Gartner Forecasts IT Spending Growth Driven by AI Infrastructure

Gartner released a market forecast projecting worldwide IT spending of $6.31 trillion in 2026, a 13.5% year-over-year increase driven primarily by investment in AI infrastructure, data centers, and AI-enabled software. Data center systems are the fastest-growing segment, with spending expected to rise 55.8% to nearly $788 billion, while IT services will exceed $1.87 trillion.

The forecast attributes the surge to scaling AI workloads, especially large-model training and generative AI development, which shift infrastructure priorities from general-purpose systems to AI-optimized stacks. Key technical pressures called out are increased demand for GPUs and AI accelerators, higher requirements for memory bandwidth and low-latency fabrics, and growing adoption of heterogeneous node architectures combining CPUs, GPUs, and domain-specific accelerators. Gartner also highlights record price increases in high-bandwidth memory, which affects device costs and replacement cycles.

• •Data center systems: +55.8%, approaching $788 billion; hyperscale cloud expansions are the primary driver
• •IT services: largest category, $1.87 trillion+, covering implementation, managed services, and infrastructure services
• •Software: +15.1%, driven by GenAI model development and enterprise AI platforms
• •Devices: projected $856 billion, growth moderated by higher memory costs and slower replacement in low-margin segments
• •Communications services: steady growth at 4.8%

This forecast signals a structural reallocation of enterprise and cloud capital toward compute and memory subsystems optimized for AI. The combination of hyperscaler capex and enterprise AI projects creates a two-speed market: high-growth pockets around AI infrastructure and AI-first software, and slower growth in traditional device and communications categories. For semiconductor and OEM vendors, the immediate implication is intensified demand for high-performance memory and AI accelerators, but also margin pressure and supply-chain constraints driven by memory shortages. For platform and tooling vendors, the expansion in AI model spending opens opportunities for optimized runtimes, orchestration layers, and cost-management tools that reduce training and inference TCO.

Monitor HBM supply and pricing trends, hyperscaler procurement cycles, and vendor product roadmaps for AI accelerators and disaggregated architectures. Also watch software licensing and managed-service offerings around GenAI, which will determine how much enterprise spending flows from capital expenditure into recurring service models.

"This latest forecast underscores the accelerating momentum in AI infrastructure and advanced memory," said John-David Lovelock, Distinguished VP Analyst at Gartner. The statement captures the core risk and opportunity: where supply constraints exist, prices and vendor economics will change rapidly, creating winners and losers in the hardware and service stacks.