Short Takes #23: The Fish Is In The Water

Key Takeaways

• AI adoption increased work pace and task scope
• Employees worked longer hours without formal AI mandates
• AI‑driven workload creep caused cognitive fatigue and burnout
• Expectations for speed rose as AI outputs became visible
• Management must address AI‑induced intensity to retain talent

Summary

The article highlights a Harvard Business Review study of a 200‑person tech firm that found generative AI tools did not reduce workload but intensified it. Employees voluntarily adopted AI, working faster, taking on broader tasks, and extending their workday, leading to higher expectations for speed. The resulting workload creep caused cognitive fatigue, burnout, and lower quality output despite initial productivity gains. The piece also frames this trend within a broader critique of modern work’s cultural and ideological foundations, arguing that tools both shape and are shaped by these systems.

Pulse Analysis

The hype around generative AI promises that machines will shoulder routine tasks, freeing employees to focus on higher‑value work. Early adopters have rolled out enterprise subscriptions without mandating usage, betting on voluntary uptake to boost efficiency. Yet the cultural narrative that “tools work for you” masks a deeper shift: AI makes more work feel possible, instantly accessible, and often rewarding, prompting workers to stretch beyond previous limits. This dynamic reshapes expectations around speed and output before any formal policy changes.

A Harvard Business Review study of a 200‑person U.S. tech firm tracked eight months of AI‑augmented workflows. Researchers observed that employees voluntarily adopted chat‑based generators, which accelerated task completion but also expanded the scope of responsibilities—product managers began writing code, engineers reviewed AI‑produced drafts, and everyone juggled more open tickets. The faster pace created a self‑reinforcing loop: higher speed raised expectations, prompting deeper reliance on AI, which in turn flooded schedules with additional work. Participants reported feeling busier, experiencing cognitive overload, and seeing early signs of burnout despite nominal productivity gains.

For leaders, the findings signal that AI cannot be treated as a simple efficiency plug‑in. Without deliberate workload controls, the technology amplifies existing cultural pressures that equate constant output with worth, fueling turnover and eroding decision quality. Companies should pair AI rollout with caps on task volume, mandatory downtime, and transparent metrics that separate speed from sustainable performance. More broadly, the debate echoes calls to confront the ideological underpinnings of modern work—recognizing that tools both reflect and reshape the values we embed in the workplace.