Fortysouth was born out of the now One NZ’s sale of its mobile tower infrastructure in late 2022. It took out the Innovation Leadership Through an Emerging Technology award at the recent New Zealand CIO Awards for its digital twin program which is being rolled out across 1,700 telecommunications towers across New Zealand.

“We didn’t, in our wildest dreams, think it was going to be this good.”

The system, which turned a process taking six months into a 10-minute task, uses drones to capture thousands of images of each tower, creating a highly detailed virtual model that engineers, customers and operational staff can access remotely.

Clarke says the award reflected the project’s adoption, rather than just its technical sophistication.

‘The reason we won the award is not because of the technology, it’s because we’ve got everybody using it,” he told iStart.

What makes Fortysouth’s approach unusual, is who those users are.

While most organisations deploy digital twins to improve maintenance, asset inspections and operational efficiency, Clarke says Fortysouth has focused on making the technology part of the customer experience.

“For me, it’s the customer. We’re the only people I’ve found in the world that are really using digital twin to make the customer’s life easy. Most are using it for maintenance.”

The customer-first approach has transformed a traditionally slow and heavily manual process.

Historically, telecommunications companies wanting to place equipment on a tower would request engineering drawings – which could prove a challenge to find and weren’t always accurate – review site records wait for structural assessments and work through multiple iterations with engineers. Finding documentation alone could take weeks, and that documentation wasn’t always accurate, while engineering reviews could stretch the process out to six months.

Under the digital twin model, customers can access a virtual tower, choose equipment from a BIM (building information modelling) catalogue of specific equipment and place it directly onto the igital model. The system provides visibility of available space, checks structural capacity, references lease and regulatory information held in Fortysouth’s asset management system, and provides an initial engineering assessment.

“At the end of 10 minutes customers have a high degree of confidence that the whole thing will work,” Clarke says. Formal engineering calculations still follow, but customers can move ahead with planning instead of waiting for information to be gathered manually.

For customers, Clarke says the process is ‘very, very simple’. Customers select equipment from catalogues containing their actual hardware and use simple drag-and-drop tools to visualise installations and tower suitability.

“The hardest thing is getting someone to see it first,” Clarke says. “Once people see it, they love it.”

Cutting the Gordian knot

The ease of use became a major factor in adoption, both externally and internally.

When Fortysouth began the project many of its engineers were unconvinced. Adoption of digital twins was part of the conditions attached to its acquisition of the tower assets from One NZ (then Vodafone NZ), and Clarke is blunt that FortySouth initially had little sense of how valuable the technology would be.

“We didn’t really know how it would be used,” he says. “Our engineers were sceptical because they’d all grown up on paper drawings.”

The scepticism didn’t last long.

Engineers quickly discovered the digital models were often more useful than traditional records because they represented the asset as it actually existed, rather than how it appeared on drawings that may have become outdated. “They flipped overnight from being sceptical to being it’s the one thing you can trust,” Clarke says.

Customers too, ‘got it very quickly’.

The experience also highlighted another challenge familiar to infrastructure owners: Poor asset records.

When Fortysouth acquired the network, it inherited large volumes of engineering documentation.

“They won’t thank me for saying this, but they were handing over a bit of a mess. Telco’s records are terrible. I think that’s sort of a universal truth.” While those records are now organised and searchable, Clarke says traditional asset information is often difficult to locate and may not accurately reflect what was ultimately built.

Digital twins, he says, allow infrastructure companies to create an accurate current representation of the asset and work forward from there, rather than trying to progressively improve legacy records. “It’s a bit like cutting the Gordian knot. You don’t improve the record you’ve got. You just start again,” he says.

“It just cuts through any historical data issues and gives you a near perfect record of what’s there today, which is a massively valuable thing for any infrastructure owner thinking about maintenance or changes to the network.”

Beyond telecommunications

That capability is now generating interest beyond telecommunications. Clarke says infrastructure operators have approached Fortysouth to learn more about the project. He recently spoke at a US conference, sparking ‘a lot of interest’ in the project.

The company believes the opportunity extends well beyond tower networks to any organisation managing large numbers of geographically dispersed physical assets. Clarke says the value becomes particularly apparent when assets are difficult, expensive or time-consuming to visit in person. But he admits it doesn’t work for all assets. Clarke has come from the power sector where building digital twins is ‘quite a different thing’. “You can’t fly a drone for those, you actually have to build them on a computer because you can’t fly a drone inside a turbine.”

Alongside the use by customers, Fortysouth is also harnessing the twin for the more traditional maintenance activities. AI tools help identify potential issues including missing bolts and signs of rust, allowing maintenance teams to focus attention on areas requiring inspection and reducing the need for staff to climb 20m towers or travel long distances to gather information.

It’s also being used to show landowners, and councils, what a proposed tower would look like ‘in a very high definition way’. “Everybody wants mobile coverage, no one wants a tower on their land,” Clarke says. The digital twin, ironically, is ‘much more human, understandable and valuable’ than a 2D drawing.

The biggest lesson

His advice to organisations considering the technology is straightforward: Give it a go.

“You will find value in it. You probably don’t know what it is until you do it, but give it a go and pass it around your various teams and customers. I’m confident that in doing that, you’ll get value out of it,” he says.

Despite the operational benefits, Clarke says the biggest lesson from the project was not in maintenance, engineering or AI. Instead it was in discovering how much value customers derived from being able to inspect assets themselves, test options and make decisions without waiting for information to be supplied by Fortysouth.

“We didn’t, in our wildest dreams, think it was going to be this good,” he says.

The post From six months to 10 minutes: Fortysouth’s digital twin advantage appeared first on iStart leading the way to smarter technology investment..

The reports comes as employers on both sides of the Tasman continue to report workforce challenges. In the latest Hays Salary Guide, 83 percent of Australian and 75 percent of Kiwi organisations said they have experienced a skills. Shortage in the last 12 months, with shortages concentrated in technical sectors, though the tech and software and services sectors reported slightly below average skills shortages and the ICT sector was -14 percent below average.

“This is no longer just a leaky pipeline.It is a structural challenge.”

Tech New Zealand’s fourth annual Digital Skills Aotearoa report, Digital Skills in the Age of AI, warns that New Zealand’s digital skills challenge has become structural, with declining participation in technology-related subjects, fewer ICT migrants and growing demand for digital workers creating pressure on the talent pipeline.

At the same time, Australia’s Committee for Economic Development of Australia (Ceda) says skills recognition remains a significant weakness in the Australian migration system, with overseas qualifications often going unrecognised and many migrants working in roles below their level of training. Ceda estimates that mismatch costs Australia around A$4 billion annually in lost wages – ‘a poor result for migrants and a waste of the economy’s capacity’.

Pipeline pressure

Tech NZ’s report, which is drawn from government, industry and education provider data and insights, says more than half of the surveyed organisations expect recruitment for digital roles to increase over the next 12 months, with digital capability is increasingly required across both technology and non-technology sectors. Demand for advanced digital skills, particularly in AI, cybersecurity, cloud infrastructure and software development, remains high.

The report says New Zealand’s tech sector has become one of the country’s strongest economic performers, contributing around $24 billion, or eight percent of GDP. The top 200 tech exporters, meanwhile, generated nearly $20 billion in total revenue in FY2025 according to the Technology Investment Network.

Yet it says the foundations supporting future growth are under pressure, with Tech New Zealand CEO Graeme Muller warning that continued growth can’t be taken for granted.

Participation in NCEA technology studies has been declining, fewer students are taking science, technology and mathematics subjects associated with digital careers and ICT migration has dropped with just 729 visas approved for ICT jobs in 2024, down 67 percent on the previous year.

“This is no longer just a leaky pipeline,” Muller says. “It is a structural challenge.”

There are some glimmers of hope, however, with domestic IT degree enrolments growing and Masters and PhD enrolments increasing strongly. Graduate numbers, however, remain modest and entry-level pathways remain limited, Tech NZ says.

“Technology is one of New Zealand’s clearest pathways to higher productivity, export growth and global competitiveness. But we cannot take that growth for granted,” he says.

Migration challenges

New Zealand’s declining ICT migration is mirrored in Australia where net overseas migration last year was down 45 percent from the 2023 peak. Committee for Economic Development of Australia (Ceda) data shows 300,955 migrants arrived in 2025, down from the post-pandemic surge of 555,800. Numbers are expected to decline to around 225,000 by 2027-28, roughly in line with pre-pandemic levels in keeping with Government moves to moderate net overseas migration and tighten aspects of international education and temporary visa systems. Higher migration from Kiwi citizens was one of the factors Ceda says is currently keeping migrant levels above the long-run average.

Despite that drop, Ceda warns migration remains a ‘flashpoint’ with political parties politicising cuts to migration, framing high intake as a driver of housing affordability and infrastructure strain.

It notes around one in three workers in healthcare, logistics, professional services and manufacturing were born overseas.

However, Ceda argues Australia’s migration system continues to fall short when it comes to recognising overseas qualifications and experience.

