 60,000 searches had been clocked up. It’s still a tiny percentage of the company’s searches, but  Simon Hargraves, realestate.co.nz chief information officer, is optimistic.

“We had just finished a project to get our data into a good state. Without that, it would have been extremely difficult to do this work.”

He told iStart users are increasingly comfortable working with AI and expectations for search are changing. “They want to be able to express their search intent more naturally, rather than just using predefined filters or having to use exact keywords.”

The AI-image search gives users the ability to search ‘at a completely different level’ – searching what’s actually in photos.

What users are searching for, however, hasn’t changed in early searches. “We have a list of traditional keywords people were searching for and generally it’s following the same trend,” Hargraves says.

What has changed is how effectively results are being surfaced. Traditional keyword search relies on exact inputs from both sides, with agents required to include the right terms in listings and users having to guess and input the same wording. AI image search removes that dependency, Hargraves notes, with the AI system examining the photos and pulling out key features.

The system also changes how results are presented, with the platform able to surface the image where the feature has been detected, rather than returning a listing with no obvious visual confirmation.

The accuracy challenge

Hargraves says the feature itself was built and released quickly – one month to build and another month spent testing, tuning and getting feedback from the business. “The really challenging part was more the focus on accuracy and making sure the results aren’t frustrating for users because the way the semantic search works is it expands what the user is searching for to understand intent and then expands the search out from there.”

As an example, early on a search for wine cellars associated them with luxury properties – returning a broad range of luxury properties rather than those with wine cellars. Worse, searching for a property with an accessible ramp expanded out to include staircases.

“Those kind of cases are obviously going to be super frustrating to users when you’re getting the opposite of what you’ve actually search for. So we spent probably half the project time actually testing it internally, across the whole company and getting feedback from users of examples where it was wrong. Then we spent quite a bit of time tuning the system.

“Making sure the experience wasn’t frustrating was the most important part.”

Data does the heavy lifting

Behind the feature sits a significant data effort.

Realestate.co.nz had just completed an 18-month re-platforming and centralisation of all of its data into a single Snowflake platform, standardising definitions and consolidating multiple data sources across the business.

“That was a huge foundational piece that allowed us to build it very quickly.”

The work enabled the rapid development of AI features, but also highlighted a clear dependency.

“You have to have that data foundation in place… if you have bad data, then you’ll get bad results out from the AI.”

In image-based search, that extends beyond structured data to the quality of photos themselves – something the company doesn’t control.

“The AI performs much better when the features [are] clearly visible,” Hargraves says.

But he notes the higher the quality the images and the larger they are, the more cost to process via AI. “There are quite a few variables that we had to take into account and tune to try and get the right kind of cost versus quality.”

He deliberately frames the AI image search as an experiment. “The technology has evolved really rapidly and these kind of features are becoming easier and easier to implement so it makes sense to build the feature and release it to users and see if it’s used and useful.”

The company is less focused on initial uptake than on whether users will return. As Hargraves notes, if users don’t find it useful, they won’t come back to it again – a key test for the future of the system.

To manage expectations, it has been clearly labelled as a beta. “Because… with AI, it’s never going to be perfect.”

Beyond search

The company’s broader approach reflects a pragmatic view of AI. Internally it is being used across the engineering process, and teams are encouraged to experiment through hackathons and rapid prototyping.

“These tools are making it super easy and super quick to build out things and test them internally and build proof of concepts,” Hargraves says.

At the same time, decisions to productise those ideas need to be made carefully, he says, noting the challenge of ensuring projects show ROI and aren’t constantly ‘experiments’.

“You have to make sure projects make sense… and as with anything its prioritising what you have in your roadmap case by case with cost versus value.”

In that context, AI image search is seen as a logical extension of existing capabilities, rather than a standalone transformation.

Hargraves says the company is already working to merge AI image search with traditional keyword search into a single, unified experience.

Longer term, there is potential to expand search into other areas, including accessibility requirements and proximity to amenities, though that will depend on the availability and quality of additional data sources.

“Finding a good data source and being able to ingest it and surface it via AI search is going to be the challenge. But I think you’ll see a lot of those features coming over time. It’s just about getting data into a good place first because without that solid foundation you can’t build high quality AI experiences on top of it.”

Beyond real estate

So what’s Hargraves advice for any other companies considering similar tools?

“Getting the data into a good place is probably the most complex thing. We’re lucky because we had just finished a project to get our data into a good state. Without that, it would probably have been extremely difficult to do this work.”

The data needs to be high quality, well-structured and accessible and good governance around it is also required as well.

“Without that, it’s going to take a lot longer and there’s going to be much higher levels of complexity.”

And be prepared to spend time tuning. “The tuning and accuracy piece is going to be the most difficult part to get right from a product perspective,” Hargraves warns.

“With AI image search you don’t have so many of the concerns you’d have with AI in other areas, especially where you have chatbots and people interacting directly with the AI. AI search is an easier place to start but as we get more into potential AI features in future – chatbots and that kind of thing – it becomes more and more concerning from a risk perspective.”

On the cost front, he says there wasn’t ‘massive’ cost. The time spent tuning was the bigger cost, with the company now spending around US$1000 a month for processing all of its listing images.

“Costs are increasing in AI across the board though, so it’ll be interesting to see how it changes over time and it’s something we’re going to have to keep an eye on.”

Hargraves also acknowledges that for some companies, AI image search could surface unexpected content.

“With our platform, the photos have all been taken and verified by vendors and agents, so personally identifying information or anything sensitive is usually scrubbed from the photos anyway. On different platforms, you would definitely have concerns though,” he says.

Despite that, Hargraves says it’s important for all local companies to be experimenting with AI.

There are huge changes coming across every industry. There’s a massive shift in the way people are working in businesses and how they are interacting with AI and that’s changing their expectations of how they use other products too.”

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The new tech hub is the second State-side for CBA – it opened one in Seattle last March – and places ‘squads in residence’ – aka CommBank engineers and technologists – in what the bank describes as ‘one of the world’s most concentrated AI ecosystems’, working directly with partners such as OpenAI, AWS, Anthropic and Microsoft.

“The goal is to have them take away all the learning… and bring [it] back to Australia, to become force multipliers, and scale and compound that capability across our 10,000-plus technologists.”

Matt Comyn, CommBank CEO, says the hub will give the bank’s engineers and technologists access to world-class tools, expertise and partners.

The hub reflects a broader strategy for the bank: Proximity to where AI models are being built and structured pathways to transfer knowledge back to Australia’s engineering workforce.

“This is part of our commitment to working at the frontier of technology, alongside leading global partners,” Comyn says. “We’re investing significantly in our people and capability, because attracting and supporting the best talent means giving them access to the best tools, expertise and opportunities globally.”

Bringing San Francisco skills back

The San Francisco hub is designed as a rotation model. Engineers, product owners and data scientists travel in small squads for short residencies working alongside AI partners and observing how leading organisations are applying new tools and techniques.

For CommBank, the goal is not simply exposure, but replication. Martha McKeen, CommBank lead for AI powered engineering and international tech hubs, says the goal is for the cohorts to take away all the learning they can from the strategic partners, taking that back to Australia to become ‘force multipliers’ and scale and compound that capability across the bank’s technology workforce of more than 10,000 staff.

“Our tech hubs are all about creating incredible surfaces for learning,” McKeen says.

The model builds on earlier success in Seattle, where more than 100 engineers have already participated in similar rotations.

In Seattle, the first cohort back in early 2025 were focused on learning to fast-track adoption of agentic AI and genAI powered solutions to help small business banking customers manage their finances and run their businesses. A second cohort looked at modernising testing to respond to customer feedback faster.

Rodrigo Castillo, CommBank co-CIO central technology, says the new hub will help the bank continue to scale AI solutions, connecting internal teams with where new models are being created. “What we are looking for is connectivity between our teams and places where AI models are being created here in the heart of San Francisco.”

Learnings beyond the tools

For engineers taking part, the value is not limited to access to tools. CBA says it extends to exposure to how leading organisations structure work, iterate on products and integrate AI across the software development lifecycle.

George Beniac, CommBank crew lead, core foundations, says working with OpenAI in San Francisco has changed the way his learning squad is thinking about how it can use AI from planning to product design, to code development and deployment.

Product owner for AI powered engineering, Henry Chan, says the environment itself plays a role in shaping thinking.

“Very quickly, from the moment you land in San Francisco, you notice all the billboards are AI-related. You realise this environment is, by default, AI-powered. Your brain automatically switches.”

