AI has not changed the importance of judgment in product leadership. What it has changed is the cost of getting it wrong.

Early in my career, I learned a principle that still guides how I think about building products: The strongest decisions rarely start with perfect data. They start with conviction, a hypothesis shaped by experience, customer insight, and pattern recognition. What ultimately separates high-performing product organizations from average ones is how quickly and confidently instinct is validated. That validation is the true role of product analytics, and increasingly, it is where AI amplifies its value.

Analytics tests whether what you believed would happen actually did, and to inform what you do next. When treating analytics as a decision engine rather than a reporting layer, it fundamentally changes how teams operate.

ANALYTICS SPRAWL REDUCES CLARITY

Across nearly every organization I have worked in, regardless of size or industry, one pattern shows up with remarkable consistency: analytics sprawl.

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