Even if AI is — or eventually becomes — an incredible automation tool, will it make workers’ lives easier? That’s the big question explored in an ongoing study by researchers from UC Berkeley’s Haas School of Business. And so far, it’s not looking good for the rank and file.
In a piece for Harvard Business Review, the research team’s Aruna Ranganathan and Xinqi Maggie Ye reported that after closely monitoring a tech company with two hundred employees for eight months, they found that AI actually intensified the work they had to do, instead of reducing it.
This “workload creep,” in which the employees took on more tasks than what was sustainable for them to keep doing, can create vicious cycle that leads to fatigue, burnout, and lower quality work.
“You had thought that maybe, oh, because you could be more productive with AI, then you save some time, you can work less,” one of the employees told the researchers. “But then really, you don’t work less. You just work the same amount or even more.”
The tech company in the study provided AI tools to its workers, but didn’t mandate that they use them. Adoption was voluntary. The researchers described how many employees, on their own initiative, eagerly experimented with AI tools at first, “because AI made ‘doing more’ feel possible, accessible, and in many cases intrinsically rewarding.” This resulted in some workers increasingly absorbing tasks they’d normally outsource, the researchers said, or would’ve justified hiring additional help to cover.
One consequence is that once the novelty of adopting AI wears off, the employees realize they’ve added more to their plate than they can handle. But other effects reverberated to the broader workplace. Engineers, for example, found themselves spending more time correcting the AI-generated code passed off by their coworkers. AI also led to more multitasking, with some choosing to manually write code while an AI agent, or even multiple AI agents, cranked out their own version in the background. Rather than being focused on one task, they were continually switching their attention, creating the sense that they were “always juggling,” the researchers said.
Others realized that AI had managed to slowly infiltrate their free time, with employees prompting their AI tools during lunch breaks, meetings, or right before stepping away from their PC. This blurred the line between work and non-work, the researchers wrote, with some employees describing that their downtime no longer felt as rejuvenating.
In sum, the AI tools created a vicious cycle: it “accelerated certain tasks, which raised expectations for speed; higher speed made workers more reliant on AI. Increased reliance widened the scope of what workers attempted, and a wider scope further expanded the quantity and density of work.”
The Berkeley Haas team’s findings add to a growing body of evidence that cuts against the AI industry’s promise that its tools will bring productivity miracles.
The vast majority of companies that adopted AI saw no meaningful growth in revenue, a MIT study found. Other research has shown that AI agents frequently fail at common remote work and office tasks. And at least one study documented how employees used AI to produce shoddy “workslop” that their coworkers had to fix — not unlike the engineers forced to correct their vibe-coding colleagues in the Berkeley Haas study — breeding resentment and bogging down productivity. Employees remain ambivalent on the tech, with a recent survey finding that 40 percent of white collar workers not in management roles thought that AI saved them no time at work.
The Berkeley Haas researchers optimistically suggest that companies should institute stronger guidelines and provide structure on how the tech is used. But it’s clear that AI can easily produce negative knock-on effects that are difficult to manage, and which we’re still unpacking.
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