Reskilling the Workforce for AI: Domain Expertise and Algorithmic Literacy

This study provides evidence that AI and algorithms act as complements to domain expertise, creating the greatest value when algorithmic literacy is broadly diffused among workers. Unlike earlier business technologies that concentrated expertise in IT specialists, AI and algorithms are most effective when domain experts themselves can interpret and apply them. Using two workforce datasets, I show that demand for algorithmic skills is rising among domain experts, frontier firms diffuse these skills broadly, and markets reward firms’ AI and algorithmic investments more when such capabilities are dispersed. The spread of no-code and natural language tools accelerates this shift by lowering barriers to use and allowing domain experts to integrate algorithms into their decision-making processes. These patterns underscore the importance of workforce training and organizational design in realizing productivity gains from AI adoption. This paper was accepted by D. J. Wu, Special Issue on the Human-Algorithm Connection. Funding: The Wharton Mack Institute provided financial assistance. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2022.03968 .

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Publication Details

Journal
Management Science
Published
2025-09-30
DOI
https://doi.org/10.1287/mnsc.2022.03968
Citations
4
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
9.46
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article

Reskilling the Workforce for AI: Domain Expertise and Algorithmic Literacy

Prasanna Tambe
4 citations
Management Science
Ethics and Social Impacts of AI
9.46
article

Reskilling the Workforce for AI: Domain Expertise and Algorithmic Literacy

Prasanna Tambe
article en
4 citations

Abstract

This study provides evidence that AI and algorithms act as complements to domain expertise, creating the greatest value when algorithmic literacy is broadly diffused among workers. Unlike earlier business technologies that concentrated expertise in IT specialists, AI and algorithms are most effective when domain experts themselves can interpret and apply them. Using two workforce datasets, I show that demand for algorithmic skills is rising among domain experts, frontier firms diffuse these skills broadly, and markets reward firms’ AI and algorithmic investments more when such capabilities are dispersed. The spread of no-code and natural language tools accelerates this shift by lowering barriers to use and allowing domain experts to integrate algorithms into their decision-making processes. These patterns underscore the importance of workforce training and organizational design in realizing productivity gains from AI adoption. This paper was accepted by D. J. Wu, Special Issue on the Human-Algorithm Connection. Funding: The Wharton Mack Institute provided financial assistance. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2022.03968 .

Management ScienceVol. 72(1)
University of Pennsylvania (US)
Openalex Percentile: Top 2%
Ethics and Social Impacts of AI
9.46
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Reskilling the Workforce for AI: Domain Expertise and Algorithmic Literacy — Prasanna Tambe · Management Science (2025) | TGRS Research Map | TGRS