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In briefGlobal investment in AI infrastructure and model architectures is projected to exceed $769 billion in 2026 — more than five times the $145 billion recorded in 2025 — according to McKinsey's Technology Trends Outlook 2026, published on 26 September.

1. The projection is based on roughly $384 billion invested in the first half of 2026, with the current rate assumed to hold for the remainder of the year. That would make AI infrastructure and model architectures the largest-funded technology trend in McKinsey's analysis, well ahead of its 2025 total of $145 billion.

2. The surge is accompanied by a fresh wave of activity among major AI companies. OpenAI is in talks with investors over additional funding that could value the company at around $1.2 trillion. SoftBank has launched an $11 billion bond offering intended to help finance a further $10 billion investment in OpenAI. Anthropic, meanwhile, is in discussions with Nvidia over a potential investment of up to $10 billion, as part of a proposed IPO that could raise as much as $100 billion, according to Reuters.

3. Safety concerns alongside the capital surge

4. The investment boom is unfolding at the same time that prominent figures inside the AI industry are voicing concern about how quickly new capabilities are being deployed. Anthropic CEO Dario Amodei has called on the global AI community to slow the release of new capabilities in order to allow more time to address safety risks.

5. OpenAI has called for mandatory national AI safety requirements, including independent assessments, cybersecurity measures and incident reporting for advanced AI systems. The company has also separately urged the United States to lead international efforts to establish technical standards for frontier AI and systems capable of recursive self-improvement, arguing that coordinated standards and incident reporting are necessary as AI capabilities continue to advance.

6. Broader technology investment trends

7. McKinsey's report identified five technology trends — agentic software development, AI infrastructure and model architectures, AI for scientific discovery and engineering, the future of space technologies, and the future of robotics — as being on course to receive more than double the investment in 2026 compared with 2025. All trends except advanced connectivity are expected to record higher year-on-year funding.

8. The report described the investment shift as reflecting the growing importance of physical infrastructure needed to scale AI, including semiconductors, data centres and power systems. Energy technologies alone attracted nearly $200 billion in investment in 2025, while spending on AI infrastructure doubled over the same year. McKinsey cautioned, however, that AI expansion could be constrained by shortages of energy, talent and capital, as well as legacy technology systems and cybersecurity risks.

9. In the United States, data centres running AI workloads are projected to consume as much electricity by 2030 as California does today. Globally, more than 2,500 gigawatts of energy projects are currently awaiting grid connections.

10. Enterprise adoption and financial returns

11. At the enterprise level, the report found that AI adoption is widening but converting that uptake into financial results remains difficult. It said 89 per cent of organisations regularly use AI in at least one business function, yet only 37 per cent report any positive EBIT impact from AI across the enterprise.

12. The report said the next phase of adoption will require companies to move beyond experimentation and redesign workflows around both humans and AI agents. McKinsey partner Oana Cheta said the central question of what she called the agentic era is not how autonomous agents can become, but how much autonomy an enterprise can safely absorb, pointing to operational and governance challenges likely to shape the next stage of AI adoption.

13. Taken together, the findings point to a widening gap between the speed at which capital is flowing into AI and the growing emphasis among leading AI companies on safety, oversight and governance as more capable systems are brought to market.

Based on reporting by ET Enterprise AI

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