AI-Optimized IaaS Spending Set to Grow 96% Through 2026

Global expenditure on AI-optimized infrastructure as a service (IaaS) is projected to increase by 96% through 2026, reaching $42 billion, according to Gartner. The market is forecast to sustain this momentum, potentially reaching $66 billion by 2027.

“This growth is driven by continued demand for infrastructure to support large language model (LLM) training and the rapid operationalization of AI across enterprise applications and workflows,” stated Hardeep Singh, Senior Principal Research Analyst at Gartner. The emergence of agentic AI increases computational intensity through autonomous, multi-step execution, establishing inference as the primary consumption model and positioning AI-optimized IaaS as a fundamental component of enterprise strategies.

“As organizations shift from model development to production-scale deployment, fine-tuned and domain-specific models (DSMs) are increasingly integrated into customer-facing and operational systems, requiring continuous, real-time execution rather than periodic training,” Singh added. “This shift is accelerating the cloud consumption patterns and creating sustained demand for AI-optimized infrastructure.”

By 2026, global spending on inference ($23.3 billion) is expected to exceed expenditure on training ($19 billion). Fifty-five percent of AI-optimized IaaS spending is projected to support inference workloads in 2026, a figure that is expected to reach 59% in 2027. This growing share of inference-related tasks is anticipated to fundamentally reconfigure cloud investment priorities moving forward.