‘There’s Just No Reason to Deal With Young Employees’
Not long after graduating from the University of Texas at Austin in 2021, Donald King landed a job as an associate at the London-based consulting firm PricewaterhouseCoopers. King had always assumed he’d work in business — he’d started his own hedge fund while still an undergrad — but a few years into the job, he decided he was more interested in tech than finance. Early in 2024, after PwC announced a $1 billion investment in artificial intelligence, he switched roles and started working as a data scientist for the company’s nascent Global AI Factory.
King worked with engineers at PwC and OpenAI to customize teams of autonomous AI systems, called agents, for Fortune 500 companies. Normally, multinational companies contract thousands of people to modernize their backend software. Home Depot, for example, might enlist an army of consultants to update inventory or its SAP accounts-payable processes. Recently, though, AI agents have gotten pretty good at that kind of work. Consultants are some of the most prolific AI users, and King thought of himself as a kind of pioneer in a New Age of automation, creating and then deploying agents for PwC’s clients. “P-dubs,” as King calls it, expected a lot from its workers. King put in 80-hour weeks, which kept the 26-year-old from going out on weekends. But he made six figures and lived in a one-bedroom high above Hudson Yards in a building with a pretty nice gym, where he sometimes took camera-off meetings while doing pull-ups. “I was a meat slave,” he says, “and it was kind of a dream job.”
The goal was to help clients “do more with less,” as King’s bosses reminded him, by automating whatever task they threw at his team. Occasionally, when King lingered on the downstream effects of his work, he felt like Dr. Frankenstein looking at his monster. “There was a sense of awe and then it’s kind of shock and fear and almost a disgust,” he says. King knew consultants were called hatchet men for a reason, but it was becoming clear to him that the agents his teams built were capable of wiping out not just individual jobs but entire job categories. “There was a large telecommunications client, and we were doing some crazy stuff for them. Once, we created an agent that was literally, like, a Microsoft Teams agent that was pretending to be a real, human employee,” King says. “That’s when me and my other teammates were like, ‘Whoa, we need to sit and just talk for a little bit. What are we even doing right now?’ Because that’s someone’s job, and if we have 45 of these agents working together, how many human jobs is that going to take? Are we just automating away people’s livelihoods?”