Gartner’s 2026 IT spending forecast shows strong headline growth but reveals a concentrated reallocation: massive capital into data center systems and IaaS for AI compute, while traditional categories like devices, communications and IT services lag.
Data center systems growth is accelerating sharply—forecasted at 62.5% in 2026—signaling a major shift of capital into AI compute capacity.
IaaS is rising as enterprises rent AI compute instead of committing to owned hardware, with forecast growth near 29.3% and $287 billion in spend.
Software, devices, communications and IT services are growing more slowly as budgets shift toward AI-ready infrastructure.
# The numbers behind the shift Gartner projects total worldwide IT spending will increase 14.2% in 2026 to $6.37 trillion. That topline hides a concentrated pattern: data center systems and IaaS are absorbing capital at many multiples of growth in traditional IT categories. This is a reallocation of budgets toward AI infrastructure on the bet that AI workload demand will materialize at scale.
# Where the money is flowing
# What's getting deprioritized Software spending will still grow—forecast at 15.5% to $1.47 trillion—but AI-ready platforms are eating into budgets that once funded broader software refresh cycles. Device spending (9.8%), communications services (4.4%) and IT services (5.3%) are growing more slowly. These categories were previously steady budget items and are now relatively smaller pieces of the enterprise technology stack.
# The strategic choice facing executives According to Gartner's John-David Lovelock, the AI compute buildout is being described as "the largest infrastructure project ever attempted by humanity." That framing captures scale and risk: this scale hasn't been run before, so ROI is uncertain.
# Proven use cases vs speculative bets A small number of AI applications have moved past pilot stage into measurable value creation: specific agentic back-office workflows, coding assistants and targeted customer-service automation. These have owners, measurable outcomes and repeatable value.
A larger set of projects remain speculative: broadly deploying large language models without a defined business owner for outcomes, or sizing infrastructure for projected workloads that haven't been validated. Funding speculative cases at the same pace as proven ones means the enterprise is financing the industry's forecast rather than its own business case.
# Practical guidance for 2027 planning Executives should review infrastructure budgets category by category and ask which dollars support validated workloads and which chase hypothetical demand. That distinction should be the starting point for capital planning and risk reduction. Teams that can clearly map infrastructure commitments to repeatable economic value will appear disciplined in the next budgeting cycle.
# Bottom line Headline IT spending growth masks a concentrated capital shift into AI compute and rental cloud capacity. The strategic question for enterprise leadership is not whether to invest, but how to allocate scarce capital between validated AI workloads and speculative capacity purchases.
AI companies continue to raise new capital to fund growth.
The AI computing specialist's latest results were strong. The real story is a backlog worth almost 29 times this year's expected revenue.
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