Effect of AI-Supported Decision-Making on Strategic Supply Management Effectiveness in Selected Oil and Gas Companies in Nigeria

Abstract

The increasing complexity of procurement networks and volatility in the global energy market have intensified the need for effective strategic supply management in the oil and gas industry. This study examines the effect of AI-supported decision-making on strategic supply management effectiveness in selected oil and gas companies in Nigeria. The specific objectives are to: (i) assess the effect of AI-supported decision-making on supplier selection effectiveness, (ii) evaluate its influence on procurement cost efficiency, and (iii) examine its impact on risk management and sourcing strategy alignment. A quantitative research design was adopted using a cross-sectional survey approach. The population of the study comprised procurement managers, supply chain managers, strategic planning managers, and IT managers in selected upstream and downstream oil and gas companies operating in Lagos, Rivers, and Delta States, Nigeria. The total population was 360 staff, 189 respondents were selected using proportionate sampling techniques. Data were collected through structured questionnaires and analyzed using descriptive statistics and inferential (multiple regression analysis). Results presented in figures and tables revealed that AI supported decision-making accounted for 71.2% of the variation in strategic supply management effectiveness (R² = 0.712). AI-driven analytics significantly influenced supplier selection accuracy (β = 0.436, p < 0.05), procurement cost efficiency (β = 0.391, p < 0.05), and risk mitigation effectiveness (β = 0.322, p < 0.05). Figure 1 showed that firms with advanced AI decision-support systems achieved an average 42% reduction in procurement cycle time, while Figure 2 indicated a 35% improvement in supplier performance evaluation accuracy. The findings demonstrate that AI-supported decision-making enhances data-driven sourcing strategies, improves cost control, and strengthens supply risk management in Nigeria’s oil and gas sector. The study concludes that AI-enabled decision systems are critical to achieving effective strategic supply management in a highly capital-intensive and risk-prone industry. The study recommends that oil and gas companies invest in AI-based decision-support platforms, integrate AI tools into procurement planning processes, and continuously upskill supply management professionals to fully leverage AI capabilities for strategic advantage.