Worldwide spending on artificial intelligence is expected to surge by 47% year-on-year to $2.59 trillion in 2026. This growth is attributed to increased investments in AI infrastructure and AI-optimized servers as businesses and cloud providers speed up the adoption of generative AI and agentic workflows, according to a report. Gartner’s report highlighted that AI-optimized infrastructure, including servers and processing semiconductors, will make up over 45% of the total spending as vendors enhance their capabilities.
The report also mentioned that spending on AI-optimized servers is projected to triple over the next five years, becoming the largest subsegment. This expansion is in anticipation of the workloads generated by GenAI models and agentic workflows. Gartner’s Distinguished VP Analyst, John-David Lovelock, emphasized the significant growth potential, with a 110% increase in AI models expected in 2026, translating to an additional $6 billion in spending for the current year.
Enterprises are set to broaden their utilization of GenAI models integrated into existing software applications and new AI agents across various workflows. The consumption of models is anticipated to rise through multi-step processes and integration into comprehensive tool suites as businesses acknowledge the value of agentic automation, as outlined in the report.
The report forecasted a notable increase in spending on AI infrastructure, from $975.581 million in 2025 to $1,431.509 million in 2026. Overall AI spending is estimated to climb from $1,764.947 million to $2,595.667 million during the same period. Lovelock highlighted that while AI spending has been predominantly led by technology firms and hyperscalers, enterprises are expected to significantly boost their investments in 2026.
CIOs are cautioned about the challenges in demonstrating the value derived from AI investments and showcasing tangible business outcomes. Lovelock stressed the importance of aligning AI initiatives with strategic business goals for successful implementation. Despite the hype surrounding AI and ambitious economic transformation aspirations, a gradual approach is advised to realize the full potential of AI technologies.