For Chan one of the things his team went to San Francisco to learn was how other leading companies were able to move so quickly and how they’ve altered or augmented their product delivery lifecycles over the last couple of years. (His insight: The importance of giving team members the freedom to experiment using AI to prototype, translating thoughts into real life use cases.)

Squads at the hub have also been looking at how AI is reshaping the way software is designed, built and maintained, with a focus on AI-powered engineering. “That is, giving our engineers the emerging best-of-breed, AI-powered engineering tools,” McKeen says. “These tools help them in their everyday workflows, and relieve the toil and burden of manual tasks and allows them to focus on what matters most.

The bank says more than 70 percent of its engineering teams are already using AI tools, with the new hub aimed at accelerating that adoption and embedding more consistent ways of working across teams.

Other Australian organisations are taking similar steps. Telstra partnered with professional services company Accenture last year to launch an AI ‘innovation and research hub’ in Silicon Valley, where Telstra works with partners including AWS, Databricks and Microsoft to build and test AI-based services. However, rather than flying in teams, the Telstra-Accenture joint venture appears to be more of a virtual offering, connecting with teams in Sydney, Melbourne and Bangalore and creating a ‘virtual door’ where teams can ideate, collaborate, build and test in a secure environment.

Australian-founded design platform Canva also expanded its presence in San Francisco last year, positioning the city as a key hub in its global operations and placing teams closer to talent, capital and early adopters.

CommBank’s hub model is built around turning short-term exposure into scaled capability. Engineers are expected to return and apply what they’ve learned across the organisation, embedding new approaches to prototyping, collaboration and AI-assisted development. For organisations across Australia and New Zealand, the key question is not access to new technology, but how effectively those practices can be distributed and embedded across teams.

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New research from Teletrac Navman (those of a certain vintage may recall that Navman was a Kiwi company founded by Sir Peter Maire back in the 1980s) shows the issue is not a lack of technology investment. In fact, 84 percent of fleets have invested in tracking, telematics and integrated equipment platforms to some degree. The problem, Teletrac Navman construction solution specialist James French told iStart, is what happens next – or more accurately, what doesn’t, with many deployments remaining incomplete, creating pockets of insight, rather than organisation-wide intelligence.

“Without all the data… you can be profitable overall, but you’re leaving money in the dirt.”

The report, which is based on a quantitative online survey of 600 companies operating commercial vehicle fleets, including 200 across Australia and New Zealand, 75 percent are still relying on manual logs either as a primary tracking method or alongside digital systems. Fewer than one-third have fully implemented utilisation technology.

French says while most operators recognise utilisation is important – and believe equipment may be underutilised – the actual picture many businesses are working from is incomplete.

“The utilisation information is often incomplete,” he says, describing fleets where some equipment is tracked, while others aren’t, or where telematics is applied only to specific projects, rather than the entire fleet. The result is what he calls a partial utilisation picture – and decisions made on partial data rarely end well.

French says utilisation initiatives commonly stall because projects are left half finished. GPS might be rolled out to part of the fleet, but not all. Maintenance systems live somewhere else. Third-party equipment has its own tracking platform. Acquisitions add yet another layer of complexity, with multiple systems running side by side because no one wants to disrupt what the newly acquired business is comfortable using.

“You’ve got disparate systems,” he says. “GPS sits here, maintenance sits somewhere else, fuel lives somewhere else again.”

Without pulling those datasets together, organisations miss the opportunity to build a full picture of how assets are actually performing – and what they really cost to run.

French says once utilisation data is integrated with maintenance, fuel and financial systems, businesses can calculate their true total cost of ownership per machine, per hour. That’s where the money starts to surface – and sometimes, where uncomfortable truths appear.

“If it costs $250 an hour to run a machine and you’re charging $220 an hour, you’re losing money,” he says. “Without all the data, you don’t know it. You can be profitable overall, but you’re leaving money in the dirt.”

Idling away

One of the headline findings from the research is that equipment is sitting idle up to 50 percent of the time.

French admits calculating idle is fraught with technical challenges.

Basic GPS can tell operators where machines are and when engines are on or off. More accurate utilisation comes when systems are connected into engine data via CAN (controller area network) bus – the vehicle standard designed to allow microcontrollers and electronic control units such as the engine, brakes and lights, to communicate with each other – pulling details such as RPM to distinguish between productive work and an engine running without doing anything useful.

Machine-level integration also matters. A crane truck may be stationary with the engine running, but if the crane is operating, that’s productive use, not idle time. Without that visibility, utilisation data risks being misleading.

Manual logs are also fraught with issues. French points to a real-world productivity study he worked on in a previous role, comparing manually recorded data with machine-generated data.

“We found about a 15 percent difference,” he says.

Human error, transposed numbers, lost paperwork and best-guess reporting cause further issues in manual reporting. With digital systems, French says, the data becomes a single source of truth that can be audited, retrieved and compared across years.

The double-pay issue

Nowhere is the financial impact more visible than in equipment hoarding.

The report found that two-thirds of organisations admit assets are sometimes held onsite but unused, largely due to uncertainty around maintenance and scheduling. French says the behaviour is understandable, but costly.

“If I ring another site asking if they’ve got a 24‑tonne excavator, they’ll often say they’re flat out,” he says. “Sometimes that’s fear they won’t get it back. Sometimes it’s that they don’t actually know whether it’s being used or not.”

Without utilisation data, businesses turn to renting an additional machine – and double-paying.

“If I think it’s being used and I go and rent another machine, now I’m paying for one excavator sitting idle and another one working,” French says. “One is internal money. The rental is external money. That costs more.”

The fix does not require sophisticated analytics from day one. French says even fleet‑wide GPS coverage can immediately change behaviour.

“If I can ring a site and say, ‘I can see that machine hasn’t worked in a week – we’re sending a truck to move it,’ that saves money immediately.”

He cites the example of one client who reported saving roughly $30,000 in just 40 days by identifying idle plant and redeploying assets based on evidence rather than assumption.

For Australian companies, there’s another big win waiting: Fuel tax credits. He says many companies are leaving cash unclaimed simply because they can’t prove how, where and when equipment is used.

GPS and utilisation data can provide an accurate picture of when vehicles and equipment are operating on ‘non-gazetted’ roads where full fuel tax rebates can be claimed.

“GPS gives a very accurate picture of what percentage you’re off road,” he says, pointing to the ability to use geofencing and location data to distinguish between on‑road travel and off‑road work.

The distinction matters across a wide range of real-world scenarios, from trucks and light vehicles operating on job sites as opposed to driving to those sites, to concrete agitators running engines while unloading, washing and equipment once they enter a site. Forestry operations are another area French highlights, with vehicles transitioning from public roads onto private land and becoming eligible for different treatment.

“In Australia there are billions of dollars sitting in unclaimed fuel tax credits and this is one of the areas you make a quick gain.”

Where utilisation delivers fastest value

French says the first integration point for utilisation data should be maintenance. With live hour data, service intervals become predictable, automated and defensible – an operational and compliance win.

From there, fuel data becomes critical, particularly as costs rise and supply remains uncertain. Understanding where and how fuel is being consumed allows operators to narrow down why similar machines are costing more on one site than another – whether that’s environment, operator behaviour or simply the wrong machine for the job.

Critically, this feeds decision-makers beyond the fleet team.

“When it all feeds into a BI platform,” French says, “the CFO can see what machines cost, what they generate, and what happens if you remove assets that aren’t being used.”

At that point, utilisation stops being a reporting metric and starts behaving like what it actually is: One of the most powerful – and under‑leveraged – drivers of financial performance in asset‑heavy businesses.

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AT A GLANCE

• Annexa

INDUSTRY

• Retail and eCommerce

BUSINESS OBJECTIVE

• Support rapid international growth across multiple markets.
• Remove manual finance and inventory reconciliation.
• Ensure systems enable scaling rather than constraining it.

SOLUTION

• NetSuite was implemented as a single ERP platform bringing financials, inventory, costing and sales data into one system across every channel and subsidiary.
• Multi-entity, multi-currency capability and live feeds from eCommerce and point-of-sale enabling real-time consolidation across eight operating countries.
• Scalable platform design to support ongoing growth.

BUSINESS BENEFITS

• Real-time visibility across eight operating countries.
• Reduced manual processes and reconciliation effort.
• Scalable platform supporting continued growth without increasing headcount.
• Stronger foundations for future AI-driven capabilities within core systems.

FOR MORE INFORMATION

Annexa

W: annexa.com.au / annexa.co.nz

How MAAP Cycling is keeping systems hard on the incline…

For fast-growing retail brands, the ravine between commercial ambition and operational capability tends to open quietly.

As transaction volumes increase the systems that supported early growth start to create drag rather than remove it. By the time the problem is visible, it is usually diagnosed as being rather extensive to resolve.

