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This article argues that AI does not reduce work and often intensifies it. The authors share findings from an eight-month study at a U.S.-based tech company with about 200 employees (a small sample, so not broadly generalizable, but still a data point to consider). Over the eight-month study, researchers observed employees in person two days a week, tracked internal work activity channels, and conducted 40+ interviews across engineering, product, design, research, and operations. AI use was not mandated, though the company provided enterprise subscriptions. The result: AI users worked faster, took on a broader range of tasks, and extended work into more hours of the day, often by choice. The upside was that work moved faster and felt easier to push forward. However, workload creep can look like productivity at first, and then gradually become the new baseline for speed and responsiveness. Over time, that intensity can contribute to burnout, cognitive strain, and decision fatigue, which can weaken judgment and decision quality. The authors suggest clear team norms for when to use AI, when to stop, and how to preserve recovery (for example, brief “decision pauses” before high-impact choices). For organizations already building strategies to reduce AI risk, such as privacy, bias, IP exposure, security, and compliance, this article offers a useful prompt to expand those efforts to include the human risks of AI-enabled work, including burnout and decision fatigue.
