In product management, the rise of artificial intelligence has tested not just technical skills but strategic discipline.
In the rush to appear innovative, many teams are rushing to integrate AI features into their products simply to keep pace with global trends and competition.
However, the real differentiator is knowing when to use it and the best way to do so. The winners in the AI era will be those who adopt it with purpose and intention, not just those who are the fastest to do so.
Every plan is a balancing act between wanting to do a lot and staying focused, and AI makes that even tougher. An effective AI strategy is not just about chasing trends but aligning AI plans with clear product goals, sustainable competitive advantage and long-term customer value.
This is where good leadership comes in as a steady hand that guides the team on deciding when AI is the right answer.
Damilola Ojo, a senior product manager who’s guided many complicated, fast-growing products, sees AI as a tool that has to justify its spot in the plan, not just a cool thing to add.
For Damilola, a good AI strategy starts with knowing the business problem you’re trying to solve. Often, teams start with a model and then search for a problem to solve with it. She does the opposite. By finding the problems that hurt customer value and make you different from the competition, she makes sure AI investments pay off in real ways.
This keeps you from using “AI for the sake of AI” and puts resources where they give you a lasting edge. For example, in a digital health platform that she managed, rather than adding AI symptom checkers just because ‘every other app had them’, she first identified the core point of friction for the user: users struggled to access timely health guidance while trying to navigate complex appointment systems.
AI was specifically applied to triage incoming queries, reducing response times by over 60% while improving patient satisfaction scores. AI wasn’t a gimmick but a direct solution to a problem with measurable business impact.
Another key thing is figuring out if you’re ready. Even a good AI idea can fail if you don’t have the right data, infrastructure, or clear governance. Damilola says teams should take it slow, test their ideas, and grow responsibly.
This means trying out AI features in small pilots, gathering user feedback from these pilots and using them to improve the features,. This avoids the trap of promising too much too soon in early roadmaps, which can produce weak, low-quality or unsustainable solutions.
She also thinks ethics and trust are very important, and sees trust as a competitive advantage in the AI era. AI products that ignore transparency, fairness and privacy will quickly lose users’ trust.
Damilola includes ethical principles from the onset, getting teams to agree on rules for using data, mitigating bias in models, and making AI outputs easy to understand via user-friendly language. This helps avoid bad press and promotes transparency, which eventually makes the product a trusted option.
Making AI part of the roadmap is where the planning turns into action. Damilola makes sure AI projects aren’t just seen as separate entities but as part of how the products improve.
This means talking to engineering about what’s possible, design about how it affects users, and leadership about the costs and benefits. She believes that AI features should help the product, not fight with what it already does well.
Finally, you have to think about long-term growth. AI models and the systems that power them need to change as the market changes, new regulations are implemented, and users’ needs evolve.
Damilola’s method includes regular monitoring, scheduling retraining, and having flexible systems that can swap out or upgrade models without diminishing the user experience. This keeps products relevant, competitive and strong over time.
In a market that is oversaturated with AI trends, being able to create an AI strategy that is realistic, ethical, and able to scale is a key mark of a senior product leader. Damilola Ojo’s work shows how making thoughtful decisions can cut through the confusion, turning AI from something trendy into a lasting edge over the competition.
For companies trying to ride the AI wave without losing their way, this level of clear-thinking isn’t just a nice extra, it’s what separates something that’s here today gone tomorrow, from having a real and lasting impact.
