For months, the conversation has revolved around the same issue:
"Which jobs will AI replace?"
It's an important question. But I don't think it's the most important one.
Every major technological revolution has done far more than change the way people work. It has changed where economic value is created.
The steam engine shifted value from muscle power to machines. The internet shifted value from distribution to information. Cloud computing shifted value from infrastructure to software.
AI is no different.
It isn't just automating tasks. It is changing the economics of intelligence itself.
For centuries, intelligence was a scarce resource. Access to it was gated — by education, by geography, by the sheer number of hours a skilled person could dedicate to a problem. Scarcity gave intelligence its price.
Today, that scarcity is dissolving. Intelligence is becoming abundant, on-demand, and nearly free at the margin.
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And here is the pattern that history keeps repeating: whenever something that was once scarce becomes abundant, value doesn't disappear. It moves.
It moves to whatever becomes the new bottleneck.
When muscle power became abundant through machines, value moved to those who could design, organize, and direct machines — engineers, managers, capital allocators. When information became abundant through the internet, value moved to attention, trust, and curation — the ability to filter signal from noise. When infrastructure became abundant through the cloud, value moved to the software layer — to whoever could turn raw compute into something people actually wanted.
The scarce resource always changes hands. The winners are the ones who see the shift before it's obvious.
This is why I believe the defining management question of this decade is not:
"How should we use AI?"
It is:
"Where does value move when intelligence becomes abundant?"
That's a fundamentally different question. "How should we use AI?" is a tooling question — it lives at the level of workflows, prompts, and productivity gains. It's useful, but it's tactical.
"Where does value move?" is a strategic question. It forces you to look past the tool and ask what becomes scarce next — because whatever that is will be where the next competitive advantage, the next premium, the next moat gets built.
If intelligence becomes cheap, then execution speed doesn't automatically become valuable — everyone gets faster. Judgment doesn't automatically become valuable either, if AI can approximate judgment too. The real bottlenecks may be subtler: trust, taste, accountability, the ability to ask the right question in the first place, access to real-world data that AI can't generate on its own, or simply the courage to make a decision and own its consequences.
Somewhere in that list — or somewhere we haven't named yet — sits the next scarce resource. And whoever identifies it early gets to build around it while everyone else is still optimizing prompts.
This single question — where does value move when intelligence becomes abundant? — has shaped the thinking behind a framework I've been developing over the past months. It's an attempt to give this shift a structure: to name the bottlenecks as they move, and to give leaders a way to think about strategy that isn't tied to any specific model, tool, or vendor.
Over the coming weeks, I'll share the core ideas here — not as AI tips or productivity hacks, but as a different way to think about strategy in the age of abundant intelligence.
I'm curious:
What do you believe will become more valuable as intelligence becomes cheaper?
Trust? Taste? Data? Relationships? Something else entirely?
Drop your take below — I'd genuinely like to know what you're seeing.
The Value Relocation Project explores how technological abundance changes the sources of competitive advantage. Through frameworks, cases, research and practical tools, the project investigates one central question: Where does business value move when intelligence becomes abundant?