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Rafael Cordeiro, colunista

AI can raise productivity without improving results

Rafael Cordeiro · 2 min read
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AI can raise a company's productivity without improving its results. It sounds contradictory, but it is not.

Doing it faster and creating more value

We are entering a phase in which automating tasks, cutting execution time and producing more with fewer resources is becoming more and more accessible.

But there is an important difference between doing things faster and creating more value.

A company can save thousands of hours with AI and still have the same problems with efficiency, quality and growth. It can even create new costs in supervision, rework and maintenance of systems that do not deliver the expected result.

Incrementality

Throughout my career building companies in technology, data and measurement, I learned an important lesson. It is not enough to measure what happened. We need to understand what happened because of what we did.

That is the concept of incrementality, which now takes on a new dimension with AI.

Editor's context. Incrementality is the effect that exists only because of an action, measured against what would have happened without it, usually with a control group.

Three things to measure

In practice, I believe we need to start measuring three things.

  • Real productivity. How much work was actually reduced, accounting for supervision, corrections and exceptions.
  • Economic impact. How much of that efficiency turned into lower costs, higher revenue or better margins.
  • Organizational capacity. How the company is using the freed-up time and resources to create new opportunities and develop its people.

What to do with twice the output

And here comes a question I consider fundamental.

If AI allows a team to deliver twice as much, that does not necessarily mean we need half the people.

We can serve more customers, develop new products, improve the experience or pursue opportunities that used to be economically unviable.

But we also need to recognize that, in some sectors, automation may reduce demand for human work.

These are business decisions, not inevitable consequences of technology.

Measured, concrete and sustainable results

This is exactly the vision we are bringing to building OperOS AI. Not just implementing artificial intelligence, but operating it, governing it and proving the value it generates for companies.

Because I believe the next big competitive advantage will not simply lie with whoever uses the most AI. It will lie with whoever can turn that technological capability into measured, concrete and sustainable results.

And that takes much more than good AI models. It takes strategy, data, governance and leadership.

In short

  • AI can raise productivity without improving results.
  • It is not enough to measure what happened. We need to understand what happened because of what we did.
  • How the time freed up by AI is used is a business decision, not an inevitable consequence of technology.

Further reading

Originally published on LinkedIn on October 13, 2026. See the original post. This version has been revised and expanded with context. The views are those of the author, a co-founder of OperOS AI.

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