Why AI and Software Development Projects Fail

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I’ve seen hundreds of AI and software projects crash—and it’s rarely because of the tech. In this video, I break down the real reasons these initiatives fail: from executive misalignment and hype-driven planning to weak teams, overengineering, bad data, and missing sales strategies. If you’re leading or launching an AI product, this will show you what to fix before it’s too late. Learn how to avoid common traps and build toward results, not regret.

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► TIMESTAMPS
00:00 - Intro
00:10 - Why AI Projects Fail
00:30 - Accountability Requires Leadership Buy-In
01:58 - Solving Real Problems
03:06 - The Wrong Team Can Sink Your Project
03:55 - Overengineering and IP Obsession
05:31 - Pain-Point Solver
06:08 - Bad Data and Poor Process Mapping
07:46 - Why Process Mapping Is Essential
08:57 - Culture Clashes & Speed Mismatches
11:17 - Misunderstanding Tech Capabilities
13:31 - No Monetization Strategy
14:17 - Not Future-Proofing Solutions
16:54 - Weak KPIs
17:48 - Outro

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