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Why AI will flatten organisations

The coordination machine

For decades, companies scaled by adding management layers. More people meant more coordination. More coordination meant more managers. More managers meant more process.

Over time, organisations became highly optimised coordination machines. This made sense when execution capacity was expensive and highly specialised. The larger the company became, the more management infrastructure it required.

And for a long time, that trade-off was unavoidable. Human expertise was scarce. If you wanted to launch a new initiative, you needed specialists across every domain:

  • product
  • engineering
  • design
  • marketing
  • operations
  • finance
  • legal

The problem is that every handoff introduces friction. Context gets compressed. Intent gets reinterpreted. Trade-offs get lost.

Every cross-functional initiative becomes a coordination challenge before it becomes an execution challenge. And as organisations scale, that coordination tax compounds.

When execution gets cheap

AI changes the economics that made those structures necessary in the first place.

Most people think about AI vertically:

  • engineers code faster
  • marketers produce content faster
  • analysts produce insights faster
  • sales teams generate pipeline faster

But the more important shift may be horizontal. AI reduces the cost of moving across functions. One person can increasingly:

  • think
  • write
  • prototype
  • analyse
  • design
  • code
  • automate
  • execute

The distance between intention and execution collapses. And that changes something fundamental inside organisations.

Historically, companies scaled by dividing work into increasingly specialised functions. But if one highly capable operator can now move across multiple domains independently, the value of coordination-heavy structures starts to decrease.

The bottleneck shifts. It's no longer: "Can we produce enough work?". It becomes: "Can we maintain clarity and alignment as execution accelerates?"

The rise of the AI-native operator

Over the past few months, I've repeatedly noticed how much work I can now move through independently that previously required multiple stakeholders, specialist support, or dedicated teams.

Because AI reduced the friction between:

  • thinking
  • creating
  • communicating
  • and executing

Instead of:

  • writing detailed specs
  • waiting for prioritisation
  • coordinating multiple teams
  • translating intent across functions
  • managing dependency chains

I can increasingly move directly from idea → execution myself. Not perfectly, but fast enough that the coordination cost often becomes more expensive than the work itself.

That's the shift I think many organisations are still underestimating. AI doesn't just accelerate specialists. It increases the leverage of context-rich operators.

And that may fundamentally change what high-performing organisations look like.

Flatter companies, smaller teams

If AI continues increasing the leverage of individuals, organisations may need:

  • fewer coordination layers
  • fewer approval chains
  • fewer translators between functions
  • fewer rigid organisational boundaries

The highest-leverage managers may increasingly become player-coaches: people who still operate directly, stay close to execution, and use AI to extend their leverage rather than distance themselves from the work.

Likewise, the highest-leverage individual contributors may begin operating with the output and influence that once required entire teams.

Smaller organisations may suddenly compete with much larger ones. Not because they work harder. But because they lose less energy to coordination.

For decades, scale meant adding layers. AI may redefine scale as increasing the leverage of individuals instead. And the companies that adapt fastest may not be the ones with the largest headcount.

They may be the ones that remove the most friction between context, decision-making, and execution.