When generative AI became popular, it gave its users a promise: A promise to automate routine tasks, free our time and just boost our productivity in most settings. Students and employees assumed that their workload would reduce and that they would have more time for challenging tasks which they enjoyed. But that has not been the case. A study this year suggested that although AI saves time, employees are not working less.
Furthermore, as AI’s scope has grown, its boundaries have become more hazy, and workers are willingly putting in more hours. As a result, even after AI might be making us fast we don’t feel any less busy. This ends up complicating our assumption of how productive we would be after using AI. Most quantitative data has linked AI to higher productivity but qualitative research describes these gains may come with hidden work intensification.
AI intensifies work in these three main ways 1. task expansion, where workers take on more responsibilities and roles informally; 2. blurred boundaries, where “quick prompts” during breaks make work more continuous and decrease recovery; and 3. multitasking rhythms, where parallel AI threads increase switching and cognitive load, making workers feel more productive but not less busy.
Moreover, improvement in productivity is often assumed to mean that the workload will be reduced but productivity measures output while workload reflects the intensity of work. When workers stagnate, AI has been demonstrated to be able to save time and revive productivity. Yet, it depends on the organization and employees if they want to convert that saved time into rest or more work.
The decision many take is to do more work and this has risks. In the short-term, there may be burnout and even the quality of decisions may deteriorate over time due to sudden productivity spikes caused by AI. So, while AI can enhance measurable productivity and organizational performance these outputs do not lead to consistent performance.
In general, whether AI increases productivity is not the true point of discussion as productivity does improve. What matters is how the increased productivity is slowly reshaping expectations, pace of work, and performance norms inside organizations. We can only help employees integrate AI into their daily work to protect them from the hidden pressures of doing more. Otherwise, efficiency may quietly translate into work intensification.
Food for thought: If AI makes it easier to do more, where do we draw the line?
References
- Filippucci, F., Gal, P., Jona-Lasinio, C., Leandro, A., OECD, LUISS Lab of European Economics, & LUISS Business School. (2024). The Impact of Artificial Intelligence on Productivity, Distribution and Growth. OECD Artificial Intelligence Papers.
- Kassa, B. Y., & Worku, E. K. (2025). The impact of artificial intelligence on organizational performance: The mediating role of employee productivity. Journal of Open Innovation Technology Market and Complexity, 11(1), 100474. https://doi.org/10.1016/j.joitmc.2025.100474
- Ranganathan, A., & Ye, X. M. (2026, February 9). AI Doesn’t Reduce Work—It Intensifies It. Harvard Business Review. https://hbr.org/2026/02/ai-doesnt-reduce-work-it-intensifies-it