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Understanding the Adoption of Artificial Intelligence in Local Government Decision‐Making: The Influence of Institutional Pressures and Managerial Perceptions
Open accessAbstract
Artificial intelligence (AI) systems are increasingly being integrated into public sector decision‐making processes, with public managers relying on them to enhance their capabilities. As AI adoption becomes more widespread, discussions about its advantages and drawbacks intensify, alongside growing external expectations and pressures. However, the extent to which these pressures influence AI adoption remains unclear. Drawing on institutional theory, we conducted a randomised between‐subjects survey among 497 public managers in Belgian municipalities to examine how coercive, normative, and mimetic pressures influence their willingness to adopt AI in decision‐making. Results indicate that all three types of institutional pressures increase public managers' willingness to adopt AI, albeit to varying degrees. Moreover, the effects of coercive and normative pressures diminish when managers have more positive perceptions of AI. By linking institutional theory with individual‐level observations, the study contributes to understanding how institutional contexts shape AI adoption and the broader digital transformation of public administration.
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“This subtheme also has global and multi-sector relevance because the same governance tensions now appear in welfare administration, local government, insurance analytics, and health planning.”
From Toward Trustworthy Artificial Intelligence in Law and Public Administration: Transparency, Accountability and Decision Support (2026) · cites this paper as Rodriguez Müller, Tangi & Lerusse 2025
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“This orientation complements the public-management literature, which highlights how institutional pressures and managerial perceptions shape AI adoption in local government and related service settings”
From Toward Trustworthy Artificial Intelligence in Law and Public Administration: Transparency, Accountability and Decision Support (2026) · cites this paper as Rodriguez Müller, Tangi & Lerusse 2025
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Cited by
Pasupuleti, M. K. (2026) · International Journal of Academic and Industrial Research Innovations(IJAIRI) · doi:10.62311/nesx/rp-1-28-30032026
Metadata
- Authors
- Rodriguez Müller, A. P., Tangi, L., & Lerusse, A.
- Affiliations
- European Commission, Joint Research Centre Seville Spain
- Joint Research Centre (IT)
- Leiden University (NL)
- Venue
- Public Administration
- Publisher
- Wiley
- Published
- 2025-11-19
- ISSN
- 0033-3298 (ISSN-L)
- 1467-9299
- OpenAlex
- W4416383106
- Cited by
- 28
- References
- 9
- Citations by year
- 2026: 27 · 2025: 1
- FWCI
- 103.59
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Public Administration (publishedVersion, cc-by)
- Funders
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (VI.Vidi.201.128)
- Topics
- Social Sciences › Political Science and International Relations › E-Government and Public Services
- Social Sciences › Public Administration › Public Policy and Administration Research
- Social Sciences › Urban Studies › Smart Cities and Technologies
- Keywords
- artificial intelligence adoption, local government, public sector decision-making, institutional pressures, coercive pressure, normative pressure, mimetic pressure, digitalization of public administration, municipal managers
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