AI capability racing ahead of infrastructure and workplace change, McKinsey finds

Artificial intelligence is developing faster than the infrastructure and organisational change required to put it to work, leaving businesses to contend with a new set of bottlenecks, according to a report by the McKinsey Global Institute released this month.

The complexity of tasks that AI can reliably handle has been doubling roughly every four months since 2023, the report estimates. Data centres, power capacity and chip manufacturing, by contrast, are expanding at a far slower pace.

"The tools are here. But the reorganization is not," the report observes, describing a widening gap between how quickly AI is maturing and how slowly companies are reshaping themselves around it.

Adoption is broad but shallow. Among organisations surveyed in 2026, 89 per cent reported using AI in at least one business function, yet only 46 per cent had moved past the pilot stage. Outside a small set of high-performing firms, only about a quarter of respondents had redesigned workflows around AI rather than bolting the tools onto existing processes.

That gap is likely to shape how soon AI translates into productivity gains and broader economic growth, the report suggests. AI is already helping firms finish individual tasks faster, but wider gains will depend on reworking workflows and rolling those changes out across operations.

The nature of the constraints has shifted over time. Access to advanced chips and computing capacity was initially the main obstacle, followed by electricity supply and grid connections. Looking ahead, applications, workforce skills and organisational workflows are expected to become the binding limits on wider adoption.

Investment in AI infrastructure continues to climb. McKinsey estimates cumulative global spending on data centres could reach USD 7 trillion between 2025 and 2030, a large share of it driven by AI demand. The report cautions, however, that infrastructure spending could outrun actual demand and leave excess capacity behind.

For businesses, the risk is that AI capabilities move faster than their ability to adapt technology, workflows and organisational structures. The report urges leaders to build capacity for rapid adaptation and to use AI not just to automate existing tasks but to develop new products, businesses and sources of growth.

Its conclusion is that AI's eventual impact will rest not only on technological progress but also on how infrastructure, investment, regulation, organisations, markets and workers respond to capabilities that are advancing quickly.