By Farrah Lakhani | Uber | Member since 2024
If you are an enterprise executive today, it can feel like everyone has an AI story and almost no one has measurable results. Boards hear about pilots, proofs of concept, and new tools almost weekly, yet few enterprises can point to AI programs that deliver sustained, enterprise-wide ROI.
Despite heavy investment in talent, infrastructure, and experimentation, most AI initiatives never scale. According to a McKinsey survey, nearly two-thirds of enterprises remain stuck in the experimental phase, unable to move AI into core operations where it can materially affect performance.
I’ve seen this firsthand while leading enterprise AI transformations across large, complex organizations, often under heavy regulatory constraints, legacy technology platforms, and highly fragmented workflows. The pattern is consistent: organizations attempt to scale AI as a technology initiative, when the real determinant of success is leadership alignment, and an operating model built for enterprise adoption.
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