I find myself asking that question with increasing urgency as the technology advances. When AI tools can write all manner of business documents I am asked to produce (product visions, business requirements, testing and launch plans, etc.) with surprisingly little prompting and iterate to a “good enough” version within hours, what should I focus on? As AIs gather more data in various contexts about the business, understand how to interface with stakeholder groups (so much of my job is “stakeholder management,” a fun euphemism for meetings, email and Slack), how do I evolve my approach? How does my job change?
My job as a product leader is to drive outcomes. That sounds ambiguous (because it is) but at the end of the day, I own delivering the optimal solution to customers at the right moment. I have to spend a lot of time with customers to deeply understand their problems. Ideally, if I can feel the pain of a problem myself I can articulate the impact to all of the stakeholders who own pieces of the solution. Then, I have to achieve alignment across my cross-functional team. Really, alignment is getting those stakeholders (customer success, business implementation, software development, go to market, etc.) to agree with me that a particular problem is worth solving. To do that, we all have to buy into the same story about the customer problem and why we can address it.
I tell those stories by bringing my stakeholders on a journey with me. We start with actually seeing and feeling what it is like to encounter the problem. For example, this could mean conducting site visits and watching users interact with our products. Traveling to a site with my partners is valuable because it grounds the whole team in a shared understanding of the problem. Observing a user struggle navigating a webpage, or, worse, having no idea our solutions even exist has a way of clarifying what we need to improve.
Collecting user feedback, even if done together as a team, is not enough to gain that necessary alignment. I have to synthesize it all together into a narrative that moves the entire team forward in the same direction. Discovering that the feature we think is valuable for users is actually languishing behind a poor user experience means the new narrative becomes one about user-driven discovery, rather than assuming that “if you build it, they will come.” Sure, AI can probably discover the same insight if it is fed the webpages and prompted to uncover why usage metrics are low. AI can also consider other possibilities that may not be immediately apparent. It could also model out the impact of multiple solutions and suggest an optimal one. But bringing everyone needed to solve the problem along for the ride means they understand the story, too.
At the end of the day, AI is approximating human behavior. We still need humans telling other humans compelling stories to inspire the best actions to get optimal outcomes. Simply understanding that a problem exists is rarely good enough to get momentum to solve it. The true magic happens when everyone feels a connection to the end user and imagines themselves as that user struggling to perform some function of their job. The best product leaders are the ones who can weave all of the relevant inputs into a captivating story about how to solve the most important problems. In this new age of AI, where it has so many wondrous abilities, we still need human storytellers establishing a shared reality. When we can do that, AI can help us deliver exponentially better outcomes as a team.
Adam F. Caplan is a technical product leader with a background in logistics, workforce development, and healthcare technology; wellness and fitness enthusiast.