The Role of Artificial Intelligence in Enhancing Supply Chain Performance within Nigeria’s Oil and Gas Sector

This study examines the application of artificial intelligence (AI) in enhancing supply chain performance within Nigeria’s oil and gas sector, with a focus on efficiency, agility, and resilience. As global energy demands and operational complexities rise, the need for digital transformation in supply chain management has become increasingly vital. However, in many developing economies, AI adoption remains limited due to organizational, cultural, and infrastructural barriers. A quantitative research design was employed, using survey data collected from professionals within the Nigerian oil and gas industry. The dataset was analyzed using Random Forest and Gradient Boosting algorithms to predict transformation of oil and gas supply chain operations based on organizational readiness, familiarity, improvement initiatives, risk tolerance, and upskilling intent. Descriptive statistics and machine learning models were used to assess both perception-based insights and the predictive capacity of key transformation indicators. Findings revealed a high level of AI awareness (83.7%) among respondents but low organizational adoption (23.3%). Digital readiness and infrastructure development were generally rated poor, while resistance to change and implementation cost were identified as the primary barriers. Despite this, a majority of participants believed AI would improve operational performance, and over 70% expressed willingness to pursue AI-related upskilling. Machine learning results indicated that risk level, improvement, and readiness were the strongest predictors of digital transformation of supply chain operations in the oil and gas industry. Both models demonstrated moderate predictive performance, with Gradient Boosting slightly outperforming Random Forest in classification accuracy. The study concludes that while the foundation for AI adoption exists, strategic readiness and investment are critical for tangible transformation. It recommends prioritizing risk-aware leadership, infrastructure upgrades, and regulatory support to foster a digitally capable supply chain. The findings have practical implications for policymakers, industry leaders, and supply chain strategists aiming to align AI technologies with organizational capabilities.