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Gen-AI: Artificial Intelligence and the Future of Work

Cazzaniga, Jaumotte, Li, Melina, Panton, Pizzinelli, Rockall, Tavares

2024IMF Staff Discussion Notes112 citations

Exposure / measurementTheoretical model

LLM / Generative AIAI (General)Augmentation vs. substitutionGeneral automationGenderDeveloping economiesSenior / older workersOccupational mobilityTraining / upskilling

DOI: 10.5089/9798400262548.006

Abstract

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

Summary

Cazzaniga et al. construct a global AI exposure and complementarity framework using O*NET task data and ISCO-08 occupations across 125 countries, combine this with a calibrated task-based model and empirical labor market transition analysis, to assess AI's differential impacts on employment, productivity, and inequality across advanced economies, emerging markets, and low-income countries

Main Finding

Almost 40% of global employment is exposed to AI (60% in advanced economies, 40% in emerging markets, 26% in low-income countries), with AI potentially negatively affecting half of exposed jobs while boosting productivity in the other half; high-income workers face greater exposure but also higher complementarity potential, suggesting AI may exacerbate inequality with labor income gains positively correlated with income levels

Primary Datasets

O*NET

Other

O*NET; ILO ILOSTAT

Secondary Datasets

International Telecommunication Union (digital infrastructure data); World Bank (human capital index); World Economic Forum; Fraser Institute; United Nations; Universal Postal Union

Key Methods: Global AI exposure measurement using AIOE scores and novel complementarity index; task-based structural model with heterogeneous agents calibrated to UK; wage regression analysis of occupational transitions in Brazil and UK; employment share decomposition by demographics and income deciles
Sample Period: Cross-sectional
Geographic Coverage: International
Sample Size: 125 countries covering global workforce; detailed microdata analysis for 6 countries (UK, USA, Brazil, Colombia, South Africa, India) representing different income levels
Level of Analysis: Occupation, Country, Individual
Occupation Classification: ISCO-08
Industry Classification: ISIC Rev 4

