Worldwide spending on artificial intelligence is projected to jump 47 per cent year-on-year to $2.59 trillion in 2026, driven by accelerating investments in AI infrastructure and AI-optimised servers as enterprises and cloud providers deepen adoption of generative AI and agentic workflows, according to a new report by research firm Gartner released on Tuesday, 19 May. The forecast marks one of the most aggressive single-year spending projections ever recorded for the technology sector.

Infrastructure Leads the Charge

AI-optimised infrastructure — encompassing AI-optimised Infrastructure-as-a-Service (IaaS), servers, network fabric, processing semiconductors, and devices — will account for over 45 per cent of total AI spending as vendors race to expand capacity. Spending on AI infrastructure alone is forecast to climb from $975,581 million in 2025 to $1,431,509 million in 2026.

John-David Lovelock, Distinguished VP Analyst at Gartner, noted that spending on AI-optimised servers is set to triple over the next five years, becoming the largest subsegment within AI infrastructure. 'Within this segment, spending on AI-optimised servers will triple over the next five years to become the largest subsegment, as cloud services providers expand capacity in anticipation of the workloads created by GenAI models and agentic workflows,' Lovelock said.

AI Models Outlook Raised Sharply

Gartner has revised its short-term outlook for AI models upward to 110 per cent growth in 2026, adding an estimated $6 billion in incremental spending for the year. Enterprises are expected to broaden their use of both generative AI models embedded in existing software and new AI agents deployed across multiple workflows.

Model consumption is anticipated to grow through multistep processes and integration into wide suites of enterprise tools, as organisations recognise the potential of agentic automation to streamline operations at scale. Total AI spending is forecast to rise from $1,764,947 million in 2025 to $2,595,667 million in 2026.

Enterprises Yet to Fully Engage

Lovelock pointed out that AI spending to date has been dominated by technology companies and hyperscalers, with enterprises yet to fully deploy their spending potential. 'Enterprises have yet to really flex their spending potential, which is set to happen in 2026,' he said, signalling a significant demand shift ahead.

This comes amid growing pressure on Chief Information Officers (CIOs) to demonstrate tangible business outcomes from AI investments. The report flagged that proving return on investment remains a central challenge for enterprise technology leaders navigating the current AI hype cycle.

The Accountability Challenge

Gartner cautioned that aligning AI initiatives with measurable strategic business objectives is critical for success. 'Aligning AI initiatives with strategic business objectives is the essential step for success. This incremental approach persists despite AI hype and valuations that reflect aspirations to transform the broader economy,' Lovelock said.

Notably, the cautionary note arrives even as valuations across the AI sector continue to reflect transformative expectations — a tension that analysts argue could widen if enterprise deployments fail to deliver verifiable productivity gains. As 2026 approaches, the scale of enterprise AI adoption will be the decisive variable in whether these projections hold.