Artificial Intelligence Adoption and Perceived Financial Reporting Accuracy: Evidence from Accounting Professionals in Nigeria
DOI:
https://doi.org/10.66461/zzxfre08Keywords:
Artificial Intelligence, Perceived Financial Reporting Accuracy, Accounting Information Systems, Organizational Readiness, Nigeria, Emerging Economy Context, Financial Reporting Quality, Technology Adoption, Accounting ProfessionalsAbstract
Artificial Intelligence (AI) is increasingly transforming accounting practices by automating routine tasks, improving data processing, enhancing predictive analysis, and supporting financial reporting activities. However, empirical evidence remains limited on how accounting professionals in Nigeria perceive the relationship between AI adoption and financial reporting accuracy. This study examines the association between AI adoption and perceived financial reporting accuracy among accounting professionals in Nigeria, drawing on the Technology Acceptance Model, the Technology-Organization-Environment framework, and the DeLone and McLean Information Systems Success Model. A quantitative cross-sectional survey design was employed using questionnaire data collected from 384 accounting professionals, including accountants, auditors, financial analysts, finance managers, chief financial officers, accounting consultants, and other professionals involved in financial reporting and accounting information systems. Data were analyzed using descriptive statistics, reliability and validity tests, Pearson correlation analysis, and regression analysis. The findings indicate that AI adoption is positively and significantly associated with perceived financial reporting accuracy. AI adoption is also positively associated with perceived error reduction, reporting timeliness and efficiency, and accounting information systems quality. Organizational readiness is positively associated with AI utilization, while AI adoption challenges are negatively associated with AI utilization. In the main regression model, AI adoption, organizational readiness, and accounting information systems quality significantly predicted perceived financial reporting accuracy, whereas AI adoption challenges had a negative but statistically weaker association when the other predictors were included. The study contributes perception-based evidence from Nigeria and shows that AI-enabled accounting technologies may strengthen perceived reporting processes when supported by adequate infrastructure, management commitment, skilled personnel, reliable accounting information systems, and appropriate governance safeguards. Because the study relies on cross-sectional self-reported data, the findings should be interpreted as perceptions of financial reporting accuracy rather than direct evidence of objectively measured reporting accuracy.
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