AI Adoption in Public Accounting Firms: Drivers, Barriers and Financial Information Quality — Evidence from Algeria

Abstract

This empirical study examines the determinants and barriers to artificial intelligence (AI) adoption in Algerian public accounting firms, as well as its effects on financial information quality. Grounded in an integrated theoretical framework combining the TOE model (Tornatzky & Fleischer, 1990), the TAM model (Davis, 1989), and agency theory (Jensen & Meckling, 1976), the study draws on a survey of 218 accounting professionals, analyzed through PLS-SEM using SmartPLS 4.0. The results confirm that perceived usefulness and digital competencies are the main drivers of adoption, while perceived cost represents the primary barrier. AI adoption exerts a positive and significant effect on financial information quality (β = 0.421, p < 0.001). These findings enrich the technology acceptance literature in accounting contexts within developing countries and offer concrete recommendations for firms, professional associations, and Algerian regulators.