"According to Melanie Freeze, a director of research at Gartner, failure most commonly occurs for several reasons, including unrealistic expectations of what AI tools can do, and skills gaps during the actual pilot."
"Many I&O leaders reported that their AI initiatives failed because they expected too much, too fast. They assumed AI would immediately automate complex tasks, cut costs, or fix long-standing operational issues."
"The survey revealed that ROI from AI is not driven by the sophistication of the model, but by how well the technology is integrated, governed, and aligned with real operational needs."
"Gartner identified three success factors, including embedding AI into the systems and processes people already use, which boosts adoption as AI becomes part of day-to-day operations."
A Gartner survey indicates that only 28% of AI use cases in infrastructure and operations succeed in meeting ROI expectations, while 20% fail completely. Common reasons for failure include unrealistic expectations and skills gaps during pilots. IT departments often experiment without proper integration, leading to stalled projects. Success is linked to how well AI is integrated and aligned with operational needs, rather than the sophistication of the technology. Gartner identifies three success factors, emphasizing the importance of embedding AI into existing systems and processes.
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