AI infrastructure investment is projected to reach around $769 billion in 2026, more than five times the $145 billion invested in 2025, according to McKinsey’s Technology Trends Outlook 2026. The estimate is based on nearly $384 billion invested in the first half of 2026, assuming the current pace continues through the year.
McKinsey identifies AI infrastructure and model architectures as the most heavily funded technology trend it tracks, driven by rising demand for the physical systems needed to scale advanced models.
AI infrastructure driving the investment surge
The investment boom reflects growing spending on semiconductors, data centres and power systems required to support large-scale AI deployment. Major companies and investors are committing substantial capital: OpenAI is in discussions for additional funding at a potential valuation of around $1.2 trillion; SoftBank has launched an $11 billion bond offering to support a further $10 billion investment in OpenAI; and Anthropic is in discussions with Nvidia over a potential investment of up to $10 billion, according to Reuters.
Safety, governance and energy constraints
The rapid flow of capital is occurring amid rising industry concerns that safety measures and governance frameworks may not keep pace with increasingly capable AI systems. Anthropic CEO Dario Amodei has called for a slower rollout of new AI capabilities to allow more time to address safety risks. OpenAI has publicly backed mandatory national AI safety requirements, including independent assessments, cybersecurity measures and incident reporting for advanced AI systems.
McKinsey also identified five technology trends on track to attract more than twice as much investment in 2026 as in 2025: agentic software development; AI infrastructure and model architectures; AI for scientific discovery and engineering; space technologies; and robotics.
Energy could become a key constraint on further expansion. McKinsey estimates that US data centres running AI workloads could consume as much electricity by 2030 as California uses today. Globally, more than 2,500 gigawatts of energy projects are waiting for grid connections, highlighting infrastructure bottlenecks that could limit growth.
AI adoption is spreading across businesses—89 percent of organisations regularly use AI in at least one business function—but only 37 percent report a positive impact on EBIT, revealing a gap between adoption and measurable financial returns. The next phase of investment is therefore expected to focus not only on building larger models and infrastructure but also on integrating AI into business workflows while managing energy, cybersecurity, governance and safety risks.
