When I joined Atomic Object nearly 16 years ago, I was drawn in by many factors: people who were generous with their time, interesting development tools and clients, personal connections, and wanting to work with the smartest people I could find. Threaded through all of that was a deep curiosity that resonated with me. The opportunity to be curious as a consultant is easily my second-most cited reason for sticking around for 16 years (the first is relationships). And I believe there are few better places for the insatiably curious than a consultancy.
Curiosity has always been valuable. But right now, in the age of AI, I believe it’s becoming the single most important trait a leader can cultivate, in themselves and in their organizations.
The Playbook Trap
I talk to a lot of business leaders. Many of them are watching AI with genuine interest, but they’re waiting. Waiting for a vendor to show them the right tool. Waiting for a competitor’s case study they can learn from. Waiting for a proven framework that maps AI capabilities to their specific situation. Waiting for certainty.
I understand the instinct. Restraint feels responsible. But the pace of change in AI is unlike anything most of us have experienced. Models improve on a weekly cadence. New capabilities emerge, and the best practices from three months ago are already being revised. The playbook these leaders are waiting for will be out of date by the time it arrives, if it arrives at all.
The leaders I see making real progress aren’t following a roadmap. They’re asking ambitious questions about what’s possible, trying tools on real problems, learning from what doesn’t work, and sharing those lessons with their teams. They’re being curious.
We’ve Seen This Before
This dynamic isn’t new. In the mid-1990s, business leaders faced a similar fork in the road with the internet. In 1995, only 14% of American adults had internet access, and just 8% of internet users had ever made an online purchase. The web was promising but unproven. Most businesses couldn’t see a clear ROI from building a website, much less investing in e-commerce.
Some leaders experimented anyway. Jeff Bezos left a comfortable career at D.E. Shaw in 1994 after noticing that web usage was growing at 2,300% per year. He didn’t have a playbook for selling books online; he had curiosity and a willingness to figure it out. Amazon wasn’t born from certainty. It was born from a question: what could this become?
By 2000, online purchasing had jumped from 8% to 48% of internet users. The companies that had spent those five years experimenting — even imperfectly — had built organizational muscle for a digital world. The late adopters eventually got their playbook, but it was written by the curious.
Go back further, and you’ll find the same pattern. When factories electrified in the 1890s, they bolted electric motors onto layouts designed for steam power and saw almost no productivity gains. It took 30 years and a generation of curious engineers willing to rethink the factory floor from the ground up before electrification delivered on its promise. The technology wasn’t the bottleneck. The willingness to reimagine how to use it was.
Curiosity Goes Deeper
I want to be clear about what I mean by curiosity, because it’s more than just trying the latest tool. Plenty of people signed up for ChatGPT, ran a few prompts, and moved on. That’s sampling. That’s not curiosity.
Curiosity is the persistent drive to understand why something works, how it might apply to your specific context, and where the boundaries are. It’s pushing past the first demo. It’s asking the second and third questions. It’s the difference between “I tried it” and “I understand what it can and can’t do for us.”
And right now, when AI capabilities are changing on a near-weekly basis, curiosity requires something even harder: the persistence to keep asking questions instead of giving in to exhaustion. The pace is relentless, and it’s tempting to decide you’ve seen enough. The curious resist that pull. They stay engaged not because it’s easy, but because they understand the questions keep changing — and the answers matter.
Research backs this up. Neuroscience studies show that curiosity literally improves how we learn and retain information: people recall information they were curious about significantly better, even weeks later. And Harvard Business School professor Francesca Gino’s research on curiosity in organizations found that curiosity is the best predictor of leadership strength across seven key competencies, including strategic orientation, change leadership, and collaboration. Curiosity isn’t a nice personality trait. It’s a coachable cognitive ability and strategic advantage.
Curiosity Has to Be Organizational
Here’s where it gets uncomfortable for leaders. Gino’s research also found that only 24% of employees report feeling curious in their jobs, and 70% say they face barriers to asking questions at work. In a separate study, leaders of over 500 organizations admitted to actively discouraging curiosity, fearing it would lead to disagreements, slow decisions, and make their teams harder to manage.
That’s a problem in any era. In the age of AI, it’s a serious liability.
A curious leader who experiments alone isn’t enough. The real advantage comes when curiosity is a value the whole organization practices. That means giving teams permission and resources to try things and share what they learn, including what didn’t work. It means creating space for the second and third question, not just the first. It means rewarding the people who say “what if we tried…” for the second and third time rather than only the ones who rely on established answers.
The difference between one leader tinkering with AI tools and an organization that’s learning together is the difference between a flashlight and a floodlight. Leaders set the conditions for the kind of lighting they get.
Cultivating Curiosity
If you’ve read this far and you’re nodding along but wondering whether you’re actually a “curious person,” the research has good news. Curiosity isn’t a fixed personality trait. It’s a practice with a built-in reward system.
Psychologist George Loewenstein’s information gap theory explains the mechanism: curiosity fires when you know just enough about something to realize what you don’t know. That gap between what you have and what you want creates a pull that’s almost uncomfortable — and that discomfort is the spark. Loewenstein found that even a small amount of new information acts as a “priming dose,” dramatically increasing your drive to learn more. You don’t need to be naturally curious about AI or any other topic. You just need enough exposure to notice a gap worth closing.
Once you start pulling that thread, the neuroscience research I referenced earlier shows what happens next: your brain’s reward circuitry activates, releasing dopamine not just when you find the answer, but while you’re in the curious state itself. Even unrelated information you encounter along the way gets encoded more deeply. Curiosity doesn’t just help you learn the thing you set out to learn — it makes you better at learning everything around it. That’s a feedback loop.
Psychologist Todd Kashdan, whose research on the dimensions of curiosity has shown that people access curiosity through different like joyful exploration or the discomfort of not knowing, offers one deceptively simple strategy: spend time with people who are different from you. Different disciplines, different industries, different assumptions. That exposure surfaces gaps you didn’t know you had. It’s also why consultancies, cross-functional teams, and diverse organizations tend to be more curious: the gaps are built into the environment.
Another small way to start: pick something you’re already working on and ask one more question than feels necessary. Not a theoretical question. A specific one. “Why does our quoting process take three days?” is more useful than “I wonder what AI can do.” The first question leads to a second, and the second creates a gap that pulls you forward.
The Window Is Open
The barrier to experimenting with AI right now is the lowest it’s ever been. The tools are accessible. The cost of trying something is small. The cost of waiting—while the curious are building skills, discovering applications, and reshaping how work gets done—is compounding every day.
You don’t need a roadmap. You don’t need to wait for a case study that matches your industry and your situation exactly. You need the willingness to invest in questions, the persistence to keep asking them as the landscape shifts, and the organizational environment that makes both of those possible.
The curious have always had an edge. In the age of AI, that edge is growing.