Artificial intelligence in public sector accounting information systems: adoption or resistance among accountants and auditors?

Natalia Alonso-Morales and Alejandro Saez-Martín

Journal of Public Budgeting, Accounting & Financial Management, 2026, vol. 38, issue 6, 61-80

Abstract: PurposeArtificial intelligence (AI) in accounting information systems (AIS) may reshape how public sector accounting information is prepared and audited. Its impact, however, depends on whether accounting and audit professionals are willing to adopt it. This study analyses and compares AI acceptance among public sector accountants and auditors, focussing on the factors that shape differences in intention to use.Design/methodology/approachUsing survey data from 386 public sector professionals, the study combines contrast tests, PLS-SEM with multigroup analysis and cluster analysis to examine both common and divergent adoption mechanisms.FindingsThe results show that public professionals prioritise service quality, while professional experience is associated with resistance to technological change. Nevertheless, clear divergent adoption patterns emerge. Public sector accountants display more favourable attitudes toward AI, driven by perceived usefulness and job relevance, whereas public auditors exhibit greater caution, shaped primarily by social influence and the need for institutional legitimacy. Cluster analysis further reveals two distinct adoption profiles, revealing latent heterogeneity within the public sector.Originality/valueThis study provides a comparative analysis of AI adoption across two key roles in the public sector accounting cycle, integrating accountants and auditors within a single framework. By combining multiple methods, it offers novel evidence on professional heterogeneity and differentiated adoption mechanisms in highly institutionalised public sector contexts.

Keywords: Artificial intelligence; Accounting information systems; Public sector heterogeneity; Supreme audit institutions; Institutional logics; Technology adoption (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:eme:jpbafm:jpbafm-12-2025-0382

DOI: 10.1108/JPBAFM-12-2025-0382

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