Gartner predicts a 10.8% expansion in IT spending, fueled by hyperscale providers’ ongoing acquisition of servers optimized for artificial intelligence.
According to Gartner’s most recent projection, worldwide information technology expenditure is anticipated to climb by 10.8%, reaching $6.15 trillion by 2026, with the majority of this increase driven by AI infrastructure investments.
This outlook reveals a persistent surge in spending, seemingly unaffected by discussions regarding a potential AI bubble. Businesses and cloud service providers are significantly investing in AI-specific hardware and software, with data center systems emerging as the primary catalyst for this trend, as noted by the research company.
“Despite apprehensions about an AI bubble, the expansion of AI infrastructure continues at a swift pace, with increasing outlays for both AI-centric hardware and software,” stated John-David Lovelock, a distinguished VP analyst at Gartner, in the report. “Hyperscale cloud providers’ sustained demand is propelling further investment in servers specifically designed for AI tasks.”
This updated forecast indicates an upward adjustment from Gartner’s previous October prediction of $6.08 trillion for 2026, implying that the intense focus on AI is intensifying rather than diminishing.
The figures corroborate this, as expenditures on servers and data centers are projected to escalate at rates significantly surpassing the general growth in IT.
Data Centers: The Primary Destination for Capital
To understand the trajectory of IT budgets in 2026, one must focus on data centers. Spending on data center infrastructure is anticipated to leap by 31.7%, surpassing $650 billion, a substantial rise from approximately $500 billion in 2025, marking an astounding $150 billion increase within just one year, according to the report.
Gartner’s analysis indicates that server expenditures alone will soar by 36.9% annually, fueled predominantly by hardware specifically optimized for AI. Major hyperscale providers, such as AWS, Microsoft Azure, and Google Cloud, are engaged in a rapid expansion effort to develop the necessary infrastructure for training and deploying progressively larger AI models.
Furthermore, the expansion isn’t merely about increasing server quantity. These are bespoke systems equipped with advanced GPUs and tailor-made silicon, engineered specifically for AI operations, thereby justifying their exceptionally high costs.
Software Expansion Moderates, Yet Generative AI Remains Robust
The software sector is still poised for healthy expansion in 2026, though Gartner has marginally adjusted its prediction downwards. Software expenditure growth is currently forecast at 14.7%, a slight decrease from the prior estimate of 15.2%, covering both application and infrastructure software categories.
“Even with this slight adjustment, overall software spending will comfortably exceed $1.4 trillion,” Lovelock further elaborated in the analysis.
The key trend within the software domain is generative AI. “Forecasts for generative AI model expenditures in 2026 are holding steady, anticipating an 80.8% growth,” Gartner stated. “GenAI models are sustaining vigorous growth, and their proportion of the software market is projected to increase by 1.8% in 2026,” the report also mentioned.
This expansion underscores the rapid integration of GenAI as a fundamental component across all enterprise software. From customer support systems to development utilities and productivity applications, providers are actively incorporating AI functionalities into their offerings—and pricing them accordingly.
Device Market Encounters a Setback
Not all segments of the IT landscape are experiencing explosive growth. The device sector, encompassing personal computers, tablets, and smartphones, is predicted to reach $836 billion in expenditure by 2026, yet its growth rate will decelerate to a mere 6.1%, a decrease from the more robust performance observed in 2025, as per the forecast.
The primary reason? Memory costs. “This deceleration primarily stems from escalating memory prices, which are driving up average selling prices and deterring consumers from upgrading devices,” Lovelock clarified. “Furthermore, increased memory expenses are leading to supply scarcities in the more affordable market segments, where profit margins are narrower.” This exemplifies a typical supply chain challenge: memory producers are prioritizing the manufacture of profitable components for AI servers and data center equipment, forcing the consumer and business device markets to contend with supply shortfalls, the report highlighted.
