AI Compresses Dependency Chains

By Philippe Cailloux ยท

AI does not replace people. People using AI replace people who do not.

I made that point years ago in a conference talk, and I still believe it. What feels clearer to me now is that this is only the first-order effect.

The deeper shift is recursive. AI is not just another tool that helps people do the same work faster. It changes how much human dependency sits between intention and execution.

Recent public comments from major AI companies are moving closer to that reality. The workforce impact is no longer something abstract to debate from a safe distance. It is starting to show up in org design, team size, hiring plans, and expectations about what one capable person can now do.

The first layer: tools have always changed who wins

This pattern did not start with AI.

People using steam power replaced people using muscle power. Farmers using tractors replaced farmers using horses and larger field crews. Finance teams using spreadsheets replaced slower chains of clerks, calculators, and reporting steps.

AI fits the same historical pattern. A person using AI can often move faster than a person not using it. Writing, analysis, research, prototyping, coding, documentation, planning, and support all start to compress.

That part is visible now. The less visible part is more important.

The real shift: dependency compression

A person using AI does not just outperform a person without AI. That person can also replace work that used to depend on another person.

Think about the executive who once dictated a letter to a typist. Then came the word processor. Then email. Now AI.

The tool did not simply accelerate the same workflow. It removed part of the workflow. The executive no longer needed the same human dependency to move from thought to output.

That is why I do not think the real story is simply job automation.

The real story is dependency compression.

When AI sits close to the point of intent, fewer people are needed to translate, relay, summarize, polish, coordinate, reformat, or restate the work on the way to execution. A lot of organizational structure was built around exactly those handoffs.

A simple logical model

Sometimes the cleanest way to say it is as a compact model:

Then the pattern looks like this:

In plain English:

That is the recursive effect. Once one layer compresses, the next layer feels it too.

Why this matters for organizations

When the dependency chain shrinks, the management chain often shrinks with it.

If fewer handoffs are needed, fewer layers are needed to manage the handoffs. If smaller teams can produce more, some support functions get absorbed into the core team. If one strong operator can move from idea to execution with much less assistance, the shape of the organization changes.

That is why I expect the first phase to be compression and reduction.

Not because companies suddenly need no people. Not because human judgment stops mattering. Not because AI becomes an independent actor.

It is because many existing structures were designed for a world where information had to pass through more human nodes to become useful. AI lowers that requirement.

Compression is not the end state

I also do not think reduction is the destination.

Once organizations understand what AI actually changes, they will still need people who can operate, orchestrate, create, strategize, and judge. In some ways, they will need them even more. The difference is that these people will sit closer to the work itself, with less drag around them.

That is where many discussions still miss the point. AI is already very good at execution across a wide range of tasks, from tactical work to abstract reasoning support. But it still does not create in the human sense. It does not think in the human sense. It does not judge in the human sense.

So the durable advantage moves upward, not upward in title, but upward in capability.

The payoff

For 2.5 million years, humans using better tools have replaced humans using worse ones. AI does not break that pattern. It accelerates it.

What makes this moment different is the scope of the compression. AI does not just improve the worker. It compresses the human chain around the work.

The first phase will look harsh in many organizations. But the long-term winners will not be the companies with the most automation. They will be the companies with the highest concentration of people who can create, think, and judge, while using AI with real skill and proximity to execution.

That is where the next advantage will come from.