Artificial Intelligence and Technology Integration in Audit Practices in Ghana: A Comprehensive Empirical Study

In this major research paper, we explore the integration of AI and advanced technologies in audit practice of Ghana, a developing West African economy, using AI-based audit tools, machine learning algorithms, and data analytics technologies in Ghana’s financial sector. Using a multiple regression analysis with SPSS statistical software, we present the results of 250 audit professionals across Ghana's major audit firms, banks, and financial institutions in the research study based on an analysis of the data of audit professionals with high audit efficiency (β = 0.645, p < 0.001), fraud detection (β = 0.578, p < 0.001), and overall quality of audit in Ghana (β = 0.512, p < 0.001) in the financial industry. However, there are key challenges in digital infrastructure, poor training of auditors, the lack of legal framework, regulatory uncertainty, and high implementation costs, which make it difficult to adopt these technologies in large numbers. The study is also an opportunity to understand barriers to AI adoption in developing country audit and provide guidance to audit regulators, professional bodies, and auditing firms in Ghana. The research highlights that AI integration needs to be done in a coordinated fashion, both in terms of capacity building, regulatory framework creation, and organizational culture transformation with a focus on developing countries where there is limited institutional capacity.