Matthew Nott has managed finance teams through these exact growth phases. He worked on the expansion of tea retailer T2 and the global scaling of skin, hair and body care brand Aesop, to the point at which it was acquired by L’Oreal in 2023 in a deal valued at US$2.53 billion.

Now, as chief financial officer at premium cycling brand MAAP, he oversees the financial operations of a company expanding across eight countries on the same platform.

There’s nothing quite like growth to expose operational gaps…

MAAP was founded in Melbourne in 2014 and now operates via eCommerce, wholesale, and a growing physical retail network. When Nott joined, the technology stack was divided. A financial platform operated in isolation from the inventory tool, and reconciling sales across channels was a manual, convoluted process.

Speaking during a panel session at SuiteConnect 2026, Oracle NetSuite’s annual customer conference, Nott described the moment high-growth businesses outrun their systems. For leaders navigating that transition, his view on what the technology needs to do was clear.

“[For any other businesses in a similar high-growth] stage, where you’re scaling up, you really want to think about ensuring that your technology is going to enable your growth and not hold it back,” he says.

“Often the times where a business has been growing for a period of time, and there’s a moment where the scale and the high growth starts to arise, you’ll quickly outgrow systems. You really need to be thinking about a tool. In our case [that involves] multi-entity, multi-currency, real-time data and reporting, consolidation, intercompany.”

MAAP’s Netsuite implementation, delivered in partnership with Annexa, brought all the company’s transactional data into a single system; financials, inventory, costing, and sales across every channel and subsidiary. Live feeds from e-commerce and point-of-sale now consolidate in real time across all eight operating countries.

“Those things from a Netsuite context are just a given, built in from the ground up, so that doesn’t become part of your decision making when you’re scaling, it’s an enabler for scaling,” Nott says.

The AI mandate

At the same event, NetSuite outlined its next-generation product direction, NetSuite Next. AI capabilities are being introduced continuously across the platform, with NetSuite Next bringing these advancements into a more unified, embedded experience within the ERP core. The solution is expected to be available within the next 12 months.

The release will introduce Ask Oracle, a contextual natural language assistant, alongside autonomous close capabilities designed to reduce month-end friction. AI agents will monitor financials throughout the period, flag anomalies, and handle reconciliations automatically. The goal is a zero-day close managed through AI operating in the background.

Nott expects to consume AI capabilities directly through core vendors rather than building separate models. He favours this integrated approach.

“We’re very much at the start of experimenting with AI … we’re really expecting to rely on our vendors and NetSuite as our core system to deliver a lot of these tools for us to then better use, as opposed to the potential for trying to stitch together your own agentic AI models and having a gigantic technology team to support that,” he says.

“We want to really keep the relationship with our customers pretty human. But even in that space, we think product visualisation and those things are incredibly useful in terms of speed to market.”

The announcement is welcome news for Australian-based ERP and NetSuite systems integrator Annexa, which had worked closely with MAAP on its integration.

“Customers have been coming to us for advice on how they can apply AI capabilities, particularly as they’re emerging across NetSuite and the wider technology ecosystem,” Annexa director Matthew Owens said during a separate webinar.

“There’s a huge amount of opportunity there, and a big part of our work now is helping teams identify where AI can genuinely improve business processes and how to introduce it safely into operational systems.”

Doing more with the same resources

Finance leaders are asking a consistent question across the industry. The focus has shifted from managing immediate scale to driving long-term efficiency without proportionally expanding headcount.

MAAP is continuing to grow, and Nott’s confidence in the current technology stack to support that expansion is high, and his attention has shifted to the question that sits behind it, how to extract more output from the same team as the business scales.

“We’re continuing to focus on growth, and we’re still in a high-growth phase. We’re wanting to open more stores in more countries and regions,” he says.

“The pleasing thing to me is that to do that within our current tech stack environment, the technology is in no way holding us back.

“The theme that I hear from a lot of other CFOs is, how are we going to do more with less? We’re not necessarily wanting to reduce our resources overall, but we just want them to be able to do more and allow them to grow and achieve more.

“These tools that are coming to market are constantly blowing me away with what they can do, so there’s a real preparation to take advantage of them.”

Getting the foundations right

The efficiency gains Nott described on the panel at SuiteConnect depend heavily on what happens before and after go-live. During a separate webinar discussing international growth strategy for retail brands, he was candid about where the complexity concentrates.

“The integration is the devil in the detail. The integration is the hardest part of the entire thing. That’s the area, one hundred percent, to be aware of and focus on,” Nott says.

Nott had worked with Matthew Owens, director of Annexa, in a previous role and brought him in when it came time to scope a solution for MAAP.

Managing multiple third-party logistics providers across different markets has been one of the more demanding elements of the build, with MAAP changing 3PL providers more than once since go-live, each move requiring new technical connections.

Annexa’s Owens understands what retailers need from a systems integrator at this stage of growth, noting that the conversation should start with commercial understanding rather than software features.

“It’s not so much about buying a bit of software and understanding the features of a module. It’s about, can the partner or the system integrators that I’m speaking with understand holistically how to run an online retail business? And how are you going to enable us to actually facilitate growth, expansion, integrations and do it in a way that’s going to be quick to market and sustainable to support?” he says.

“Getting the core system live is the big project, the big change. But equally important is how you sustain it. Do you have the right partnerships and people available when you need them? This is important not just for keeping the lights on but also for the bigger ticket innovation initiatives that retailers can take on” he says.

Annexa has supported a number of Australian retail and consumer brands through similar transitions.

For example, Aussie skincare brand Ultra Violette re-platformed its operations across five global markets in six months, moving from fragmented systems to a single integrated ERP built for scale.

Meanwhile, Davie Group, best known for The Oodie, overhauled its global fulfilment model, shifting from a 4PL structure to direct 3PL integrations embedded in NetSuite, unlocking real-time visibility and reducing fulfilment delays to under 24 hours.

Furthermore, Global biotech company Life Cykel’s move to NetSuite gave the business the operational visibility and control needed to enter the competitive US retail market, a step that fragmented legacy systems would have made significantly harder to execute with confidence.

For growing retail brands, the technology decisions made during periods of high growth tend to compound, in both directions. The right foundations enable speed, visibility, and efficiency at scale. The wrong ones cause operational drag that is expensive to diagnose and harder to unwind.

As embedded AI shifts from emerging capability to standard infrastructure, the businesses best placed to take advantage will be those that already have their data, systems, and integrations in order.

Annexa’s Owens says this positioning will really drive how effective AI can be from an embedded operation perspective.

“A big part of what’s changing right now in AI is how it’s starting to show up inside the systems that finance teams rely on every day,” he says. “That’s where it becomes more relevant, because it’s no longer sitting outside the business as a separate tool, it’s starting to influence the workflows and decisions happening inside core systems.”

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“We started using machine learning and predictive analytics about seven years ago, so this isn’t new for us” Bain tells iStart. “What people think of as AI now is really just the latest evolution of things we’ve been doing for a long time.”

“These projects aren’t really AI projects – they’re data projects.”

From the outset, Spark discovered that deploying AI – particularly where customer data is involved – raised complex questions that couldn’t be solved by technology alone.

“When you’re building models, it can be hard to explain how they choose. So the starting point for all of this was really strong ethical guidelines around how we use the technology.”

Rather than reacting case by case, Spark invested early in defining what it considered acceptable – and unacceptable – uses of AI. “What that looks like: What do we want to use this for, what data is acceptable, how is the data stored securely, and making sure that if a model does something we can explain why it did it.”

The principles were designed to be enduring, rather than technology-specific.

“The technology changes really quickly,” Bain notes. “But if we start from a foundation of what we believe is right and wrong as a business, and what we would never do – even if it was commercially attractive – then those principles still apply as the technology evolves.”

Over time, those principles were embedded operationally, supported by internal tools Spark developed to help teams assess proposed AI use cases before they’re deployed. “We’ve now got tools that allow our people to see the use case, understand what it’s being used for and the system will flag whether this is permissible.” The tool translates Spark’s ethical principles into practical decision-making, helping teams evaluate how data will be used, whether a human needs to remain in the loop and whether the use case aligns with published governance standards. Embedding these checks early reduces ambiguity and gives teams the confidence to move quickly once a project is cleared, Bain says.

He says this foundational work gave Spark a level of maturity before generative AI entered the mainstream.

“We already had a baseline. Our teams understood the effects, the principles and how they turn into actions.”

A Skinny test

That groundwork was tested with an ambitious project to clone a customer for an advertising campaign for Skinny – Spark’s low cost mobile and broadband brand – in what Bain says was a world-first.

