EVALUATING THE IMPLICATION OF ARTIFICIAL INTELLIGENCE ON THE ACCURACY OF FINANCIAL REPORTING IN EMERGING ECONOMIES

Abstract

This study investigates the impact of artificial intelligence (AI) adoption on financial reporting accuracy within emerging economies, with a specific focus on firms in Ibadan, Nigeria. Employing a mixed-methods design, the research integrates panel-data regression analysis of 120 firms over five years with semi-structured interviews of 25 finance executives, auditors, and regulatory officials. Quantitative findings reveal that a one-standard-deviation increase in the AI Adoption Index is associated with a 12–15% reduction in financial restatement frequency (Fixed Effects: β = -0.145, p = 0.005; Random Effects: β = -0.138, p = 0.004) and a significant decrease in audit adjustments. Interaction effects indicate that regulatory oversight amplifies AI’s positive influence on reporting accuracy (β = -0.078, p = 0.019). Qualitative analysis highlights AI’s role in anomaly detection, predictive forecasting, and continuous auditing, while emphasising the indispensable function of human judgement in interpreting algorithmic outputs. Implementation challenges identified include “black-box” opacity, limited technical expertise, and data quality constraints. Integrated findings underscore that AI’s effectiveness is contingent upon organisational readiness, high-quality data, competent personnel, and active regulatory engagement. The study concludes that AI serves as a complementary enabler rather than a substitute for professional expertise, offering substantial potential to enhance financial reporting integrity when embedded within robust governance and oversight frameworks.