Global IT spending is entering a new phase of expansion, propelled by surging investment in AI and the infrastructure required to support it. Gartner forecasts that worldwide IT spending will hit $6.31 trillion in 2026, a remarkable 13.5% increase from last year.
The biggest shift is occurring in data center systems, where spending is expected to grow by a jaw-dropping 55.8%, easily outpacing all other IT segments. This leap reflects the massive, industry-wide scaling of AI workloads, which call for high-performance computing platforms and pricey specialized hardware. As enterprises and hyperscalers expand their AI capabilities, vast levels of capital are being spent on servers, accelerators, and advanced memory.
“The push towards more variety in AI workloads in the cloud, and moving towards an agentic AI operation in many enterprises, is stretching the demand for compute resources,” Jack Gold, President of J. Gold Associates, told Techstrong.it.
“Most inference and agent workloads run on traditional CPUs rather than GPUs, and while we see continued investments in GPU capacity, CPUs are now approaching parity in investments driven by the change from training to agents, along with physical AI, where general purpose compute is required and CPUs outperform GPUs in this area.”
IT Services Remains Largest Category
While infrastructure dominates growth, IT services remain the largest spending category, projected to exceed $1.87 trillion. The investment goes toward sustained demand for implementation and managed services as enterprises move from experimentation to real-world deployment of AI systems. The sheer complexity of these environments is reinforcing reliance on service providers to manage hybrid and cloud-based architectures.
Software is also seeing strong gains, driven largely by generative AI. Investment in AI model development and related platforms is expanding at a faster rate than traditional enterprise software, prompting changes in how organizations allocate budgets.
Most significant: AI is no longer treated as a standalone initiative but is increasingly embedded across applications and workflows.
The overall IT sector, however, is not moving uniformly. Device spending is expected to rise to approximately $856 billion, but growth is slowing relative to other segments. Higher memory costs are pushing up prices, which in turn is delaying replacement cycles, particularly in lower-margin categories. This trend highlights the uneven impact of AI across the IT landscape.
Far Different Spending Rates
What the Gartner numbers reveal is a market moving at very different rates. Hyperscalers and AI-focused vendors are spending aggressively (some might say recklessly), while more traditional enterprise segments are growing at a more measured pace. The result is a widening investment gap between areas directly tied to AI and those that are indirectly affected by its cost pressures.
On the high end, hyperscalers are expanding capacity to support AI training and inference, driving significant increases in server and data center investment. Spending in this category is expected to approach $788 billion, highlighting the scale of infrastructure required to sustain AI growth.
At the same time, pricing pressures in memory components are both affecting device sales and shaping procurement strategies. In sum, organizations are balancing the need to invest in AI capabilities with the financial realities of constrained supply and rising input costs.
Higher Than Expected
As strong as AI spend has been of late, Gartner’s revised outlook includes upward adjustments that indicate earlier projections underestimated both the pace and scale of AI-driven investment. This is particularly true in infrastructure, software, and cloud services.
Overall, AI is not simply adding incremental demand on a cyclical basis, it is reorganizing the structure of how IT budgets are distributed. Infrastructure is becoming the center of enterprise strategy, while services and software are evolving to support increasingly complex, data-intensive environments.
For decision makers, investment in AI is essential for competitiveness, and Gartner’s numbers suggest that this trend will continue as AI continues to scale.
