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Worldwide spending on AI is forecast to total $2.7 trillion in 2026, a 49.5% increase year-over-year, according to Gartner, Inc., a business and technology insights company.
“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 even 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 market, vendors across different software types are rapidly embedding agentic AI within their existing products to maintain relevance in the market and defend against new cross-functional agents. With GenAI firmly in the Trough of Disillusionment in 2026, enterprises are using these simpler embedded AI features from their incumbent software providers to grow operational efficiency and automate workflows, improve customer engagement and enhance decision making.
“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 are forecast to drive a $1.2 trillion opportunity in AI services by 2030."
Near-Term Outlook Changes
The short-term outlook for AI application development platforms has increased from 28% growth in 2026 in the previous forecast to 39% in this quarter’s forecast, as enterprises, software providers and services firms seek to develop custom AI applications tailored to their individual needs. Enterprises are looking to their providers to help them manage their costs and embed usage tracking into their workflows to evaluate success. For model providers, the pressure to offer more cost-efficient models that are aligned to enterprise use cases is opening a small but growing opportunity for domain-specific language models (DSLMs). As a result, the 2026 growth rate for generative AI models has increased from 110% growth in the previous forecast to 117% growth in the current forecast.
Long-Term Outlook Changes
In the current forecast, Gartner has separated cross-functional agents and assistants from AI software and added consumer agents and assistants into the AI spending forecast to better show the emerging opportunity in this area.
