Published on the 26/07/2023 | Written by Heather Wright

Generative AI might be grabbing the bulk of mindshare – and tech coverage – at the moment, but it’s just one of many advances on the horizon that could further transform business and solve global challenges according to McKinsey.

Generative AI is the only new trend in the consulting firms newly released Technology Trends Outlook 2023, which draws on data including patent filings, private and public market investments, job postings and research publication activity, along with search engine queries and media coverage.

“Organisations shouldn’t focus too heavily on the trends that are garnering the most attention.”

The report notes that the first half of 2023 has seen ‘a resurgence of enthusiasm’ about the potential impact of technology for both business and society – largely credited to generative AI, which is the only new entrant in the 15 trends highlighted.

The 15 trends are grouped into five categories: The AI revolution, which includes industralising machine learning and applied AI; building the digital future with next-generation software development, trust architectures and Web3; compute and connectivity frontiers; cutting-edge engineering and a sustainable world.

While generative AI is riding high, it’s applied AI that has made big moves, and is proving its worth.

The proportion of responding organisations adopting AI, which includes underlying technologies such learning, computer vision, natural-language processing and deep reinforcement learning, more than doubled since 2017, from 20 percent to 50 percent in 2022.

Among the real-world examples highlighted in the report is Emirates Team New Zealand’s use of AI to train a digital twin replica of a sailor to test designs, reducing costs by 95 percent over using human sailors to test designs, and enabling the testing of 10 times as many designs.

United States mining company Freeport-McMoRan, meanwhile increased production by 10 percent and reduced capital expenditure through deployment of an AI model to optimise production processes and total output at a copper mill.

While the numbers of new organisations adopting AI has levelled off, McKinsey says those who have adopted the technology are ramping up their AI work, nearly doubling the number of capabilities, such as natural language generation or computer vision, that they use.

Of those adopting AI, 25 percent attributed five percent or more of their companies’ EBIT to AI.

And there’s still plenty of equity investment being pumped into applied AI too – some $104 billion in 2022, down from a high of $146.8 billion in 2021.

“With investments flowing, AI continues to post state-of-the-art results with continuous improvements in areas such as model accuracy,” McKinsey says, noting that the cost to train image classification systems dropped by 64 percent, with training times improving by 94 percent since 2018.

“However, additional potential for applied AI could be unlocked by combining it with new emerging AI technology.

“For example, the foundational models underlying generative AI could process large amounts of unstructured manufacturing data, such as notes and logs, to enrich current AI solutions that optimise performance.”

Michael Chui, McKinsey partner, believes there isn’t an industry or business function that couldn’t enhance its performance through applying AI. “But capturing the value of AI is a journey that requires taking action across multiple dimensions, from talent to technology,” he cautions.

Advanced connectivity, including low-power wide area networks, Wifi 6 and 7 and 5G/6G and optical fibre, and cloud and edge technologies scored high for adoption, alongside applied AI.

The report notes that technologies such as cloud and edge computing have shown steady increases in innovation and continue to have expanded use cases across industries. More than 400 edge use cases have been identified, McKinsey says, with edge computing projected to have double-digit growth globally in the next five years.

Many of the technologies listed are slow burners. McKinsey says adoption of next-generation software development via new tools including AI pair programmers, low- and no-code platforms, infrastructure as code and automated code review, is slow – something it says might be due to technical challenges, the need for retraining and organisational hurdles. But it also notes that ‘significant’ productivity gains seen in early trials suggest widespread usage is on the horizon.

McKinsey research has shown time savings of 25 to 45 percent in code generation and 20-30 percent in code refactoring through use of AI-enabled tools.

“They also report an improvement in happiness, flow and fulfilment while using AI-enabled tools, which suggests that adopting these tools could help companies retain talent in a competitive talent market,” the report notes.

Also on the slow burn is Web3, with its underlying technologies of blockchain, smart contracts, and digital assets and tokens, including NFTs. While its saw $62 billion in equity investment in 2022 – and plenty of hype back in 2021 – McKinsey’s optimism is tempered by pragmatism, noting that new ventures are still testing and scaling viable business models and incumbent businesses are exploring Web3 use cases.

“Early adopters face several challenges, including unclear and evolving regulations and immature and emerging technology platforms, often with a poorer user experience than existing Web2 utilities.

“However, companies are beginning to find success with Web3 pilots, including new user engagement models and financial product offerings.”

Nike, with its .Swoosh Web3 platform, is among the big names making a play in the Web3 space – it dropped its first NFT digital sneaker collection earlier this year generating more than US$1 million in sales.

But despite some successes, the report notes that the value proposition and user experience of Web3 compared with incumbent systems – which are also evolving – are often not fully understood and the benefits remain unclear to many enterprises and consumers.

While investment in most tech trends tightened – and in many cases including applied AI, advanced connectivity, cloud and edge computing declined – year on year, trust architectures and digital identity saw a nearly 50 percent increase as technology resilience became increasingly front of mind – and vital – for organisations.

“Organisations shouldn’t focus too heavily on the trends that are garnering the most attention,” McKinsey notes.

“By focusing on the most hyped trends, they may miss out on the significant value potential of other technologies and hinder the chance for purposeful capability building.

“Instead, companies seeking longer-term growth should focus on a portfolio-oriented investment across the tech trends most important to their business.”