Rethinking Business Models in an AI World

When people talk about AI, they usually mean one of two things. Either they mean "cool tricks": chatbots, image generators, little things that seem magical. Or they mean "end of the world": AI getting smarter than humans and wiping us out.

But while everyone argues about the future, something quieter,  and maybe more important,  is happening now. AI is already changing how businesses work. Not just how they operate, but how they make money. Their business models.

And like most important changes, it's happening unevenly. Some industries are already feeling it. Others haven't yet, but they will. Some companies are adapting without even realizing it. Others won't adapt until it's too late.

Over the last few months, I've talked with founders and executives in a bunch of different fields (consulting, finance, and healthcare). Almost all of them are starting to ask the same question: "If AI can do more of what we do, what happens to our business?"

The answer is: it depends.

It depends on a few basic things about how your company works. And interestingly, they're not new things. They're just things people usually didn't have to think about too much before.

For example: does your company sell time or results?

If you sell time, like lawyers, consultants, agencies, AI is a bigger threat. AI makes things faster. And if you're billing by the hour, faster is worse, not better. You have fewer hours to bill.

If you sell results, like getting a client a good outcome, AI can be an advantage. If you can deliver better outcomes faster, you can either charge more or win more customers. Or both.

Another example: is your product about processing information or making hard decisions?

If your value comes from organizing and presenting information, AI can probably replace you. It can already do research faster than most humans. It can summarize, generate, and categorize almost instantly.

But if your value comes from making judgment calls (weighing messy, uncertain data and making smart decisions) you're harder to replace. At least for now.

Or think about how personal your service is. Industries where personal relationships matter (like private banking, elite consulting, healthcare) may find that AI doesn't replace humans, but augments them. An AI that helps a doctor diagnose faster is useful, but it doesn't replace the doctor's bedside manner. An AI that helps a financial advisor find investment opportunities is powerful, but clients will still want someone they trust to help them choose.

Some people seem to think that AI will just replace humans wholesale, but history suggests otherwise. Usually what happens is that technology shifts the value higher up the stack. In the early days of the internet, people thought bookstores would disappear. Instead, bookstores evolved. Some became more focused on community and curation. Others disappeared. Same with newspapers, travel agents, even taxi drivers.

AI will likely have the same effect. It won't destroy entire industries overnight. It will reshape them, sometimes subtly, sometimes brutally.

Take law firms. They're the classic case. They mostly bill by the hour. If AI can draft contracts, summarize cases, or prepare memos faster, that's fewer hours to bill. So revenue drops, right?

Maybe. But also: if you can do the same work faster, you can serve more clients. Or you can offer a premium service, faster higher-quality legal work, and charge more for it. Or you can focus your lawyers on the kinds of work AI can't do yet: high-level strategy, negotiation, trial work.

The same logic applies in marketing, consulting, accounting, even education.

Where companies get into trouble is when they assume they can bolt AI onto their existing model and keep working the same way. They treat AI like a productivity tool, instead of realizing it's a business model tool.

That's why companies that think carefully about how AI changes their value proposition, and how they charge for that value will pull ahead. And companies that just try to be a little bit more efficient will fall behind.

Another interesting shift is happening inside companies themselves.

In the past, the technology team was often seen as a support function. They kept the servers running. They built internal tools. They didn’t set the direction of the company.

Now, the people who understand AI are setting strategy. They're not just being asked, "Can we do this?" They're being asked, "What should we be doing?"

In a lot of companies, the CTO is becoming the most important person in the room. Because they’re the only ones who really understand what AI is about to make possible.

This seems to be similar to the early internet days. In the mid-90s, the companies that won weren't the ones that had the best websites. They were the ones that realized the internet would change how business itself worked. Amazon didn't just open an online bookstore. They realized you could rethink distribution itself.

We are at the same kind of inflection point now.

If you're running a company you should be asking yourself a few hard questions:

• What part of my value chain could AI collapse?
• What part could AI make 10x better?
• What will users or customers value more after AI becomes normal?
• Am I selling time or outcomes? Information or judgment? Transactions or relationships?

And maybe the most important question: if a smarter competitor started from scratch today, what would they build?

Because someone out there is probably already building it.