I had a product manager friend call me last week, voice trembling. 「The AI is coming for our jobs,」 he said. 「My CEO just replaced three junior PMs with an AI co-pilot.」
My response? 「Congratulations. Now you can finally do your real job.」
Here’s the uncomfortable truth everyone’s whispering but afraid to say aloud: AI isn’t replacing product managers. It’s exposing the ones who were never really doing the job in the first place.
Remember when we used to spend 40% of our time gathering requirements, another 30% writing specs, and the rest in endless status meetings? That wasn’t product management. That was glorified administration. AI eats administrative work for breakfast.
The real product manager’s role has always been about three things: vision, judgment, and leadership. These are precisely the areas where AI falls spectacularly short.
Take vision. Can an AI tell you what customers will want three years from now? Can it spot the cultural shifts that create billion-dollar opportunities? Steve Jobs famously said customers don’t know what they want until you show it to them. AI can only analyze what customers already know.
Then there’s judgment. When you have conflicting data points – your analytics say one thing, user interviews say another, and the sales team is screaming about a third thing – AI can give you probabilities. But making the final call? That’s human territory.
And leadership? Good luck getting an AI to inspire a team through a pivot, negotiate with an angry stakeholder, or take responsibility when things go wrong.
This brings me to The Qgenius Golden Rules of Product Development. One principle stands out here: 「Product managers are responsible for the business model.」 Not the features. Not the roadmap. The business model.
AI can optimize an existing business model. It can’t invent Airbnb’s marketplace model or Tesla’s direct-to-consumer approach. Those came from human insight about unmet needs and broken systems.
Another Qgenius principle: 「Successful products aren’t about equal value exchange, but unequal value exchange.」 The magic happens when users get more than they give. AI can help measure this imbalance, but creating it? That requires understanding human psychology at a level machines can’t reach.
I’ve seen PMs using AI tools to do incredible work. One team at a fintech startup used AI to analyze thousands of support tickets, uncovering a hidden pain point about international transfers. But here’s the key: the AI found the pattern. The PM understood why it mattered and built a business case around it.
This is the new division of labor: AI handles the 「what」 – the data, the patterns, the optimization. Humans handle the 「why」 – the meaning, the context, the judgment.
Ben Horowitz was right when he said the hard thing about hard things isn’t the technical challenges, but the human ones. AI makes the technical parts easier. That means we have more time for the hard human parts.
So if you’re worried about AI taking your product management job, ask yourself: were you doing the administrative work, or were you doing the real work? The market is about to render its verdict.
The best PMs I know are already using AI to automate the boring parts and focus on what matters: understanding users at a deeper level, making bolder bets, and leading their teams through increasingly complex challenges.
In the age of AI, being a mediocre product manager became obsolete. Being a great one became more valuable than ever. Which one are you?