“Overseas qualifications often go unrecognised in Australia, leaving migrants in roles below their training,” the organisation says.

The Australian report also notes that the country’s permanent migration programme remains heavily weighted towards skilled migration, with around 70 percent of places allocated to skilled migrants and thousands of offshore places reserved for workers aligned with long-term workforce needs.

The AI paradox 

Back in New Zealand, the Tech NZ report also highlights an emerging ‘AI paradox’, noting the often contradictory findings when it comes to AI’s impact on ICT professionals and technical roles. While many report being able to complete some digital tasks faster, AI can also increase code complexity, technical debt and security risks while decreasing code quality when used without sufficient expertise.

“As AI tools remove some entry-level tasks, the remaining work is often raising, not reducing, the need for deep technical expertise,” the report says, noting the value of experienced practitioners who can validate outputs, manage risk and govern AI systems.

The displacement of entry-level work is also creating an experience chasm that’s harder to cross, the report says, while AI can enable junior developers to generate huge volumes of code quickly, which can overwhelm senior review capacity further increasing the value of experienced professionals who can validate and govern what is produced.

Says Muller: “New Zealand needs people who understand the technology deeply enough to use it safely, productively and responsibly: from software engineers and AI specialists to cybersecurity experts, cloud professionals, systems architects and leaders who can govern data, risk and ethics.”

The post NZ seeks digital talent, AU talent goes unused appeared first on iStart leading the way to smarter technology investment..

From 10 December 2026, new disclosure requirements under the Privacy and Other Legislation Amendment Act will require organisations to disclose when automated decision-making systems use personal information to make, or substantially assist in making, decisions that significantly affect an individual’s rights or interests.

“The obligations will extend beyond high-risk AI systems to capture commonly deployed enterprise and customer-facing technologies.”

The change comes as financial industry regulator APRA (the Australian Prudential Regulation Authority) warns banks, insurers and superannuation funds that governance and assurance practices are not keeping pace with the scale and speed of AI adoption. It’s calling for a ‘step-change’ in how AI-related risks are managed.

The combined message from privacy and financial regulators is straightforward: Organisations required to follow the Australian Privacy Principles will need to know where AI is being used, what personal information it relies on, and the types of decisions made.

The Privacy and Other Legislation Amendment Act introduced a range of privacy reforms, including clarifying ‘reasonable steps’ to protect the security of personal information, introducing the offence of doxxing and providing ministerial powers to ‘whitelist’ countries that provide substantially similar privacy protections. Many of the changes kicked in in 2024.

What the new rules require

Law firm Macpherson Kelley says businesses that use personal information in automated or semi-automated decision-making that could reasonably be expected to have a significant effect on an individual’s rights or interests will need to update their privacy policies by December 2026. The policies will need to describe the types of personal information used and the types of decisions being made.

The requirement extends beyond generative AI tools. Mark Metzeling, principal lawyer commercial for Macpherson Kelly notes the rules apply where a computer program either makes a decision itself or performs a task that is ‘substantially and directly related’ to making that decision. An automated decision could include outcomes affecting contractual rights, access to services, eligibility determinations and other decisions that significantly affect individuals.

Among the examples of those most likely to be caught by the new requirements are financial services companies relying on credit-scoring, fraud detection and algorithmic trading, ecommerce and digital platforms using recommender systems or dynamic pricing, telcos harnessing automated customer identity checks and service provisioning, and insurers, healthtech and medtech companies using predictive analytics.

Areas including insurance eligibility assessments, recruitment screening, automated billing, hardship assessments and disconnections, and other AI-driven decisioning systems are also likely to be impacted.

The Office of the Australian Information Commissioner (OAIC) says the new transparency requirements are intended to give individuals greater visibility into how automated decision-making systems use their personal information – reducing AI’s ‘black box’ challenge. In a May consultation paper, the regulator said greater transparency would help people understand how their information is being handled and enable them to take further action where appropriate.

Veronica Scott, partner at Pinsent Masons, and Gagan Singh, associate at the law firm, say the OAIC has taken a broad, technology-neutral approach to the meaning of a ‘computer program’ that is used for ADM.

“This may include commonly used software; apps; word-processing tools; AI systems; generative AI tools; chatbots and virtual assistants; and tools that analyse, classify, summarise or generate content,” they warn.

“This signals that the obligations will extend beyond high-risk AI systems to capture commonly deployed enterprise and customer-facing technologies. This has the potential in practice to result in lengthy disclosures.”

They note many common digital business practices such as targeted advertising and content delivery, may fall within scope particularly where algorithmic curation may limit access to employment opportunities or personalised or differential pricing for significant good or services is provided.

Ashurst Perkins Coie also cautions that organisations should prepare for targeted advertising and algorithmic pricing to come under scrutiny.

The tech challenge

For tech leaders, the challenge may not be interpreting the legislation, but instead ensuring they can trace what all the systems are doing in practice, the decisions they influence and the personal information sitting behind it – and provide the plain English disclosures required.

A January review by the OAIC into how Australian government agencies use ADM in decision making and communicate that information on their websites found just 17 percent disclosed that they were using ADM and none had published guidelines or policies explaining how those systems were used.

Meanwhile an APRA review in April of large financial institutions found AI adoption accelerating across regulated industries, with organisations moving from experimentation to customer-facing use cases including claims triage, loan processing, fraud detection, customer interactions, insight generation and software engineering.

Governance, however, has not kept pace APRA warned.

The regulator says while boards showed a strong interest in AI’s strategic potential, many were still developing the technical literacy needed to effectively challenge AI-related risks and provide oversight. APRA also noted an ‘over-reliance on vendor presentations and summaries without sufficient examination of key AI risks such as unpredictable model behaviour and the impact on critical operations.”

Among APRA’s expectations is that organisations maintain an inventory of AI tooling and AI use cases, alongside clear accountability, human involvement in high-risk decisions and governance arrangements covering the full AI lifecycle.

Mapping and disclosures required

Macpherson Kelley’s Metzeling warns the ADM requirements apply to any qualifying decision made on or after 10 December 2026, regardless of when the algorithm or system was originally implemented.

He’s urged organisations to prepare early, mapping algorithms and evaluating whether – and where – automated decisions involving personal information are occurring within the organisation.

Ashurst Perkins Coie echoes that, saying organisations need to close the loop on governance and ensure they can trace what systems are actually doing in practice – and keep disclosures aligned with reality.

The post Know your ADM: New rules put automated decisions under scrutiny appeared first on iStart leading the way to smarter technology investment..

AppWrap August 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.

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The Talbot Mills research, conducted for Datacom, found 83 percent of senior business and tech leaders surveyed are concerned about storing data offshore or with an overseas provider, while 72 percent consider ownership and control of data an important or critical priority for their organisation. Yet despite those concerns, only 35 percent have a formal written policy governing where critical data should reside and how those decisions are made and just 41 percent have a documented exit or migration plan if their primary provider becomes unavailable or unacceptable.

“More than half were concerned foreign governments could gain access to data stored in New Zealand if the underlying infrastructure was owned by a multinational.”

The findings come as organisations across New Zealand and Australia face growing scrutiny of data governance, cybersecurity and operational resilience.

Peter Nelson, Datacom New Zealand managing director, says are paying closer attention to how and where information is managed.

“Organisations are paying much closer attention to where their critical data sits, who controls the infrastructure it relies on and what would happen if access was disrupted,” he says.

The challenge, however, is turning that awareness into practical action.

According to the survey, concerns around offshore storage extend beyond questions of location. Among respondents worried about offshore data, 77 percent cited data breaches as a concern, while 60 percent were worried about legal access by foreign governments. More than half were also concerned foreign governments could gain access to data stored in New Zealand if the underlying infrastructure was owned by a multinational provider.

At the same time, most organisations are already keeping critical information close to home. The survey found 64 percent store their most sensitive or business-critical data entirely in New Zealand, while a further 21 percent use a combination of local and offshore storage.

The survey also highlights the difference between data residency and data control, an issue increasingly discussed in regulatory and governance circles on both sides of the Tasman. Australian governance and sovereignty commentary has increasingly focused on questions of who controls data and which jurisdictions can claim legal access to it, rather than simply where data is physically hosted.

Among organisations using local or hybrid storage models, 56 percent said their data is hosted in facilities operated by hyperscale cloud providers including AWS, Microsoft Azure and Google.

Governance lags

While concern about sovereignty is widespread, formal governance appears less common, particularly among smaller businesses.

The report found 70 percent of organisations with 20 or more employees have a formal policy governing where critical data is stored and managed. Among organisations with fewer than 20 staff, just seven percent reported having such a policy.

The survey suggests a similar gap may exist between confidence and preparedness.

Eighty-five percent of respondents said they were confident their organisation could continue operating critical services during a disruption to offshore cloud access, network connectivity or a cloud control plane. However, only 41 percent had a documented exit or migration plan if their primary provider became unavailable or unacceptable and just 39 percent had tested restoration of critical systems and data within the previous six months. Thirteen percent admitted they had never tested recovery capabilities.

