Institutional readiness and resistance to AI-based accounting platforms: evidence from Indonesian local governments

Purpose This study aims to examine how perceived benefits (PB), challenges (PC) and threats (PT) signal readiness and resistance in adopting Indonesia’s artificial intelligence (AI)-based public sector accounting platforms: the Sistem Informasi Pemerintahan Daerah and Artificial Intelligence for Financial Advisor. Design/methodology/approach Survey data were collected from 364 Public Sector Financial Officers across 44 local governments. Measurement validity was tested using confirmatory factor analysis, group comparisons applied Mann–Whitney U tests and aggregation indices (rwg, intraclass correlation) assessed institutional-level reliability. Findings Officers with direct system experience reported stronger recognition of predictive and reporting benefits, alongside heightened awareness of operational challenges and career-related threats. These dual patterns reflect both digital maturity and institutional frictions in AI adoption. Research limitations/implications This study is constrained by its voluntary, cross-sectional design, which limit causal inference and generalizability. Future studies should adopt longitudinal designs, integrate perceptual with administrative data and examine organizational factors such as leadership, infrastructure and interagency coordination. Theoretically, this study extends New Public Management, the Technology Acceptance Model and Innovation Resistance Theory by operationalizing readiness and resistance through PB, PC and PT. Practical implications Public managers should embed predictive and reporting gains into budget routines, enforce explainability and workflow standards and align AI-enabled work with competency frameworks and career development pathways. Social implications The findings highlight that AI reform must align with institutional capacity and professional growth, ensuring accountants in the public sector acquire the skills to work effectively alongside AI systems. These measures strengthen accountability, safeguard discretion and support equitable digital transformation in decentralized governance. Originality/value By treating PB, PC and PT as perceptual indicators of readiness and resistance, this study demonstrates how frontline experiences inform institutional variation in digital maturity and provide actionable insights for AI governance in the public sector.