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When Marco Riedesser reached out and suggested that we have a serious conversation about AI and jobs, my first reaction was probably the same as yours: haven’t we already been having that conversation?
Every day, it seems, there is another headline about a company cutting thousands of jobs and blaming some part of it on AI. Every week there is another story about college graduates discovering that the entry-level jobs they were told to prepare for may no longer exist in quite the same way. And every few days, someone confidently tells us that this is either the beginning of a golden age or the end of work as we know it.
The truth, as usual, is probably somewhere more complicated.
That is why I wanted to talk with Marco. He is an entrepreneur from Innsbruck, Austria, and he comes at this subject from an interesting angle. He is not an academic theorist. He is not an AI alarmist standing outside the technology industry throwing rocks. He is a hardware guy who has spent his career building real things.
Marco started in electronics. One of his early companies built laser-based training equipment for police, military and defence applications. Later, he founded Controlino, a company in the industrial automation world. More recently, he launched Friend, a physical AI companion designed to be more than another smiling chatbot.
In other words, Marco is not anti-technology. He builds technology. He understands automation. Perhaps that is why his warnings about AI job disruption land differently.
He is not saying, “Smash the machines.” He is saying, “We should probably start planning.”
That is the useful distinction.
Why This Time Feels Different
We have been here before, at least in broad outline. Two hundred years ago, the industrial revolution used steam, water power and machines to change factory work. Later, farm automation reshaped agriculture. More recently, industrial automation transformed manufacturing. Each time, people warned that machines would destroy jobs. Each time, the world did not end.
However, Marco’s argument is that AI may be different in one important respect: he does not yet see the same scale of replacement jobs appearing on the other side.
Yes, there will be some new jobs in AI compliance, management and oversight. But if a company cuts 7,000 or 8,000 people, it is not going to hire 8,000 AI compliance specialists. That math does not work. And the pain, he believes, may be especially sharp at the entry level.
The Entry-Level Jobs Problem
The conversation becomes uncomfortable at this point.
For years, the standard advice to young people was simple: learn to code. Take STEM classes. Get technical skills. The future belongs to software. Now, Marco is telling his own brother’s son not to assume that coding will automatically be the safe path. His view is that entry-level coding work is already being eroded, and that even more senior coding work may change dramatically over the next five years.
He described a developer who is no longer typing code in the traditional way. Instead, he talks to an AI agent, tells it what needs to change, corrects it, redirects it and shapes the result. That still requires expertise today. Over time, however, Marco sees the role shifting from coder to something closer to director. One visionary person may be able to guide the AI while much of the mechanical production of code disappears.
Marco was careful not to suggest that all work disappears. Jobs that involve real physical contact, human trust or craft may last longer. A carpenter still has to build the kitchen. A hairdresser still has a human relationship with a customer. People may continue wanting to deal with other people in certain settings, even when technology can technically do the job.
Yet the list of vulnerable categories is broad. Customer service, call centres, sales support, transportation, factory work and entry-level software development are not obscure corners of the economy. They are major pathways into work.
What Happens If Work Changes?
AI is not arriving alone. It is arriving alongside robotics. Marco pointed to robots moving through factories, autonomous driving systems, transportation automation and eventually broader physical automation. AI may start as software, but it does not stay trapped inside the laptop.
This is where the conversation moved from technology to government.
Marco’s central point is that governments need to begin thinking seriously about how society handles large-scale disruption to work. Not after the crisis has already happened. Not after people are angry enough to “storm data centers,” as he put it. Now.
His view is that some form of universal income will eventually have to be part of the answer. That may sound radical in the United States, but it sounds less radical in much of Europe, where there is a stronger tradition of social support and a broader comfort with the idea that society has an obligation to take care of people.
One of the most important divides in the AI debate may lie here. In Europe, the response may be shaped by social security systems, national health care and a political culture more comfortable with government intervention. In the United States, the transition may be harder because work, income and identity are so deeply tied together. We like to think of ourselves as capitalist, self-reliant and individually responsible.
It is a powerful tradition. It is also a difficult framework if the economy suddenly needs far fewer workers in categories that once provided stable careers.
The darker version of this conversation is easy to imagine. Job losses. Social unrest. Loss of purpose. Mental health problems. A generation wondering what it is supposed to do with its time.
The conversation was not simply apocalyptic, however. There was another possibility running underneath it. Maybe AI reduces some of the pressure of survival. Maybe people no longer have to define their worth entirely through their jobs. Maybe younger people who are already pushing back against 60-hour workweeks and the old culture of constant hustle are not lazy at all. Maybe they are seeing something the rest of us are late to understand.
Marco, who has practiced karate for more than 30 years, talked about the importance of having purpose outside of work. That matters. If technology changes the economics of work, society will also have to rethink meaning, ambition and impact. It is a much bigger conversation than whether AI can write code or answer customer service calls.
Near the end of our discussion, we turned to Friend, Marco’s physical AI companion. The idea is interesting because it reflects his broader philosophy. Friend is not designed to be another AI system that simply tells you that you are brilliant, attractive and correct. Marco wants it to challenge you, because a real friend challenges you.
Perhaps that is the right metaphor for the whole AI conversation.
We do not need technology that merely flatters us. We also do not need panic. What we need is a serious, adult conversation about what happens if AI really does change work at the scale many people now expect.
Marco may be wrong about the timing. He may be wrong about the severity. History may surprise us again, as it often does, and create new kinds of work we cannot yet imagine. But he is almost certainly right about one thing: waiting until the disruption is obvious is not a plan.
The value of conversations like this lies not in providing neat answers. It does not. It raises harder questions than it answers, and that is exactly why we should be asking them now.
