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Using AI in Performance Management: A Global Analysis of Local Government Practices

Author

Listed:
  • Godfrey Maake

    (Department of Business and Information Management Services, Tshwane University of Technology, Pretoria 0183, South Africa)

  • Cecile M. Schultz

    (Department of People Management and Development, Tshwane University of Technology, Pretoria 0183, South Africa)

Abstract

The integration of artificial intelligence plays a critical role in human resource management in local governments by ensuring smooth, essential HR operations, including recruitment, performance management, and workforce planning. The current study is a systematic review focused on determining the performance management factors that should be considered when using artificial intelligence in the local government sector. Although artificial intelligence (AI) is becoming increasingly integrated into the governance and administrative systems of local governments around the world, this study raises critical questions about how performance should be managed, measured, and improved. Articles were screened based on their title, abstract, and keywords, following which the inclusion and exclusion criteria were applied. A comprehensive search was conducted in the EBSCOhost, Emerald Insight, Taylor & Francis, Scopus, and SpringerLink databases. These databases were chosen because they are prominent sources that publish various materials related to the social sciences. This scoping review followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines and included 22 peer-reviewed empirical studies published between 2015 and 2025. Analysis of the identified 22 peer-reviewed articles revealed that the successful application of AI in local government performance management depends on six critical performance management factors: data quality and accessibility; strategic alignment with performance goals; evaluation criteria and metrics; ethical and legal oversight; institutional capacity and leadership; and change management and stakeholder engagement. These factors are interdependent and represent both technical and organisational dimensions of public administration. This study highlights that AI entails more than innovation; it reshapes the foundations of performance governance, requiring new capabilities, values, and institutional practices.

Suggested Citation

  • Godfrey Maake & Cecile M. Schultz, 2025. "Using AI in Performance Management: A Global Analysis of Local Government Practices," Administrative Sciences, MDPI, vol. 15(10), pages 1-21, October.
    • Handle: RePEc:gam:jadmsc:v:15:y:2025:i:10:p:392-:d:1767115
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    References listed on IDEAS

    as
    1. Karina Kenk & Toomas Haldma, 2019. "The use of performance information in local government mergers," Journal of Public Budgeting, Accounting & Financial Management, Emerald Group Publishing Limited, vol. 31(3), pages 451-471, September.
    2. Pei‐Chao Lin & Chich‐Hsiu Hung, 2015. "Mental health trajectories and related factors among perinatal women," Journal of Clinical Nursing, John Wiley & Sons, vol. 24(11-12), pages 1585-1593, June.
    3. Hussein Gibreel Musa & Indah Fatmawati & Nuryakin Nuryakin & M. Suyanto, 2024. "Marketing research trends using technology acceptance model (TAM): a comprehensive review of researches (2002–2022)," Cogent Business & Management, Taylor & Francis Journals, vol. 11(1), pages 2329375-232, December.
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