AWS survey of 3,739 senior IT decision-makers across nine countries: 45% say generative AI is their top spending priority in 2025, 30% security, and 13% compute
Generative AI will surpass cybersecurity in many corporate tech budgets this year — with 45% of global IT leaders naming …
Context & Ripple Effects
Enterprise AI adoption had already accelerated well before the current budget cycle, with a Gartner survey documenting a sharp rise in enterprise deployments. AWS also previously funded customer efforts to build generative-AI tools through a $100M customer-building program, giving this survey a commercial backdrop beyond a single spending-intentions data point.
The survey matters because it frames generative AI as a leading budget category rather than solely an experimental capability. It also follows evidence that security teams see AI as useful in detection and response, as reflected in a Google Cloud and Cloud Security Alliance security survey.
First-order effects
- Among the surveyed IT leaders, generative AI ranks ahead of security and compute as the leading stated 2025 spending priority, strengthening AWS's case that demand extends beyond foundational cloud capacity.
- Security remains the second-ranked priority, signaling that AI deployment budgets will still compete with—and likely need to incorporate—security requirements.
Second-order effects
- Cloud providers and AI software vendors are pushed to sell deployable, governed applications and services, rather than treating model access or raw compute as sufficient enterprise offerings.
- Security vendors can position controls, monitoring, and response capabilities as prerequisites for AI rollouts, not simply as a separate budget claim.
Third-order effects
- If stated priorities convert into procurement, enterprise AI moves from a discrete innovation line item toward an operating layer embedded in software, cloud, and security buying.
- The low ranking of compute as a top-level priority does not imply lower infrastructure demand; it may indicate that buyers increasingly purchase capacity through managed AI products rather than as a standalone objective.
The trend: Enterprise AI spending is shifting from adoption intent toward industrialized deployment, where applications, governance, security, and cloud capacity are bought as an integrated stack.