Working Paper No. 378: Returns to AI skills

PublicationWorking paper
Artificiell intelligens

Abstract

This paper assesses whether workers who develop and apply artificial intelligence experience an earnings premium. I link skill requirements specified in job vacancies to the individuals ultimately hired to fill those positions using a combination of Swedish job vacancy and matched employer-employee register data. By identifying positions that explicitly necessitate AI skills, this paper seeks to determine if an earnings premium is associated with these skills while controlling for other individual attributes. Findings suggest a significant earnings premium for individuals hired to positions requiring AI skills. Discerning between AI developers and AI users, the results indicate that the former group experiences a stronger earnings premium. The premium is partly driven by workers being hired into high-wage industries. However, transitioning into roles requiring AI skills does not result in additional earnings increases, indicating that firms do not engage in wage competition for these workers.

Hellsten, M. (2024). Returns to AI skills. Ratio Working Paper No. 378.


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Abstract

Taking three recent business books on artificial intelligence (AI) as a starting point, we explore the automation and augmentation concepts in the management domain. Whereas automation implies that machines take over a human task, augmentation means that humans collaborate closely with machines to perform a task. Taking a normative stance, the three books advise organizations to prioritize augmentation, which they relate to superior performance. Using a more comprehensive paradox perspective, we argue that, in the management domain, augmentation cannot be neatly separated from automation. These dual AI applications are interdependent across time and space, creating a paradoxical tension. Over-emphasizing either augmentation or automation fuels reinforcing cycles with negative organizational and societal outcomes. However, if organizations adopt a broader perspective comprising both automation and augmentation, they could deal with the tension and achieve complementarities that benefit business and society. Drawing on our insights, we conclude that management scholars need to be involved in research on the use of AI in organizations. We also argue that a substantial change is required in how AI research is currently conducted in order to develop meaningful theory and to provide practice with sound advice.

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