By John Barrows | February 28, 2026 | 4 min read
Curiosity is the superpower that separates reps who use AI to get better from the ones who get replaced by it. I quit fantasy football a while back. Not because I wasn’t good at it. Because the platform made it too easy, and I got lazy.
Here’s what happened.
I really enjoyed playing fantasy football initially. I researched players, built my team strategically, monitored the waiver wire, talked trash. But then I got busy, work, family, travel, and one week I just didn’t have time to set my roster. I used the auto-lineup feature.
I won that week. By a lot.
So the next week, when I got busy again, I used it again. Won again. One year, I won the league championship without setting my own lineup once.
That should feel good. It didn’t.
The auto-lineup made it too easy to stop paying attention, so I stopped learning, and eventually stopped caring. By the end, I couldn’t even have a real conversation with my friends about which players were performing well or why. The championship felt hollow. All the joy had been sucked out of the process.
I’m worried AI is going to do the same thing to a lot of people in sales.
Have You Seen Wall-E?
Wall-E is a Pixar movie about humans who have been so fully served by technology that they can no longer do anything for themselves. They float around on hover chairs, staring at screens, consuming content, too atrophied to walk.
That’s where we’re heading if we’re not careful.
I see too many reps outsourcing their thinking and learning to AI without understanding the “why” behind the output they’re looking for.
Here’s a specific example. A rep uses AI to research an account, find a trigger event like M&A activity, and write a personalized email that connects it to their value proposition. AI does this better and faster than the rep ever could. That looks like a win for productivity.
But has that rep ever been through an M&A? Do they understand what happens at different stages of a merger, specifically for the role they’re reaching out to, say, a CRO? What happens when the prospect responds and gets on a call, only to realize the rep has no real understanding of what they’re going through?
The email worked. The rep didn’t.
The Meeting Prep Problem
I see the same pattern with AI-powered meeting prep tools. You input the company website and LinkedIn profile, and the tool produces a beautiful 3-4 page analysis: insights on the business, how you can help, questions to ask, likely objections, a suggested agenda.
That’s genuinely useful, IF the rep reads it, understands it, and digs deeper into anything they don’t fully grasp before the meeting.
What actually happens most of the time: the rep skims it, checks the box, and shows up thinking they’re prepared. They’re not. They have the summary. They don’t have the understanding.
There’s a meaningful difference between holding information and understanding it.
The Search Engine to Answer Engine Problem
The underlying issue is bigger than any individual rep’s behavior.
We’ve gone from a search engine to an answer engine, and that’s a genuinely dangerous shift.
With Google, there was at least the perception of choice. You had to read a few things, synthesize, and arrive at an answer yourself. With AI, it just gives you the answer, and that answer, by definition, cannot be 100% accurate. It’s a probabilistic synthesis of everything it was trained on.
The reps who outsource their thinking to that answer are not just risking bad information. They’re atrophying the judgment muscle that made them valuable in the first place.
Curiosity Is the Superpower
For those of us who are genuinely curious, AI is the best co-pilot, coach, strategist, and learning tool any of us has ever had access to. When used right.
For those who are lazy and just looking for AI to give them the answer, it’s not a superpower. It’s a replacement.
If all you’re going to do is copy and paste or autogenerate a response, what’s the value of the human in that equation? I’d argue zero.
If you’re curious, and you use AI to learn along the way, the value of the human can be amplified better and faster than ever before.
Here’s the distinction in practice: when you get an AI-generated call summary, don’t just skim and move on. Read it. Ask why the AI flagged those things. Ask what you might have missed. Ask what the prospect’s response tells you about their actual priorities. Use the output as a starting point for your thinking, not a replacement for it.
That’s what separates the reps who get better with AI from the reps who get replaced by it.
Go Back to Setting Your Own Lineup
I still use AI tools on every call and in almost every part of my workflow. But at some point I caught myself doing with Otter what I did with fantasy football – letting it make everything so easy that I stopped engaging with the process.
I went back to taking notes by hand during calls and using the transcript for reference afterward rather than as a substitute. The act of writing forces me to listen differently. The summary helps me verify I didn’t miss anything. But the thinking stays mine.
That’s the balance: use AI to get you close, then do the thinking yourself.
Get curious. It’s the one advantage that’s genuinely yours.
Frequently Asked Questions
Why is curiosity the superpower in AI-driven sales?
Because AI raises the floor. It makes competent, structured output available to everyone. Curiosity is what raises the ceiling. Reps who are genuinely curious use AI to learn faster and go deeper. Reps who are not curious use AI to skip the learning entirely, which atrophies their judgment and makes them replaceable.
Can AI replace sales reps who rely on it too heavily?
Yes. If a rep’s value is in executing a process – research, write email, send, follow up – and AI can run that process better and faster, the rep becomes redundant. The reps who remain valuable are the ones who bring judgment, context, and genuine understanding of the buyer’s situation. Those things require engagement with the work, not just execution of it.
What’s the difference between using AI to learn and using AI to skip learning?
Using AI to learn means engaging with the output. It means questioning it, digging into what you don’t understand, using it as a starting point for your own thinking. Using AI to skip learning means taking the output at face value, checking the box, and moving on without really processing what you received. The first makes you better. The second makes you dependent.
How should sales reps use AI meeting prep tools effectively?
Don’t just skim the summary. Read it carefully. Identify anything you don’t fully understand and research it before the call. Ask follow-up questions of the AI to go deeper on points that matter. Use the document to inform your hypotheses about what the buyer is dealing with. Then test those hypotheses in the conversation. The prep tool is a starting point, not a substitute for preparation.
Get weekly sales insights from John Barrows — subscribe to the JB Sales Learning Lab Newsletter
