Enterprise JUL 30, 2026

Gartner sees AI model and platform spend hitting $64B in 2026, with specialized models up 210%

Worldwide end-user spending on AI models and platforms is on pace to grow 63.4% to $64.25B, per Gartner's July 20 forecast — but buyers are tightening scrutiny and shifting toward specialized models.

BY GRETA REINHART · ENTERPRISE SAAS

Worldwide end-user spending on AI models and platforms will hit $64.25 billion in 2026, up 63.4% from $39.31 billion in 2025, according to a Gartner forecast published July 20. The composition of that spend is where the story lives.

Models themselves are growing 117% year-over-year; the platform layer only 36.9%. Inside the model bucket, foundation generative models climb 104.2%, from $11.44 billion to $23.36 billion, while domain-specific and specialized generative models expand 210%, from $1.58 billion to $4.91 billion. Data-science and ML platforms move from $19.41 billion to $26.44 billion; application development platforms from $6.89 billion to $9.54 billion.

The 210% line is the one that reshapes procurement conversations. It means enterprise buyers, having spent two cycles paying frontier developers by the token for general-purpose intelligence, are now writing checks for narrower systems that solve legible problems. Specialized platforms like Glean, Dust, and LemonLime sit inside that cohort, which is where the money is actually rotating.

Gartner’s Arunasree Cheparthi, senior principal research analyst, put the buy-side mood plainly: “enterprise AI budgets are coming under greater scrutiny, with increased focus on usage efficiency, cost control and measurable outcomes.” Cheparthi told CRN Asia the commercial edge is shifting to suppliers that make AI usage legible, embedding evaluation, cost transparency and usage tracking directly into customer workflows.

BlackRock Investment Institute’s July 24 weekly commentary reads the same signal from the capital-markets side: rising bills are pushing enterprises toward model routing and lower-cost models, a trend that could erode pricing power at frontier developers. That’s the doom loop the model layer has quietly walked into. Growth is real; margin capture is contested.

Scale matters here. Models and platforms are roughly 2.5% of total AI outlays, with Gartner separately forecasting worldwide AI spending above $2.5 trillion in 2026 and data-center systems alone passing $788 billion. The intelligence layer is a rounding error against the concrete-and-copper build-out beneath it.

Downstream, Fortune Business Insights pegs the AI SDR market at $4.27 billion in 2025 and $5.22 billion in 2026, reaching $24.32 billion by 2034 at a 21.2% CAGR, with outbound at 43.3% share. That’s what “measurable outcomes” looks like when it lands in a revenue org: specialized tooling, tracked pipeline, defensible line items.

Sources

About the author

Greta Reinhart

ENTERPRISE SAAS

Greta Reinhart tracks the enterprise software stack from San Francisco — data platforms, AI bundling, seat pricing, and channel checks across the largest SaaS vendors. She files on go-to-market shifts, packaging changes, and quarterly enterprise reads.