Notes

IMF Staff Discussion Note 2024/001; Non-US paper; included for international comparison [Claude classification]: IMF Staff Discussion Note 2024/001. Constructs novel AI Preparedness Index (AIPI) across four themes: digital infrastructure, innovation and economic integration, human capital and labor market policies, and regulation and ethics. Task-based structural model builds on Moll, Rachel and Restrepo (2022) and Drozd et al. (2023). Complementarity index validated through principal component analysis and leave-one-out robustness checks. Special focus on Arab League countries throughout the analysis. [Claude classification]: IMF Staff Discussion Note 2024/001. Constructs novel AI Preparedness Index (AIPI) across four themes: digital infrastructure, innovation and economic integration, human capital and labor market policies, and regulation and ethics. Task-based structural model builds on Moll, Rachel and Restrepo (2022) and Drozd et al. (2023). Complementarity index validated through principal component analysis and leave-one-out robustness checks. Special focus on Arab League countries throughout the analysis. [Claude classification]: IMF Staff Discussion Note 2024/001. Constructs novel AI Preparedness Index (AIPI) across four themes: digital infrastructure, innovation and economic integration, human capital and labor market policies, and regulation and ethics. Task-based structural model builds on Moll, Rachel and Restrepo (2022) and Drozd et al. (2023). Complementarity index validated through principal component analysis and leave-one-out robustness checks. Special focus on Arab League countries throughout the analysis. [Claude classification]: IMF Staff Discussion Note 2024/001. Constructs novel AI Preparedness Index (AIPI) across four themes: digital infrastructure, innovation and economic integration, human capital and labor market policies, and regulation and ethics. Task-based structural model builds on Moll, Rachel and Restrepo (2022) and Drozd et al. (2023). Complementarity index validated through principal component analysis and leave-one-out robustness checks. Special focus on Arab League countries throughout the analysis. [Claude classification]: IMF Staff Discussion Note 2024/001. Constructs novel AI Preparedness Index (AIPI) across four themes: digital infrastructure, innovation and economic integration, human capital and labor market policies, and regulation and ethics. Task-based structural model builds on Moll, Rachel and Restrepo (2022) and Drozd et al. (2023). Complementarity index validated through principal component analysis and leave-one-out robustness checks. Special focus on Arab League countries throughout the analysis. [Claude classification]: IMF Staff Discussion Note 2024/001. Constructs novel AI Preparedness Index (AIPI) across four themes: digital infrastructure, innovation and economic integration, human capital and labor market policies, and regulation and ethics. Task-based structural model builds on Moll, Rachel and Restrepo (2022) and Drozd et al. (2023). Complementarity index validated through principal component analysis and leave-one-out robustness checks. Special focus on Arab League countries throughout the analysis. [Claude classification]: IMF Staff Discussion Note 2024/001. Constructs novel AI Preparedness Index (AIPI) across four themes: digital infrastructure, innovation and economic integration, human capital and labor market policies, and regulation and ethics. Task-based structural model builds on Moll, Rachel and Restrepo (2022) and Drozd et al. (2023). Complementarity index validated through principal component analysis and leave-one-out robustness checks. Special focus on Arab League countries throughout the analysis. [Claude classification]: IMF Staff Discussion Note 2024/001. Constructs novel AI Preparedness Index (AIPI) across four themes: digital infrastructure, innovation and economic integration, human capital and labor market policies, and regulation and ethics. Task-based structural model builds on Moll, Rachel and Restrepo (2022) and Drozd et al. (2023). Complementarity index validated through principal component analysis and leave-one-out robustness checks. Special focus on Arab League countries throughout the analysis. [Claude classification]: IMF Staff Discussion Note 2024/001. Constructs novel AI Preparedness Index (AIPI) across four themes: digital infrastructure, innovation and economic integration, human capital and labor market policies, and regulation and ethics. Task-based structural model builds on Moll, Rachel and Restrepo (2022) and Drozd et al. (2023). Complementarity index validated through principal component analysis and leave-one-out robustness checks. Special focus on Arab League countries throughout the analysis. [Claude classification]: IMF Staff Discussion Note 2024/001. Constructs novel AI Preparedness Index (AIPI) across four themes: digital infrastructure, innovation and economic integration, human capital and labor market policies, and regulation and ethics. Task-based structural model builds on Moll, Rachel and Restrepo (2022) and Drozd et al. (2023). Complementarity index validated through principal component analysis and leave-one-out robustness checks. Special focus on Arab League countries throughout the analysis. [Claude classification]: IMF Staff Discussion Note 2024/001. Constructs novel AI Preparedness Index (AIPI) across four themes: digital infrastructure, innovation and economic integration, human capital and labor market policies, and regulation and ethics. Task-based structural model builds on Moll, Rachel and Restrepo (2022) and Drozd et al. (2023). Complementarity index validated through principal component analysis and leave-one-out robustness checks. Special focus on