Gartner has forecast that worldwide spending on artificial intelligence will total $2.52 trillion in 2026, representing a 44% year-on-year increase, as enterprises and technology providers continue to invest heavily in AI foundations.
According to Gartner, the surge in spending will be driven largely by AI infrastructure, as vendors race to build out the compute, storage and networking capabilities required to support large-scale AI deployments. Infrastructure alone is expected to add $401 billion in incremental spending, accounting for 17% of total AI expenditure in 2026.
AI maturity, not just money, shaping adoption
Despite the sharp rise in investment, Gartner cautioned that AI adoption is increasingly being shaped by organisational readiness rather than pure budget allocation.
“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 at Gartner. “Organisations with greater experiential maturity and self-awareness are increasingly prioritising proven outcomes over speculative potential.”
Gartner expects AI to remain in the Trough of Disillusionment through 2026, influencing how enterprises buy and deploy AI solutions.
“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,” Lovelock added. “Improved predictability of ROI must occur before AI can truly be scaled up by the enterprise.”
Infrastructure dominates AI spending
Gartner’s projections show that AI-optimised servers and infrastructure will see a 49% increase in spending, as organisations modernise data centres and cloud environments to support AI workloads. This infrastructure push underpins growth across software, platforms and services, reflecting the reality that AI scalability depends on robust foundations.
Worldwide AI spending forecast (2025–2027)
| Market | 2025 | 2026 | 2027 |
| AI Services | 439,438 | 588,645 | 761,042 |
| AI Cybersecurity | 25,920 | 51,347 | 85,997 |
| AI Software | 283,136 | 452,458 | 636,146 |
| AI Models | 14,416 | 26,380 | 43,449 |
| AI Platforms for Data Science and Machine Learning | 21,868 | 31,120 | 44,482 |
| AI Application Development Platforms | 6,587 | 8,416 | 10,922 |
| AI Data | 827 | 3,119 | 6,440 |
| AI Infrastructure | 964,960 | 1,366,360 | 1,748,212 |
| Total AI Spending | 1,757,152 | 2,527,845 | 3,336,690 |
From experimentation to predictable value
The forecast highlights a decisive shift in enterprise behaviour—from experimental AI projects to more pragmatic, outcome-driven adoption. As AI spending approaches multi-trillion-dollar levels, Gartner expects competitive advantage to hinge less on who invests the most, and more on who can align AI infrastructure, software and skills to deliver predictable, scalable business value.