A new IT Pro analysis highlights emerging research showing that artificial intelligence isn’t reducing people’s workloads as promised — it’s intensifying them, leading to longer hours, cognitive strain, and rising burnout among employees. Researchers from the Haas School of Business at UC-Berkeley studied how AI adoption impacted a 200-person tech company over eight months and found that while workers did report productivity gains, they also ended up working faster, on more tasks, and for longer stretches than before. These changes occurred even when using AI wasn’t mandated, underscoring how tools designed to make work easier can instead ramp up expectations.
One major factor is “work intensification.” As AI lowers barriers to task completion — enabling people to take on coding, research, or writing work they once delegated — job scopes expand. Product managers start doing engineering work, researchers take on technical tasks, and engineers find themselves reviewing AI-generated outputs from colleagues, adding to already heavy workloads. The study also found that AI blurred the boundary between work and rest, with employees slipping tasks into lunch breaks, evenings, or meetings because the tools run in the background and make more work seem feasible.
Researchers warn that this intensification isn’t sustainable without intentional practices to counteract it. Cognitive strain, constant multitasking, and workload creep can erode the very productivity benefits AI is supposed to deliver, and may lead to weakened decision-making and higher turnover if left unchecked. Experts suggest building structured breaks, coordination practices, and human connection into AI-augmented workflows to help mitigate burnout and ensure that gains in output don’t come at the cost of worker well-being.
This trend is echoed in other surveys and studies showing that many employees feel overwhelmed rather than relieved by AI. Broader research finds that a large share of workers report AI increasing their workload or adding stress because of higher performance expectations and organizational pressures to do more with less, often without clear guidance or support. These dynamics mean that businesses need not only the right tools but also workplace norms and governance to balance the promise of AI with the realities of human limits.