Arab League countries throughout the analysis. [Claude classification]: IMF Staff Discussion Note 2024/001. Constructs novel AI Preparedness Index (AIPI) across four themes: digital infrastructure, innovation and economic integration, human capital and labor market policies, and regulation and ethics. Task-based structural model builds on Moll, Rachel and Restrepo (2022) and Drozd et al. (2023). Complementarity index validated through principal component analysis and leave-one-out robustness checks. Special focus on Arab League countries throughout the analysis. [Claude classification]: IMF Staff Discussion Note 2024/001. Constructs novel AI Preparedness Index (AIPI) across four themes: digital infrastructure, innovation and economic integration, human capital and labor market policies, and regulation and ethics. Task-based structural model builds on Moll, Rachel and Restrepo (2022) and Drozd et al. (2023). Complementarity index validated through principal component analysis and leave-one-out robustness checks. Special focus on Arab League countries throughout the analysis. [Claude classification]: IMF Staff Discussion Note 2024/001. Constructs novel AI Preparedness Index (AIPI) across four themes: digital infrastructure, innovation and economic integration, human capital and labor market policies, and regulation and ethics. Task-based structural model builds on Moll, Rachel and Restrepo (2022) and Drozd et al. (2023). Complementarity index validated through principal component analysis and leave-one-out robustness checks. Special focus on Arab League countries throughout the analysis. [Claude classification]: IMF Staff Discussion Note 2024/001. Constructs novel AI Preparedness Index (AIPI) across four themes: digital infrastructure, innovation and economic integration, human capital and labor market policies, and regulation and ethics. Task-based structural model builds on Moll, Rachel and Restrepo (2022) and Drozd et al. (2023). Complementarity index validated through principal component analysis and leave-one-out robustness checks. Special focus on Arab League countries throughout the analysis. [Claude classification]: IMF Staff Discussion Note 2024/001. Constructs novel AI Preparedness Index (AIPI) across four themes: digital infrastructure, innovation and economic integration, human capital and labor market policies, and regulation and ethics. Task-based structural model builds on Moll, Rachel and Restrepo (2022) and Drozd et al. (2023). Complementarity index validated through principal component analysis and leave-one-out robustness checks. Special focus on Arab League countries throughout the analysis. [Claude classification]: IMF Staff Discussion Note 2024/001. Constructs novel AI Preparedness Index (AIPI) across four themes: digital infrastructure, innovation and economic integration, human capital and labor market policies, and regulation and ethics. Task-based structural model builds on Moll, Rachel and Restrepo (2022) and Drozd et al. (2023). Complementarity index validated through principal component analysis and leave-one-out robustness checks. Special focus on Arab League countries throughout the analysis. [Claude classification]: IMF Staff Discussion Note 2024/001. Constructs novel AI Preparedness Index (AIPI) across four themes: digital infrastructure, innovation and economic integration, human capital and labor market policies, and regulation and ethics. Task-based structural model builds on Moll, Rachel and Restrepo (2022) and Drozd et al. (2023). Complementarity index validated through principal component analysis and leave-one-out robustness checks. Special focus on Arab League countries throughout the analysis. [Claude classification]: IMF Staff Discussion Note 2024/001. Constructs novel AI Preparedness Index (AIPI) across four themes: digital infrastructure, innovation and economic integration, human capital and labor market policies, and regulation and ethics. Task-based structural model builds on Moll, Rachel and Restrepo (2022) and Drozd et al. (2023). Complementarity index validated through principal component analysis and leave-one-out robustness checks. Special focus on Arab League countries throughout the analysis. [Claude classification]: IMF Staff Discussion Note 2024/001. Constructs novel AI Preparedness Index (AIPI) across four themes: digital infrastructure, innovation and economic integration, human capital and labor market policies, and regulation and ethics. Task-based structural model builds on Moll, Rachel and Restrepo (2022) and Drozd et al. (2023). Complementarity index validated through principal component analysis and leave-one-out robustness checks. Special focus on Arab League countries throughout the analysis. [Claude classification]: IMF Staff Discussion Note 2024/001. Constructs novel AI Preparedness Index (AIPI) across four themes: digital infrastructure, innovation and economic integration, human capital and labor market policies, and regulation and ethics. Task-based structural model builds on Moll, Rachel and Restrepo (2022) and Drozd et al. (2023). Complementarity index validated through principal component analysis and leave-one-out robustness checks. Special focus on Arab League countries throughout the analysis. [Claude classification]: IMF Staff Discussion Note 2024/001. Constructs novel AI Preparedness Index (AIPI) across four themes: digital infrastructure, innovation and economic integration, human capital and labor market policies, and regulation and ethics. Task-based structural model builds on Moll, Rachel and Restrepo (2022) and Drozd et al. (2023). Complementarity index validated through principal component analysis and leave-one-out robustness checks. Special focus on Arab League countries throughout the analysis.