It seems like every other headline is about AI either replacing product managers or being a magic bullet for product-market fit. The reality, as usual, is more nuanced and, frankly, more interesting.
Beyond the hype, the most significant impact of AI I’m seeing is in the trenches of product discovery. We all know the grind: sifting through hundreds of support tickets, interview transcripts, and App Store reviews to find a single, actionable insight. It’s vital work, but it’s a time-sink that keeps us from focusing on higher-level strategy.
This is where AI is quietly becoming a PM’s best co-pilot. Modern tools can now ingest and analyze vast amounts of unstructured customer feedback, identifying emergent themes, sentiment shifts, and user pain points in minutes, not weeks. This frees us from the manual labor of data synthesis to do what we do best: talk to users to understand the ‘why’ behind the data, collaborate with engineering on innovative solutions, and build a more strategic roadmap.
Instead of being replaced, the PM role is being elevated. By offloading the tedious analysis, we can spend more time on strategy and creativity. Platforms like https://leera.io are already leaning into this, helping teams unify disparate feedback to get to the core of what users truly need.
How are you leveraging AI in your discovery process today, and what have been the most surprising benefits or challenges?