· Mark James
Are We in an AI Bubble? (And Why It Doesn't Matter)
Smart people disagree violently on whether we're in a bubble. For most business leaders, the answer is simple: it doesn't matter. The capability is already here. What remains is tooling, change management—and knowing where to focus.
Everyone's asking the wrong question.
The financial pages are full of it. The Economist reports that investors expect AI use to soar while business adoption is actually flatlining. The Telegraph warns of something "rotten" in the AI money-go-round. Nobel laureate Daron Acemoglu says we're investing more than we should. Nvidia's CEO opens earnings calls trying to deflate bubble fears.
Smart people disagree violently on whether we're in a bubble. And for most business leaders I talk to, I have a simple response:
It doesn't matter.
Even if AI doesn't improve much beyond current levels—if what we have now with Claude, GPT, Gemini is roughly what we're working with—the changes to business and the broader economy will still be profound. The capability is already here. What remains is process design, tooling and change management.
I'm confident we're entering a new industrial revolution. And just like the original, there's no best practice yet. No industry standards. No proven playbook. The companies that thrived in the industrial revolution weren't following a template—they were figuring it out, reinventing how work gets done to harness new levels of productivity.
That's where we are now. And it's exactly why we need to be disciplined about what we focus on. When there's no map, principles matter more than tactics.
We've seen this before, of course. The dotcom bubble was real—Pets.com became a punchline, investors lost fortunes—and yet Amazon, Google, and others emerged stronger. They weren't 'internet companies' chasing valuations. They were solving real problems with the internet as an enabler. The lesson: focus on value creation, and bubble dynamics become background noise.
Okay, But What Does "Value Creation" Actually Mean?
"Focus on value creation" is easy to say and hard to do. So let me make it concrete.
Picture a simple stick. At the top is what your customer is willing to pay—not what you charge, but the maximum they'd pay if pushed. At the bottom is what your employees and suppliers need to receive to work with you—their walk-away price. The gap between those two points is the total value created.
That's it. Every business improvement either raises the top (customers would pay more) or lowers the bottom (your supply side would accept less). Price and cost sit somewhere in the middle, dividing up the value between you and everyone else.
(This is the 'value stick' framework—if you want the full treatment, Felix Oberholzer-Gee's Better, Simpler Strategy is excellent.)
The Automation Trap
Automation is the leading use case for AI right now. Businesses everywhere are asking: where can we cut costs with AI?
It's the obvious question. It's also incomplete.
Replacing a customer service rep with an AI agent, or a graphic designer with an image generator—that's cost reduction. It might lower your expenses. But if it also degrades the customer experience, you've lowered the bottom of the stick while simultaneously lowering the top. Your costs went down, but so did what customers are willing to pay. You might have destroyed value while celebrating the savings.
The real opportunity is automation that does both: reduces costs and raises (or at least protects) what customers are willing to pay. That means you're not just taking a bigger slice—you're growing the whole pie while improving your share of it.
To find these opportunities, you need to understand two things: your processes (where does the work happen?) and what your customers actually value (which processes contribute to that, and which ones don't?). Automate the stuff that costs you money but doesn't drive customer value, and you win. Automate the stuff customers care about without understanding why they care, and you might've shot yourself in the foot.
Where AI Fits
Here's where it gets interesting. AI provides capabilities we've never had before—pattern recognition at scale, natural language processing, automation of cognitive work. These aren't incremental improvements; they're genuinely new.
But capability without clear direction is just expensive experimentation. When you know where value is created in your business, when you can see where you could raise customer willingness to pay and lower your supply-side costs, AI stops being a shiny object and becomes a precision tool. You're not asking 'what can AI do?' You're asking 'what's the highest-value problem AI can solve for us?'
That's the combination that makes bubble dynamics irrelevant: a clear value target and a powerful enabler. Miss either one and you're exposed—AI without a value target is expensive experimentation, and a value target without the right tools is just a wish list.
The Bottom Line
The intelligence shift is happening regardless of bubble dynamics. AI capabilities are real and improving. The question isn't whether AI is overhyped—it's whether you're building a business that creates genuine value.
If you are, the tools will serve you. If you're not, no amount of AI will save you—bubble or no bubble.
Stop watching the financial pages for permission. Start with the value.
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