Contrast two AI projects.

One cost $600,000 to build, $500,000 per year to maintain and was shut down as functionally unusable.

The other cut energy waste, reduced equipment damage, and returned 35.8% on investment.

Same tech. Different outcomes.

The difference had nothing to do with the AI — and everything with how the project was set up and managed.

In this episode:

  • The New York City AI chatbot that confidently told people to break the law
  • The Korean steel plant that used AI to solve one specific measurable problem — and returned 35.8% on its investment
  • The five reasons AI transformations fail and how to avoid every one of them
  • Why AI is execution and product thinking is judgment — and why you cannot out-execute a wrong decision

This episode is for you if:

  • You are a business or political leader with an AI budget and want to make sure it is not wasted
  • You are a corporate innovator trying to make the case for an AI initiative internally
  • You want a clear framework for evaluating AI projects before you commit to them

Timestamps:

  • 00:00 – The $600K AI chatbot that failed vs. the AI that worked
  • 02:11 – NYC's government AI chatbot disaster
  • 07:01 – Korean steel company's successful AI project
  • 09:23 – Why the steel company's AI project succeeded
  • 10:45 – Why 80% of enterprise AI projects fail (RAND research)
  • 11:45 – 5 reasons AI transformation projects fail
  • 14:06 – 2 solutions to fix failing AI initiatives
  • 15:12 – Why product thinking matters more than AI technology

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Transcript: https://www.techfornontechies.co/blog/321-why-80-of-ai-projects-fail-and-it-s-not-the-ai-s-fault-2

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