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Applying AI to Rebuild Middle Class Jobs

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  • David Autor

Abstract

While the utopian vision of the current Information Age was that computerization would flatten economic hierarchies by democratizing information, the opposite has occurred. Information, it turns out, is merely an input into a more consequential economic function, decision-making, which is the province of elite experts. The unique opportunity that AI offers to the labor market is to extend the relevance, reach, and value of human expertise. Because of AI’s capacity to weave information and rules with acquired experience to support decision-making, it can be applied to enable a larger set of workers possessing complementary knowledge to perform some of the higher-stakes decision-making tasks that are currently arrogated to elite experts, e.g., medical care to doctors, document production to lawyers, software coding to computer engineers, and undergraduate education to professors. My thesis is not a forecast but an argument about what is possible: AI, if used well, can assist with restoring the middle-skill, middle-class heart of the US labor market that has been hollowed out by automation and globalization.

Suggested Citation

  • David Autor, 2024. "Applying AI to Rebuild Middle Class Jobs," NBER Working Papers 32140, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:32140
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    Cited by:

    1. Igor Livshits & Ahmad Omar, 2024. "Missed Rent: Path to Eviction or Loan from Landlord?," Economic Insights, Federal Reserve Bank of Philadelphia, vol. 9(4), pages 10-18, December.
    2. Shigeru Fujita & Madison Perry, 2024. "Nonworking Parents or Hungry Children," Economic Insights, Federal Reserve Bank of Philadelphia, vol. 9(4), pages 2-9, December.
    3. Bloom, David E. & Prettner, Klaus & Saadaoui, Jamel & Veruete, Mario, 2025. "Artificial intelligence and the skill premium," Finance Research Letters, Elsevier, vol. 81(C).
    4. Alexander Bick & Adam Blandin & David Deming, 2023. "The Rapid Adoption of Generative AI," On the Economy 98843, Federal Reserve Bank of St. Louis.
    5. Christoph Riedl & Eric Bogert, 2024. "Effects of AI Feedback on Learning, the Skill Gap, and Intellectual Diversity," Papers 2409.18660, arXiv.org.
    6. Flavio Calvino & Chiara Criscuolo & Luca Fontanelli & Lionel Nesta & Elena Verdolini, 2024. "The role of human capital for AI adoption: Evidence from French firms," CEP Discussion Papers dp2055, Centre for Economic Performance, LSE.
    7. Enrico Maria Fenoaltea & Dario Mazzilli & Aurelio Patelli & Angelica Sbardella & Andrea Tacchella & Andrea Zaccaria & Marco Trombetti & Luciano Pietronero, 2024. "Follow the money: a startup-based measure of AI exposure across occupations, industries and regions," Papers 2412.04924, arXiv.org, revised Dec 2024.
    8. Aaron Chatterji & Daniel Rock & Eduard Talamàs, 2025. "Transformative AI and Firms," NBER Chapters, in: The Economics of Transformative AI, National Bureau of Economic Research, Inc.
    9. Findeisen, Sebastian & Dauth, Wolfgang & Schlenker, Oliver, 2024. "Organized Labor Versus Robots? Evidence from Micro Data," CEPR Discussion Papers 19192, C.E.P.R. Discussion Papers.
    10. Minniti, Antonio & Prettner, Klaus & Venturini, Francesco, 2024. "Unslicing the pie: AI innovation and the labor share in European regions," Department of Economics Working Paper Series 369, WU Vienna University of Economics and Business.
    11. Minniti, Antonio & Prettner, Klaus & Venturini, Francesco, 2025. "AI innovation and the labor share in European regions," European Economic Review, Elsevier, vol. 177(C).
    12. Teutloff, Ole & Einsiedler, Johanna & Kässi, Otto & Braesemann, Fabian & Mishkin, Pamela & del Rio-Chanona, R. Maria, 2025. "Winners and losers of generative AI: Early Evidence of Shifts in Freelancer Demand," Journal of Economic Behavior & Organization, Elsevier, vol. 235(C).
    13. Ben Etheridge & Aitor Irastorza-Fadrique & Michael J. Böhm, 2024. "The impact of labour demand shocks when occupational labour supplies are heterogeneous," IFS Working Papers W24/28, Institute for Fiscal Studies.
    14. Teutloff Ole & Braesemann Fabian, 2025. "Resilienz statt Reskilling: Wie KI den Arbeitsmarkt verändert und wie wir darauf reagieren müssen," Wirtschaftsdienst, Sciendo, vol. 105(10), pages 715-719.
    15. Bonney, Kathryn & Breaux, Cory & Buffington, Catherine & Dinlersoz, Emin & Foster, Lucia & Goldschlag, Nathan & Haltiwanger, John & Kroff, Zachary & Savage, Keith, 2024. "The impact of AI on the workforce: Tasks versus jobs?," Economics Letters, Elsevier, vol. 244(C).
    16. Fasheng Xu & Jing Hou & Wei Chen & Karen Xie, 2025. "Generative AI and Organizational Structure in the Knowledge Economy," Papers 2506.00532, arXiv.org.
    17. Benjamin G. Hyman & Benjamin Lahey & Karen Ni & Laura Pilossoph, 2025. "How Retrainable are AI-Exposed Workers?," NBER Working Papers 34174, National Bureau of Economic Research, Inc.
    18. Yan Liu, 2024. "Generative AI : Catalyst for Growth or Harbinger of Premature De-Professionalization ?," Policy Research Working Paper Series 10915, The World Bank.
    19. Jacob Schaal, 2025. "A theory-based AI automation exposure index: Applying Moravec's Paradox to the US labor market," Papers 2510.13369, arXiv.org.
    20. Li, Chao & Lao, Wenyu & Li, Xiang & Zhang, Yuhan, 2024. "Automated workforce, financial precarities and family consumption: The importance of demand-side policies under the background of automation applications," Economic Analysis and Policy, Elsevier, vol. 84(C), pages 1287-1308.
    21. Kali Aloisi, 2024. "Regional Spotlight: Technology vs. the Middle Class," Economic Insights, Federal Reserve Bank of Philadelphia, vol. 9(4), pages 19-25, December.
    22. Manuel Hoffmann & Sam Boysel & Frank Nagle & Sida Peng & Kevin Xu, 2024. "Generative AI and the Nature of Work," CESifo Working Paper Series 11479, CESifo.
    23. Lee, Joonbae, 2025. "IT investment and labor displacement: Evidence from Korea," Telecommunications Policy, Elsevier, vol. 49(7).
    24. Bouchra Al MAWLA & George M. El KAZZI & Hiba S. OTHMAN, 2025. "Artificial intelligence as a disruptive force in economics: transformations, challenges, and future prospects," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(2(643), S), pages 87-106, Summer.
    25. Chen, Qin & Ge, Jinfeng & Xie, Huaqing & Xu, Xingcheng & Yang, Yanqing, 2025. "Large language models at work in China’s labor market," China Economic Review, Elsevier, vol. 92(C).

    More about this item

    JEL classification:

    • J01 - Labor and Demographic Economics - - General - - - Labor Economics: General
    • J2 - Labor and Demographic Economics - - Demand and Supply of Labor
    • N30 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy - - - General, International, or Comparative
    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology

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