Nelson says organisations needed to test, rather than assume, resilience.

“A backup strategy is only as good as an organisation’s ability to restore from it when something goes wrong,” he says.

Of course, it wouldn’t be a 2026 survey if it didn’t include AI, which is placing additional demands on data governance frameworks. Forty-five percent of respondents said AI adoption had influenced data infrastructure and storage decisions during the past year. At the same time, 43 percent said legacy systems, fragmented data platforms or unclear governance were slowing their ability to adopt AI safely.

Those challenges are not unique to New Zealand. The Governance Institute of Australia’s 2025 AI Deployment and Governance Survey identified governance, privacy and implementation challenges as organisations seek to move AI projects into production environments.

Lou Compagnone, Datacom director of AI, says many organisations are discovering that AI initiatives depend on the quality of underlying governance and data management practices.

“The organisations that get the most value from AI will be the ones that have done the foundational work first – trusted data, strong governance, clear access controls and confidence in where information is stored and who can access it,” Compagnone says.

More than a third of organisations surveyed said they are already reviewing where critical data is stored and managed, or plan to begin a review within the next six months.

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The technology allows attendees to enter venues through facial authentication – much like unlocking your smartphone or a SmartGate at the airport – rather than scanning a barcode.

“Meaningful consent requires people to understand what they are agreeing to and retain the ability to withdraw that consent.”

Geelong Football Club has introduced an ‘express lane’ for members at its home venue, the GMHBA Stadium. Members upload a selfie to their account to be verified at the entrance.

Similar systems have been an option at the Australian Open since 2024 and the technology is used in the United States for NFL games and college sports. Other AFL clubs are also reportedly exploring the technology.

The move comes as the often controversial technology appears to be broadening beyond traditional use cases such as border control, mobile device authentication and workplace access. The latest deployments suggest biometrics are beginning to move into mainstream customer interactions with organisations exploring ways to use biometric data for access control, payments, digital identity, loyalty programs and age verification.

Replacing tickets, cards, passwords and physical identification documents with biometric authentication has the potential to reduce friction for customers while streamlining transactions and access processes. Sports venues are promoting facial authentication as a faster way to move people through entry gates, but similar opportunities are emerging across retail, financial services and customer service environments.

Face, palm, pay

In New Zealand, Eftpos New Zealand recently launched biometric-ready payment terminals designed to eventually support face and palm authentication for payments, digital identity verification and age verification. Neither Eftpos NZ nor technology provider Verifone have indicated when biometric payments will become available, or disclosed whether the biometric matching will happen on the terminal itself or through the cloud.

At the same time, New Zealand organisations are adjusting to a new regulatory environment. The Biometric Processing Privacy Code came into force in November 2025, establishing specific rules governing the collection and use of biometric information. The code requires organisations to demonstrate biometric processing is lawful, necessary and proportionate, while implementing safeguards around collection, storage and disclosure.

Consent under scrutiny

As biometric technologies move from controlled environments to customer-facing applications, questions about governance and privacy are continuing to garner attention.

Curtin University lecturer and ethics of AI researcher Adam Andreotta notes facial authentication differs from broader facial recognition systems because users voluntarily provide a selfie to verify their identity, rather than being identified from images captured in public spaces. Even so, facial images and biometric information are classified as sensitive information under Australian privacy law, requiring informed consent for collection and use. Writing in The Conversation, Andreotta argues that meaningful consent requires people to understand what they are agreeing to and retain the ability to withdraw that consent.

The debate has already played out in the Australian and New Zealand retail scene. Bunnings and Kmart both attracted attention in Australia over their use of facial recognition technology in stores with regulators examining how biometric information was collected and used.

In 2024, the Office of the Australian Information Commissioner found that Bunnings’ use of facial recognition technology on customers entering its stores – for security purposes – breached privacy law. The regulator concluded that customers had not provided informed consent for the collection of facial information and found the retailer’s use of the technology was not proportionate to the risks it was seeking to address.

Earlier this year, the Administrative Review Tribunal found, partly at least, in Bunnings favour, accepting that the use of the technology was permitted, but agreeing that the company had failed to implement adequate privacy governance practices or provide sufficient specific notice to customers about the collection of their facial images. It also confirmed that even momentary or transient processing of personal information can constitute ‘collection’.

In New Zealand, the Office of the Privacy Commissioner ran an inquiry alongside FoodStuffs’ North Islands trial use of facial recognition, finding that use complied with the Privacy Act and safeguards were in place.

The acceptance gap

Research suggests public attitudes towards facial recognition remain highly dependent on how the technology is used.

A 2024 survey conducted by researchers from Monash University and the Australian National University found Australians were generally supportive of facial recognition being used by emergency services to identify victims of disasters or war, and law enforcement agencies to catch criminal suspects but considerably less comfortable with its use in retail stores and workplaces.

Chief investigator Professor Mark Andrejevic said people want greater transparency around how facial recognition systems operate, how information is stored and used, and what accountability measures are in place. The survey also found overwhelming support for notification and consent requirements.

Academic researchers have also questioned whether existing privacy frameworks are keeping pace with rapid developments in facial recognition technology. The University of Technology Sydney’s Human Technology Institute has argued Australia needs dedicated facial recognition legislation, saying existing privacy laws were not developed with widespread biometric deployment in mind. Its proposed model law recommends a risk-based approach designed to protect privacy while allowing appropriate innovation.

Supporters of biometric systems argue the technology can reduce friction in customer interactions by replacing physical credentials such as tickets, cards and passwords. Industry advocates point to faster venue entry, streamlined payments and simplified identity verification as potential benefits.

For local technology leaders, the significance of Australia’s sports venue rollout extends beyond the stadium gate. With biometric-ready payment infrastructure now entering the local market and new privacy rules governing biometric processing, the question is no longer whether biometrics will enter mainstream customer interactions. The technology is already on that path. The challenge will be demonstrating that the benefits can be delivered while meeting increasingly stringent expectations around consent, transparency and governance.

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New research shows the shift from traditional ERP to what is being dubbed ERX – or enterprise resource experience – is creating a new decision point for CIOs.

“This a huge reimagining of ERP and what’s really exciting is that it’s achievable.”

ERX is positioned as the next evolution of ERP. Rather than acting primarily as a system of record and workflow management platform, ERX combines AI, automation and agentic capabilities to create systems able to sense changes, support decision-making and increasingly execute processes autonomously. Gartner has forecast that by 2030 more than 50 percent of foundational ERP tasks will be autonomously executed by AI, reducing human involvement in finance, supply chain and HR.

Neha Ralhan, Gartner senior principal analyst, describes ERX as a continuum, with organisations moving at different speeds towards intelligent and autonomous enterprise operations.

She told iStart the move is not a repackaging of ERP, but a reimagination.

“It is not the system of old. It’s not the system you recognised from five years ago. It won’t be, can’t be. AI has fundamentally changed ERP.”

While traditional ERP was a passive system of record and digitised ERP layered in AI to enhance insight, ERX harnesses real-time orchestration, composable extensions, user-first experiences and native intelligence to drive faster decision velocity and continuous adaptability to volatility.

Assessing the future

For CIOs and ERP leaders, however, the immediate challenge is not adopting ERX. It’s understanding whether existing ERP strategies remain fit for purpose.

“The first thing is just to assess and audit your current ERP maturing and do this without blinkers,” Ralhan says. “Lots of organisations have spent a lot of money, and not just money but effort and resourcing and strategy, on their ERP. But to have that almost dispassionate view of where ERP stands is really important.”

The assessment extends beyond technology to vendor strategy.

“People need to evaluate vendor offerings,” she says. “You might be surprised what you find, both in terms of the audit of your ERP and also the offerings.”

Existing ERP ecosystems are increasingly misaligned with the pace and complexity of AI-driven businesses, Gartner says.

As organisations begin comparing future capabilities against their own ambitions, some may discover their current platform is no longer the best fit.

“It may not be the one. That isn’t anything that’s a reflection on the vendor or organisation. It’s just that things are moving at such a rapid pace and your ambition my not be completely aligned with what the vendor’s roadmap is and vice versa,” she warns.

When it comes to ERX, Gartner is clear – the technology is not yet fully available. Yet despite that, vendor decisions made today must be ERX-aligned.

“CIOs should prioritise partners with a credible ERX vision and architectures that support composability, open integration and AI-driven evolution,” analysts write in From ERP to ERX: The CIOs Guide to AI-Powered ERP Systems. “Those that do so will position themselves as leaders in the AI era, while those that delay will face escalating costs, reduced relevance and lost market opportunities.”

Roadmap rethink

The advice comes as many organisations continue to execute ERP transformation plans developed before the surge of interest in agentic AI.

Asked whether organisations with established ERP roadmaps should simply press on with their modernisation plans and layer ERX capabilities on later, Ralhan recommends a pause for reflection.

“Take a breath,” she says. “A lot of organisations we speak to have a gorgeous roadmap developed 19 months ago and they’ve put it on the shelf.

“What ERX also forces organisations to do is to have that roadmap as a living document. It’s not a one and done exercise.”

