Global GenAI spending to reach $644Bn in 2025: Gartner Report

Global spending on generative AI (GenAI) is set to rise dramatically in 2025, reaching USD 643.86 billion, according to Gartner’s latest forecast. This prediction marks a substantial 76.4% jump compared to 2024, where total GenAI-related IT spending stood at USD 364.96 billion. The figures, released on March 31, 2025, in Gartner’s “Forecast Alert: GenAI IT Spending, 2023–2028, Worldwide,” point to a maturing market where enterprises are doubling down on automation, performance optimization, and AI-enhanced experiences, driven by real business use cases rather than experimental hype.

In 2024, GenAI investments surged by an astounding 336.7% from the previous year, fueled largely by early enthusiasm, internal proof-of-concept (PoC) projects, and widespread integration into IT service models. That year, devices accounted for the lion’s share of spending nearly USD 199.6 billion, while software and services came in at USD 19.16 billion and USD 10.57 billion respectively. Servers supporting AI workloads received USD 135.6 billion in investments.

Looking ahead to 2025, each of these categories is set to grow even further. Device-related spending alone is projected to nearly double, hitting USD 398.3 billion. Software investments will also grow substantially to USD 37.15 billion, up 93.9% year-over-year. Services are expected to more than double as well, reaching USD 27.76 billion, a 162.6% rise from 2024. Server spending will continue to rise, albeit at a slower pace, reaching USD 180.6 billion (up 33.1%).

It is believed the biggest driver behind this expansion is the increasing presence of AI capabilities in consumer and enterprise hardware. Gartner notes that nearly 80% of total GenAI spending in 2025 will go toward AI-enabled devices. These include smartphones, PCs, and specialized servers, many of which now ship with AI features as standard, even if end-users aren’t actively seeking them.

While consumer enthusiasm may be tapering off due to unmet expectations from early GenAI use cases, enterprises are continuing to adopt off-the-shelf AI tools that integrate more seamlessly with their existing ecosystems. This clearly reflects a shift in strategy of enterprises from building AI solutions in-house to deploying commercial solutions with predictable value and quicker implementation.

The data as well showcases a broader trend as GenAI is no longer an emerging technology, it’s becoming an embedded layer across IT ecosystems. And, for CIOs and IT leaders, the challenge will now be to navigate this growth with clarity, ensuring AI investments deliver measurable outcomes while balancing cost, complexity, and long-term scalability. As AI capabilities become core to digital transformation, spending patterns will likely continue to evolve, shifting from speculative to strategic.