According to Gartner, global spending on AI is expected to total $259 trillion in 2026, a 47% increase from the previous year.
“Over the next few years, the need for capacity will drive AI infrastructure, including AI-optimized IaaS, AI-optimized servers, AI network fabrics, and AI processing semiconductors and devices, to become the largest segment of the market, accounting for more than 45% of spending and led by vendors,” said John-David Lovelock, Distinguished VP Analyst at Gartner. “Within this segment, spending on AI-optimized servers will triple over the next five years, making it the largest subsegment, as cloud service providers expand capacity in anticipation of the workloads created by GenAI models and agent workflows.”
Enterprises will expand their use of both GenAI models built into existing software applications and new AI agents within multiple workflows. As companies realize the potential value of agent automation, we expect to see increased usage of models through multi-step processes and integration into broader tool suites. The move means the short-term outlook for AI models has been raised to 110% growth in 2026, increasing spending by $6 billion this year.
Global AI spending by market, 2025-2027 (USD millions)
| market | 2025 | 2026 | 2027 |
| AI service | 436,351 | 585,527 | 759,418 |
| AI Cyber Security | 25,920 | 51,347 | 85,997 |
| AI software | 282,897 | 453,209 | 638,431 |
| AI model | 15,494 | 32,604 | 59,161 |
| AI platform for data science and machine learning | 21,292 | 29,928 | 42,639 |
| AI application development platform | 6,587 | 8,416 | 10,922 |
| AI data | 826 | 3,126 | 6,480 |
| AI infrastructure | 975,581 | 1,431,509 | 1,890,310 |
| Total spending on AI | 1,764,947 | 2,595,667 | 3,493,358 |
Source: Gartner (May 2026)
“Historically, spending on AI has been primarily driven by technology companies and hyperscalers,” Lovelock said. “Companies have yet to truly flex their spending potential. That is just around the corner, and 2026 will be the year of transition. Currently, organizations are showing limits in their willingness to use AI to drive disruptive enterprise change. Instead, they are favoring tactical AI initiatives that incrementally improve efficiency and productivity.”
“This challenges CIOs to prove the value of their AI investments and demonstrate tangible business outcomes,” Lovelock said. “Aligning AI efforts with strategic business objectives is a critical step to success. This incremental approach persists despite AI hype and valuations that reflect the desire to transform the entire economy.”
