A few days ago, I caught myself doing something that has probably become normal for many of us.

I had a question.

Instead of opening several documents, searching through old notes, or asking someone in the team, I typed the question into AI.

Within seconds, I had an answer. Then another option. Then a summary. Then a recommendation.

My first reaction was simple: This is incredibly efficient.

But a few moments later another thought came to me.

If I can reach an answer much faster, does that automatically mean I understand the problem better?

Speed changes the experience of thinking

For much of my career, getting to a useful answer required friction. I had to read, compare, ask, challenge, remember and sometimes sit with uncertainty for a while.

AI removes a large part of that friction. In many situations, that is a major advantage. I can explore alternatives faster, test my thinking, summarize complex information and prepare myself before a discussion.

But friction also served another purpose: it forced me to engage with the problem.

When the answer arrives instantly, it becomes easier to confuse access to knowledge with ownership of knowledge.

An answer is not yet judgment

AI can give me a recommendation. It cannot carry my accountability for the consequence.

That distinction matters most when decisions are ambiguous: hiring someone, changing a policy, investing in a project, restructuring a team, responding to a customer problem or deciding how much risk is acceptable.

In those moments, the useful question is not simply “What does AI recommend?” It is “What assumptions sit behind this recommendation, what context might be missing, and what am I prepared to own?”

There is also a capability question

If I use AI to do something faster, I still need to ask what capability I am strengthening—and what capability I may be allowing to weaken.

For example, using AI to challenge a draft can improve my writing. Asking AI to write everything while I stop thinking about structure, audience and argument may slowly make me dependent on it.

The same tension exists in management. AI can help a leader prepare better questions. It should not become a substitute for listening. It can highlight patterns in employee data. It should not become a substitute for understanding the human context behind the numbers.

Perhaps the goal is not to resist speed

I do not want to return to slower work simply because it is slower. That would miss the point.

The opportunity is to use the time that AI gives back to us for higher-quality thinking: reflection, dialogue, experimentation, judgment and human connection.

If AI saves me thirty minutes, the most valuable use of those thirty minutes may not be producing thirty minutes more output. It may be spending part of that time asking whether I am solving the right problem in the first place.

The question I want to keep asking

I am increasingly convinced that the real competitive advantage will not come only from who has the fastest AI or the most AI tools.

It may come from people and organizations that combine speed with judgment—using machines to accelerate information while protecting the distinctly human disciplines of responsibility, context and wisdom.

So I keep the question open for myself:

Am I becoming wiser and smarter—or have I simply become faster?

I share these reflections as practical starting points, not as a substitute for context-specific judgment. If your organization is working through a similar question, start a conversation with me →