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Effect of AI adoption on decision-making in quoted Nigerian deposit money banks

D. Mlanga, S. Mlanga

The study examined the effect of AI adoption proxies — AI-Based Automated Bookkeeping Usage and Predictive Analytics for Financial Forecasting — on Decision-Making efficacy within Nigeria's Quoted Money Deposit Banks (QMDBs). Using a quantitative survey design, data from 300 professionals across 13 NGX-listed banks were analyzed via multiple linear regression. Results demonstrate that both proxies significantly enhance decision-making quality, speed, and effectiveness, collectively explaining 79.6% of variance (R² = 0.796). Predictive Analytics exhibited the strongest impact (β = 0.402, p < 0.001), followed by AI-Based Bookkeeping (β = 0.317, p < 0.001). The findings validate AI's role in optimizing strategic outcomes amid Nigeria's infrastructural deficits, data fragmentation, and skill shortages. The study advocates for context-specific strategies, including integrated data infrastructure, workforce reskilling in AI interpretation, regulatory sandbox expansion by the Central Bank of Nigeria (CBN), and managerial change initiatives to foster data-driven cultures.

Artificial intelligence integration and Africa business growth: The Nigerian experience

A. Abiegbe, H. Osisioma, M. Chiekezie

Artificial Intelligence (AI) is increasingly recognized as a transformative force for economic growth and business innovation globally, with its impact in emerging economies such as Nigeria gaining particular attention. This study explores the potential of AI integration in Nigerian businesses, emphasizing its role in enhancing productivity, fostering innovation, and driving sustainable growth. Employing a qualitative research design, the study conducted a secondary data analysis of scholarly sources published between 2018 and 2024, sourced from databases such as Google Scholar, Scopus, JSTOR, and Science Direct. Thematic analysis revealed that AI applications are reshaping diverse sectors, including finance, where chatbots and predictive analytics enhance customer service and risk management, and agriculture, where AI-driven tools support yield optimization through real-time weather and soil data insights. Findings indicate that Nigeria's youthful, tech-savvy population and vibrant economy provide fertile ground for AI adoption; however, significant barriers such as poor infrastructure, limited access to quality data, inadequate regulatory frameworks, and insufficient AI-related skills remain.

Budget governance in Nigeria: Mismanagement, corruption, and accountability

Idowu Eferakeya, A. O. Amughoro, Tedlyn A. Etu

The study examines budget governance system in the context of mismanagement, corruption, and accountability in Nigeria. It employed a qualitative document analysis of budget-related official documents, reports, and audits spanning from 2017 to 2024 to categorize recurring themes. Using thematic coding, the study identified eight dominant themes and their frequencies: misallocation of funds, mismanagement, corruption, financial embezzlement, budget padding, accountability mechanisms, institutional reforms, and sustainable development. The findings reveal the most prevalent challenges to be misallocation of budgeted funds, mismanagement, corruption, widespread financial embezzlement, and a lack of accountability. The findings are broadly categorized into illicit practices, corruption, embezzlement, administrative inefficiencies, and institutional gaps, all of which contribute to mismanagement and misallocation of funds. The study recommends that Nigeria must undertake comprehensive reforms to enhance the autonomy and capacity of oversight institutions and institutionalize transparency.

Audit quality as a determinant of financial performance in listed oil and gas companies in Nigeria

C. D. Mbatuegwu, J. F. Adebisi, S. A. Arua

The Audit Quality as a determinant of financial performance in listed Oil and Gas companies in Nigeria was investigated in this study from 2014 to 2023. Return on assets (ROA), return on equity (ROE), and Tobin's Q were used to measure financial performance, while audit size, audit tenure, audit firm industry specialization, and audit fees were used as proxies for audit quality. Panel regression models were used to analyze the data, which came from the annual reports of the sampled companies. The results show that audit tenure has a negative but negligible impact on financial performance, whereas auditor size, industry specialization, and audit fees have a positive and significant impact. Leverage had a negative correlation with financial performance, whereas firm size had a positive one. The study concludes that high audit quality enhances the profitability and market valuation of oil and gas companies in Nigeria by strengthening reporting credibility and investor confidence. It recommends that listed oil and gas companies should engage Big 4 auditors, ensure regular auditor rotation, invest in industry-specific audit expertise, and maintain transparency in audit fee determination.