Enterprise AI Adoption · Index

Thank you for reading this post, don't forget to subscribe!

Home / Indexes / Enterprise AI Adoption / Enterprise AI 2026

Enterprise AI Statistics 2026

What enterprises actually spend on AI in 2026, how far AI agents have scaled, and the gap between expected and realized ROI. Every figure is linked to its primary source and dated.

By The AI Index · Updated Jun 20, 2026 · 7 min read · 6 sourced figures

Enterprise AI spending & deployment

Enterprise generative-AI spending reached roughly $37 billion in 2025 — more than triple the prior year (Menlo Ventures), split approximately $19B on applications and $18B on infrastructure. At the same time, 23% of organizations are now scaling agentic AI with another 39% experimenting (McKinsey), yet Gartner warns that more than 40% of agentic AI projects will be canceled by 2027 (Gartner).

Where enterprise GenAI budgets go

Within the $19 billion 2025 application-layer spend, the departmental breakdown is concentrated in engineering — coding tools alone account for roughly $4 billion (~55% of departmental spend), per Menlo Ventures. Coding has clean, measurable productivity outcomes and the fastest time-to-value among enterprise GenAI workloads, compounding on a developer base organizations already pay for.

The rise of AI agents

Agentic AI is the defining enterprise trend of 2026. McKinsey finds 23% of organizations already scaling an agentic system, with another 39% experimenting. Gartner expects 33% of enterprise software applications to embed agentic AI by 2028, up from less than 1% in 2024 — while cautioning that much of today’s activity is early-stage and that “agent washing” (rebranding non-agentic products as agents) is widespread.

ROI: high expectations, uneven reality

Expectations are sky-high: in PagerDuty’s 2025 survey of 1,000 executives, companies anticipate an average 171% ROI on agentic AI (192% in the U.S.), and more than half say they’ve already deployed agents. But these are projected returns. The realized picture is more sober — McKinsey finds only 39% of organizations attribute any EBIT impact to AI so far, and a small group of roughly 6% “AI high performers” captures a disproportionate share of the value.

Top barriers: governance & cost

Gartner projects 40%+ of agentic AI projects will be canceled by 2027 due to unclear ROI, escalating costs, and inadequate controls. “Agent washing” means only a small fraction of vendors claiming agentic capabilities actually deliver them, so buyer due diligence is now critical. The high performers that report meaningful EBIT impact redesign workflows around AI rather than bolt it on — and although unit inference is cheap, total cost can scale rapidly with agentic loops and multi-step reasoning.

The numbers in full

Figures reflect each source’s latest release.

Frequently asked

How much do enterprises spend on AI?
Enterprises spent roughly $37 billion on generative AI in 2025, up 3.2× from $11.5 billion in 2024 — split approximately $19B on applications and $18B on infrastructure. (Menlo Ventures)

What is the ROI of enterprise AI in 2026?
Companies anticipate an average 171% ROI on agentic AI (192% for U.S. enterprises) — but these are projections. In practice, only 39% of organizations attribute any EBIT impact to AI, with returns concentrated among a small group of high performers. (PagerDuty / McKinsey)

How many enterprises use AI agents?
23% of organizations are scaling an agentic AI system and 39% are experimenting. Gartner forecasts 33% of enterprise software applications will embed agentic AI by 2028, up from under 1% in 2024. (McKinsey / Gartner)

Why do enterprise AI projects fail?
The main causes are weak governance, unclear ROI, and runaway costs. Gartner projects over 40% of agentic AI projects will be canceled by the end of 2027. (Gartner)

Primary sources