I continue to see the role of Product Management being vigorously debated on social media platforms like LinkedIn. I have contributed to this debate in my article Did Silicon Valley Kill Product Management, where I argued that the role had been dumbed down with the emergence of the technology-led product era, at the expense of product-led thinking, resulting in Product Delivery being confused as Product Management. But a related debate I am seeing is with regard to the balance between how much domain expertise is required versus core product management skills.
Take my own experience as an example. When I was Global Product Director at AT&T, we had just split from our global partner and suddenly had no way to bill international clients locally. This made us significantly more expensive than our primary competition, as our customers couldn’t claim back local sales tax. It was a major issue, and I had to fix it.
At the time, I had no deep knowledge of international billing systems. But I had to become an expert, fast. I learned everything I could, figured out a solution, and implemented it. I did it so well that, in the next internal restructuring, the international billing group was added to my portfolio.
1. You don’t always know where you need to develop expertise until the problem becomes clear.
2. You need the ability to pivot, adapt, and learn, quickly.
Product Management isn’t just about delivery or pipeline management, it’s about driving business success. Good PMs understand their product’s P&L and work cross-functionally to ensure their product thrives. If someone believes a PM needs executive authority to succeed, they’re hiring the wrong skill set. The best leaders, and the best CEOs, don’t dictate; they influence. That’s exactly what great PMs do.
As I wrote in “AI and the Context Problem - An Opportunity for Product Management”, the next generation of great Product Managers will need to be AI leaders. AI is not just another technology wave, it fundamentally changes how products function, interact, and create value. PMs who understand AI at a conceptual level will be better equipped to leverage it as a tool rather than merely follow trends.
Product Managers don’t need to become machine learning engineers, but they do need to understand how AI models work, their limitations, and how they can be applied effectively. Just as I had to rapidly gain expertise in international billing at AT&T, today’s PMs must be willing and able to dive into AI and develop a working knowledge of its applications within their product domain.
So, how much domain expertise does a PM need? Enough to understand the business landscape and ask the right questions, but not so much that they become overly specialized and lose the ability to adapt. A great PM is a master of learning, not just a jack of all trades, but a master of some.
Product Management is a fantastic path for those who want to lead because it teaches the skills that make great CEOs, problem-solving, strategic thinking, and cross-functional leadership. The best PMs don’t need to start as domain experts; they need to be relentless learners who can develop expertise when and where it’s needed.
The question isn’t whether a PM should have deep domain expertise. The question is whether they have the ability to acquire it, fast.