Does AI adoption redefine financial reporting accuracy, auditing efficiency, and information asymmetry? An integrated model of TOE-TAM-RDT and big data governance

Accounting and auditing firms (AAFs) are experiencing a paradigm shift with the integration of artificial intelligence (AI), which has the potential to revolutionise important areas like fostering financial reporting accuracy, auditing efficiency, and diminishing information asymmetry. Yet, the effectiveness of AI adoption in achieving this goal is not guaranteed. Hence, this study aims to empirically explore what shapes AI adoption among AAFs, and what its potential role is in financial reporting accuracy, auditing efficiency, and information asymmetry. By applying a validated model of TOE-TAM-RDT and analysing using PLS-SEM, we found that AI adoption was shaped by competitive pressure, vendor ecosystem, top management support, relative advantage, AI readiness, and innovation climate. The adoption of AI-driven systems among AAFs exerted a positive impact on financial reporting accuracy, and auditing efficiency, while a negative impact on information asymmetry. Results further reveal a significant moderating effect of big data governance, demonstrating that proper management, quality, and ethical use of data within AAFs can amplify AI adoption benefits, boosting financial reporting accuracy, auditing efficiency, and mitigating information asymmetries between AAFs and stakeholders. These outcomes not only advance scholarly conversations on AI adoption in the financial and accounting landscape but also deliver actionable strategies for stakeholders to maximise AAFs’ benefits from this emerging revolutionary technology. • Accounting and auditing firms (AAFs) are experiencing a paradigm shift with the introduction of AI, potentially revolutionizing financial reporting accuracy, auditing efficiency, and information symmetry. • Concerns about embracing AI-powered systems in accounting and auditing practices regarding information asymmetry between AAFs and stakeholders have been raised. • By applying a validated model of TOE-TAM-RDT, we found that AI adoption was shaped by competitive pressure, vendor ecosystem, top management support, relative advantage, AI readiness, and innovation climate. • AI adoption among AAFs exerted a positive impact on financial reporting accuracy, and auditing efficiency, while a negative impact on information asymmetry. • Proper management, quality, and ethical use of big data governance amplify AI adoption benefits, boosting financial reporting accuracy, auditing efficiency, and mitigating information asymmetries between AAFs and stakeholders.