AI Spending Set to Grow 49.5 Percent in 2026

The convergence of massive AI infrastructure investment and the deep embedding of AI into software services is driving global spending to unprecedented levels, according to Gartner. Worldwide spending on AI technologies is forecast to total $2.7 trillion in 2026, marking a 49.5% increase year-over-year.

“Demand for AI infrastructure (including AI-optimized IaaS, AI-optimized servers, AI network fabric, AI processing semiconductors and devices) to support anticipated future workloads remains strong and inelastic to pressures from memory-related pricing increases,” said John-David Lovelock, Distinguished VP Analyst at Gartner. “The buildout of AI data center capacity is the largest infrastructure project humanity has ever undertaken. The capacity growth from hyperscalers and service providers purchasing AI-optimized servers will continue to be the largest single area of spending.”

In the software segment, vendors are rapidly integrating agentic AI into their existing product lines to defend against new cross-functional competitors and maintain market relevance. With GenAI entering the "Trough of Disillusionment" in 2026, enterprises are increasingly turning to these embedded features from incumbent providers to drive operational efficiency, automate complex workflows, and enhance both customer engagement and decision-making processes.

“Meanwhile, enterprises are turning to service providers less often to help them manage the business transformation, and more often for the smaller indirect projects to exploit AI features of their incumbent software system," said Lovelock. “The risks associated with vendor lock-in, data sovereignty, and run-away costs are not deterring buyers from adopting these proprietary capabilities. The combination of transformation and indirect projects is forecast to drive a $1.2 trillion opportunity in AI services by 2030."

The short-term outlook for AI application development platforms has seen a significant upward revision, with projected growth rising to 39% in 2026. This reflects a surge in demand from enterprises and service firms seeking to develop custom AI applications tailored to their specific operational needs. For model providers, the pressure to deliver cost-efficient models aligned with enterprise use cases is creating an opening for domain-specific language models (DSLMs). Consequently, the 2026 growth rate for generative AI models has been revised upward from 110% to 117%.