I’ve noticed something interesting about my own use of artificial intelligence. The more I use AI, the more productive I become. But instead of using that newfound efficiency to work less, I find myself taking on more.

I’m building things, exploring ideas, solving problems, and pursuing opportunities that previously would have required far more time and effort. I’m not necessarily becoming less busy. I’m becoming more ambitious. And I feel more accomplished, motivated, and inspired because of it.

This experience has me thinking about an economic concept known as Jevons Paradox, and what it might tell us about the future of AI, employment, and the economy.

When Efficiency Creates More Demand

In 1865, British economist William Stanley Jevons observed something counterintuitive about coal consumption during the Industrial Revolution. As steam engines became more efficient and required less coal to produce the same amount of work, total coal consumption actually increased. Greater efficiency made steam power more economical, encouraging industries to adopt it more widely and find new applications for it.

This became known as Jevons Paradox: under certain conditions, improving the efficiency of using a resource can increase its overall consumption rather than decrease it. Now consider artificial intelligence. AI is dramatically reducing the time and effort required to complete many intellectual and creative tasks. Writing software, conducting research, analyzing information, developing content, and exploring business ideas are becoming faster and more accessible.

The immediate assumption is that if fewer hours are required to accomplish the same amount of work, businesses will need fewer employees. And in some cases, that’s exactly what may happen. But that assumption overlooks something important. What if the amount of work we want to accomplish isn’t fixed?

AI Doesn’t Just Make Work Faster. It Makes New Work Possible.

Imagine a software developer who previously needed two weeks to build a working prototype. With AI assistance, that same developer might accomplish the task in two days. Does the developer now take the remaining eight days off?

Perhaps. But another possibility is that the developer builds four more prototypes, experiments with new features, or launches an entirely new product.

The productivity improvement hasn’t eliminated work. It has expanded the developer’s capacity to pursue opportunities. This is what I’m experiencing personally. AI isn’t simply helping me complete my existing responsibilities more efficiently. It’s making previously impractical ideas feel achievable. The barrier between imagination and execution is becoming smaller.

And when the cost of pursuing an idea decreases, we naturally become more willing to explore it. Now imagine that effect multiplied across millions of people and thousands of organizations. How many new businesses are emerging right now? How many scientific questions could be investigated? How many products, educational experiences, and services could become economically viable for the first time?

We tend to evaluate AI by measuring the tasks it can automate. Perhaps we should pay equal attention to the opportunities it creates.

The Workforce Equation Is More Complicated Than We Think

We’re already seeing companies announce workforce reductions while citing AI-driven efficiencies. The narrative is often straightforward: AI can perform work previously completed by humans, so fewer humans are needed. There is genuine reason to be concerned about displacement, particularly in occupations where routine tasks make up a significant portion of the work. But the economic outcome isn’t necessarily that simple.

Consider two businesses that experience the same dramatic productivity improvement. One business uses AI to reduce operating expenses while maintaining its current output. It may reduce its workforce. Another business uses AI to expand into new markets, develop additional products, and serve customers it previously couldn’t afford to reach. It may maintain or even expand its workforce.

Both businesses benefit from the same technological advancement. Their strategic responses are fundamentally different.

Of course, new economic activity doesn’t automatically translate into new jobs, and displaced workers cannot necessarily move easily into emerging roles. Skills, geography, experience, and the speed of technological change all matter.

There’s also a meaningful difference between creating more things and creating more things that people are willing and able to pay for. Jevons Paradox offers a useful perspective, but it doesn’t guarantee that AI will generate enough new demand to offset every job it displaces. What it does suggest is that we shouldn’t assume the future economy will require the same amount or types of work as today’s economy.

From Productivity to Human Potential

We’re entering a period when one person’s ability to create value is expanding substantially. An individual entrepreneur can develop products that once required a team. A professor can create more engaging educational experiences. A scientist can investigate possibilities that previously required extensive resources. A small organization can compete in markets that were once accessible only to much larger companies.

These opportunities are exciting because they represent something beyond productivity. They represent increased human agency. AI can give people greater capacity to act on their ideas, solve problems, and bring their ambitions to life. But we also need to consider who actually benefits from these advances.

If AI doubles productivity, does the resulting value flow primarily to shareholders through higher profits? To consumers through lower prices? To workers through better compensation and improved working conditions? Or into investment, innovation, and new employment opportunities? Most likely, some combination of these outcomes will emerge, and not necessarily in equal proportions.

That distribution will be influenced by leadership decisions, competitive markets, education, public policy, and the choices we collectively make about how this technology should serve society. In other words, technological progress and broadly shared prosperity are not automatically the same thing.

The Question We Should Be Asking

Much of today’s conversation about artificial intelligence centers on a familiar question: How many jobs will AI replace? It’s an important question, and one we shouldn’t dismiss. Workers, educators, business leaders, and policymakers need to understand the disruption that may be coming.

But I believe there’s another question that deserves just as much attention. How much new human ambition will AI unlock?

My own experience suggests that when people become more capable, they don’t necessarily become less active. They become more curious. More entrepreneurial. More creative. More willing to pursue ideas that previously seemed out of reach. That possibility gives me tremendous optimism about the future.

The challenge is ensuring that this expanded human potential translates into economic opportunity for more people, rather than concentrating its benefits among a relatively small number of organizations and individuals.

AI may not simply change how we perform existing work. It may fundamentally change what work we consider possible, valuable, and worth pursuing. And perhaps that’s where the most important conversation about the future of AI should begin.

The most consequential question may not be how much human labor AI can replace, but how much new human ambition AI can unlock, and whether our economy can translate that ambition into broadly shared prosperity.