Few people have done more to automate the office than Daniel Dines. So it is striking that the UiPath founder’s message on AI and jobs is a plea for patience, and a confession that he feels the anxiety too.
Dines built UiPath into one of Europe’s biggest software success stories by selling robots that do the repetitive parts of white-collar work. The company has since pushed hard into AI agents, most recently by buying the compliance-automation firm WorkFusion. Yet on the company’s podcast, The Path Forward, Dines spent much of his time warning against the very thing his tools enable: cutting staff in a hurry.
“Everybody feels some sort of anxiety, me included,” he said, in conversation with UiPath colleague Andrada Morar. “We don’t know how our kids’ career is gonna look like.” His answer to that unease is a line he repeats often. In times of anxiety, action is the answer.
No Einstein in the data centre
Dines is impatient with the biggest promise of the moment. Some in the industry talk of “50 million Einsteins in the data centre.” He thinks that is only half right. A model, he argues, is an average of everything it has read. “An average by definition doesn’t have a taste.”
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He tested this himself, asking models to write fiction in a given style. The results came back bland. Taste, he says, comes from lived experience, not memory. He reaches for skiing to make the point. You can memorise every book ever written about the sport. It will not make you a skier. You have to fall on the slope.
That gap matters inside a company. Every enterprise runs the same handful of frontier models, with the same weights. Feeding them different data does not make them grasp your customer or your process. “Our memory is not our identity,” he said.
Two ledgers, not one
His warning to executives is blunt. Do not read a job as a single output. Take a lawyer who reviews contracts. The visible outcome is a signed deal, and AI can speed that up. The hidden outcomes are harder to see. The same lawyer might mentor juniors, hold a client relationship together, or carry years of unwritten knowledge.
Dines wants firms to keep two ledgers, one for visible outcomes and one for hidden ones. Cut blindly, he says, and you destroy value you never measured. It is a pointed message from a man who sells automation. It also lands against a backdrop of real cuts. Carmakers have shed more than 20,000 white-collar jobs, and a growing chorus of bosses now pitch AI as a way to do more with fewer people. That is a sharp reversal from two years ago.
He also thinks the shift is slower than the hype suggests. Agents cannot simply plug into messy processes. Most firms have never mapped who is allowed to approve an invoice, or pay one. That knowledge sits in people’s heads and across departments. Documenting it will take years, he says, not a weekend.
The identity problem
The deepest worry in the conversation is not about tasks. It is about identity. Dines traces his interest in the subject to a lawyer friend. She told him her fear was not that her job would vanish. It was that her identity would become irrelevant. Many people build a sense of self around their work. He calls protecting that a shared human interest, and frames the human cost as the thing enterprises risk losing.
He is unconvinced AI will grow a self of its own. To him it is a tool, closer to electricity than to a colleague. He borrows an idea from an American philosopher of the 1970s, an argument that echoes Harry Frankfurt.
There are two orders of will.
A model can want something. Only a person can want to want something, to want to become better. Chasing a machine that truly reasons, he adds, would mean finding a way to inject pain, and risk building a Frankenstein no one understands.
Curiosity over credentials
Morar picked up the human thread. Models have memory, she said, but they lack the motivation to be excellent. AI can hand you knowledge. It cannot hand you curiosity, or the grit to push through when something breaks. She looks for those traits in her own team. She also argues that companies must still hire and mentor junior staff.
Skip that, and there are no senior leaders in a few years.
There is a customer angle too. So much support has moved to bots that people now jab at their phones asking for a human. That friction, she suggests, is a clue about what only people offer.
None of this is disinterested. UiPath sells the agents and robots that make the cuts possible. A message that transformation is long, careful, and human-heavy also happens to describe a long, expensive engagement.
Even so, coming from an automation billionaire, the caution is worth hearing. Governments are already counting the jobs AI touches. Dines’s bet is that the roles left standing will be richer, not poorer. The anxiety, his own included, is the price of not yet knowing.
Stephan is the sports journalist for the Maple Grove Report.
