News

Survey: 54% of I&O Leaders Turning to AI to Cut Costs

• By David Ramel
• 11/03/2025

Gartner reported that 54% of infrastructure and operations (I&O) leaders are adopting AI with cost optimization as the primary goal, based on a survey of 253 respondents conducted online from May through July 2025 across the U.S., U.K., India, and Germany.

The firm positioned AI as the top growth area for future I&O investment while also detailing the practical hurdles facing adopters and recommended steps to get started.

Gartner said I&O leaders should approach AI intentionally, emphasizing smaller, feasible efforts over broad, open-ended initiatives. Research Director Melanie Freeze said, "While AI is the top growth area for future I&O investment, integration difficulties (48% of respondents) and lack of budget (50% of respondents) were cited as top adoption challenges." The guidance underscores the need to balance ambition with execution by focusing on well-scoped pilots and incremental upgrades rather than attempting monolithic programs.

Freeze further advised that "Rather than chasing big AI projects, they should start with high-value, feasible pilots and flexible upgrades," adding a practical example: "For example, organizations could use GenAI for cloud cost management to automatically analyze cloud billing, resource usage and infrastructure efficiency." That cost-management use case aligns with the study's finding that cost reduction is the top driver and illustrates how AI can be applied directly to common I&O spend categories such as compute, storage, and network utilization.

Beyond cost-focused adoption, respondents indicated where they expect to increase I&O investments next: cybersecurity operations and talent/skills development ranked second and third, at 49% and 48% respectively, according to Gartner's summary of results. Those areas, shown in an accompanying figure, reflect ongoing needs to secure infrastructure and upskill teams as AI and automation expand across operational workflows.

The survey points to a familiar pattern for many enterprises: growing interest in AI coupled with resource constraints and integration complexity. Gartner's recommendations target that gap by sequencing adoption around pilots that can demonstrate measurable value quickly, then scaling through flexible upgrades. In practice, this could include applying generative AI to analyze and flag cloud billing anomalies, map workload resource patterns to right-sizing actions, and surface infrastructure efficiency opportunities that can be operationalized within existing platforms and processes.

Methodology details for the survey specify an online format and a respondent base of 253 I&O leaders across four countries, captured during May-July 2025. Gartner attributed the percentages and investment outlooks to this respondent set, with the cited adoption challenges of budget and integration representing the most frequently reported impediments among participants.