“We’d never cloned a human before,” he says. “That’s a whole new level. Someone’s identity. Their voice. Their mannerisms and physical likeness.”

The technology made it possible to produce creative content faster and at a lower cost – and it feed into the Skinny brand – ‘cheeky and innovative’, using AI based on a real person, rather than a completely synthetic human to keep marketing costs low.

“We could put her in space. We could put her on the moon. We could test creative ideas really quickly and get to a finished product much faster than traditional filming.”

The visible outcome however, understated the work required behind the scenes.

“Above the waterlines is what you see,” Bain says. “Below the waterline was a huge amount of new thinking – particularly around security – because this is actually more sensitive than the personal information we usually hold.”

Skinny treated the AI likeness as requiring a higher standard of protection than typical customer data.

“Before we even captured the data, we had to decide who could access it, how many people, whether it could be downloaded, and where it could live. It could only exist in a very secure environment and could never leave it.”

Legal and privacy teams were involved throughout, running alongside the technical work.

“Some of these things you don’t realise until you hit them, so the practical steps evolved as we went,” Bain says. “Our legal and privacy teams were actively involved, making sure they were always a few steps ahead.

Liz Wright, the customer who was cloned, has remained involved throughout the campaign.

“She was more involved each time. We didn’t just do things and put them out there without her knowing, even where we could have done that legally. We didn’t think that was the responsible way to handle it.”

There are clear limits too, on usage. “We have rights for a defined period, and then we destroy the data. We don’t want to hold it for longer than we need to.”

Guardrails unlock speed

While the governance work was intensive upfront, Spark says it was this effort that now allows teams to move quickly.

“What we found was that we spend more time upfront evaluating the risks and making sure we have those covered. But once the guardrails are in place, teams can move very fast inside them.”

Bain argues that the common perception – that AI governance slows innovation – misunderstands where the real friction lies.

“Building the models is really quick these days,” he says. “The hard part is the guidelines and the ethical approach.”

Once teams understand how AI works and what the boundaries are, Bain says fear drops away. “When people understand the technology and the risks, they’re emotionally comfortable with it, that’s when they can really move.

Bain notes that AI governance must accommodate technologies that change continuously. “These models are doubling in capability every six months. You can’t imagine now what will be possible in two years.”

Rather than constantly rewriting rules, Spark applies the same principles to each new use case as it emerges.

“You need to govern it like a piece of technology that will constantly change,” Bain says. “Have broad principles, then apply the same framework every time.”

That approach, he says, creates clarity internally and avoids paralysis. “It means people are never ambiguous about where the business stands. And it lets them move quickly within those guidelines.

Hard won lessons

When asked which AI capability Bain is most proud of at Spark, he points not to the latest offering, but to its customer intelligence platform that uses hundreds of machine-learning models to understand individual customer preferences and predict what will be most relevant to them. “We now have hundreds of models running against our customer base that say things like: Heather loves music, she’s not price-sensitive, she prefers iPhones, she’s an early adopter,” Bain says. That insight is used across channels – emails, texts, retail stores and call centres – to personalise interactions in real time. “What we found was that we massively improved engagement with those communications.”

Adding that same intelligence helps frontline staff make more relevant recommendations when customers get in touch. “That’s a pretty cool thing – and it’s still pretty unique in the market today.”

Another internal AI tool is a system allowing staff to query financial and performance data using plain language, rather than writing manual SQL queries. Traditionally, Bain says, answering questions about revenue, sales or margins meant a slow loop between analysts, spreadsheets and follow-up requests. “We built an AI that could understand text, turn it into an SQL query, query the database and then create a multimodal report with graphs, tables and written insights.”

What once took days now happens in seconds or minutes, dramatically speeding up decision-making and allowing finance teams to focus on higher-value analysis rather than producing reports.

So what are Bain’s three key tips for companies finding their way with AI and data?

Get your data in order first Bain says data quality is the single biggest constraint on successful AI use. “These projects aren’t really AI projects – they’re data projects,” he says, adding that ‘the underlying data is 90 percent of the work’. Where data definitions are inconsistent or ambiguous, models become confused and unreliable. By contrast, when data is clear, structured and robust, Bain says AI solutions can be deployed very quickly and deliver real value.

Start now — the learning curve is unavoidable

Bain warns that delaying adoption doesn’t reduce complexity, it just postpones learning. “If you don’t get started now, there’s a learning curve – and that learning curve will be the same no matter when you start,” Bain says. He recommends beginning with low‑risk use cases so organisations can build confidence, understanding and capability before scaling more complex applications.

The technology is no longer the barrier — mindset is What used to be expensive and exclusive is now widely accessible. “What used to only be possible for a Spark is now available to small businesses – we’re using the same technologies,” Bain says. The real work is educating teams, demystifying how AI works, and putting appropriate guardrails in place. “By understanding it, you can mitigate the risks,” Spark says, adding that responsibility and confidence – not fear – are what allow businesses to move forward productively.

The post Spark’s Matt Bain on the unsexy work enabling AI success appeared first on iStart leading the way to smarter technology investment..

CPA Australia’s latest Small Business Survey of more than 4,100 businesses across APAC, shows both Australia and New Zealand are sitting near the bottom of the region for growth, innovation and technology adoption. It’s the second year New Zealand has ranked last for growth, something Rick Jones, CPA Australia regional head, dubs ‘a worrying trend’.

“Existing technology spend is not translating into profitability.”

In New Zealand just 38 percent of small businesses reported growth in 2025 – up on last year’s 36 percent but still well below the APAC average of 62 percent, and ranking New Zealand last out of the 11 markets surveyed. Just 26 percent said technology investment improved profitability, less than half the regional average and digital adoption remains weak. Australian results paint a similarly weak picture of low digital uptake and poor returns from tech investment.

Jones told iStart the problem is two-fold: Overall digital uptake in both markets remains well below Asia Pacific peers, and where businesses do spend, investment is heavily weighted toward basic IT such as computer equipment, rather than tools that change how the business operates. Online sales, digital payments and use of social media for customer insights, rather than visibility alone, remain underused, even as productivity pressures intensify.

With productivity firmly on the political agenda in both countries this election year, Jones says lifting small business technology should be a central priority.

“Our data consistently shows that businesses which invest effectively in technology grow faster, hire more people and are more likely to innovate. Countries like Singapore have demonstrated what targeted digital support programmes can achieve – there are proven approaches in our region that could work here,” he says.

Low adoption, low returns

The survey data shows that limited digital adoption remains a key issue across both markets, but the effect is most pronounced in New Zealand.

Only 32.4 percent of New Zealand’s small businesses generated more than 10 percent of their revenue from online sales in 2025, less than half the Asia Pacific average and the lowest results across all surveyed markets. Use of digital payment platforms is similarly low with just 35.4 percent receiving more than 10 percent of sales via services such as PayPal, Apple Pay or Google Pay, again ranking last in the region.

Technology use remains basic elsewhere too. Almost 31 percent of Kiwi small businesses don’t use social media for business purposes at all, compared with a regional average of 12 percent.

The pattern is mirrored in Australia, where 44 percent of businesses reported earning more than 10 percent of revenue online, still well below the Asia Pacific. The report notes however, that while New Zealand and Australian small businesses continue to be the least likely to generate online sales, Australia, at least, experienced an improvement year on year in 2025, while New Zealand’s decline continued. In Australia, 68 percent used social media for business, trailing the regional norm of 88 percent.

The gaps matter because the survey shows a strong relationship between digital adoption and performance. Businesses with higher use of online sales channels, digital payments and basic automation are most likely to report growth, hiring and innovation. “Technology continues to play a more critical role for high-growth small businesses than for other businesses,” the report notes.

Maintenance, not momentum

Where small businesses do invest in technology, the type of investment helps explain why returns remain weak locally.

In New Zealand, computer equipment was again the most heavily invested tech category last year – continuing a trend echoed repeatedly in the survey since 2020 – followed by website and accounting software. Australia was similar, favouring accounting software, followed by computer equipment and website.

In comparison, high-growth businesses across the region were most likely to invest in AI followed by cloud computing and CRM software.

CPA says this indicates A/NZ spending is often directed toward replacement or maintenance, rather than productivity-enhancing systems.

The profitability data reinforces that conclusion. Just 25.6 percent of Kiwi small businesses surveyed said tech investment improved their profitability in 2025, compared with a survey average of 56.3 percent. Australia recorded a similar outcome, with only 30 percent of businesses reporting profitability improvements from tech investments.

