Learning from Experts: Leading in the Age of AI
By Ryan Kurt, CEO & Founder, The AI Lab
Before going further, a quick note on language. When we say "AI" in this context, we're mostly talking about a new generation of tools—like Copilot, Claude, ChatGPT, and others—that can read, write, analyze data, hold conversations, and increasingly take on tasks with minimal direction. Think of them as very capable digital assistants that keep getting smarter. Sometimes in this article "AI" refers to the broader technology trend, and other times it refers to actually sitting down and using one of these tools. Both matter.
We don't have to guess anymore.
For a long time, conversations about AI were mostly about what might happen. That's starting to change. We're beginning to see real signals—in research, in economic data, and in the work happening inside actual companies—that reflect what a growing number of people are experiencing firsthand: when this technology is applied to the right kind of work by the right kind of person, the results are hard to ignore.
We're still early, but the signals are worth paying attention to. A recent survey of heavy AI users found that the primary benefit has shifted—it's no longer mainly about saving time, but about increased output and entirely new capabilities that didn't exist before.¹ A study at Procter & Gamble found that individuals using AI performed at the level of a two-person team without it. And economist Erik Brynjolfsson recently noted that U.S. productivity grew roughly 2.7% in 2025—nearly double the average of the past decade—and that this coincided with a significant downward revision in job growth. Output went up while labor input went down. That's a pattern worth watching.
None of this is settled science yet. But it lines up with what we're seeing on the ground.
We work with two companies in the insurance space—one a large carrier, one a very small brokerage. The carrier spent millions on AI initiatives: months of decision-making, enterprise tool evaluations, big rollouts. The return so far has been minimal. Meanwhile, the CEO of the small brokerage took a different approach. He told his head of operations to start using an AI assistant—a tool called Claude, which is essentially a conversational AI that can read, write, analyze, and help build workflows—and just go. That one person, in a matter of days, automated entire processes, eliminated tasks completely, and built a brand-new client service: systematically analyzing every claim to determine if the right amount was paid, essentially acting as a true fiduciary. The carrier has an entire legal team doing similar work from the other side of the coin, spending millions a year. The small brokerage went to market in about two weeks. Their CEO is now rethinking the growth trajectory of the entire business.
We also work with a professional services firm that came to us to build a single AI agent—think of it as a digital worker that can handle a specific task on its own—for a back-end process. Within weeks it was live and shown to their top clients. The response was immediate. A potential investor told them they were the only company in their market with this kind of capability. Today, they're packaging all of their domain expertise into these systems. Their clients will feel less like they're logging into software and more like they've hired someone who understands their business. Their projected company valuation has nearly doubled.
I share these not to hype the technology, but because the pattern matters. In both cases, it wasn't about who spent the most. It was about giving the right person the right tools and the room to move.
That leads to something I think every leader should be paying attention to. We're starting to see individual contributors—people with the right curiosity and drive—develop so much personal capability through AI that their output starts to rival what entire teams used to produce. Some are beginning to realize they could go independent, take on their current employer as a client, add a few more, and significantly increase both their earnings and their impact. That's not a threat—it's a signal. It tells you how much untapped capacity might already exist inside your organization, waiting to be unlocked. The companies that figure out how to channel that energy will be the ones that pull ahead.
And to be clear: we believe this should be a story about elevating people. Despite the doom and gloom you hear in the headlines—AI is coming for your job, entire professions are about to disappear—the reality on the ground looks very different. It has never been a better time to be a motivated, curious, white-collar individual contributor. The prevailing narrative treats AI as something that happens to workers. We see the opposite. It's a tool they can pick up today to elevate their own capabilities, expand their reach, and increase their value in ways that simply weren't possible a year ago. This is practically an equal opportunity situation—the tools are accessible, the learning curve is shrinking, and the people who lean in now will have an outsized advantage. We're firm advocates for putting these tools in the hands of your workforce, training them well, and letting their growth become the company's growth. When your people win, you win.
My honest belief is that the winners in this next chapter won't be the ones who use AI to do more with less—they'll be the ones who use it to do more with more. More capacity. More ideas. More output. That becomes the fuel for entering new markets, launching new products, expanding reach. Not cutting—building.
AI is just a tool. What it means for your team and your company comes down to what you do with it. The right people, trained well, pointed at the right problems—that's where the value is.
One last thought: this is the worst AI will ever be. It gets better every day. The teams that start learning now will carry that advantage forward.
¹ AIDB Intelligence, January AI Usage Pulse Survey (n=583)
Ryan Kurt is CEO & Founder of The AI Lab, where executives come to think clearly about AI. He writes about AI transformation, organizational readiness, and the human side of enterprise AI adoption.