Few people have done more to automate the office than Daniel Dines. The Romanian-born founder of UiPath built one of Europe’s largest software success stories by selling robots that handle the repetitive parts of white‑collar work. His company, which went public in 2021 at a valuation of nearly $30 billion, has since pushed aggressively into AI agents, most recently by acquiring the compliance‑automation firm WorkFusion. Yet on UiPath’s own 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. But the action he prescribes is not the wholesale replacement of employees. It is a deliberate, cautious transformation that preserves the human elements of work.
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 large language model, he argues, is an average of everything it has read. “An average by definition doesn’t have a taste.”
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, but 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. This insight challenges the notion that simply deploying AI will instantly unlock productivity. Without the nuanced understanding that humans develop through years of experience, automation risks becoming a blunt instrument.
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 about the company’s history and culture.
Dines wants firms to keep two ledgers — one for visible outcomes and one for hidden ones. “Cut blindly, 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, when many firms were still struggling to hire.
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 processes are not ready for the agents,” he argued.
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 when they automate too quickly.
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, but only a person can want to want something — can 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 — empathy, improvisation, and the ability to read between the lines.
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 with clients. But 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.
To understand his perspective, it helps to know his journey. Dines started UiPath in 2005 in Bucharest, originally as a software outsourcing firm. The pivot to robotic process automation came after he noticed his own team spending endless hours on manual data entry. He built a tool to automate that, and soon realised there was a global market for it. The company grew rapidly, riding the wave of digital transformation in finance, healthcare, and manufacturing. By the late 2010s, UiPath was the world’s largest RPA vendor, with customers including NASA, Uber, and the UK’s National Health Service.
His views on AI are shaped by that pragmatic background. He has seen firsthand how badly automation can go when it is deployed without understanding the underlying processes. In a 2022 interview, he said that many RPA projects fail because companies try to automate broken workflows. “You shouldn’t automate chaos,” he warned. The same principle applies to AI agents today.
The broader economic context also matters. Global productivity growth has been sluggish for a decade, and many companies see AI as a silver bullet. Yet the history of technology adoption shows that productivity gains often take years to materialise, as organisations restructure around the new tools. Dines’s message echoes that lesson: do not fire people first and ask questions later.
There is also a moral dimension. The anxiety he admits to is widespread. Surveys show that a majority of workers fear AI will replace them. Dines’s counter‑argument — that automation can elevate human work rather than eliminate it — is a necessary corrective. But it only works if leaders act on it. So far, the evidence is mixed. While some companies have used AI to redeploy workers to higher‑value tasks, others have simply reduced headcount.
The human element, Dines insists, will remain central. “We are not our memory,” he said. “We are our taste, our curiosity, our drive to become better.” Those qualities, he argues, are what create lasting value in any enterprise. And they are precisely the ones that no machine can replicate.