CPA links this to quality, rather than quantity of investment. Simply purchasing hardware – replacing devices, upgrading networks, maintaining on-premise systems – may keep the lights on, but it rarely changes cost structures, revenue flows or decision-making.

“What the survey shows is that existing technology spend is not translating into profitability,” Jones says. He says where business are investing it’s often without the sequencing or support needed to make the tools deliver operational change.

“The question is, how do we support these business owners in that capability piece, so they are not just investing in technology, but are investing in the right technology? That’s not just about using it right, it’s around making it work for the business so they are seeing returns,” he says.

Cashflow and time pressure points

Across both countries, the operational pressures facing small businesses underline why businesses are cautious – and why digital matters.

In New Zealand, 54 percent of businesses said increasing costs had a major negative impact in 2025, ranking highest among surveyed market. Hiring remains weak with only 7.4 percent increasing employee numbers, and just 14 percent expecting to hire in 2026. Innovation plans are similarly subdued with only 4.9 percent planning to introduce a new product, service or process in the coming year.

Australia’s results show similar stagnation, with CPA Australia business and investment lead Gavan Ord warning that prolonged underperformance among small businesses is feeding into a wider productivity slowdown. “When small businesses underperform year after year, it become a national economic problem, not just a sector issue,” he says.

Against that backdrop, the technologies most closely linked to measurable gains are not experimental. Jones points to practical improvements such as faster invoicing and payments, online ordering and booking systems and digital finance and reporting tools that reduce manual work across payroll, inventory and customer management.

He notes when businesses experience clear time savings and faster payments, confidence in technology investment tends to rise, easing hesitation around further adoption.

The older demographics of Australian and New Zealand businesses also has a role to play in tech adoption. New Zealand has the oldest small business ownership profile in the region, with 68 percent of owners aged 50 or over. Australia shows a similar generational divide, though less pronounced.

“It’s not an age thing in isolation, but what the survey showed is that business owners under 40 certainly reported growth,” Jones says. “They showed a lot more revenue through online sales and their digital and tech uptake is a lot higher. Younger business owners have a higher risk appetite and are more likely to invest in digital capability.”

In the wake of the survey results, Jones says business technology adoption needs to be made an essential priority for New Zealand (and Australia’s) growth and productivity agendas.

“We need to introduce some better sequence digital adoption support programmes,” he says, suggesting we look to Singapore for examples of programmes which have a proven track record in providing comprehensive support for small business.

“The government should consider designing business digital support programmes with more deliberate bundling and sequencing of measures, drawing on approaches used in Singapore,” CPA Australia says. “This would increase programme effectiveness, accelerate the diffusion of productivity enhancing technology and promote more effective use of existing digital capabilities. Over time this would support stronger productivity, greater business dynamism and a more competitive small business sector.”

In Australia the organisation is also calling for government to incentivise tech adoption and the development of stronger digital capability.

CPA is also calling for a coordinated package of measures to lift participation of younger people in small business. In New Zealand, that includes a ‘start-up apprenticeship’ or mentoring programme and improved access to finance and professional advice for younger owners, potentially through a ‘First Business Owners programme’ connecting participants with accredited advisers and possibly including a SME loan guarantee component.

Jones, who dubs the survey a ‘challenging read’ for New Zealand, says it’s not just about government investment, however. He’s calling for other organisations and consultants to step up and provide the mentoring relationships to help small businesses, and for the businesses themselves to more actively share with other small businesses their successes and learnings. CPA Australia itself is working on providing extensive professional development for its own members to help them on the journey – and ensure their small business customers can also move forward.

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The report is based on ‘insights’ from more than 4,000 eCommerce founders which Australian company Ecommerce Equation has worked with, and draws a clear line between founders who are seeing commercial impact from AI and those who feel increasingly overwhelmed by it.

“Where that understanding is missing, AI simply creates more activity, complexity and noise.”

The report highlights that AI performs best when companies already understand their business constraints. Those seeing real gains are the ones who know exactly which problem they’re trying to solve.

Or as says Jay Wright, Ecommerce Equation founder, says:  “The founders getting real results aren’t the ones doing the most with AI. They’re the ones who knew their business well enough to know exactly where to point it.”

Founders who skip this step tend to deploy AI broadly, without a clear objective or identifying a bottleneck, resulting in more output but little impact on revenue, margin or time saved, a pattern described as  ‘activity without moving the dial’.

In contrast, those who are seeing results are described as starting with a precise diagnosis: A conversion issue on one product, uncertainty in reordering decisions, a slowdown in creative testing or excessive manual operational work. In these case, AI is applied narrowly to the bottleneck and measured against a defined outcome, such as conversion rate, marketing efficiency, time saved or cash conversion speed. In essence, AI doesn’t fix unclear fundamentals; it amplifies existing systems. Where founders already know what ‘good’ looks like in their business, AI accelerates progress. Where that understanding is missing, it simply creates more activity, complexity and noise.

“The short version is this. AI is delivering real value for a small number of founders who have done the diagnostic work first. For everyone else, it’s generating activity without moving the needle.”

Where AI delivers real value: Revenue and conversion

The strongest, most immediate wins documented in the report occur on the revenue side of eCommerce operations. These include conversion rate optimisation, creative production, advertising performance and customer experience.

Lead-side work of getting products in front of the right people and converting are where most brands find their first meaningful wins, the report says, with successful brands using AI to tighten the connection between product and customer with clearer landing pages, tailored ads and a stronger read on what is resonating and the speed to act on it. “The feedback is fast, the impact is visible and the tools are mature enough to act on.”

For those who are getting it right, the report claims the wins are visible and fast, with conversion rates jumping 24 percent in a week from a single tool built around one specific customer problem.

That 24 percent figure relates to Australian apparel brand The Lullaby Club. It identified that a best-selling product fit differently from the rest of the range, rendering the standard size guide ineffective. A custom AI fit-finder was built in Claude for that single product. When it was tested with the 40,000-strong customer community, it achieved a 97 percent sizing accuracy. Within a week, conversion increased by 24 percent and returns fell. With confidence in that project, Lullaby turned its focus to other initiatives including a velocity trends tracker to show how products were selling and trends, using the same data foundation.

“We’re seeing brands go from sub-three percent to 7-11 percent conversion every day by feeding AI the right context about the customer,” the report says of some of the quick wins achieved.

The report also points to growing, if less headline-grabbing, wins on the operational side. Inventory forecasting, purchase ordering and customer service workflows are emerging as areas where AI is beginning to reduce manual effort and uncertainty.

Companies using AI to draft purchase orders, track sell-through rates and flag shifts in momentum are tightening cash conversion cycles and reducing guesswork.

Australian independent apparel brand Dr Moose is one example. The company identified that growth was being constrained its website. Rather than outsourcing work to an agency, she used Claude tools to redesign site UX, introduce bundles and adjust commercial settings herself. Changes previously scoped as a $15,000 web development project were implemented internally, lifting daily revenue from around $600 to $3,000. To get the most from the tools she used ChatGPT to work out what to ask Claude, avoiding burning tokens on trial and error.

Where AI falls flat

The report is equally direct about common failure modes. The most frequent is confusing activity with impact. Those who deploy AI before identifying a real bottleneck often rebuild systems that already work, or chase issues they don’t have.

But the report also notes there are real risks companies need to understand before they go too far down the rabbit hole. “AI will produce data it doesn’t have, confidently and without

flagging it. It too easily gives everyone asking the same question the same answer. And it will sand off the rough edges that make your brand distinct if you let it.”

Those getting the most out of it are the ones who stay in the loop, sense check the output and never let it make the call they should be making themselves, the report notes.

The report leaves little ambiguity about what separates results from noise: AI delivers value where it is applied with intent, against clearly defined constraints with humans remaining closely involved in the outcomes.

Where it is treated as a general productivity layer or a substitute for decision‑making, it tends to add complexity rather than remove it. The implication for eCommerce founders is practical rather than philosophical: AI works best not as a strategy, but as an execution tool, applied deliberately, measured against specific outcomes, and expanded only once it proves its worth.

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The long-awaited strategy and accompanying Cyber Security Action Plan 2026-2030, released earlier this month, signal that cyber resilience must now be treated as a core governance, risk-management and strategic decision-making responsibility. It also flags that regulatory change is likely on its way.

“The Strategy clearly signals that regulatory reform is being considered.”

Alongside the Strategy and the Action Plan, the Department of the Prime Minister and Cabinet also released a discussion document seeking industry feedback on a new approach to the cybersecurity of critical infrastructure.

In it together

The Strategy adopts a whole of society model, outlining shared responsibility on government, industry and individuals. Businesses sit at the centre, with the Strategy’s four national objectives – Understand, Prevent and Prepare, Respond, and Partner, defining practical expectations.

