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EFFECT OF ARTIFICIAL INTELLIGENCE ADOPTION IN ACCOUNTING ON AUDIT QUALITY IN NIGERIAN FIRMS

Abstract

The rapid advancement of Artificial Intelligence (AI) has fundamentally transformed business operations and professional accounting practices across the globe. In the accounting profession, Artificial Intelligence technologies including machine learning, robotic process automation (RPA), intelligent data analytics, natural language processing, and predictive analytics are increasingly being integrated into auditing processes to enhance the accuracy, efficiency, and reliability of audit engagements. AI-powered accounting systems enable auditors to automate repetitive tasks, analyze large volumes of financial data in real time, identify anomalies, detect fraudulent transactions, and improve risk assessment procedures. In Nigeria, the growing adoption of digital technologies and the increasing demand for high-quality financial reporting have encouraged accounting firms and corporate organizations to embrace AI-enabled audit tools. However, despite these technological advancements, concerns remain regarding the extent to which AI adoption translates into improved audit quality, particularly in an environment characterized by varying levels of technological readiness, professional expertise, and organizational capacity. Against this background, this study investigates the effect of Artificial Intelligence adoption in accounting on audit quality in Nigerian firms while examining the mediating role of audit efficiency and the moderating role of professional competence.The study is anchored on the Technology Acceptance Model (TAM), the Resource-Based View (RBV), and Human Capital Theory. The Technology Acceptance Model explains how perceived usefulness and ease of use influence the acceptance and utilization of AI technologies within accounting and auditing functions. The Resource-Based View posits that technological capabilities, such as AI systems, constitute valuable strategic resources capable of enhancing organizational performance and competitive advantage. Human Capital Theory emphasizes that the effectiveness of advanced technologies depends largely on the knowledge, skills, experience, and competencies of professionals responsible for their implementation and utilization. Guided by these theoretical perspectives, the study seeks to determine the direct effect of Artificial Intelligence adoption in accounting on audit quality, assess whether audit efficiency mediates this relationship, and examine whether professional competence moderates the influence of AI adoption on audit quality in Nigerian firms.A quantitative research design will be adopted using a structured questionnaire administered to external auditors, internal auditors, professional accountants, audit managers, finance managers, information technology specialists, and partners in audit firms, as well as accounting personnel in selected public and private organizations across Nigeria. A stratified random sampling technique will be employed to ensure adequate representation of respondents from audit firms, financial institutions, manufacturing companies, and other corporate organizations. Data collected from respondents will be analyzed using descriptive statistics to summarize demographic characteristics and respondents' perceptions. Structural Equation Modeling (SEM) will be employed to examine the direct, mediating, and moderating relationships among the study variables. The reliability and validity of the research instrument will be assessed using Cronbach's Alpha, Composite Reliability (CR), Average Variance Extracted (AVE), and Confirmatory Factor Analysis (CFA). Additional diagnostic tests, including multicollinearity and model fit assessments, will be conducted to ensure the robustness and adequacy of the structural model.The study anticipates that Artificial Intelligence adoption in accounting will have a significant positive effect on audit quality by improving the accuracy, consistency, objectivity, and comprehensiveness of audit procedures. AI technologies are expected to enhance auditors' ability to process large datasets, detect unusual transactions, identify potential fraud, strengthen risk assessment, and provide more reliable audit evidence, thereby reducing human error and increasing confidence in audit outcomes. Furthermore, audit efficiency is expected to mediate the relationship between AI adoption and audit quality. AI-driven automation is anticipated to reduce the time required for routine audit tasks, improve workflow management, accelerate data analysis, enhance audit planning, and enable auditors to focus on complex judgment-based activities. Consequently, improvements in audit efficiency are expected to serve as the mechanism through which AI adoption contributes to higher audit quality.Furthermore, professional competence is expected to moderate the relationship between Artificial Intelligence adoption and audit quality. Auditors possessing high levels of professional knowledge, technical expertise, digital literacy, analytical skills, and continuous professional development are expected to utilize AI technologies more effectively, thereby maximizing their contribution to audit quality. Competent professionals are better positioned to interpret AI-generated outputs, exercise professional judgment, evaluate complex financial information, and ensure compliance with auditing standards and ethical requirements. Conversely, limited professional competence may reduce the effectiveness of AI implementation due to inadequate technological understanding, improper system utilization, and overreliance on automated processes. Therefore, professional competence is expected to strengthen the positive relationship between AI adoption and audit quality by enhancing the effective integration of technological innovation with human expertise.This study is expected to make significant theoretical and empirical contributions to the accounting, auditing, and information systems literature by integrating audit efficiency as a mediating variable and professional competence as a moderating variable into the relationship between Artificial Intelligence adoption and audit quality. Unlike previous studies that primarily examined the direct effects of AI on audit performance or accounting efficiency, this research provides a more comprehensive framework by explaining the operational mechanism through which AI improves audit quality and identifying the professional conditions necessary for maximizing its effectiveness. The findings will provide valuable insights for audit firms, professional accounting bodies, corporate organizations, regulators, policymakers, accounting educators, software developers, and investors regarding the strategic importance of combining advanced AI technologies with continuous professional competence development. The study will also offer evidence-based recommendations for strengthening AI integration in accounting practice, improving audit efficiency, enhancing professional training, and promoting high-quality auditing standards that support financial reporting credibility and corporate governance in Nigeria.

Keywords: Artificial Intelligence adoption, accounting, audit quality, audit efficiency, professional competence, auditing, accounting information systems, mediation, moderation, Structural Equation Modeling (SEM).