Search arXivSearch

arXiv · 2511.11021

AI and Worker Well-Being: Differential Impacts Across Generational Cohorts and Genders

Abstract

This paper investigates the relationship between AI use and worker well-being outcomes such as mental health, job enjoyment, and physical health and safety, using microdata from the OECD AI Surveys across seven countries. The results reveal that AI users are significantly more likely to report improvements across all three outcomes, with effects ranging from 8.9% to 21.3%. However, these benefits vary by generation and gender. Generation Y (1981-1996) shows the strongest gains across all dimensions, while Generation X (1965-1980) reports moderate improvements in mental health and job enjoyment. In contrast, Generation Z (1997-2012) benefits only in job enjoyment. As digital natives already familiar with technology, Gen Z workers may not receive additional gains in mental or physical health from AI, though they still experience increased enjoyment from using it. Baby Boomers (born before 1965) experience limited benefits, as they may not find these tools as engaging or useful. Women report stronger mental health gains, whereas men report greater improvements in physical health. These findings suggest that AI's workplace impact is uneven and shaped by demographic factors, career stage, and the nature of workers' roles.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Voraprapa Nakavachara. 2026-03-02. AI and Worker Well-Being: Differential Impacts Across Generational Cohorts and Genders. https://arxiv.org/abs/2511.11021

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Local Media and the Shaping of Social Norms: Evidence from the Ebola outbreak

Media's influence on norms and behavior is widely recognized. Less is known about the role played by media being local. I examine this in a high-stakes context, the Ebola outbreak in Guinea. I exploit quasi-random variation in access to radio and the timing of a public-health campaign aired on community radio. I find that 12-17% of Ebola cases could have been prevented if places with access to a neighboring community radio station had instead had their own. Impacts are driven by radio being local rather than by ethno-linguistic belonging. Local media facilitates coordination in behaviors observed and sanctioned locally.

econ.GN

Productivity Shocks and Input Misallocation: A Decomposition

This paper asks how much input misallocation productivity uncertainty generates and at which stage of input decisions it arises. I separate revenue productivity by when each component is revealed and trace each into the gap between an input's marginal revenue product and its price. In six European countries, shocks revealed after an input is committed account for 20 percent of capital gap dispersion and 5 percent of labor gap dispersion. An unanticipated one percent rise in productivity raises the capital gap by 0.92 percent and the labor gap by 0.19 percent, because most of the shock passes into the wage.

econ.GN

When Do Type-Specific Wages Buffer Distributional Incidence in TANK?

When do relative wages buffer the unequal incidence of aggregate shocks? I derive a consumption-gap decomposition and a present-value condition for partial offset in a TANK model. An extension separates wage-setting demand elasticity from substitution between labor segments and allows each segment to contain both financial types. With a zero inherited wage gap and a same-sign discounted wedge, substitution above one gives offsetting earnings reallocation; substitution below one gives amplification. The channel disappears when financial types have identical segment exposure. Numerical experiments assess these mechanisms, shock persistence, policy feedback, and aggregate-IRF matching. In the nested perfect-alignment monetary benchmark, the peak consumption gap is about two-fifths smaller under type-specific wages than under the common-wage closure. These are conditional model comparisons, not empirical effect estimates or welfare rankings.

econ.GN