She warns that looking to other organisations to copy their initiatives could prove futile. “It’s really important to realise that what one organisation is doing may not be right for your organisation. It is a continuum and people will have different ambitions and different starting points. For some organisations the ambition may just be scalable ERP, but for others this is a great opportunity to move from laggard status and make a quantum leap.”

Gartner is urging organisations to reject the ‘digitisation trap’ of layering AI over fragmented or legacy business processes – something that ‘merely accelerates the production of poor outcomes and limits the ability to scale’.

“Without structural transformation, your ERP will never evolve to become an ERX and will remain an expensive liability, failing to deliver a competitive insight.”

Setting a North Star

Instead the analyst company is urging businesses to identify their North Star – defining a goal as human-centric decision intelligence. “This vision is not about total human displacement, but about removing cognitive friction by repositioning subject matter experts as supervisors of contextual intelligence, delivering intelligent automation to handle routine execution while humans focus on oversight, exception management and value-based decision making.”

Composable, event-driven technology foundations need to be architected to deliver real-time data streams, open protocols and a layered AI control plane. Business partners will need to be pulled into the mix to align strategic objectives, secure sustained funding, dismantle silos, while governance guardrails for partner and system integrator ecosystems will be needed to enforce clear configuration guardrails, open composability principles and shared performance metrics – recasting vendors and system integrators as strategic co-innovators.

Here in A/NZ the evolution is exposing weaknesses in the fragmented ERP environments many organisations have accumulated over time.

“Unfortunately, it’s sort of the ad hoc nature of ERP that a lot of organisations have, which is we’ll procure this little bit of tech here and then we’ll integrate it with this and then we’ve got a little bit of shadow ERP going as well. I think the timeline for that is numbered.

“It needs to be a little bit more strategic, which a lot of organisations in this part of the world haven’t been, either because of the legacy they’ve adopted, and also part of it is that sometimes we don’t have access to all the offerings available globally.”

There’s good news for those organisations running fragmented ERP systems with Ralhan saying they will be able to participate just as effectively, particularly for those for whom the fragmentation was done ‘mindfully’ – adding on best of breed systems – and may have greater agility now.

“Now is the time internally to set a North Star,” Ralhan says. “A lot can be achieved in a lot shorter period. I’m not saying it’s going to be easy, but this a huge reimagining of ERP and what’s really exciting is that it’s achievable.”

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PwC New Zealand’s AI-powered Consumer: How shopping behaviour is changing in New Zealand report suggests AI is becoming a regular part of the shopping journey for many, influencing how customers discover products compare options and decide what to buy, with many saying they trust AI enough to let it complete purchases for them.

“Almost one-third of consumers are now comfortable allowing AI agents to complete purchases on their behalf.”

The survey of 1,000 New Zealand consumers who have used AI for shopping-related activities in the past 12 months shows AI has become the third most-used channel, behind search engines and retailer websites or apps, for product research among that group of consumers, with 56 percent of consumers who shop online using AI weekly for shopping. At the same time, 44 percent say AI has reduced their use of search engines when researching purchases.

It’s a similar story across the Tasman. The Navigators’ AI Brandscape 2026 survey earlier this year found 39 percent of Australians are already using AI to help make buying decisions, with 38 percent using AI as a complement or replacement for traditional search. The study surveyed 1,736 Australian consumers.

“Many retailers are still asking how AI can improve today’s customer experience,” says Phil Wheeler, PwC New Zealand partner, deals strategy, value creation and analytics. “An equally important question is: How will AI change the way customers buy tomorrow?”

Search is no longer the only starting point

The PwC survey found 44 percent of respondents have reduced their use of search engines, thanks to AI use. Consumers are increasingly using AI tools to compare products and prices (64 percent), research planned purchases (62 percent), or just to seek shopping inspiration (52 percent). Seventy-seven say AI helps them find better value.

The Navigators found AI is already influencing how consumers discover and evaluate brands. According to that research, 39 percent of Australians have used AI for purchasing decisions with 38 percent using it to complement or replace search. Another 41 percent say they pay attention to AI-generated search summaries, but only 29 percent say they trust those summaries.

It found 31 percent have acted on AI recommendations with the report describing generative AI as becoming part of consumer decision-making, influencing information search, option comparison and brand selection. The figures soar for those under 35 years, with 62 percent applying AI tools to help make buying decisions and 54 percent reporting they’ve used AI for buying decisions.

The new battleground

One of the strongest themes from both reports is the issue of visibility for brands.

PwC notes that consumers are increasingly using AI to simplify the process of finding and evaluating products, while the Navigators says AI is becoming part of how consumers create shortlists and recommendations.

That has implications for how product information is presented and discovered online.

PwC says retailers have spent years optimising for search engines and digital conversion. But it argues that organisations increasingly need to consider how products and services appear within AI-driven discovery and recommendation environments.

The Navigators reached a similar conclusion, describing generative AI as an emerging influence on consumer choices and highlighting the growing importance of brand visibility within AI systems.

It’s not just online shopping being impacted, with 30 percent of respondents in the Kiwi report saying AI use has led them to shop online more and visit stores less. For 20 percent, AI use had increased both online and in-store shopping activity.

The impact varied ‘significantly’ depending on the category, PwC says. AI-assisted online conversion was strongest in travel, electronics, gifts and fashion, while categories including grocery and homeware remain store-led and tactile in nature.

Agentic commerce on the horizon?

Wheeler says the research suggests the future may be closer than many businesses realise, with respondents indicating a willingness for agentic commerce, where AI systems can act for consumers throughout parts of the shopping process.

“While consumers are already using AI to research and compare products, our research suggests that almost one-third [31 percent] are now comfortable allowing AI agents to complete purchases on their behalf,” he says.

“For retailers, the opportunity is to build trusted AI-assisted shopping experiences today while preparing for a future where AI agents play a more active role in customer interactions and purchase decisions,” PwC says.

Australian consumers are showing similar levels of interest in AI purchasing. The Navigators found 27 percent are open to buying directly through AI tools – or as The Navigator terms them, AI buying agents.

“With one quarter of all Australians willing to transact online via their main AI tool, few categories will be immune from a rapid shift once buying agent capabilities roll-out,” the Australian report says.

At the same time, trust levels are high among existing AI users. PwC found 97 percent trust AI recommendations, at least to some level, while more than half also expect their use of AI for shopping to increase.

Perplexity scores twice as high for trusted outputs than Microsoft Copilot, with Claude twice as trusted as Meta AI, which was second least trust, with only DeepSeek ranking lower. Meta was also below Copilot when it came to consumer trust of reliability and accuracy of outputs.

Impressing AI

Both reports note that for retailers, the challenge now is no longer simply attracting customers to websites and apps. Increasingly the first interaction may occur inside an AI tool, long before a customer reaches a brands digital front door.

The Navigators says organisations need to treat AI as a discovery channel, managing their brand presence where AI answers are formed – while also noting fragmentation of AI ecosystems adding further challenges for companies – and establishing leading indicators for AI visibility and influence. Building trust and rewiring commercial capability – planning for compressed journeys AI-led recommendations and buying agents – is also required, it says.

PwC meanwhile advises mapping customer journeys to identify where AI is influencing discovery, research and purchase decisions, and prioritising investment toward the categories, channels and customer segments most exposed to AI-driven shopping behaviours.

It says strengthening product meta data and creating content reflecting customer needs, purchase occasions and shopping missions will become increasingly important as AI becomes a key discovery channel.

A roadmap for AI-assisted commerce and customer-facing AI experiences is also recommended by PwC.

“For retail and consumer businesses, the challenge is not simply whether to adopt AI. It is how to respond strategically to a customer journey that is already beginning to change.”

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That’s according to new analysis from the Stanford Institute for Human-Centred Artificial Intelligence, which examined sovereignty initiatives from Microsoft, Google, AWS, Nvidia and OpenAI and concluded that while they can increase domestic control over infrastructure, data governance and model deployment, they often ‘reconfigure, rather than eliminate dependence on these companies’.

“The tools also ensure these countries will remain structurally dependent on them for the long-term.”.

The Commercial Landscape of AI Sovereignty Offerings report notes there is no shared definition of what sovereign AI actually means and that many commercial offerings marketed as sovereign remain heavily dependent on the global technology companies providing them.

The rise of sovereign AI

The researchers describe AI sovereignty as one of the defining concepts in global AI development, saying it has rapidly become a central concept in global tech policy.

Countries around the world are looking to reduce dependence on a small number of foreign tech providers, while maintaining access to advanced AI capabilities. The result has been a wave of investments, programs and products marketed around sovereignty as commercial vendors have moved quickly to capitalise on demand.

One problem, according to the report, is that nobody agrees on precisely what sovereignty means. For some organisations it means local ownership of infrastructure. Others associate it with data residency, domestic AI models, supply chain security or national technology capability.

“The term is invoked to describe everything from investing in national language model projects to establishing domestic chip manufacturing capabilities to implementing data localisation requirements,” the researchers note.

