This lesson examines why most AI initiatives disappoint, despite significant investments.

 

Research shows that nearly 90% of CEOs are disappointed with their AI returns and over 80% of AI projects fail.

 

The lesson introduces five common mistakes that lead to failure:

  • starting with technology rather than business problems,
  • poor data quality,
  • skills gaps,
  • lack of organizational buy-in,
  • and attempting too much too quickly

 

Through contrasting examples of Target’s failed pregnancy prediction system versus Walmart’s successful food waste reduction initiative, the video illustrates how success comes from starting with clear business problems, ensuring you have the right data,

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