AI Will Not Make Everyone More Productive - Vincent Schmalbach

Skip to content

Currently Available: Need a skilled Software Developer for your next project?

Hire Me Today

Categories

Business Economics LLM

AI Will Not Make Everyone More Productive

May 15, 2026<br>by Vincent Schmalbach

When everyone gets access to AI, not everyone becomes more efficient. Some people and companies will become much faster while some may become even less productive.<br>I'm writing this while working on vroni.com, my AI coding tool for turning tasks into pull requests.

AI helps a strong developer explore solutions faster, a good writer sharpen structure and wording, and a capable operator analyze options, prepare decisions, and reduce repetitive work.

In all of those cases, AI shortens the distance between intent and execution, making those people more productive.

But more output does not always mean more productivity.

Confusing output with productivity

One of the main traps with AI is confusing output with productivity.

AI makes it easy to produce more text, slides, emails, reports, and meeting notes. That extra volume is not the same as value.

In many knowledge-work environments, the bottleneck is not producing more material. The bottleneck is attention, trust, clarity, and decision-making.

A long AI-generated document may save time for the person who created it. But if ten other people now have to read it, evaluate it, and respond to it, the work has not disappeared. It has been shifted.

The individual may feel more productive, while the organization slows down.

AI creates coordination costs

Before AI, creating a long document took effort. That effort acted as a filter. It was an imperfect filter, but it still made unnecessary material costly to produce.

AI cuts that cost dramatically.

Organizations may end up with polished but low-value communication: long emails that should have been short, reports generated mainly because they were easy to produce, summaries that add little, and strategy documents that sound coherent but contain little actual thinking.

AI in everyday work can make low-quality work look professional enough to circulate.

That matters because coordination is already expensive. Every extra document, email, and update asks for someone else's attention. AI can reduce friction in production and add it everywhere else.

AI creates the wrong incentives

There is also an incentive problem here.

If someone becomes much more productive with AI, the organization does not automatically capture the full benefit. In many jobs, the employee does not receive much upside from revealing that they can now do the same work in half the time.

The likely reward may be more work, higher expectations, or less job security.

So it can be rational to use AI quietly: produce the expected output with less effort, rather than dramatically increase output for the same compensation.

This is not about laziness. It is about incentives.

AI changes what individuals are capable of, but organizations still need structures that make those gains visible and worth sharing.

This is also true for sharing best practices around AI. If someone found a great way to become more productive through AI usage, what's his incentive to share this with coworkers?

Company size matters, but other factors matter too

Small teams and independent workers often have an advantage because they get feedback faster. If a freelancer, founder, or small company becomes more productive, the benefits are direct. They can ship faster, serve more customers, reduce costs, or earn more.

Large corporations have advantages too: data, distribution, capital, established workflows, and scale. They can benefit when AI is integrated into systems like customer support, software development, finance, legal review, operations, or internal search.

But large organizations are also more exposed to the downside. They have more layers, more handoffs, more meetings, and more internal communication. If AI is used mainly to generate more documents, messages, and presentations, it can speed up the existing bureaucracy without changing it.

That accelerates the wrong thing instead of transforming it.

AI's real divide

The real divide is between people and organizations that use AI to reduce work and those that use it to create more work.

Good AI use removes friction, clarifies decisions, automates repetitive tasks, and helps people get to a better result faster.

Bad AI use creates polished noise and increases the amount of material in circulation. It looks productive while consuming more collective attention.

This distinction matters more than access to the tools themselves. Access will become common. Good usage will not.

AI will widen productivity gaps

AI will not make everyone more productive in the same way; it will widen the gap between people who use it well and people who do not.

AI will amplify existing differences in judgment, incentives, and organizational...