Conference Paper

ARTIFICIAL INTELLIGENCY AND ENTERPRISES RISK MANAGEMENT IN HEALTHCAE SECTOR

Abstract This study focused on the relationship between artificial intelligence (AI) and enterprise risk management (ERM) in the healthcare sector of Ogun State, Nigeria. A stratified multistage sampling approach was used to conduct a cross-sectional survey of healthcare personel from six healthcare zones. Data were gathered from 259 respondents via Google Forms and analyzed using descriptive and inferential statistical methods. The reliability analysis via Cronbach's Alpha of 0.944, indicating great internal consistency. The study observed a strong positive correlation (r = 0.670, p < 0.01) between AIMC and RI, as well as a moderate but significant correlations (r = 0.560, p < 0.01) between AIPE and RA. Regression analysis revealed that AIMC and AIPE significantly predict RI and RA, accounting for 44.9% and 31.4% of the variance, respectively. The study concluded that AI improves risk management procedures by increasing risk detection, evaluation, and overall decision-making efficiency. It suggested that state hospitals should engage in AI-driven risk management techniques, predictive analytics, and automated risk detection technologies to effectively mitigate possible hazards. Furthermore, policymakers should create conditions that encourage AI innovation through research incentives, mentorship programs, and the development of strategic initiatives targeted at increasing intellectual mobility and lowering brain drain. Keywords: Artificial Intelligency, Risk Management