Why 95% of Enterprise AI Projects Fail — The 3 Execution Mistakes C-Suites Keep Repeating
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About this listen
Most AI initiatives don’t fail because of technology.They fail because of execution mistakes at the leadership level.Across enterprises, the same three problems show up again and again:• AI projects run in silos with no cross-functional ownership• No structured adoption plan for business users• No clear definition of success, ROI, or KPIsWhen business, data, tech, and infrastructure teams don’t work as one squad, AI becomes just another IT experiment. And when success isn’t defined upfront, failure is almost guaranteed.In this conversation, we break down why nearly 95% of AI projects fail — and how leaders should be thinking about ownership, adoption, and measurement to unlock real AI value.🎙️ Watch the full podcast here:👉 https://youtu.be/QQavgfHrzHM?si=v_Rqs79bOP5L3IkP
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