That ambiguity has created fertile ground for vendors eager to position themselves as sovereignty partners.

Sovereignty as a service

The report maps a growing commercial market for sovereign AI offerings across every layer of the tech stack.

Hyperscalers including Microsoft, Google and AWS have developed products aimed at customers with sovereignty requirements, while opening local facilities and pushing them as ‘sovereign’. Nvidia has promoted sovereign AI infrastructure initiatives, while OpenAI has increasingly become part of government and national AI discussions.

Gartner has forecast global sovereign cloud infrastructure-as-a-service spend to increase 35.6 percent this year, hitting US$80 billion as organisations outside the US and China invest more in sovereign cloud IaaS to gain digital and technological independence and keep wealth generation within their own borders.

The Stanford researchers acknowledge that these offerings can provide genuine benefits. Many increase customer control over where data is stored and processed. Others offer governance controls designed to address regulatory requirements or support local deployment models.

But the report says the initiatives also present a ‘fundamental paradox’. “They promise that countries will own their AI stack, but at the same time they deepen dependencies on US big tech.

“While the tools these companies sell under the banner of sovereignty may genuinely improve purchaser countries’ control over certain aspects of AI development and deployment, they also ensure these countries will remain structurally dependent on them for the long-term,” the researchers wrote.

It notes that adopting Nvidia’s sovereignty offerings to power your entire AI stack could reinforce vendor-lock-in as migrating to rivals would bring high switching costs, and extensive code rewrites. OpenAi’s sovereignty offerings, meanwhile, may increase localised access to cutting-edge models, but they don’t allow for inspecting or modifying underlying systems. The close ties between OpenAI for Countries and the US government also poses risk in becoming bound to US interests.

A familiar argument

The findings echo arguments previously raised by locally-owned cloud providers and digital sovereignty advocates. They have long argued that data residency and sovereignty are not the same thing, despite hyperscalers heralding new local builds as providing ‘true digital sovereignty’. Storing workloads on infrastructure owned by multinational vendors is not the same as maintaining sovereign control, even when the workloads are hosted within national borders, they note.

Keeping data within national borders may satisfy regulatory requirements, but it does not necessarily change who owns the infrastructure, controls the platform, develops the software or sets the commercial terms.

That debate has intensified as AI has moved into the mainstream.

An organisation may deploy AI workloads in-country. Data may remain within Australia or New Zealand. Governance controls may be managed locally. Yet the underlying foundation model, cloud platform, chip architecture or software stack may still be owned and operated elsewhere.

Sovereignty vs self-sufficiency

The report notes that few sovereignty initiatives actually aim for complete independence. Instead, they focus on increasing control over parts of the AI stack while maintaining access to global technologies and supply chains.

The researchers found that even providers marketing sovereignty solutions often rely on internationally developed infrastructure, hardware, software frameworks and AI models. Complete technological independence remains rare.

As a result, sovereignty is increasingly being framed as a question of strategic diversification rather than autonomy.

That perspective may be particularly relevant as Australia continues to invest in sovereign technology capability. Federal and state governments have increasingly highlighted AI capability, digital resilience and local infrastructure as strategic priorities, while vendors have responded with a growing range of sovereignty-focused offerings.

The Stanford report does not argue against those efforts. Instead, it suggests the conversation is more nuanced than the marketing often implies.

“Decision-makers should avoid treating sovereignty as an end goal and prioritise solutions that expand strategic choice without losing access to frontier capacity,” the report says.

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While the incident may sound like a warning from the future, the techniques involved were anything but futuristic. According to OpenAI and Hugging Face, the attack relied on familiar tactics including vulnerability exploitation, privilege escalation and lateral movement, highlighting that AI doesn’t necessarily require an entirely new security playbook – but the existing one has never been more important.

“If their existing approach to cybersecurity defence, detection and response is strong they are capable of defending against cybersecurity attacks regardless of their origin.”

OpenAI, which says it considers the incident to be ‘an unprecedented cyber incident involving state-of-the art cyber capabilities, says the incident occurred during an internal evaluation involving a combination of its models, including GPT-5.6 Sol and a pre-release model, being tested under conditions designed to evaluate advanced cyber capabilities. During the evaluation, the models identified and chained vulnerabilities across OpenAI’s research environment and Hugging Face’s production infrastructure in pursuit of solving a testing challenge.

Al evidence suggests the models were ‘going to extreme lengths to achieve a rather narrow testing goal’, OpenAI says.

According to OpenAI, the models first identified and exploited a previously unknown vulnerability in a package registry cache proxy, allowing them to obtain internet access. They then conducted a series of privilege escalation and lateral movement activities until they reached systems capable of accessing external resources. The models subsequently identified Hugging Face as a potential source of information relevant to the benchmark they were attempting to solve.

The activity ultimately resulted in unauthorised access to Hugging Face ‘a limited set of internal datasets and several credentials’ used by the company’s services. It was detected by Hugging Face’s own AI, including agents using open-weight AI models.

Hugging Face describes the intrusion as being driven ‘end to end, by an autonomous AI agent system’, calling it unlike anything the company had previously encountered. The company says the campaign involved thousands of actions executed across a network of short-lived sandboxes, matching the long-discussed ‘agentic attacker’ scenario security experts have been warning about.

Familiar tactics, new actor

But Gartner analysts say the incident shouldn’t be immediate cause for concern, and IT teams should focus on the fundamentals and ignore the hype.

In a First Take on the incident, Gartner analysts John Watts, Dennis Xu, Charlie Winckless, Wayne Hankins and Franz Hinner say while AI clearly enables less-skilled attackers and helps skilled attackers with speed and quality of attacks, there is no evidence today that AI-augmented attacks create novel threats.

“However, there is increasing evidence of rogue-agent risks based on lab and researcher observation.When AI agents are paired with frontier AI models, it raises the risk of drifting from their intended purpose and pursuing unauthorised goals such as hacking.”

Around 80 to 90 percent of AI driven attacks can be stopped with some basic security controls, Gartner says and standard cybersecurity mitigation remains an effective barrier against frontier AI-driven agentic attacks.

“CISOs should reassure executive stakeholders that if their existing approach to cybersecurity defence, detection and response is strong they are capable of defending against cybersecurity attacks regardless of their origin.”

The incident does, however, present the opportunity to strengthen defences and invest in continuous threat and exposure management capabilities.

Gartner’s advice is to double down on cybersecurity basics, maintaining a thorough asset inventory, eliminating unnecessary exposed systems, patching vulnerabilities both directly and indirectly and hardening configurations.

Standard mitigations remain an effective barrier. Likewise, Gartner says “AI-driven attacks are typically not stealthy and can be detected by existing detection capabilities.” Enhancing those detection capabilities is however advocated along with guarding source code repositories as attackers are more effective with source code access, and patching frequently.

Treat agents like privileged insiders

For organisations with access to cybersecurity-capable frontier models, Gartner says the incident is a wake-up call.

“An escape from the model’s intended purpose may result in unauthorised hacking of internal and third-party environments. This creates a new risk of rogue agents.”

Among it’s advice is a warning organisations to take a model-agnotistic approach, noting Hugging Face found a commercial frontier AI model limited capabilities, leading it to switch to the GLM 5.2 open-weight model to complete its forensic analysis.

Meanwhile, the Cloud Security Alliance industry organisation says the Hugging Face breach exposed a growing gap in enterprise security thinking: Organisations are deploying increasingly autonomous AI agents without always treating them as privileged actors inside their environments.

In its post-mortem of the incident, the CSA argues that AI agents should be viewed as ‘bounded, privileged insider identities’ with strict controls around what they can access, what actions they can perform and how their activity is monitored. The incident, it says, highlighted long-standing concerns around excessive privileges, limited visibility into agent behaviour and a lack of controls capable of stopping an agent before it acts.

The CSA’s recommendations are familiar ones. It’s advocating stronger credential management, tighter access controls, comprehensive monitoring and rapid incident response capabilities.

Rather than requiring an entirely new security framework, the incident demonstrates why existing security disciplines need to be extended to cover increasingly autonomous AI systems operating inside enterprise networks.

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Banal? Perhaps. But Green, emeritus professor and special innovation advisor at UTS, says it has enormous value, eliminating variability, improving quality, optimising production processes and delivering measurable productivity and quality improvements. While it might not be making headlines, it may tell local businesses more about AI’s future than the latest wave of generative AI announcements.

“They turned the general-purpose AI into industrial AI to improve productivity of their manufacturing and create new opportunities.”

Green has been heading up a nine-month research program led by the University of Technology Sydney, looking at how organisations are putting AI to work in the real world. Rather than focusing on frontier models – which Green told iStart are beyond Australia and New Zealand to develop with their huge financial investments – the team looked at how manufacturers, technology companies and research institutions were applying existing AI technologies to solve practical business problems.

What they found was a common pattern: Successful organisations are turning general purpose AI into industrial AI – and reaping the benefits.

Green defines industrial AI as ‘the application of general-purpose AI to physical products and systems.

