AI and the Future of Work: Liberation vs. Control
Something strange is happening. The most powerful technology of our generation has arrived, and the majority of companies are using it to double down on the very management practices that were already failing.
More monitoring. More control. More centralization. Fewer decisions for the people closest to the work.
It is like watching someone inherit a fortune and flush it all down the toilet.
We need to talk about AI and the future of work. And not in the same way everyone else does. Let's not mindlessly repeat the panicky narrative that AI will replace humans, saving costs at any human expense and building control mechanisms on steroids.
Sure, AI can make your company more efficient. The question nobody seems to be asking is: efficient at what?
Efficient at surveillance? Efficient at replacing the people who actually understand your customers? Efficient at centralizing decisions in the hands of executives who are furthest from the work?
What a decade of research into progressive organizations taught us
We have spent the last decade visiting over 200 pioneering organizations around the world. We have seen what happens when you trust people, flatten hierarchies, and share power.
Revenue goes up. Employee turnover goes down. People start solving problems that management did not even know existed.
Research backs this up. A 2025 study from the German Socio-Economic Panel found that 38% of German workers already use AI at work, but that the relationship between AI and worker autonomy is far more complex than the headlines suggest. The positive link between AI use and autonomy disappeared entirely once existing workplace conditions were taken into account. In other words: AI does not automatically liberate or oppress. It amplifies whatever system it is plugged into.
That finding should make every leader pause. If your organization already runs on control, AI will give you more control. If it runs on trust and autonomy, AI can multiply that too.
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Two pathways for AI in organizations
The way we see it, there are two pathways for AI and the future of work.
Pathway 1: Control. Use AI to monitor, measure, rank, and replace. Tighten the screws. Make the pyramid steeper. This is the path most companies are sleepwalking down right now. Critics rightly point out that under corporate rule, AI often intensifies surveillance rather than reducing it. When profit is the only driver, AI's supposed liberation becomes a thin disguise for deeper data-driven control.
Pathway 2: Liberation. Use AI to eliminate the boring tasks that make people hate Mondays. To give teams the information they need to make their own decisions. To remove the layers of bureaucracy that exist for no reason other than the fact that they have always existed.
We are going all in on Pathway 2.
The questions we want to answer
We are launching a research project to figure out how AI can make organizations more human, not less. We are looking for companies where AI is replacing outdated approval processes, where teams are using it to coordinate without hierarchy, and where the technology is making the organization more purposeful and more successful.
Here are some of the big questions driving our research.
Which layers of corporate bureaucracy can AI genuinely replace, and which ones will it accidentally reinforce? Early evidence suggests the answer is uncomfortable. The German SOEP study found that AI use is heavily concentrated in high-level, non-routine occupations where digital infrastructure already exists. Workers in manual and lower-skilled roles are far less likely to use AI at all. That means AI is not flattening hierarchies by default. It is following them. Unless organizations deliberately redesign how AI is deployed, the technology will reinforce existing power structures rather than replace bureaucracy. Critics of techno-optimism make the same point: AI embedded in corporate control systems tends to deepen surveillance, not dissolve it.
When AI makes a team of 10 as productive as a team of 20, what happens to the other 10? The data here is genuinely mixed, which is itself revealing. One widely cited Stanford study found that employment for workers in their early 20s in high-AI-exposure jobs declined roughly 13% after the release of ChatGPT. But a broader study by economists Johnston and Makridis found that high-AI-exposed occupations actually saw gains in both wages and total employment. A Swedish study tracking firms that received AI adoption grants showed increased job postings with no net employment decrease over five years. The pattern seems to depend entirely on intent: are companies using productivity gains to grow, or simply to cut headcount?
How do you design a hybrid organization where people and AI agents collaborate? How are self-managing teams using AI tools to coordinate without managers? Can AI serve as the operating system for a team? These are the questions where we have found the least existing research. That is exactly why we are pursuing them.
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Why this matters right now
AI is going to change how your organization works. That is already happening, whether you are steering it or not.
History shows that technological revolutions ultimately create more jobs than they destroy, but the transition matters enormously. The real question is not whether AI will transform work. It is who gets to decide how.
Right now, the loudest voices in this conversation are talking layoffs and machine-replaces-man. Somebody needs to be in this space asking a different question. That is what we are going to do.
We will be publishing everything we learn: case studies, frameworks, mental models, and honest accounts of our own experiments as a small, self-managed team using AI every day.
Let's use AI to give humans wings, not to put them on a leash.
Don't add AI to a broken system
AI will amplify whatever system it is plugged into. So before you add AI to your organization, make sure the organization itself is worth amplifying. Learn how Ikea prevented AI layoffs by reskilling their workforce.
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