Gartner's 2026 AI Spending Forecast: $64B on Platforms & Models Inside a $2.59 Trillion Market

Within this $64 billion bucket, GenAI models — both foundation and domain-specific — are the high-growth engine, while traditional data science/ML platforms and AI app-development platforms grow at a steadier pace.

The Fastest-Growing Subcategories

Domain-specific language models (DSLMs) and specialized GenAI models are the standout category, with spending more than tripling in a single year. Gartner senior principal research analyst Arunasree Cheparthi noted that organizations are increasingly seeking models tailored to their industry or task, rather than relying solely on general-purpose foundation models .

Foundation GenAI models, while growing at a lower percentage rate (104.2%), still represent a larger absolute increase — from $11.4 billion to $23.4 billion — and remain the single largest spending line within the model category .

How $64 Billion Fits Inside $2.59 Trillion (May 2026)

Gartner issued a broader worldwide AI spending forecast on May 19, 2026, covering the full AI technology stack . The key numbers:

• Total worldwide AI spending (2026): $2.59 trillion, up 47% year-over-year from roughly $1.76 trillion in 2025 .
• AI infrastructure dominates: More than 45% of the total goes to vendor and hyperscaler infrastructure build-out — servers, semiconductors, and data center hardware .
• AI agent software is the fastest-growing overall segment, rising from $86.4 billion in 2025 to $206.5 billion in 2026, about +139% .
• AI software (including platforms, models, and AI-enhanced SaaS) is a subset of this $2.59 trillion; the $64 billion platforms-and-models figure sits inside the broader AI software category, which Gartner estimates at roughly $400 billion+ in total enterprise AI software spending .
• AI services (consulting, implementation, managed services) and AI-embedded devices (GenAI smartphones, etc.) account for the remainder.

The key relationship: The $64 billion "AI platforms and models" market is the end-user spending on core building blocks. It represents roughly 2.5% of the $2.59 trillion total AI spend — because the vast majority of that $2.59 trillion goes to vendor-side infrastructure, AI-enhanced hardware, services, and embedded AI in products (e.g., AI PCs, smartphones) rather than platform/model procurement alone .

Caveat: Two Forecast Updates in 2026

Gartner revised its total-AI spending forecast upward between January and May 2026. The January 2026 forecast pegged total AI spend at $2.52 trillion (44% YoY) ; the May update raised that to $2.59 trillion (47% YoY), adding roughly $70 billion, partly due to higher expected model consumption . The July 2026 platforms-and-models forecast is consistent with that upward revision.

What This Means

The data paints a clear picture: GenAI models, especially domain-specific ones, are the growth engine within AI spending. But the numbers also show that the bulk of AI investment remains in infrastructure — the servers, chips, and data centers that power those models. For enterprises, the takeaway is that model spending is accelerating fast, but infrastructure costs still dominate the overall AI budget.