AI is giving companies more leverage over execution. Some of the work disappearing in the process was also how people learned the business and developed judgment.
Less-experienced people built judgment by working through real decisions alongside people who had more experience. They saw reasonable assumptions fail once they met customers, constraints, and the rest of the business. Someone with more experience could often see the problem earlier because they had encountered some version of it before. Eventually, the person who once needed help making those calls had enough experience to make them independently.
Read the full TPW Update: The Judgment Supply Problem on The Product Way
A meaningful share of that work can now move to AI. Much of it should. There is no reason to preserve unnecessary effort simply because someone once learned from doing it. The challenge is that some of the work being removed also created the repetitions through which people became capable of handling more consequential decisions.
The hiring market makes the tension easier to see. An analysis of 2,448 AI product-management openings found that just 1.5% were entry-level or associate roles. Companies are heavily weighted toward hiring people who can already operate with significant independence and judgment.
IBM found something related inside companies. Seventy-one percent of executives now prioritize the ability to supervise, validate, or override AI outputs, while only 26% of organizations clearly distinguish between work that is human-led, AI-assisted, or AI-executed.
Companies are placing more value on experienced judgment while AI takes on more of the work that helped people develop it.
That can work for a long time when the experienced people are already there. They know the business well enough to recognize when something looks wrong, even when the output appears convincing. AI can make those people much more productive because they can direct more work without personally carrying all of the execution.
As that happens, their judgment becomes more consequential. One decision can influence much more work than it could before. The organization gets more execution from the same amount of senior attention, but it still needs enough people capable of making the decisions that direct that execution.
The pressure appears when too much of that capability remains concentrated in the people who already have it. Growth eventually requires more people who can carry important decisions without pulling the same senior leaders back into every difficult call. Hiring experienced people can fill some of that need, but every company cannot solve the same supply problem by competing for the same people.
Companies will need to think more deliberately about how people develop judgment when AI removes some of the work that used to provide the experience. The answer will probably look different from the apprenticeship model many current leaders came through, because the work itself is changing.
The implications extend beyond the product career pipeline. As AI increases execution capacity, the distribution of judgment starts to affect how much management leverage the organization can actually create and how well that leverage holds as the company grows.
