Enterprise AI 2026

Enterprise AI spending jumps 35% to $407B as 86% of companies plan to increase their AI budget

Global enterprise AI spending is projected to hit $407 billion in 2026, up 34.8% from last year, with cloud infrastructure and governance both claiming a growing share of the budget.

Enterprise AI spending isn't slowing down after its initial pilot phase — it's accelerating. Global enterprise AI spending in 2026 is projected at $407 billion, up 34.8% from $302 billion in 2025, according to Value Add VC's sector-by-sector breakdown. On the broader market level, Gartner forecasts worldwide AI spending at roughly $2.5 trillion in 2026, up from about $980 billion in 2024.

Budgets are still going up, not flattening

86% of enterprises say their AI budget will rise in 2026, and only about 2% expect a cut — a sign that AI investment has moved well past the discretionary pilot-budget phase into a sustained line item.

Where the money is actually going

Within a typical 2026 enterprise AI budget, software tooling accounts for 30–40% of spend and cloud infrastructure another 20–25%. The notable shift is governance: it has climbed to 8–12% of budget, up from just 3–5% in 2024 — enterprises are now budgeting for compliance and oversight as a first-class cost, not an afterthought.

Infrastructure is the fastest-growing piece

IDC reports AI infrastructure spending held near $90 billion in Q1 2026 alone, with the full-year forecast raised to $497 billion. Global cloud infrastructure spending rose 29% year-on-year in Q4 2025, marking the sixth consecutive quarter of 20%+ growth, per Omdia. AI-related cloud spending now makes up 19% of total cloud spending in 2026, up from just 8% in 2023.

What this means for mid-market businesses

The spending data reflects large enterprises, but the underlying trend — governance and infrastructure now treated as core budget lines rather than afterthoughts — applies just as much to a growing business building its first serious AI or data platform. Underinvesting in the data foundation and governance layer is the most common reason AI initiatives stall. See Cor Advance Solutions' data warehousing and analytics services or AI & Machine Learning services to see how that foundation gets built without an enterprise-scale budget.

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