AI-Optimized IaaS Spend To Grow 96% In 2026


Inference-Driven AI Infrastructure Spending to Grow 55% in 2026


Hardeep Singh, Sr Principal Research Analyst at Gartner

FinTech BizNews Service

Mumbai, 10 August, 2026: Worldwide AI-optimized infrastructure as a service (IaaS) spending is projected to grow 96% through 2026, reaching $42 billion, according to Gartner, Inc., a business and technology insights company.

“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,” said Hardeep Singh, Sr Principal Research Analyst at Gartner.

The market is forecast to sustain high growth and reach $66 billion in 2027. 

Spending on Infrastructure as a Service, Worldwide, 2025-2027 (Millions of Dollars)

 

 

 

 

Segment

 

 

 

2025 Spending

 

 

 

2025 Growth (%)

 

 

 

2026 Spending

 

 

 

2026 Growth (%)

 

 

 

2027 Spending

 

 

 

2027 Growth (%)

Total AI-optimized IaaS

 

21,529

 

180.0

 

42,276

 

96.4

 

66,143

 

56.5

Total IaaS

222,170

25.3

287,347

29.3

359,899

25.2

Source: Gartner (August 2026)

Inference Workload Spending to Surpass Training Spending in 2026

The rise of agentic AI amplifies compute intensity through multistep, autonomous execution, making inference the dominant consumption model and positioning AI-optimized IaaS as a critical enabler of enterprise AI 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,” said Singh. “This shift is accelerating the cloud consumption patterns and creating sustained demand for AI-optimized infrastructure.”

In 2026, global spending on inference ($23.3 billion) will surpass that of training ($19 billion). Fifty-five percent of AI-optimized IaaS spending is forecast to support inference in 2026 and is set to reach 59% in 2027. The growing share of inference workloads is expected to reshape cloud investment priorities.

 

 

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