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Labor Impacts of AI

Friday, November 6, 1:45 to 3:15pm, Property: Boston Marriott Copley Place, Floor: 4th Floor, Room: Yardmouth

Session Submission Type: Panel

Abstract

Recent advancement in Artificial Intelligence (AI) are having profound impacts on labor markets, raising concerns about job loss, resistance to AI adoption at the organizational level, and questions about how to reskill the existing labor force to remain relevant in a dynamic AI environment. To address these pressing issues, this panel brings together three papers that examine AI’s impact on task-based jobs, managerial resistance attitudes to AI adoption, and the disparate effects of AI on the productivity of younger versus older workers. These three studies investigate diverse yet inter-related aspects of the labor market using various methodologies, ranging from theoretical and experimental approaches to empirical analyses based on data from multiple countries.
The first study is theoretical in nature and introduces a multi-level framework for understanding how responsibility, decision-making, and skill expectations evolve across career pathways in AI-integrated organizations. It argues that career development is no longer defined solely by traditional role-based progression, but by an expanding set of capabilities that reflect increasing interaction with AI systems. The second study relies on a survey experiment conducted with 2,000 managers across the United States and the United Kingdom to examine the causal impact of providing information on (a) AI's productivity benefits and (b) its labor-displacing potential, compared with a neutral group. Providing information about labor displacement leads managers to substantially reduce their AI adoption, advocacy and staffing intentions. In contrast, information on AI productivity benefits has no meaningful average effect, through it does increase AI advocacy among managers with low AI familiarity. These findings underscore the critical role of AI-related positive and negative information on middle managers' adoption and employment decisions. The third study examines the impact of generative AI on older workers’ labor market outcomes compared to younger workers, and how occupation-specific tasks and primary skills condition these effects. The data are drawn from the Survey of Income and Program Participation (SIPP) from 2014 - 2024 and merged with O*NET occupation identifiers to construct measures of occupation-specific tasks and average skill profiles. The launch of GPT in November 2022 is used as an exogenous shock to identify causal effects. Using a sample of working-age individuals (ages 30–80) who are currently employed, the study first implements a difference-in-differences (DiD) design to compare outcomes for younger and older workers around the AI shock, controlling for time-invariant individual heterogeneity as well as occupation- and year-specific macroeconomic conditions. Results indiciate that the AI shock worsens hourly wages and annual earnings of older workers relative to younger workers. Furthermore, using a restricted sample of relatively older workers (ages 50–80), among older workers, non-routine physical adaptability and non-routine interpersonal adaptability provide protective effects against the AI shock, mitigating declines in earned income. Overall, the panel brings together diverse, timely and rigorous studies covering multiple dimensions of AI’s impact on labor markets.

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