Purpose Artificial intelligence (AI) can transform public sector auditing by automating tasks, improving risk detection and enhancing data analysis efficiency. Beyond efficiency gains, AI has the potential to strengthen public accountability by supporting more timely and evidence-based external oversight. Despite increasing modernisation pressures and the favourable framework of the AI Act (Regulation EU 2024/1689), the adoption by European public audit institutions remains limited. This reveals a literature gap: the factors influencing AI adoption by external public auditors in Europe are not yet clearly understood, so this study aims to identify the determinants of the intention to adopt AI. Design/methodology/approach An integrative model combining UTAUT and TAM3 frameworks was tested using survey data from 547 auditors in Supreme and Regional Audit Institutions across 29 European countries. Partial least squares structural equation modelling was applied to validate hypothesised relationships. Findings Perceived external control – the belief that the organisation provides adequate resources, technical support and training – was the strongest predictor of AI adoption intention, followed by social influence, expected effort and expected performance. The results of this study suggest that adoption depends on not only individual perceptions but also organisational capacity and social acceptance. Originality/value To the best of the authors’ knowledge, this study is among the first to explore AI acceptance in a diverse European sample of public auditors, integrating two established acceptance models. The findings of this study highlight the need for strategies that strengthen institutional capabilities, foster innovation-oriented cultures and ensure alignment between regulatory initiatives and operational conditions. This study offers key implications for both public policy design and future research on digital transformation in public sector auditing.
Alonso-Morales et al. (Tue,) studied this question.