#33 How Good Is Your AI, Really?

Episode 33 of the The Identity Navigator podcast, hosted by Rohit Agnihotri, titled "#33 How Good Is Your AI, Really? " was published on January 24, 2026 and runs 24 minutes.

January 24, 2026 ·24m · The Identity Navigator

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Summary

Most AI projects don’t fail because the models are dumb. They fail because the business questions are. In this episode, we breaks down why “95% accuracy” has become the most dangerous comfort blanket in enterprise AI and what leaders should be looking at instead.Through a healthcare claims story, email spam examples, fraud scenarios, and churn prediction, we walks you from the simple accuracy metric into the world of confusion matrices,precision, recall, and F1, translated into dollars, risk, and customer pain. You’ll hear how a “highly accurate” model can quietly route all your complex work to the wrong people, miss the customers you most needed to save, or block the transactions you can least afford to lose.This is a practical, and very human conversation about thresholds as business knobs, not technical parameters; about choosing consciously what you can afford to getwrong; and about the handful of questions every identity, security, and AI leader should ask before signing off on the next “95% accurate” pilot.If you’ve ever sat through a model-performance review and thought, “This sounds great, but what does it do to my P&L?”, this episode is for you.

Episode Description

Most AI projects don’t fail because the models are dumb. They fail because the business questions are.

In this episode, we breaks down why “95% accuracy” has become the most dangerous comfort blanket in enterprise AI and what leaders should be looking at instead.

Through a healthcare claims story, email spam examples, fraud scenarios, and churn prediction, we walks you from the simple accuracy metric into the world of confusion matrices,precision, recall, and F1, translated into dollars, risk, and customer pain. You’ll hear how a “highly accurate” model can quietly route all your complex work to the wrong people, miss the customers you most needed to save, or block the transactions you can least afford to lose.

This is a practical, and very human conversation about thresholds as business knobs, not technical parameters; about choosing consciously what you can afford to getwrong; and about the handful of questions every identity, security, and AI leader should ask before signing off on the next “95% accurate” pilot.

If you’ve ever sat through a model-performance review and thought, “This sounds great, but what does it do to my P&L?”, this episode is for you.

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