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 has been accepted by D. J. Wu for the 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 .
Prasanna Tambe (2025) studied this question.