There’s a lot of noise around AI right now. Every other book seems to be asking whether artificial intelligence will replace us, outthink us or completely reshape the future of work. Who Leads When AI Thinks? asks a far more interesting question. Assuming AI is here to stay, how do we make sure humans don’t stop thinking altogether?
That’s the conversation Adrian Wolfberg wants to have, and it’s one worth paying attention to.
What immediately sets this book apart is that it isn’t written from the perspective of a technologist trying to explain AI. It’s written by someone who’s spent decades making decisions where getting the problem wrong had real consequences. That background shows. Rather than focusing on what AI can do, Wolfberg keeps returning to what leaders need to do before AI ever enters the conversation. Define the problem. Question assumptions. Know when the situation has changed enough to rethink everything.
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It sounds obvious until you realise how often we skip those steps.
One of the strongest ideas running through the book is that AI isn’t replacing judgment. It’s exposing how little time we spend exercising it. The more capable these tools become, the easier it is to accept the first answer they produce. Wolfberg argues that the real risk isn’t bad technology. It’s becoming so comfortable with good technology that we stop asking better questions. That idea stayed with me long after I finished reading.
I also appreciated that the book never drifts into fearmongering. It’s realistic about AI’s strengths and just as honest about its limits. The examples pulled from healthcare, business and national security make that point incredibly well because they’re rooted in situations where there isn’t always a clear right answer. Data helps. Experience helps too. Neither is enough on its own.
The dance metaphor could have felt overused, but it actually works. Leadership, AI and decision-making aren’t static. Sometimes the human leads. Sometimes the machine does the heavy lifting. Sometimes both need to step back and rethink the music entirely. It’s a surprisingly effective way of explaining something that’s often made to sound far more complicated than it needs to be.
This isn’t a book for someone looking to learn how to write better prompts or automate their workflow. There are plenty of books doing that already. This one is more interested in what happens before and after the prompt. Before we decide what to ask. After we decide whether the answer makes sense.