AI tools promise to lighten workloads, but new research reveals they often have the opposite effect. Workers using generative AI are taking on more tasks, working longer hours, and experiencing increased cognitive strain.
Aruna Ranganathan and Xingqi Maggie Ye report for Harvard Business Review on their eight-month study at a U.S. technology company with 200 employees. The researchers observed how voluntary AI adoption changed work patterns across departments.
The study identifies three key ways AI intensifies work. First, task expansion occurs as employees step into roles previously handled by others. Product managers write code, and researchers tackle engineering tasks because AI fills knowledge gaps. Second, boundaries between work and personal time blur as prompting AI feels effortless. Workers send “quick” prompts during lunch or before leaving their desk. Third, multitasking increases as employees manage several AI-assisted threads simultaneously, creating constant cognitive switching.
One engineer summarizes the paradox: “You had thought that maybe, oh, because you could be more productive with AI, then you save some time, you can work less. But then really, you don’t work less. You just work the same amount or even more.”
The researchers warn that initial productivity gains can mask unsustainable workload creep, leading to burnout and reduced decision quality. They recommend developing an “AI practice” with intentional pauses, sequenced workflows, and protected time for human connection. Without deliberate structure, AI makes it easier to do more but harder to stop.
