Gartner’s $239B AI forecast: Agentic workflows take half of GenAI model revenue
Agentic workflows will drive 50% of generative AI model revenue by 2030, up from 5% in 2025. Gartner published that projection on September 17, 2026, in its forecast analysis of the generative AI models market (G00861842). The number changes how every enterprise buyer should read the firm’s $239 billion AI platforms and models forecast.
Multistep reasoning, tool integration, and repeated validation steps multiply the inference events behind every completed business process. Gartner puts the impact at $38 billion in additional spending by 2030 from scaling agentic workflows alone.
Falling inference prices won’t offset it. Cheaper units unlock deeper automation, and deeper automation drives up token volume per task faster than prices fall. Gartner calls this a structural tailwind for GenAI model spending.
That consumption flywheel sits inside a market growing from $39 billion in 2025 to $239 billion by 2030 at a 42.8% compound rate, per Gartner’s June 25 forecast (G00855897). I built this analysis from both Gartner reports and Gartner’s country-level dataset, which covers 1,316 rows across 9 regions and 7 years. For the agentic spending crossover that sets up this post, see Gartner’s $5.95 trillion AI forecast puts the chatbot era on a 2027 deadline (August 5, 2026).
Model revenue is also one of the streams that has to pay for the infrastructure build-out. How far it falls short is the subject of my AI revenue gap comparison across Gartner, Goldman, Bain and JPMorgan.
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