Understand is around improving cyber awareness and literacy across organisations and New Zealanders, providing improved reporting of cybersecurity and sharing of information between government and industry to better understand the threat environment. NCSC will establish a single cyber security reporting service, with processes established for other types of online harm and cyber-enabled crime and redirected to other agencies. Critical infrastructure providers garner special mention, with the strategy noting there will be tailored guidance, including assessments, strategies for risk management and guidance to implement technical controls to protect IT and OT networks, for them (more on that later).

Prevent and Prepare is about strengthening cyber risk management, resilience and preparedness across government and industry. That includes strengthening the existing mandate for the Government Chief Digital Officer to entrench a culture of security from procurement to systems operations, with the Government Chief Information Security Officer establishing and enforcing minimum cybersecurity standards and working with digital supply chain vendors to apply more consistent security controls across agencies. Industry and public consultation on core elements of the regulatory framework is also proposed, including additional non-regulatory actions the government can take to better partner and support critical infrastructure owners and operators to manage cyber risk.

The Respond section says resilience and preparedness must be strengthened across government and industry, ensuring effective, coordinated responses to cyber incidents. Victims of cybersecurity incidents will be ‘supported to remediate and recover’. Legislative frameworks will be modernised to account for the complexity and global nature of cyber threats, with work to address jurisdictional barriers to Kiwi enforcement agencies can access cyber evidence to investigate cybercrime.

Partner highlights the need for ‘strategic and targeted cooperation’, both locally and internationally, with industry and international partners.

The Action Plan, meanwhile, provides the actions required over the next two years to put the Strategy into action, detailing lead agencies for each action.

Notably, the Critical Infrastructure discussion document highlights that if accepted, critical infrastructure entities would be required to develop, implement and maintain a risk management programme aligned with an internationally recognised cybersecurity framework – either endorsed by the NCSC or recognised internationally, such as the US National Institute of Standards and Technology Cybersecurity Framework.

The discussion document also outlines requirements to allow government to collect specific information, such as (initially) a description of their operations including critical components, information on the owners and controllers of the entity, and mapping of key dependencies and interdependencies.

The establishment of a voluntary information exchanges connecting organisations across the critical infrastructure system with each other and the government to coordinate cyber security efforts, a requirement for sharing of certain information with other critical infrastructure organisations – for example information on projected restoration times – and a requirement for cyber incidents to be reported are also proposed.

Regulatory change

The Strategy clearly signals that regulatory reform is being considered across several areas including strengthened requirements for the cybersecurity of critical infrastructure, which encompasses everything from the electricity grid to telco networks, health and transport services and financial systems.

The Strategy document notes that around 120 countries have some form of critical infrastructure regulation. “As a first step, the government will consult industry and the public on the core elements of a regulatory framework, including additional non-regulatory actions the government can take to better partner and support critical infrastructure owners and operators to manage cyber risk.”

The critical infrastructure discussion document highlights that cyber risks are ‘not well understood or collectively managed to a consistent level’ across the system, and that effective protection requires understanding ‘critical components, ownership and control structures, and mapping of dependencies’.

The document suggests the reach of proposed obligations could extend beyond the core operator to include third-party service providers with operational control of critical components.

Another potential area for regulatory change is the potential introduction of a civil pecuniary penalty regime to the Privacy Act aimed at incentivising protection of personal information. The Ministry of Justice will provide advice on options to incentivise protection as part of the two-year action plan.

Thomas Anderson, MinterEllison solicitor says if implemented it would mark ‘a notable shift in New Zealand’s privacy landscape’ which currently has no civil penalties for breaches of the Privacy Act.

“At present, the Act relies on a complaints-based enforcement model administered by the Privacy Commissioner, which can result in recommendations or, in serious cases, referral to the Human Rights Review Tribunal. However, there is no power to impose civil fines for contraventions of the Act (such as a failure to comply with the data security requirements in information privacy principle 5), unlike comparable regimes in Australia, the European Union and the United Kingdom,” he says.

Also on the table is the creation of a potential new offence for handling – including disseminating – illegally obtained personal information. That’s an area the Ministry of Justice has been charged with providing potential advice on the new offence.

The proposal would extend liability beyond the breached organisation to anyone knowingly handling unlawfully obtained personal information. While the intention is to deter malicious actors from circulating stolen data, Anderson notes the wording also captures organisations or third-party recipients who are aware that the information they are accessing or using was acquired through unauthorised means.

“Together, these two actions seem to signal a clear intent: The Government plans to use both stronger Privacy Act enforcement tools and new criminal offences to create meaningful financial and legal consequences for the mishandling or exploitation of personal information after a cyber incident.”

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The round was led by Peter Thiel’s Founders Fund, which has been a long-time investor in the company, backing it in its Series A round in 2017. Existing investors Blackbird, Icehouse Ventures, DCVC, Bond, Bessemer, Ubiquity, NewView and Promus also participated.

“Halter is beginning its largest ever hiring effort, seeking more than 200 people across product, engineering and customer operations.”

The US$220 million raise is one of the largest-ever in agtech globally and smashes Halter’s own record for the largest VC raise by a Kiwi-founded company. It follows earlier reporting that the round was heavily oversubscribed with some of the biggest names in VC keen to get involved.

Halter’s GPS-enabled collars use audio cues and vibrations to contain and herd both dairy and beef cattle within virtual boundaries, enabling farmers and ranchers to move herds from a smartphone, redrawing fence lines from their smartphone. Animal health can also be monitored through the smartphone, along with pasture management, with live data on animal locations, health and feed availability providing a digital twin of farms and ranches, and providing users with access to complex data points in simple and easy to interpret ways. Versions are available for both dairy and beef cattle, with Halter saying beef farming needs its own technology, not a dairy product repurposed for beef cattle as everything about beef systems varies massively. The company has positioned the systems as full herd management, from a smartphone, at US$5 to US$8 per animal per month.

Since launching in the US in 2024, Halter says American ranchers using Halter have built 60,000 miles of virtual fencing. Globally it claims 645,000 kilometres of fencelines have been drawn since 2024.

Founder and CEO, Craig Piggot, who was recently named Innovator of the Year at the 2026 Kiwibank New Zealander of the Year Awards, says Halter was started because of the belief technology could fundamentally change what it means to run a farm, and enable farmers to use innovation to build long-term futures on their land.

“Our farmers need tools that work and the fact they’re using Halter tells us our technology has earned their trust. This raise lets us bring it to far more of them, and faster.”

Scaling up

As part of the Series E expansion stage, Halter says it is beginning a recruitment drive, seeking more than 200 people – its largest-ever hiring effort. Positions will cover product, engineering and customer operations with many based at its Auckland headquarters. Additional staff will also be hired in Australia and the United States in the coming weeks as well. The company employs more than 300 staff, including a team of more than 100 engineers and designers.

Founded in New Zealand and maintaining an Auckland headquarters, Halter also has Australian operations, based in Melbourne, and a US office, which it opened in Colorado in 2024 following its US$100m Series D funding round.

The company, which topped the 2024 Deloitte Fast 50 Index with 1,539 percent revenue growth and secured $165 million in 2025 to accelerate its global expansion, has rapidly scaled across New Zealand, Australia and the United States, with more than 2,000 farmers and ranchers as customers, and a million of the solar-powered smart collars sold.

The Series E funding round will support several initiatives for the company, which says it will enable it to accelerate its commercial expansion across the United States and fund the roll-out of a range of new products in the coming months.

“Investment will continue across product development, including animal health monitoring and pasture management, shaped by how customers are using the system in the field,” Halter says. “The focus remains on supporting farmers building their operations with Halter.”

The company says it will also enter the United Kingdom and Ireland later this year, along with key South American markets.

Piggot says farmers in the UK and Ireland have long expressed interest in Halter.

“The UK and Ireland are very similar to New Zealand in terms of landscape and climate – we know we can have impact there,” he says.

Halter’s growth sits within a wider movement toward virtual fencing and precision livestock management. Research and Markets has put the precision agriculture market at US$9.5 billion in 2025, with projections to reach US$17.3 billion by 2031.

Across New Zealand and Australia, Halter’s uptake aligns with increasing adoption of agricultural automation.

Founders partner Amin Mirzadegan says while agriculture is a “multi-trillion dollar industry that feeds the world”, it remains one of the least digitised sectors on earth.

“Halter is changing that by bringing software, sensors and AI directly into livetock operations in a way that farmers actually adopt.”

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“Once these foundations are established, the lessons learned – both technical and institutional – can be applied to other sectors.”