“It’s just whatever suits the production process that you’re applying it to,” he says. Rather than being a separate category or technology, it can involve generative AI, agentic AI, digital twins, sensors or smaller language models, with a common threat that the AI is applied directly to physical systems to improve productiity, quality and competitiveness.

For Green, industrial AI is about more than productivity. It’s about economic survival. Australia’s manufacturing sector has fallen from around 30 percent of GDP in the 1960s to roughly five percent today, while countries such as Germany continue to use advanced manufacturing to drive innovation and R&D investment. Industrial AI could help reverse that decline by enabling manufacturers to produce smarter, higher-value products and compete in global markets without trying to match overseas rivals on scale alone.

When machines talk back

While much of the AI conversation in Australia and New Zealand remains focused on copilots, content creation and workplace productivity, many European and Nordic organsiations are embedding AI directly into production systems, machinery, manufacturing processes and robotics.

“We visited several in the Netherlands, Germany, the Nordics,” Green says. “They had one common theme, that they turned the general-purpose AI into industrial AI to improve productivity of their manufacturing and create new opportunities.”

Some of the applications, like the screwdriving project in Dortmund, Germany, were surprisingly simple and unlikely to feature in a keynote presentation, but nonetheless adding ‘enormous value’.

Elsewhere, the researchers encountered examples involving sensors, digital twins and AI-driven manufacturing optimisation.

At Siemens in Munich, operators are already interacting with industrial systems through a ChatGPT-like interface. Instead of manually coding robots, workers can tell machines what they want in natural language, with the system generating the required code automatically.

“The screen just says, ‘How can I help?’,” Green says. “You just type in what you want, and it interprets through language how the machine should operate.”

It’s a glimpse into the world of physical AI: AI embedded into machines, robotics, warehouses and production environments rather than operating solely in software.

And it’s a market which is attracting growing attention from investors. Physical AI startups focused on warehouse automation, robotics and autonomous industrial systems attracted US$8 billion in venture capital funding during the first half of 2026, according to PitchBook.

From consumer to creator

For Green, however, the more important story is what happens next in Australia and New Zealand. He argues that there is a risk both countries will become merely consumers of AI, rather than creators of value from it.

Industrial AI, he says, will be fundamental for A/NZ to escape that future. “Otherwise we’re just hosting data centres here as landlords,” he says. “They come here, they use up all the energy and the water, thanks very much, and export their data, which doesn’t mean anything to us because it’s all going out of wire somewhere. All while sucking our IP dry in the process.”

He’s critical of strategies that focus exclusively on attracting hyperscale infrastructure while overlooking opportunities to apply AI to domestic industries and production systems. Instead, he believes organisations should be identifying specific operational problems where AI can improve competitiveness.

The research also challenges the assumption that businesses need access to enormous frontier models to achieve results.

“For a lot of industrial applications you only need a small language model,” Green says. “We can develop those here, not very expensively.”

That may be particularly relevant for Australia and New Zealand organisations searching for pragmatic returns on AI investments. Rather than spending heavily on frontier models, organisations can deploy smaller, purpose-built models trained for specific tasks such as equipment monitoring, quality assurance or operational support.

Industrial AI, Green says, should not be viewed as a technology reserved for automotive giants or multinational manufacturers.

“No matter how big or small you are, you can make use of industrial AI and implement it in production systems and in the creation of new products,” he says.

The opportunities extend well beyond manufacturing. New Zealand’s horticulture sector, food producers and packing houses are obvious candidates, while Australia’s mining, manufacturing and resources industries are already rich in operational data that could be combined with AI, sensors and digital twins to improve quality, productivity and decision making.

Winning ecosystems

The research found successful innovation ecosystems consistently shared a similar structure. High-quality research institutions worked closely with industry. Large anchor organisations helped attract investment and talent. SMEs participated in connected supply chains. And businesses collaborated, rather than operating in isolation.

“It’s better to work in a clustered, place-based environment,” Green says.

For CIOs and business leaders, Green’s advice is less about chasing the newest AI release and more about identifying where AI can improve physical operations, products and production systems.

The companies making progress in Europe are not waiting for perfect conditions. Nor are they mesmerised by whichever model tops the benchmark charts this month.

“The lesson,” Green says, “is don’t get ready. Get started.”

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The number of New Zealand businesses registered to receive eInvoices – which enable businesses to send and receive invoices directly between accounting systems – has more than doubled from 52,000 to 113,000 in the past year.

“According to the research, businesses can save around 16 minutes and $11 on every invoice processed through eInvoicing.”

At the same time, NZIER research released by Small Business and Manufacturing Minister Cameron Brewer estimates widespread eInvoicing adoption could deliver up to $800 million a year in productivity gains.

According to the research, businesses can save around 16 minutes and $11 on every invoice processed through eInvoicing. Scaled across the economy, that could add up quickly, particularly for organisations processing thousands of invoices each year.

More importantly for business leaders, eInvoicing is becoming harder to ignore.

Last October the government introduced rules requiring government agencies to mandate eInvoicing for large suppliers – including Australian businesses – from January 2027. The move is designed to support faster payments and reduce administrative overheads across supply chains, but it also signals a broader shift in how governments expect businesses to exchange invoices.

“We’re not just asking businesses to make the switch, we’re doing it ourselves. When government pays on time, that money flows straight through to the small businesses and subcontractors down the chain,” Brewer says.

The billion-dollar pitch

The latest figures provide an interesting update on some of ambitious forecasts made when Australia and New Zealand first started promoting eInvoicing more aggressively.

Back in 2023, the when the then prime ministers of both countries signed off on a joint statement confirming agreement to use OpenPeppol, economic gains of up to $30 billion across both countries over a decade were projected from eInvoicing use and related digital trade initiatives. New Zealand’s share was estimated at NZ$4.4 billion over 10 years, or roughly $440 million annually. At the time, uptake remained relatively modest and critics questioned whether businesses would ever embrace the technology at the scale required to unlock those benefits.

Three years on, the conversation has become more practical.

Instead of talking about transforming the trans-Tasman economy, ministers are talking about saving 16 minutes per invoice. Instead of promoting billion-dollar opportunities, they’re pointing to 113,000 businesses already connected to the network. Ironically, that more grounded message may be proving more persuasive than the grander vision ever was.

The shift isn’t unique to New Zealand with countries around the world pushing down similar paths. From September, companies exporting to France will be required to issue and receive invoices electronically, with Germany, the Philippines and the UAE following in January.

In Australia the federal government is establishing eInvoicing as the default method for exchanging invoice information in government procurement and has set targets requiring federal agencies to increase the proportion of invoices received through the Peppol network. Officials there are promoting many of the same benefits being highlighted in New Zealand: Improved productivity, stronger cashflow and reduced fraud.

While neither government has mandated economy-wide business-to-business eInvoicing, they are steadily building procurement requirements that make participation harder to avoid.

Adoption challenges

One reason eInvoicing adoption has taken longer than advocates predicted is that the technology has occupied an awkward middle ground between obvious and annoying. The benefits were rarely disputed, but neither was the reality that for larger organisations this is rarely just a switch-flip exercise. Configuring ERP, finance and procurement systems, onboarding trading partners and navigating Peppol requirements required more effort than many organisations were prepared to invest. Or, for the major beneficiaries (such as high volume retail networks), had already invested in long ago by establishing their own EDI gateways. 

Peppol’s network uses a ‘four-corner model’ – a supplier (corner 1) sends an invoice to its service provider or ‘access point’ (corner 2), which then queries the DCL (digital capability locator) using the receivers identifier such as the ABN or NZBN. The DCL then provides the suppliers access point which access point the buyer is using so the invoice can be routed through the Peppol network to the buyer’s service provider (corner 3) to deliver to the buyer (corner 4).

While OpenPeppol was designed to simplify document exchange by allowing businesses to connect once and exchange invoices with any other participant on the network, organisations still needed a reason to prioritise the work.

What appears to be changing is not the technology itself, but the growing pressure to adopt it.

Whether New Zealand ultimately realises $800 million in annual productivity gains remains to be seen. But, after years of forecasts, policy papers and industry evangelism, eInvoicing may be crossing an important threshold.

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While model prices are falling and capabilities are improving, businesses are handing increasingly complex work to AI agents. What starts as a few prompts quickly becomes research projects, workflow automation, reporting, coding and decision support. The result is a new challenge for CIOs and CFOs: How do you keep AI costs under control when adoption is exactly what you want?

“The real metric is ‘useful work per dollar’, not simply the cost of individual AI transactions.”

A recent report from cloud finops and spend management company DoIt found 79 percent of the 500 US and UK enterprises surveyed were experiencing AI cost overruns. Meanwhile, Flexera’s 2026 State of ITAM report tells a similar story, saying  just 31 percent of organisations have visibility into their AI software, while 59 percent report increased wasted AI spend.

As iStart reported recently, the AI free lunch is starting to look not so free anymore. Uber revealed it had exhausted its entire 2026 AI coding budget in just four months, driven by token-maxxing where engineers were encouraged to maximise usage. Another unnamed company reportedly accrued a US$500 million bill for Anthropic Claude use in a single month after giving staff unrestricted access and uncapped API token usage for agentic workflows.

