Gartner sees AI spend hitting USD $2.52trn by 2026

Gartner forecasts worldwide spending on artificial intelligence will reach USD $2.52 trillion in 2026, driven by increased investment in infrastructure and AI-optimised servers.

The research group said total AI spending will rise 44% year-on-year from USD $1.76 trillion in 2025. It also projected total AI spending will reach USD $3.34 trillion in 2027.

Gartner's figures break the market into AI services, cybersecurity, software, models, platforms and infrastructure. Infrastructure accounts for the largest share of projected expenditure across the period, the forecast shows.

Infrastructure focus

Gartner said spending on AI infrastructure will total USD $1.37 trillion in 2026, up from USD $965 billion in 2025. It expects the category to reach USD $1.75 trillion in 2027.

It also flagged a separate infrastructure effect this year. Gartner said AI infrastructure will add USD $401 billion in spending in 2026 as technology providers continue to build out AI foundations.

Gartner said investment in AI-optimised servers will increase by 49% in 2026. It said this will represent 17% of total AI spending for the year.

Enterprise buying

The forecast points to changes in how enterprises source AI. Gartner argued that incumbent vendors have an advantage as organisations look for more predictable returns.

"AI adoption is fundamentally shaped by the readiness of both human capital and organisational processes, not merely by financial investment," said John-David Lovelock, Distinguished VP Analyst, Gartner.

Gartner's view links AI adoption to workforce skills, organisational readiness and operating processes. It also suggests that boards and executive teams will set a higher bar for measurable outcomes as spending expands.

"Organisations with greater experiential maturity and self-awareness are increasingly prioritising proven outcomes over speculative potential," said Lovelock.

Gartner also characterised market sentiment as cautious during 2026. "Because AI is in the Trough of Disillusionment throughout 2026, it will most often be sold to enterprises by their incumbent software provider rather than bought as part of a new moonshot project," said Lovelock.

The analyst added that large-scale deployment still hinges on clearer business cases. "The improved predictability of ROI must occur before AI can truly be scaled up by the enterprise," said Lovelock.

Market breakdown

Outside infrastructure, Gartner forecast AI services spending of USD $589 billion in 2026, up from USD $439 billion in 2025. It expects services to rise to USD $761 billion in 2027.

Gartner forecast AI software spending of USD $452 billion in 2026, compared with USD $283 billion in 2025. It expects the category to reach USD $636 billion in 2027.

AI cybersecurity is smaller in absolute terms but grows rapidly in the forecast. Gartner projected spending of USD $51.3 billion in 2026, up from USD $25.9 billion in 2025, before reaching USD $86.0 billion in 2027.

The forecast also includes spending on AI models and supporting tools. Gartner projected AI models spending of USD $26.4 billion in 2026, up from USD $14.4 billion in 2025, and USD $43.4 billion in 2027. It forecast USD $31.1 billion for platforms for data science and machine learning in 2026, rising to USD $44.5 billion in 2027.

Gartner projected AI application development platforms at USD $8.4 billion in 2026, up from USD $6.6 billion in 2025. It forecast USD $10.9 billion in 2027.

The dataset also shows a sharp rise for AI data spending. Gartner put the category at USD $3.1 billion in 2026, up from USD $827 million in 2025, before rising to USD $6.4 billion in 2027.

Gartner's forecast implies that suppliers of compute, storage, networking and server systems will capture a significant share of AI budgets in the near term, even as spending on software and services climbs. It also suggests that enterprises will evaluate AI purchases through procurement and governance processes that place greater weight on demonstrable returns.

"Organisations with greater experiential maturity and self-awareness are increasingly prioritising proven outcomes over speculative potential," said Lovelock.