Stop Solving Problems. Start Creating Them.
March 5, 2026
The dominant narrative around AI right now is about efficiency. Faster code. Fewer steps. Less manual work. And that narrative is true — AI is making us dramatically more efficient at solving problems.
But efficiency was never the point. The point is what we do with the time and capacity we get back.
Every major technological leap in history has done the same thing: it raised the level of abstraction at which humans operate. Assembly lines didn't eliminate work — they freed people to design better products. Spreadsheets didn't replace accountants — they turned them into analysts. The internet didn't kill commerce — it created entirely new industries that no one had imagined.
AI should do the same. And if we're intentional about it, it will.
From Problem Solvers to Problem Creators
For most of modern business history, the most valued skill has been problem solving. Someone identifies an issue, and you figure out how to fix it. That's where careers are built, promotions are earned, and organizations gain an edge.
AI is very good at solving problems. It's getting better at it every month. Give it a well-defined problem with clear parameters and it will find an answer faster and cheaper than a team of people can. That's not a threat — it's a fact, and it's a gift if we treat it right.
Because the real competitive advantage — the thing AI can't do — is deciding which problems are worth solving in the first place. That's problem creation. It's asking the question nobody thought to ask. It's seeing a market that doesn't exist yet. It's looking at a process that "works fine" and imagining what it could become if you rebuilt it from first principles.
Problem creation requires context, imagination, lived experience, and taste. It requires understanding what people actually need — not just what they say they want. AI can synthesize data, but it can't walk a factory floor and feel that something's off. It can't sit with a customer and sense the frustration behind a polite smile. It can't look at an industry and ask, "Why does it have to work this way?"
That's human work. And it's the highest-value work there is.
The Case for Creating More Work, Not Less
There's a conversation happening in boardrooms right now that goes something like this: "AI can do this job, so we don't need as many people doing it." It's a logical conclusion. It's also the wrong one.
Humans need work. Not just economically — although that matters — but existentially. Work gives people purpose, structure, community, and identity. The Greek word ergon means your proper function — the thing you were designed to do, done with excellence. Strip that away and you don't get a leisure society. You get a lost one.
The goal of AI adoption shouldn't be to reduce headcount. It should be to raise the ceiling on what your people can accomplish. When AI handles the repetitive, mechanical, and routine, your people can move up the abstraction stack — into work that's more creative, more strategic, and more meaningful. Not less work. Better work.
And here's what the efficiency-obsessed narrative misses: when you operate at a higher level of abstraction, you see more problems worth solving. You find new markets. You identify unmet needs. You build things that create demand — and demand creates jobs. Not the same jobs that AI automated, but new ones that didn't exist before. The pattern has held through every technological revolution. There's no reason to believe this one is different — unless we choose to make it different by being short-sighted.
The Leader's Responsibility
If you lead an organization, this is your call to make. You can use AI to cut costs and shrink teams. That's one path, and the short-term numbers will look great. But the long-term cost is a hollowed-out organization that lost its ability to think, create, and adapt — because you optimized the humanity right out of it.
Or you can use AI to elevate your people. Give them better tools so they can tackle bigger problems. Invest the efficiency gains into exploration, innovation, and growth. Let AI handle the solving so your people can focus on the creating.
The organizations that will define the next decade won't be the ones that automated the most. They'll be the ones that imagined the most — because they kept their people engaged, purposeful, and operating at a level of abstraction that no algorithm can reach.
AI is a lever. What you lift with it is a choice. Choose to lift your people higher, not push them out the door.
Stop using AI to solve problems faster. Start using it to create problems worth solving.
Jason Oglesby is the founder of Ergon Insights, based in Johnson City, Tennessee. He brings 30+ years of experience in software development and technology leadership. Ergon (ἔργον) — one's proper work, done with excellence.