That shift has prompted OpenAI to publish guidance on managing AI investments in the agentic era.

Cheaper AI, bigger bills

One of the more interesting observations from OpenAI’s guidance is that leaders should stop obsessing over token prices and start focusing on outcomes. The company argues the real metric is ‘useful work per dollar’, not simply the cost of individual AI transactions.

That matters because lower prices do not automatically translate into lower spending. In fact, history suggests the opposite. When cloud storage became cheaper, businesses stored more data. When cloud computing became more affordable, they ran more workloads. When video meetings became easier, calendars filled and network infrastructure requirements grew.

AI is following the same pattern. As employees gain confidence, they use it for bigger projects, more complex tasks and increasingly business-critical processes. Lower costs remove barriers to experimentation, which often accelerates adoption rather than reducing the bill.

Start with visibility

OpenAI’s first recommendation is visibility. Leaders need to know who is consuming resources, which models are being used, which departments are generating demand and what business outcomes are being achieved.

“Without that visibility, a growing bill is hard to interpret. It could reflect waste, productive experimentation, or a workflow that is starting to become business-critical,” OpenAI says.

Outcomes, not activity

The second recommendation is efficiency. OpenAI warns that cheaper models may not always produce the best result if they require additional attempts, generate lower-quality outputs or create work requiring extensive human review. A more capable model that gets the answer right first time may be cheaper overall than a budget option that needs repeated prompting.

Rather than measuring prompts, queries or tokens, organisations should focus on outcomes such as cost per customer case resolved, contract renewed, report generated or software feature delivered. The goal is to match the model and workflow to the task: use smaller or faster models when they meet the quality bar, and reserve frontier intelligence for complex, ambiguous or high-stakes work.

Governance, growth and getting serious

Governance is the third plank. OpenAI argues organisations need clear policies and controls as AI adoption grows, and that governance should work as “the operating layer that determines which AI work can scale”. That includes expectations around approved tools, data usage, security requirements and oversight of high-impact workflows, particularly as agentic systems take on more autonomous tasks.

OpenAI also recommends investing in AI workflows that become more valuable over time. Rather than spreading spending across dozens of disconnected experiments, it suggests prioritising repeatable processes that can scale across teams, improve with use and create lasting operational benefits.

The final message is simple: do not assume today’s AI usage levels are the ceiling. As agentic AI becomes more capable, employees will find new ways to use it, driving additional demand across the business. Rather than being surprised by rising consumption, organisations should expect it, budget for it and put visibility and controls in place early.

In other words, if the AI bill is growing because people are finding genuine value in the technology, that is not necessarily a problem. The challenge is knowing the difference between productive growth and expensive curiosity.

Which brings us back to that US$55 trillion bill. An AWS billing system fault last week generated estimated invoices ranging from billions to trillions of dollars. The estimates were wildly incorrect, but the broader lesson stands: Technology costs are easy to ignore right up until they become impossible to explain.

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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.

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The scathing ‘rapid review’ – commissioned by Public Service Commissioner Brian Roche after the Government Digital Delivery Agency (GDDA), which previously sat under the Department of Internal Affairs, was moved under the Public Service Commission – found widespread concerns about the way technology projects are governed, funded and managed across government. It concluded the system lacks visibility into the nature and value of technology investment, struggles to coordinate major projects and has a central digital function that is focused more on administration than strategic leadership.

“This review gives us a clear picture of what’s working and what’s not.”

The findings are unusually blunt for a government review.

Among the more damning observations were comments from agency leaders who said the GDDA often failed to provide the expertise or leadership needed to deliver projects.

One agency leader quoted in the report says the central digital function had simply helped them ‘admire the problem’ without making project delivery any easier. Another says the organisations focused on process, rather than outcomes, while others questioned its ability to broker common solutions across agencies.

The review, which was led by former Auckland Airport chief executive Adrian Littlewood, Justin Gray (former managing director of Datacom) and transformation advisor and former Kāinga Ora CEO Matt Crockett, found the problems ran deeper than any single agency. It identified a fragmented system, lacking complete and timely information and missing the urgency to drive change, despite investing $42 million a year in the central digital function. The system was characterised by fragmented accountability, duplicated investment, weak prioritisation and poor information. Agencies were found to be pursuing similar projects independently, competing for scarce technology resources and in some cases building systems that could have been shared across government.

Examples cited in the review include multiple agencies pursuing digital identification initiatives with limited coordination, an agency developing its own payments system rather than reusing existing and mature payment systems operated by another agency, and two related organisations – in the same building – tendering for new systems independently before wider integration issues were considered.

The report notes these issues have emerged despite the existence of a central digital foundation intended to identify common opportunities and drive all-of-government outcomes.

Perhaps most concerning is the review’s conclusion that government lacks reliable information about its own technology investments.

“It was hard to get fundamental metrics to judge performance of tech investment across the agencies and there was limited understanding on baseline tech spend funded through appropriations vs project spending,” the report notes.  Existing reporting was described as largely focused on expenditure and activity, rather than business outcomes and public value. Limited central visibility into agency spending – with ‘skunk-works’ projects hidden in budgets and financial reporting, is also creating accountability problems, with some tech initiatives effectively hidden within operational budgets.

The review says this lack of information makes it harder to prioritise projects, assess risk and direct investment to the areas likely to generate the greatest benefit.

While the report focuses on public service IT, many of the problems it highlights will sound familiar to enterprise leaders. Large organisations frequently face similar challenges around technology sprawl, competing priorities, duplicated systems and limited visibility of investment outcomes. The challenge of balancing business unit autonomy against enterprise-wide standards is hardly unique to the public sector.

But the review highlights how much more difficult the issues become when multiple agencies, funding streams and ministerial priorities are involved.

It’s also highly critical of the current funding and approval process, saying the existing model is designed for large capital infrastructure projects rather than the fast-moving, iterative nature of modern digital delivery. Agencies often struggle to obtain funding for smaller technology initiatives, leading some to seek approval for larger projects than necessary, hide smaller discretionary projects within IT operating budgets, delay sensible upgrades or allow tech debt to grow.

The review argues current settings can actively discourage investment and innovation.

It notes agencies face lengthy approval processes while governance structures often lack the authority to make meaningful decisions or resolve trade-offs across government. Interviewees described a culture where avoiding mistakes is rewarded more than delivering value and where activity can become a substitute for outcomes.

The review also notes that engagement with tech providers is inconsistent and does not support long-term partnerships or co-investment.

Resetting for digital delivery

Roache says the review provides a solid base for a reset as part of the work to transform the public sector.

“This review gives us a clear picture of what’s working and what’s not,” he says.

To address the issues the review proposes a three-part reset.

The first focuses on prioritisation, including an assessment – led by GDDA with support from Treasury and key agencies – of digital projects across government and the reallocation of resources towards higher-value initiatives. Low-value or conflicting projects could be paused or retired, with investment concentrated on programs deemed most likely to deliver impact. Identifying ways to ‘self-fund’ new investment by reprioritising existing funding and making short-term operating and process changes that deliver ahead of new technology is also a key output identified.

The second focused on repositioning the GDDA itself. Rather than acting as a project delivery organisation, the agency would become a smaller, but more capable, strategic authority responsible for standards, assurance, architecture, procurement and system-wide capability. Delivery responsibility would sit with lead agencies, while the GDDA would be expected to provide expertise, direction and accountability, retaining lead on strategic procurement via a panel model for common/functional services such as cloud.

The third track targets structural reform across government, including changes to funding models, governance arrangements, accountability frameworks and reporting requirements. Legislative changes could also be considered to provide clear boundaries or support for critical enabling tech projects, such as ‘bundled consent’ options for citizen data.

The review also recommends more consistent measurement of technology costs, performance and benefits across agencies.

Underlying the recommendations is a belief that technology should be treated less as an IT function and more as a driver of productivity and service transformation.

The report cites Inland Revenue’s business transformation as evidence that major gains are possible when governance, funding and delivery settings are aligned. It also highlights potentially significant productivity opportunities in areas such as health, where technology-enabled improvements could generate substantial efficiencies if barriers to delivery were removed.

The message from the review is straightforward: New Zealand does not necessarily have a technology spending problem. It has a prioritisation, governance and execution problem.

The government’s proposed digital reset aims to fix that. Whether it succeeds may depend on whether the public sector can do something the report suggests it has struggled with for years: Stop talking about transformation and start delivering it.

Roche says he will consider the findings of the review before making decisions on ‘a way forward’.

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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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The government-backed investment agency is promoting New Zealand as a destination for large-scale data centres and AI infrastructure, arguing the country offers a rare combination of renewable electricity, available land, grid capacity and political stability at a time when global demand for computing power is surging.

“The question is whether global investors will be persuaded that renewable power outweighs and room to expand outweigh the advantages traditionally offered by larger markets.”

