Appraisal of Artificial Intelligence for Smart Project Management in the oil and gas Sector of the Niger Delta, Nigeria

• Post by: birpo
• March 4, 2026
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Stephen, Emmanuel Nse¹ & Prof. Basil Eze²

Abstract         

This study investigated the role of artificial intelligence (AI) in enhancing project management within the oil and gas sector of the Niger Delta, Nigeria. The research was motivated by the need to evaluate how AI adoption can improve efficiency, safety, and overall performance in an industry facing persistent operational challenges. The study focused on three objectives: to assess the extent of AI adoption in project management practices, to identify barriers hindering effective integration, and to determine performance areas most improved through targeted AI application. A quantitative research design was adopted. The study population comprised 550 staff, with a sample size of 232 determined using Yamane’s formula. A multi-stage sampling technique ensured proportional representation, and the survey data were complemented by secondary information from company and regulatory reports. Findings indicate that AI adoption is progressing but uneven across companies. Shell PLC’s AI-driven risk modeling increased from 25% in 2020 to 50% in 2024, while Dagrow Resources expanded from 5% to 65% over the same period, consistent with survey responses yielding a moderate grand mean of 3.35 on a 5-point Likert scale. Barriers to adoption were also identified. NNPC’s digital readiness improved from 2.5 to 3.6, compared to Shell’s consistently high baseline of 4.2–4.5, while regulatory approval timelines averaged over 145 days. Survey evidence reinforced these barriers, producing a high overall mean of 4.15. Performance improvements were most notable in downtime reduction and asset integrity, with Shell reducing downtime from 5% to 18% and Dagrow from 0% to 28%, supported by a grand mean of 4.22 from survey data. Hypothesis testing confirmed that adoption levels remained moderate and that barriers significantly hindered integration. The study concludes that AI has strong transformative potential for project management in Nigeria’s oil and gas sector, but its full realization requires sustained organizational investment and enabling institutional reforms.

Keywords: Artificial intelligence; Project management; Oil and gas sector; Niger Delta; Adoption barriers; Operational performance; Digital transformation