Impact of artificial intelligence on internal audit functions in Ghanaian public universities: perceptions, limitations and future directions.

Abstract

Recently, the incorporation of Artificial Intelligence (AI) into organisational processes has gained significant global momentum, particularly in improving efficiency, accuracy, and accountability in internal auditing. However, the incorporation of AI in Ghanaian public universities remains restricted due to the lack of sufficient research on its practical applications and associated ethical concerns, as well as numerous contextual challenges. This study examines the impact of AI on internal audit functions in public universities in Ghana, focusing on the perceptions of internal auditors, the limitations of current practices, and the potential for future integration of AI. The methodology employs a mixed-methods approach, integrating both quantitative and qualitative strategies. The data were exclusively collected from internal auditors, thereby guaranteeing that the insights were focused on audit-specific experiences and perceptions. Questionnaires were distributed to 177 internal auditors for the quantitative phase. A total of approximately 176 completed questionnaires were returned, providing a valid sample for analysis. Semi-structured interviews were conducted with six internal auditors during the qualitative phase to gain a deeper understanding of the practical challenges and implications of AI adoption. The results show that internal auditors at public universities in Ghana perceive AI as a valuable tool for enhancing internal controls, detecting fraud, and ensuring accountability. Respondents recognised AI's capacity to enhance audit accuracy, detect anomalies in real-time, and automate duties, thereby promoting a proactive auditing culture. AI was perceived as particularly effective in detecting fraud and reinforcing internal controls through continuous monitoring and predictive analytics. However, auditors face a variety of obstacles, such as inadequate training opportunities, poor management support, fragmented data systems, and a lack of technical expertise. Moreover, the smooth integration is hindered by a lack of collaboration between the audit and IT departments. Although generative AI tools such as Gemini and ChatGPT were praised, they are still underutilised due to inadequate training and exposure. The results emphasise the necessity of cross-departmental collaboration, leadership commitment, and capacity building to optimise the advantages of AI. Based on these results, it is recommended that public universities invest in regular training focused on AI for auditors. Additionally, there should be enhanced leadership support for AI initiatives, the establishment of centralised data systems, and improved collaboration between audit and IT departments to ensure the successful integration of AI.