We all talk about building AI into our products, but the more interesting conversation is about building AI into our process. The new wave of AI tools isn’t just for writing code or generating marketing copy; it’s aimed directly at the core PM workflow.
Imagine feeding an AI thousands of user interviews, support tickets, and analytics events, and getting back a synthesized list of core user problems and prioritized opportunities. Think of AI co-pilots that can draft initial PRDs, generate user stories based on a high-level epic, or identify conflicting priorities in your roadmap before you even present it to stakeholders.
This isn’t about replacing the product manager. It’s about augmenting our abilities. By automating the time-consuming data synthesis and documentation, we can free ourselves up for the uniquely human parts of the job: deep user empathy, stakeholder negotiation, and setting a compelling vision. It allows us to move faster and make more data-informed (not data-dictated) decisions. The real question is how we integrate these tools without losing our critical thinking and strategic intuition.
How are you using AI to augment your own product management workflow, and where do you draw the line between helpful co-pilot and a crutch?