When AI Removes the Easy Work, What Happens to Everything In Between?

I agree with the general idea that AI has removed a lot of the “easy work,” and in many ways that’s a real benefit. There is less time spent on administrative tasks, routine follow-ups, and basic research, which allows more focus on higher-value activities like thinking, strategy, and decision-making.

However, I think there is a second-order effect here that is being overlooked.

The “easy work” was not just overhead. It served as a kind of mental buffer that made the higher-value work more sustainable over time. Tasks like emails, light research, and reporting created natural transitions between more cognitively demanding work. They gave your brain an opportunity to reset before moving into the next decision or problem.

As those tasks are reduced or eliminated, what remains is a much more concentrated form of work. For many roles, the job increasingly becomes a continuous sequence of decisions, strategic thinking, and problem-solving with fewer built-in breaks.

The human brain is not designed to operate at that level of intensity indefinitely. Without periods of cognitive downshift, the quality of thinking tends to decline. You start to see weaker judgment, less effective strategic decisions, and a reduced ability to solve complex problems over time.

In that sense, more thinking does not automatically lead to better outcomes. At some point, it can have the opposite effect.

AI is clearly making individuals and organizations more efficient, but efficiency alone is not the goal. If that efficiency comes at the expense of sustainability, you can end up with burnout, degraded decision-making, and ultimately worse outcomes.

The organizations that will get the most out of AI will not simply remove lower-value work and replace it with more high-value work. They will be more intentional about how work is structured so that people can continue to operate at a high level over an extended period of time.