We are in the middle of an AI gold rush, driven by FOMO and massive capital expenditure. Yet, a recent MIT report reveals a startling statistic: 95% of Generative AI pilots fail to deliver measurable business impact. Why is the failure rate so high?



Prashant Kumar, Founder of Entermind, joins us to discuss his new white paper, "The Seven Original Sins of AI Investment."



He argues that the problem isn't the technology, it's the lack of "orchestration" between people, workflows, and data. We unpack why companies are failing to scale their AI pilots and why the next competitive moat won't be data, but human instinct and creativity.



We discuss:


The 95% Failure Rate: Why most AI pilots are built for demos, not the "messy reality" of the work floor.


Sin #1: The danger of forcing AI into legacy workflows instead of redesigning them.


Sin #4: "If you own the house, you are owned by the house", the trap of building everything in-house.


Sin #7: "Training brains you don't own", the risk of feeding proprietary data into public models.


The Future Moat: Why "Human Deviation" and empathy will matter more than data.

We are in the middle of an AI gold rush, driven by FOMO and massive capital expenditure. Yet, a recent MIT report reveals a startling statistic: 95% of Generative AI pilots fail to deliver measurable business impact. Why is the failure rate so high?Prashant Kumar, Founder of Entermind, joins us to discuss his new white paper, "The Seven Original Sins of AI Investment."He argues that the problem isn't the technology, it's the lack of "orchestration" between people, workflows, and data. We unpack why companies are failing to scale their AI pilots and why the next competitive moat won't be data, but human instinct and creativity.We discuss:<ul><li>The 95% Failure Rate: Why most AI pilots are built for demos, not the "messy reality" of the work floor.</li><li>Sin #1: The danger of forcing AI into legacy workflows instead of redesigning them.</li><li>Sin #4: "If you own the house, you are owned by the house", the trap of building everything in-house.</li><li>Sin #7: "Training brains you don't own", the risk of feeding proprietary data into public models.</li><li>The Future Moat: Why "Human Deviation" and empathy will matter more than data.</li></ul>

Helping you navigate the ever-changing universe of business, from headlines to the bottom line

Helping you navigate the ever-changing universe of business, from headlines to the bottom line

Advertisement