AI and Digital Solutions for Health, Safety, and Risk Management

Abstract The oil and gas industry, particularly in emerging economies like Nigeria, continues to face significant health, safety, and environmental (HSE) challenges, with traditional reactive management systems proving inadequate for predicting and preventing incidents. This study demonstrates how Artificial Intelligence (AI) and Internet of Things (IoT) technologies can transform HSE into a predictive and proactive discipline. Through an analysis of historical safety data, occupational health records, and environmental monitoring data from Nigerian petroleum operations, the research develops and validates a framework for digital integration. The results show that AI- driven predictive models can forecast equipment failures and near-misses with 30-40% greater accuracy than manual methods, leading to a 25% reduction in unplanned shutdowns in a pilot deployment. Furthermore, IoT wearables enabled real-time worker fatigue monitoring, reducing related incidents by 15%, while AI pattern recognition successfully prevented occupational exposure limit exceedances. The study concludes that integrating AI is a strategic imperative for enhancing safety, operational efficiency, and regulatory compliance. It provides a phased implementation roadmap to overcome infrastructure and skill-based barriers, positioning AI-powered HSE systems as a cornerstone for sustainable and resilient operations in the modern petroleum industry.