Unlocking true return on investment (ROI) from artificial intelligence (AI) in infrastructure and operations (I&O) poses significant challenges. Many teams experience mixed results, underscoring the importance of a sound strategy. A Gartner, Inc. survey conducted in November and December 2025, involving 782 I&O leaders, revealed that only 28% of AI use cases in I&O fully succeed and meet ROI expectations, while 20% fail entirely.
To facilitate success, I&O leaders must integrate AI with business operations during execution rather than limiting it to planning stages. Among the 77% of I&O leaders who reported success with at least one AI use case, the primary drivers were the integration of AI into existing workflows and securing strong support from business executives.
Understanding AI Use Case Failures in I&O
The 20% failure rate predominantly stems from AI initiatives that are either excessively ambitious or poorly defined. AI solutions that do not align with the organization’s operations fail to deliver ROI. For the 57% of I&O leaders who reported at least one failure, many cited overestimation of AI’s capabilities. They anticipated immediate automation of complex tasks, reductions in costs, or resolutions to longstanding operational issues. When expectations are overly optimistic and quick results do not materialize, confidence wanes, causing projects to stall.
Common areas of failure include auto-remediation, self-healing infrastructure, and agent-led workflow management across systems. Failures frequently arise when I&O leaders expect these solutions to exceed the reliable performance that AI tools can provide, especially in managing complex and unpredictable IT operations.
Factors contributing to AI project failures include skills gaps and inadequate data readiness. Thirty-eight percent of I&O leaders faced setbacks attributed to persistent skill shortages, while an equal percentage identified poor data quality or limited availability as direct causes of failure.
Critical Success Factors for AI Use Cases in I&O
The Gartner survey indicates that ROI from AI is not determined by the sophistication of the AI model, but rather by effective integration, governance, and alignment with concrete operational needs. Gartner has identified three key success factors:
-
Successful I&O leaders do not treat AI as isolated projects. Among the 33% of I&O leaders with AI successes, they integrated AI into the systems and processes already in use. By embedding AI into daily operations, adoption increases, and organizations see tangible impacts.
-
There is a direct link between success and executive support. Twenty-six percent of successful I&O leaders reported full backing from executives, while 25% benefited from cross-functional collaboration, both critical for successful AI implementation. Strong executive support aids in removing barriers, aligning priorities, and securing ongoing funding and focus.
-
High-performing I&O leaders begin with pragmatic business cases and thorough preparation. Currently, most AI successes within I&O arise from generative AI applied to IT service management (ITSM) and cloud operations—domains where markets have matured and established business value. In fact, 53% of I&O leaders noted their AI victories occurred in ITSM. Whether these victories arise in the cloud or in ITSM, it is vital for I&O leaders to disseminate this information widely within their organizations while maintaining a cohesive and centrally-led AI strategy.
How I&O Leaders Should Prioritize and Fund AI Use Cases in 2026
I&O leaders must ensure that every AI use case aligns with a business objective. It is advisable to manage AI initiatives as products to prevent overlaps, enhance synergies, and monitor their overall impact on I&O and business outcomes. Effective collaboration with CIOs, data, analytics, security, legal, and finance stakeholders can help assess the feasibility, risk, cost, and potential business impact of each use case. A collaborative scoring model can facilitate the comparison and ranking of all use cases to guide investment decisions.
Once priorities are established, I&O leaders can determine which use cases warrant funding and to what extent. Currently, many AI initiatives receive funding through individual business units. However, as expenditure on AI infrastructure continues to rise, CEOs and CFOs are increasingly required to take active roles in setting funding criteria and approving major investments.
A clearly defined, centrally endorsed AI portfolio allows organizations to concentrate resources on their most impactful areas. Ultimately, strong execution and business adoption—not just prioritization—are what drive AI’s genuine ROI.
Gartner analysts will delve into cloud strategies and trends in infrastructure and operations at the upcoming Gartner IT Infrastructure, Operations & Cloud Strategies Conferences scheduled for June 1-2 in Mumbai.
The author is Melanie Freeze, Director Analyst at Gartner.
Disclaimer: The views presented are solely those of the author and do not necessarily reflect those of ETCIO. ETCIO is not liable for any damages to individuals or organizations directly or indirectly.
Published on May 29, 2026, at 09:18 AM IST.
