AI inference spending overtakes model training for first time, Gartner says

Global spending on AI inference workloads is set to exceed training expenditures for the first time this year, a shift that Gartner ↘ 2.18% says marks a turning point in how businesses use artificial intelligence. According to a Gartner report released Monday, enterprises and cloud providers will spend $23.3 billion on inference in 2026, compared with $19 billion on training, with inference accounting for 55% of AI-optimized infrastructure-as-a-service spending.ciodive+2

The milestone reflects a broader move from building AI models to running them at scale. Overall spending on AI-optimized IaaS is projected to nearly double this year, rising 96.4% from $21.5 billion in 2025 to $42.3 billion, before climbing to $66.1 billion in 2027.gartner+2

From Experimentation to Production

Inference workloads power the operational side of AI — generating responses, recommendations, and decisions in real time. The fact that inference now commands a larger share of spending than training signals that organizations are moving past experimentation, according to Hardeep Singh, senior principal analyst at Gartner.ciodive

"For the last few years, AI infrastructure demand was largely driven by model providers training the large foundation models," Singh said. "Now, enterprises are embedding AI into applications, business processes and customer experiences, which requires continuous inference rather than periodic training."ciodive

Gartner attributed the shift partly to the rise of agentic AI and the deployment of fine-tuned, domain-specific models in customer-facing and operational systems. Inference's share of AI-optimized IaaS spending is forecast to reach 59% in 2027.expresscomputer+3

A Broader Spending Surge

The infrastructure report arrives against a backdrop of surging AI investment. Gartner forecast in January that worldwide AI spending would reach $2.52 trillion in 2026, a 44% increase over 2025. In July, the firm raised its overall global IT spending projection to $6.37 trillion, citing accelerating AI demand.cfodive+1

Top hyperscalers Google Cloud Alphabet Inc. ↗ 0.87%, Microsoft ↗ 2.38% Azure, and AWS Amazon.com, Inc. ↗ 3.29% plan to invest more than $500 billion in capital expenditures for AI infrastructure this year. Enterprise spending on generative AI models and AI agents is also expected to more than double in 2026, according to separate Gartner data from May.ciodive

What It Means for CIOs

Singh urged technology leaders to treat AI infrastructure as a strategic investment rather than an experimental budget item. As AI becomes embedded in enterprise workflows, companies need infrastructure capable of supporting higher performance, lower latency, and greater scalability, he said — prompting many to reassess their cloud strategies in favor of hybrid approaches combining public cloud, private cloud, colocation, edge, and sovereign environments.ciodive

"It is increasingly becoming a business capability that determines how quickly and effectively enterprises can scale AI across the enterprise," Singh said.ciodive