Koronios, founding CEO and managing director of the Australasian Space Innovation Institute (ASII), says the digital twin, launched last month and a flagship initiative for ASII, isn’t just another farm app or dashboard, it’s a chance to rewrite how a climate-exposed, globally competitive sector makes decisions, replacing delayed, fragmented information with AI-enabled ‘what if’ scenario modelling across climate resilience, biosecurity, water management and productivity, enabling decision-makers to test options, anticipate risks and optimise actions before implantation.

And the benefits won’t just be reaped by the agricultural sector with Koronios telling iStart the initiative will establish a national capability in digital twin infrastructure and space-enabled intelligence, which can progressively support multiple sectors of the economy.

“Agriculture provides an ideal first application because it allows us to develop the core architecture, governance frameworks and data integration methods that are necessary for large-scale digital twins. Once these foundations are established, the lessons learned – both technical and institutional – can be applied to other sectors.”

He says the same principles used to integrate satellite observations, environmental data and modelling tools for agriculture could also support digital twins for water systems, natural ecosystems, coastal environments or disaster management.

Real-time national picture

The elevator pitch is simple – but bold: Bring satellite earth observation data, sensors, climate records, soils, agronomic models and the wealth of other data already available into a single sovereign, AI-enabled system that mirrors conditions on the ground and updates continuously. The digital twin aims to end the fragmentation that has existed in agriculture and turn the abundance of data into decision-ready intelligence that can be used with confidence.

For Meat and Livestock Australia, who along with Elders and Charles Sturt University are backing the initiative, the prize is speed and certainty. Michael Lee, Meat and Livestock Australia’s group manager for science and innovation, told iStart the twin could ultimately reduce risk and potentially cut years from research cycles.

By putting hypotheses through a virtual R&D engine first, teams can refine and narrow failure modes, deploying only what looks likely to work. Producers, in turn, could see more accurate grazing plans, better timed interventions and lower operating risk, with the potential to also unlock provisions for stronger evidence for sustainability and traceability requirements – something brand owners could be rewarded for in a margin-tight industry, where proof that travels cleanly through the value chain is money.

“We are expecting that the digital twin will support evidence-based scenario testing by combining satellite imagery, climate data and agri models in one system. Industry can use this to then compare stocking plans, pasture strategies or herd timing against various climate outlooks and assess expected changes in productivity, groundcover and emissions intensity.”

This supports the kind of repeatable and transparent assessments needed by producers, researchers and other supply chain partners, which could even include banks and other policy advisors who are looking for analytical intel on how agriculture is performing and where it is heading, he says.

Lee has a long list of use cases that most excite him. Top of the list is forecasting pasture growth and testing grazing strategies under different seasons. Climate and drought scenario planning supporting early and confident decisions; landscape pest, weeds and biosecurity modelling for coordinated responses; testing water and infrastructure options for improved productivity and animal welfare and emissions and natural capital modelling using satellite data and agronomic models also feature.

Koronios has a similar list, with the addition of carbon and sustainability monitoring. “As global markets increasingly demand proof of sustainable farming practices, the digital twin could help measure land condition, vegetation cover and carbon outcomes across farms, giving Australian producers a credible way to demonstrate environmental stewardship,” he says.

“What excites me most is that these applications are not futuristic concepts. The underlying technologies already exist. The digital twin simply brings them together into a single intelligence platform that helps farmers make better decisions every day.”

Phased, with challenges…

The program will be delivered in a phased development approach, with Koronios stressing that practical benefits will be realised progressively, rather than only at the end of the program.

First up is the formal establishment of the program’s governance structure, including a steering committee and key delivery partnerships. Koronios says initial workstreams will focus on designing and building the core digital twin platform while working with industry and research partners to validate the first practical use cases.

“During this phase the emphasis will be on developing and testing the foundational capabilities: Integrating key data layers, building analytical tools, and demonstrating how the system can support real-world agricultural decision-making,” he says.

Importantly, early pilot deployments will allow farmers, agronomists, industry partners and government agencies to begin using and benefiting from the platform as it evolves, rather than waiting for a fully completed system. Koronois says these early deployments will provide immediate value while also helping refine the models through real-world feedback.

As the platform matures, the program will expand from pilot deployments to nationally scalable operational services, incorporating additional datasets, analytical models and regional applications. With each phase, new capabilities and insights will become available to users, expanding the value.

“Ultimately, the National Digital Twin for Australian Agriculture is conceived as a long-term national capability – a digital infrastructure designed to support Australia’s agricultural sector for decades to come. Much like national mapping systems or weather forecasting networks, it will act as a shared digital backbone for agricultural intelligence, supporting productivity, climate resilience, biosecurity and evidence-based policy.”

There are, of course, technical challenges, the biggest of which will be bringing together all the agricultural, environmental and satellite data sets into a single, consistent system that can operate across an entire continent.

Koronios notes currently data, models and insights remain fragmented across jurisdictions, research programs, Research and Development Corporations and proprietary platforms. “This fragmentation has resulted in duplication, inconsistent standards, slow translation of research into practice and rising costs for levy payers and taxpayers alike.”

Each of the datasets, which come from a wide range of sources including satellites, weather systems, soil databases, farm sensors and government programs – has different formats, resolutions and update cycles. Harmonising those datasets so they can be combined into a coherent, real-time model will be no mean feat.

One of the most important layers is the satellite earth observation data, which provides frequent updates on vegetation health, crop growth, pasture condition and land use across the entire country, every few days and in a few cases as frequently as daily. “This gives us a consistent, continent-wide view that simply isn’t possible from ground observations alone,” Koronios says.

Soil and moisture data will be another critical layer, helping farmers and advisors understand water availability and plant stress. When combined with weather and climate data it becomes possible to anticipate drought conditions, irrigation needs and crop development patterns.

Farm-level and environmental data, such as sensor measurements, land management information and water systems will also be integrated, providing the local detail needed to translate satellite observations into meaningful insights for individual farms.

Biosecurity and environmental monitoring datasets will also be included, helping detect changes in vegetation patterns that could signal pests, disease outbreaks or land degradation.

“The real value comes from combining these layers, because when they are analysed together they reveal patterns and trends that would not be visible in any single dataset,” Koronios says. “This is a current gap in the ecosystem.”

Scale is another challenge, Koronois is preparing for, with Australia’s agricultural regions spanning millions of square kilometres. “The system must process very large volumes of data continuously, while still delivering useful insights at the level of individual farms or paddocks.”

He says modern cloud computing, AI and advanced observations will address those issues to integrate and interpret data streams. “Rather than trying to centralise everything in one system, the digital twin works as an intelligent platform that connects existing systems and continuously updates the model as new data arrives.”

The final challenge is ensuring information is practical and usable for farmers and advisors, not just technically sophisticated, he says. That means designing tools and dashboards that translate complex data into clear insights that support real-world decisions.

“We are embarking on a journey where the priority is not the volume of data, but the acceleration of technology adoption. We want to ensure that the data we ingest translates into high-value insights and practical tools that the industry can trust and use with ease. The Digital Twin will work by integrating multiple layers of data that together describe what is happening across Australia’s agricultural landscape.”

Over time other information sources will be integrated, particularly as Australia’s sovereign earth observation capabilities advance and tech such as IoT networks with intelligent sensors are increasingly deployed across agriculture and related sectors.

“Ultimately, the Digital Twin is not a destination with a fixed finish line. It is a living R&D engine designed for continuous progress and evolution. There is no ideal amount of data, as the system is designed to learn and improve as we move forward.”

There’s a broader national dividend here, too. A sovereign digital capability for agriculture is a food‑security asset as much as it is a productivity play. It reduces reliance on offshore analytics to interpret Australia’s land and climate signals, while creating a platform for local companies and researchers to build exportable services on top. In Koronios’s framing, the twin strengthens food systems and regional economies today while laying tracks for tomorrow’s cross‑sector twins – water systems, disaster resilience, coastal environments – a reusing the architecture and governance patterns forged in agriculture.

Koronios says in practical terms the twin is designed as an open, modular platform that different users will interact with in ways that suit their needs. For agronomists and advisors, the most common interface will likely be intuitive dashboards and decision-support tools that translate complex datasets, such as satellite observations, soil moisture and weather data, into clear insights about crop health, risk conditions and management options. For agtech companies and software developers, the platform will provide APIs that allow them to integrate digital twin data directly into their own applications and farm management systems. “This means companies can build specialised tools, such as irrigation optimisation models, yield forecasting systems or sustainability monitoring platforms, using the digital twin as the underlying intelligence layer.”

Researchers and advanced users will also be able to access modelling environments and analytical tools to develop new algorithms, predictive models and agronomic insights.

