Worldwide AI-optimised infrastructure as a service (IaaS) spending is projected to grow 96% in 2026, reaching US$42 billion ($A59.5 billion), according to Gartner.
This is projected to rise to US$66 billion in 2027.
In 2026, global spending on inference ($US23.3 billion) will surpass that of training ($US19 billion), according to Gartner.
In addition, over half (55%) of AI-optimised 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, the company claimed.
Hardeep Singh, senior principal research analyst at Gartner, said the growth is being fuelled by infrastructure demand for large language model training, as well as operationalisation of AI across enterprise applications and workflows.
“As organisations 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-optimised infrastructure.”
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