Artificial Intelligence for Public Use

Magnus Lodefalk (), Erik Engberg (), Rolf Lidskog () and Aili Tang ()
Additional contact information
Magnus Lodefalk: Örebro University School of Business, Postal: Örebro University, School of Business, SE - 701 82 ÖREBRO, Sweden, https://www.oru.se/english/employee/magnus_lodefalk
Erik Engberg: Örebro University School of Business, Postal: Örebro University, School of Business, SE - 701 82 ÖREBRO, Sweden, https://www.oru.se/english/employee/erik_engberg
Rolf Lidskog: School of Humanities, Education and Social Sciences, Postal: Örebro University, School of Humanities, Education and Social Sciences, SE - 701 82 ÖREBRO, Sweden, https://www.oru.se/english/employee/rolf_lidskog
Aili Tang: Örebro University School of Business, Postal: Örebro University, School of Business, SE - 701 82 ÖREBRO, Sweden

No 2025:6, Working Papers from Örebro University, School of Business

Abstract: This paper investigates the economic and societal impacts of Artificial Intelligence (AI) in the public sector, focusing on its potential to enhance productivity and mitigate labour shortages. Employing detailed administrative data and novel occupational exposure measures, we simulate future scenarios over a 20-year horizon, using Sweden as an illustrative case. Our findings indicate that advances in AI development and uptake could significantly alleviate projected labour shortages and enhance productivity. However, outcomes vary substantially across sectors and organisational types, driven by differing workforce compositions. Complementing the economic analysis, we identify key challenges that hinder AI’s effective deployment, including technical limitations, organisational barriers, regulatory ambiguity, and ethical risks such as algorithmic bias and lack of transparency. Drawing from an interdisciplinary conceptual framework, we argue that AI’s integration in the public sector must address these socio-technical and institutional factors comprehensively. To unlock AI’s full potential, substantial investments in technological infrastructure, human capital development, regulatory clarity, and robust governance mechanisms are essential. Our study thus contributes both novel economic evidence and an integrated societal perspective, informing strategies for sustainable and equitable public-sector digitalisation.

Keywords: Artificial intelligence; Implementation of technology; Productivity; Labour demand (search for similar items in EconPapers)
JEL-codes: E24 J23 J24 N34 O33 (search for similar items in EconPapers)
Pages: 27 pages
Date: 2025-04-02
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Persistent link: https://EconPapers.repec.org/RePEc:hhs:oruesi:2025_006

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