Why «AI-First» Is a Trap

The companies that win the AI era may not be the ones that put AI first. They may be the ones that understand what becomes scarce after AI.

“AI-first” has become one of the dominant strategic ideas of our time.

Companies are redesigning processes around AI. Software vendors are rebuilding products around AI. Investors are asking whether businesses have an AI strategy. Management teams are launching AI initiatives, AI transformation programs and AI-native operating models.

The logic seems obvious:

If artificial intelligence is the most important technological shift of our generation, companies should put AI at the center of their strategy.

But there is a problem.

AI-first focuses on the technology that is becoming abundant — rather than on the things that will remain scarce.

And that can become a strategic trap.

AI is powerful. But power does not equal scarcity.

Get your free copy of
“The Value Relocation Playbook” today!

For decades, many forms of intelligence were expensive.

Writing good copy required skilled people. Software development required developers. Analysis required analysts. Design required designers. Research required researchers. Expertise was difficult to acquire, expensive to deploy and slow to scale.

AI is changing that equation.

Increasingly, intelligence can be produced at extremely low marginal cost.

Code. Analysis. Content. Translation. Design concepts. Research. Recommendations. Customer interactions.

Tasks that once required hours or days of human work can increasingly be performed in seconds.

This represents an extraordinary productivity opportunity.

But economically, something else is happening at the same time:

AI is commoditizing intelligence.

And when something becomes abundant, its ability to create differentiation tends to decline.

This where the AI-first logic becomes dangerous.

If everyone has AI, AI cannot be your strategy

Imagine two competitors.

• Both have access to advanced language models.
• Both can generate content.
• Both can automate customer service.
• Both can analyze their markets.
• Both can build software faster.
• Both can deploy AI agents.

What happens?

They become more productive. But they do not necessarily become more differentiated. This distinction matters.

AI can dramatically improve how efficiently a company operates without answering the more important strategic question:

Why should customers choose this company rather than another one?

If every competitor has access to increasingly similar intelligence, then intelligence itself becomes a weaker source of competitive advantage.

The competitive battlefield moves somewhere else.

Value does not disappear. It relocates.

This is the central idea behind Value Relocation.

Technological revolutions rarely destroy economic value completely. Instead, they change where value concentrates.

When one previously scarce capability becomes abundant, another constraint becomes more important.

AI dramatically increases the supply of intelligence.

But it does not make everything abundant.

• Trust remains scarce.
• Attention remains scarce.
• Distribution remains scarce.
• Authentic relationships remain scarce.
• Proprietary data remains scarce.
• Physical infrastructure remains scarce.
• Energy remains scarce.
• Regulatory permission remains scarce.
• Reputation remains scarce.
• Accountability remains scarce.

And perhaps most importantly:

Human willingness to choose, trust and commit remains scarce.

These constraints increasingly determine where economic value can accumulate.

The strategic question therefore changes.

Instead of asking:

“How can we use more AI?”

companies should ask:

“What becomes scarce when intelligence becomes abundant?”

That is a fundamentally different starting point.

The AI-first paradox

The better AI becomes, the less strategically interesting AI itself may become.

This sounds paradoxical, but we have seen similar patterns before.

When electricity was first introduced, access to electricity was a competitive advantage. Eventually, electricity became infrastructure. Companies did not win because they were “electricity-first.”

The internet followed a similar trajectory.

Having a website was once differentiating. Then it became expected.

Cloud computing followed.

Mobile followed.

Each technology created enormous economic value. But as adoption increased, the technology itself gradually moved from differentiation toward infrastructure.

AI may travel this path faster than any previous technology.

The models are improving rapidly. Costs are falling. Capabilities are spreading. Open-source alternatives are developing. AI functionality is being embedded into virtually every major software platform.

If that continues, access to sophisticated intelligence will become less exceptional.

Which means the real strategic question is not whether your organization has AI.

Soon, almost everyone will.

The question is:

What do you have that becomes more valuable because everyone has AI?

From AI-first to scarcity-first

This suggests a different strategic philosophy.

Not AI-first.

Scarcity-first.

Start by identifying what AI is making abundant in your industry.

Then identify what remains difficult to obtain, replicate or scale.

Finally, reposition your business around those emerging constraints.

Consider professional services.

If analysis, research and document production become dramatically cheaper, clients may no longer pay premium prices simply for intellectual output.

• But they may pay more for judgment.
• Accountability.
• Access.
• Reputation.
• Implementation capability.
• Trusted relationships.

The value has not disappeared. It has moved.

Or consider software.

If AI makes software dramatically easier to build, the ability to write code becomes less scarce.

What becomes more important?

• Distribution.
• Installed customer bases.
• Workflow integration.
• Proprietary data.
• Network effects.
• Brand.
• Switching costs.

The winners may not be the companies producing the most software.

They may be the companies controlling the scarce resources surrounding software.

AI strategy is necessary — but insufficient

None of this means companies should ignore AI.

Quite the opposite.

Organizations that fail to adopt AI may face a significant productivity disadvantage.

AI should become deeply embedded in operations, products and decision-making.

But that is increasingly operational necessity rather than strategy.

There is a difference.

Using AI can help you compete.

Understanding where value moves can help you decide where to compete.

And those are not the same question.

A company can execute an excellent AI transformation while simultaneously destroying its long-term differentiation.

It can automate the very capabilities it once charged customers for without building positions in the new sources of scarcity.

It can become dramatically more efficient at producing something customers increasingly perceive as a commodity.

That is the AI-first trap.

The boardroom question needs to change

Today, executives are frequently asked:

“What is our AI strategy?”

Perhaps that is already the wrong question.

A more important set of questions would be:

• What is AI making abundant in our industry?
• Which parts of our current value proposition will therefore become cheaper?
• What becomes scarce as a consequence?
• Where will customers still be willing to pay a premium?
• Which scarce assets can we own, control or strengthen?

And how do we relocate our business toward them before our competitors do?

These questions move the discussion beyond technology adoption.

They move it toward strategy.

The next winners will not simply be AI-first

The AI revolution is real.

Its impact will be enormous.

And virtually every company will need to adapt.

But the winners of the next decade may not be the companies that put AI at the center of everything.

Because once AI becomes ubiquitous, saying that your company is AI-first may become about as strategically meaningful as saying that your company is cloud-first or internet-first.

The more interesting companies will understand the second-order effect.

They will use AI aggressively.

But they will build their competitive advantage somewhere else.

They will identify the resources, relationships, capabilities and constraints that become more valuable precisely because intelligence has become abundant.

That is the shift from AI strategy to Value Relocation Strategy.

And it leads to a very different principle:

Don’t build your strategy around what technology makes abundant. Build it around what abundance makes scarce.

Because that is where value moves next.