“The platform is not intended to be a closed system controlled by a single organisation. Instead, it is conceived as a national innovation platform that allows multiple organisations – agtech companies, research groups, industry bodies and government agencies – to build services and applications on top of the core infrastructure.

“In that sense, the digital twin acts as a shared intelligence layer for agriculture, enabling an ecosystem of tools and innovations to emerge around it, while ensuring that the underlying data and analytical capabilities remain consistent, trusted and nationally coordinated,” Koronios says.

“If we get this right, the Ddigital twin will become something that future generations of farmers simply take for granted – much like weather forecasting or satellite navigation today – because it supports better decisions across the entire agricultural sector.”

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Currently in beta, the new suite of AI agents and features will progressively roll out across MYOB’s product portfolio including MYOB Business Lite, Pro and AccountRight, and aim to tackle one of the most persistent challenges facing SMEs: Time.

“Small improvements quickly add up to big results.”

Paul Robson, MYOB chief executive, says MYOB is targeting business pain points ‘ready for reinvention and transforming how customers and partners operate, unlocking a step-change in productivity through efficiency and insight’.

The new SME-focused AI features land against a wider backdrop of MYOB’s ongoing AI work across its wider platform ecosystem and a push to encourage local businesses towards becoming an ‘autonomous business’. Late last year Valantis Vais, MYOB general manager for product, product marketing and design told iStart that ‘practical’ was a key aspect of that push. While midsize businesses are curious about AI, they’re also wary of hype and sunk costs, wanting tools that provide practical benefits in the here and now, rather than promises of a sci-fi future.

He detailed to iStart a range of AI features going into Acumatica ERP solution, including accounts payable bill entry powered by OCR and semantic interpretation, expense management with AI-driven receipt capture, AI advisor anomaly detection and Auto Complete.

The new rollout extends the AI features to smaller businesses, including sole traders using Lite, as well as the more complex mid-market companies using AccountRight.

According to MYOB’s latest Business Monitor, 24 percent of employing SMEs say late payments exert significant pressure on their operations. The company believes embedding AI directly into existing workflows, with the likes of smart invoice reminders, automated reconciliation and AI-driven business insights, is key to unlocking productivity boosts without disruption.

Making sense of numbers and smart reconciliation

At the heart of the latest wave of promised updates is an AI Business Insights feature which will provide interactive charts and commentary to allow businesses to identify patterns and establish areas which need attention. MYOB says it will ‘plainly’ tell the story behind the numbers, providing easy-to-digest explanations for businesses, and a quicker avenue to surface trends and identify performance drivers in preparation for advisory-focused conversations for accountants and bookkeepers.

Another major addition will be Smart Reconciliation, which uses machine learning to categorise and auto-reconcile transactions based on user behaviour and pre-set schedules. Bank feeds are matched automatically, reducing hours typically spend on repetitive admin.

For small businesses, this means real-time visibility of expenditure and cashflow – an essential advantage in volatile trading conditions. For advisors MYOB says the feature means fewer errors and cleaner files when compliance deadlines loom, reducing the time spent tidying data before submission.

The focus on practical time savings echoes themes raised in MYOB’s earlier mid-market Acumatica rollout, where early adopters reported savings of upwards of 20 hours a month thanks to automation in accounts payable. While the new release doesn’t replicate those features, it shares the same underlying goal of removing manual volume so human effort can be redirected to higher-value decisions.

Behavioural cues to tackle late payments

The Business Monitor data shows late payments remain a stubborn issue for small businesses. MYOB’s Smart Invoice Reminders aims to address that, analysing late payer behaviour to recommend actions and tone, with customisable scheduling of automatic reminders.

For owners, MYOB says the offering will reduce administrative load, while providing clearer visibility of expected cashflow to reduce uncertainty in planning conversations for advisors.

Robson says the approach reflects the company’s belief that small improvements quickly add up to big results for local SMEs.

“AI can completely change the game for small businesses and their advisors, powering up productivity and accelerating innovation beyond anything we’ve seen before,” he says.

The company says it has guardrails and evaluation measures in place to ensure the accuracy and safety of its AI outputs, but does admit AI can still get things wrong. Users can view the context and data source of suggestions to review them.

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Last year saw a ‘robust’ 12 percent increase in IT spend, (IDC has suggested that growth rate is likely the highest since 1996) with S&P saying it believes enterprises increased their total IT budgets to accommodate new AI-related investments, rather than reallocate or take away from existing IT priorities.

“Enterprise IT budgets could tighten if monetisation of AI investments proves low or delayed.”

That AI spend, which includes infrastructure, software, services and AI-embedded devices, is now making up 26 percent of overall IT spend, according to Gartner figures.

In a report very much skewed towards the impacts on vendors – S&P Global is, afterall a financial intelligence company for whom credit ratings are key – S&P notes that enterprises expanded IT budgets in 2025 specifically to fund AI initiatives, rather than shifting money away from core operations, maintenance or long-standing digital transformation programs. Enterprise spending, which started the year cautiously, accelerated through the second half of 2025 to reach high single-digit growth.

However, in a now all-too-familiar tale, AI monetisation is lagging AI investment with S&P noting a ‘high degree of variability’ in its forecasts as concerns around the sustainability of AI-related investments continue to build. Despite accelerating cloud revenue growth among hyperscalers, S&P says enterprises themselves have yet to see broad, measurable returns from AI deployments and while cloud service provider capex spend is forecast for strong growth, enterprise budgets might not be so forgiving.

Despite its optimistic title, AI Tailwinds Bode Well for 2026 IT Spending, the report warns that tightening enterprise IT budgets are a risk in 2026 if AI investment payoffs remain limited or delayed.

“Negative feedback on the pace of AI monetisation could cause enterprises to re-evaluate their AI projects and cloud service providers to slow data centre expansion. Credit markets may no longer support unlimited infrastructure financing under such a scenario,” S&P says. “This has the potential to set up for a rocky 2027.”

2026 outlook

S&P is forecasting global IT spend to rise nine percent this year, far ahead of global GDP growth projections of three percent, but it notes the forecast carries a ‘high degree of variability’ due to uncertainty around the sustainability of AI investment.

Enterprise budgets for 2026 are expected to skew strongly toward cloud, cybersecurity, data and analytics and AI infrastructure, however discretionary projects remain constrained, with elongated sales cycles, particularly for large transformation deals, and continued funding uncertainty across the public sector, education and healthcare clients.

Software is forecast to grow on pace with last year, at around 10 percent, but S&P highlights that budget scrutiny has increased and deal cycles are lengthening – a potential early indicator of pressure that could intensify if AI returns fail to meet expectations.

SaaS is expected to be a key driver, along with digital transformation and cloud migration. The transition to SaaS, which now accounts for 60 percent of the total software market, was a driver for 2025 software figures, along with, and linked to, enterprise focus on cost efficiencies and digital transformation.

Despite the hype around agentic AI, S&P isn’t expecting it to be a meaningful ratings driver in 2026. “Many software companies report high client interest and growing adoption, yet the revenue impact remains low. However, we believe generative AI features may create incremental growth opportunities and value-based pricing uplift for software vendors over time and increased consumption of existing product suites.

It cites Salesforce revenue growth – the company’s Agentforce and Data Cloud 360 annual recurring revenue more than doubled year over year to hit US$1.4 billion in the most recent quarter – as an example.

While enterprises may be cautious, albeit still spending, it’s the largest data centre players whose investments are eye-wateringly high: In 2025 estimated capital expenditure for Microsoft, Amazon, Alphabet, Meta and Oracle hit a combined US$437 billion, up 68 percent year on year (and, S&P admits, far surpassing its initial forecast of 20 percent a year ago). This year, S&P is expecting cloud service providers’ capital expenditure to close in on US$600 billion thanks to a 38 percent rise in spend. Total capex spend is forecast to hit $3-4 trillion from 2025 to 2030.

The investment is focused primarily on AI training capacity and data centre buildouts, and S&P points out that hyperscalers are now reaching a point where external funding is becoming necessary, with recent debt issuances in the bond market by major operators to support continued investment.

“Their commitment to investing hundreds of billions in AI data centres and high-powered AI chips remained steadfast even in the face of the Trump administration’s threat of substantial tariffs on global trading partners in April and the cautious pace at which enterprise customers are adopting AI in the workplace.”

The release of an IT focused report by S&P is itself something of a milestone, highlighting the importance of IT spend – and AI-driven IT spend – on broader economic and credit-market assessments.

“We maintain a positive long-term view of the technology industry. Sectors from health care to energy are increasing their investments in IT, and AI in particular, to increase sales, hasten research and development and improve operational efficiency.”

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