Artificial Intelligence (AI) has the potential to reshape the global economy, especially in the realm of labor markets. Advanced economies will experience the benefits and pitfalls of AI sooner than emerging market and developing economies, largely due to their employment structure focused on cognitive-intensive roles.
There are some consistent patterns concerning AI exposure, with women and college-educated individuals more exposed but also better poised to reap AI benefits, and older workers potentially less able to adapt to the new technology.
Labor income inequality may increase if the complementarity between AI and high-income workers is strong, while capital returns will increase wealth inequality. However, if productivity gains are sufficiently large, income levels could surge for most workers. In this evolving landscape, advanced economies and more developed emerging markets need to focus on upgrading regulatory frameworks and supporting labor reallocation, while safeguarding those adversely affected. Emerging market and developing economies should prioritize developing digital infrastructure and digital skills
Contents
Executive Summary
I. Introduction
II. AI Exposure and Complementarity
III. Worker Reallocation in the AI-Induced Transformation
IV. AI, Productivity, and Inequality
V. AI Preparedness
VI. Conclusions and Policy Considerations
Annex I. Data
Annex 2. Additional Information on AI Occupational Exposure and Potential Complementarity
Annex 3. Methodology for the Worker Transition Analysis
Annex 4. Model Details
Annex 5. AI Preparedness Index
References
Boxes
1. AI Occupational Exposure and Potential Complementarity1
2. Artificial-Intelligence-led Innovation and the Potential for Greater Inclusion1
Figures
1. Employment Shares by AI Exposure and Complementarity: Country Groups and Select
2. Employment Share by Exposure and Complementarity (Selected Countries)
3. Share of Employment in High-Exposure Occupations by Demographic Groups
4. Share of Employment in High-Exposure Occupations by Income Deciles
5. Occupational Transitions for College-Educated High-Exposure Workers for BRA and GBR
6. Life Cycle Profiles of Employment Shares by Education Level for Brazil and the United
7. 1-Year Re-Employment Probability of Separated Workers
8. Estimated Wage Premia from Occupation Changes
9. Exposure to AI and to Automation and Income in the UK
10. Change in Total Income by Income Percentile
11. Impact on Aggregates (Percentage
12. AI Preparedness Index and
13. ICT Employment Share and Individual Components of the AI Preparedness Index
Cazzaniga and others. 2024. “Gen-AI: Artificial Intelligence and the Future of Work.” IMF Staff Discussion Note SDN2024/001, International Monetary Fund, Washington, DC.