AI increases labour supply rather than reduces it, and watch out for those second order effects on society at large:

Occupations more exposed to generative AI saw a rise in work hours immediately following the release of ChatGPT. Compared to workers less exposed to generative AI (such as tire builders, wellhead pumpers, and surgical assistants) those in high-exposure occupations (including computer systems analysts, credit counsellors, and logisticians) worked roughly 3.15 hours more per week in the post-ChatGPT period. This shift was accompanied by a decline in leisure time, reinforcing the idea that AI complements human work in a way that increases labour supply rather than reducing it. When leisure hours are cut, non-screen-based activities – especially entertainment and socialisation – bear the brunt. Screen-based leisure activities, such as watching television and playing video games, remain relatively stable, suggesting that workers are more likely to sacrifice activities that require active participation rather than passive consumption, signalling a shift towards more isolated and sedentary downtime.

There’s two drivers of this effect:

First, AI raises worker productivity, creating incentives for longer hours. When AI complements human labour rather than replacing it, the process makes each hour of work more valuable. This effect is strongest in jobs where AI helps employees perform tasks more efficiently, such as finance, research, and technical fields. Employers may expect more output; workers, incentivised by productivity-linked pay, may extend their hours. AI-exposed occupations have indeed seen wage increases, suggesting that firms are sharing some productivity gains. However, higher wages have not translated into more leisure time. Instead, workers appear to be substituting additional earnings for longer hours, a pattern consistent with the economic principle that when work becomes more rewarding, people may choose to do more of it.

The second mechanism is AI-driven performance monitoring. Digital surveillance tools have expanded, particularly in remote and hybrid work environments. AI enables real-time tracking of employee effort, leading to longer working hours. Our study examines the COVID-19 period as a natural experiment, when AI-driven monitoring surged due to remote work. Jobs that were more ‘remote-feasible’ at the onset of COVID-19 experienced dramatic improvement in remote work monitoring during the next two years. Occupations with high exposure to AI surveillance technologies – such as customer service representatives, stockers and order fillers, dispatchers, and truck drivers – experienced longer work hours post COVID even after workers returned to the office. This effect was absent among the self-employed, confirming that it is not simply the nature of AI-exposed jobs but the principal-agent dynamics of employment that drive longer work hours.