The strategy is built around a simple proposition. As AI drives unprecedented demand for data centres, access to power is becoming a critical constraint. And if electricity is becoming the scarce resource, New Zealand believes it has an advantage. Earlier this year Boston Consulting Group flagged data centres as a key growth opportunity for New Zealand, proviing a $70 billion opportunity for the country.

Invest NZ describes New Zealand as ‘the secure, green solution’, highlighting that more than 88 percent of the country’s electricity generation comes from renewable sources. It says established data centre hubs are increasingly facing limits around power, land and environmental capacity, while New Zealand still has room to grow.

The pitch, launched last week, comes as global spending on Ai infrastructure reaches unprecedented levels. Microsoft, Amazon, Alphabet, Meta and Oracle collectively spent US$437 billion on capital expenditure in 2025, up 68 percent year-on-year, with spending forecast to continue rising as hyperscalers build out AI capacity.

Boston Consulting Group, which has been advising on New Zealand’s data centre opportunity, says global computing capacity is expected to more than double by 2030, with demand continuing to outstrip supply. Its research argues New Zealand has a ‘right to win’ a larger share of international investment because of its renewable energy resources, fibre connectivity and stable operating environment.

But New Zealand is entering a competitive market.

Australia has been attracting large-scale investments from AWS, Microsoft and Google for years, supported by a significantly larger domestic market and a more established cloud footprint. Those investments have largely been concentrated around Sydney and Melbourne, where providers can serve large enterprise and government customer bases.

Invest NZ is effectively arguing that, in the AI era, the equation is changing. Rather than being built solely where customers are located, some future AI infrastructure may be built where long-term electricity supply is available and affordable. It’s an argument BCG also supports. It says a growing share of workloads, particularly AI model training, are not latency-sensitive, so distance is no longer a constraint and computing capacity can increasingly be located where power and infrastructure are most competitive.

56 and counting

The country isn’t starting from scratch.

Last year a Tech New Zealand report into data centres noted there were already 56 operational data centres in the country, with another 20 planned or under construction, claiming the sector ‘directly employs over 1,000 people’. That report also painted a glowing picture of data centres in New Zealand, saying the sector underpins $93b in economic activity, with $16.5b in ICT GDP and $76.5 billion in knowledge-intensive services. And, like BCG and Invest NZ, it also pushed the sustainable power card, noting local data centres achieve on average power usage effectiveness. (PUE) of 1.3 – ‘significantly’ outperforming the global average of 1.54, and are rapidly transitioning to 100 percent renewable energy sources.

Recent years have also seen major investments from local operators including Spark, Datacom and CDC, alongside expansion by international cloud providers. Amazon Web Services has previously announced plans to invest NZ$7.5 billion in its Auckland cloud region over 15 years.

But the clearest example of the proposition Invest NZ is now selling offshore may be Datagrid’s Southland project. A subsidiary of Singapore’s BW Digital, and headed up by founder and CEO Rémi Galasso who was also the founder of the Hawaiki Cable (Callplus founder Malcolm Dick is Datagrid’s other co-founder), the company has secured approvals for a $5 billion ‘AI factory’ at Makarewa, north of Invercargill. The 78,000m² 

development will comprise six large data halls and is designed to support hyperscale AI and cloud workloads.

Galasso has described the development as having the potential to transform Invercargill into a digital destination, while the company has consistently promoted Southland’s renewable energy resources, cool climate and international connectivity as key advantages.

But the project also highlights the scale of infrastructure required to support AI ambitions. When fully operational, the facility is expected to draw up to 280MW. It’s been granted approval however, to scale up to an eye-watering 1GW capacity – twice the power consumption of the Tiwai aluminium smelter, whose future has been a key factor in New Zealand’s energy planning. Even at 280MW, the facility will be the second-largest electricity user after Tiwai and accounting for six percent of national electricity consumption. (Globally, a UN University report – which notably doesn’t include New Zealand suggesting the country’s current limited visibility in global AI infrastructure development – says by 2030, AI could be consuming three percent of the world’s electricity.

Earlier this year Datagrid secured a 15-year 140MW/year power purchase agreement with Mercury to help underpin future supply requirements.

The infrastructure challenge extends beyond electricity. Hyperscale AI facilities require extensive cooling systems, and Datagrid plans to use groundwater and on-site stormwater for thermal management at its Southland facility. As New Zealand pursues large-scale AI investment, energy, water and connectivity are all becoming part of the equation.

The company is also expected to benefit from the Tasman Ring Network, a 6,000km trans-Tasman subsea cable linking Invercargill with Sydney and Melbourne that has received approval and is intended to improve international connectivity for cloud and AI workloads.

Supporters see such projects as evidence New Zealand can compete internationally.

University of Waikato AI Institute director Albert Bifet has previously said facilities such as Datagrid provide the computing power and connectivity needed to train and run modern AI systems, noting that other regions are investing heavily in comparable infrastructure to support innovation and economic growth.

Others point to broader economic questions around who ultimately benefits from such investments.

University of Auckland researcher Angus Dowell has noted that major data centres can be physically located in one region while remaining economically integrated into global cloud and AI networks, where customers, decision-making and commercial returns are often concentrated elsewhere. “The key issue is therefore not just whether the project brings investment, but how the benefits of that investment are structured and distributed,” he said earlier this year.

For now, Invest NZ is focused on making the investment case.

At an Auckland event last week, business and energy leaders were presented with a vision for turning New Zealand into a significant destination for AI infrastructure investment. Contact Energy chief executive Mike Fuge described the opportunity as a ‘once-in-three-generations opportunity’.

The question is whether global investors will be persuaded that renewable power, available capacity and room to expand outweigh the advantages traditionally offered by larger markets.

With hundreds of billions of dollars continuing to flow into AI infrastructure globally, that is the bet New Zealand is now taking to market.

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“The program is the first major step in an ambitious program designed to strengthen connection between education and industry.”

The Industry Accelerator – Teachers to Industry Program will see educators undertake professional development and industry immersion with organisations including Adobe, Macquarie Technology Group and Omron Automation and Robotics Australia. It’s designed to give teachers hands on experience and direct exposure to current technologies, workplace practices and employer expectations, before returning those insights to the classroom.

The launch follows a successful pilot involving 34 advanced manufacturing teachers, which drove the program to progress to full implementation last week with an initial cohort of 50 digital and finance teachers beginning their initial professional development phase before beginning industry placements.

TAFE NSW says participating teachers will focus on priority skills areas and then share learnings across the wider organisation to broaden the program’s impact.

The move comes amid ongoing concern across Australia and New Zealand about the availability of digital skills.

In New Zealand, technology industry body TUANZ recently issued another call for ‘urgent, coordinated investment in home-grown digital capability’, including encouraging diverse pathways of training, expanding industry-led reskilling programs with tax credits or subsidies, and mandating technology upskilling in the core curriculum.

While employers are continuing to invest in AI, cybersecurity, automation and data-driven technologies, industry groups on both sides of the Tasman have continued to warn that demand for digital capability is outstripping supply. At the same time, employers on both sides of the Tasman have long complained that graduates often arrive with qualifications but lack exposure to the tools, platforms and technologies being deployed in business environments, with the technical skills learned in education settings often not matching those required in the real world.

In announcing the initiative, TAFE NSW said the program would help educators remain at the forefront of industry practice by providing hands-on experience with ‘leading employers across NSW like Adobe, Macquarie Technology Group and Omron’. The aim is to strengthen expertise in priority skills areas and improve the relevance of training delivered to students, ensuring it better reflects workplace expectations.

The organisation says industry partnerships will play a critical role in ensuring training reflects current workplace requirements and future workforce needs, and representatives from Microsoft, Google, SAS, Adobe, Macquarie Technology Group, Palo Alto Networks and Omron on hand for last week’s launch at the Institute of Applied Technology, Digital at TAFE NSW Meadowbank.

There is, of course, a difference between learning how modern organisations use technology and learning how tech companies would like organisations to use technology. TAFE NSW has framed the program around industry practice and workplace readiness, but it remains to be seen whether educators return with deeper insight into employer needs, vendor ecosystems or a healthy dose of both.

Fiona Watts, TAFE NSW senior manager education standards, says the program is the first major step in an ambitious program designed to strengthen the connection between education and industry while providing direct exposure to emerging technologies and workforce requirements.

Watts, who is leading the initiative, says the program is about creating genuine partnerships to help educators understand where industry is heading so they can prepare learners for careers that may not even exist today.

The new scheme forms part of a broader push by TAFE NSW to strengthen tech capabilities across its training network. Other recent initiatives include the launch of microskills programs covering AI, cybersecurity and data centres, and specialists training facilities and centres of excellence focused on emerging technologies. The Meadowbank facility, into which the Albanese and Minns Labour Governments have invested $11 million, is one on those new centres of excellence and is expected to train more than 50,000 Australians annually, upskilling and reskilling students and workers in cybersecurity, AI, big data, cloud and software.

The launch also follows the New South Wales Government’s announcement of a A$2.7 billion investment in TAFE NSW, including funding for network upgrades, classroom technology modernisation and new devices for staff and students.

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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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