ARTIFICIAL INTELLIGENCE (AI) AND CHANGE MANAGEMENT IMPLEMENTATION IN THE NIGERIAN OIL AND GAS BUSINESS ENVIRONMENT

Laguo Livingstone Gilbert; Christian Clifford Edum

doi:10.5281/zenodo.23468037

Laguo Livingstone Gilbert Department of Business Administration Federal University Otuoke Bayelsa State, Nigeria
Christian Clifford Edum Department of Business Administration Federal University Otuoke Bayelsa State, Nigeria

DOI: https://doi.org/10.5281/zenodo.23468037

Keywords: Artificial Intelligence, Change Management Implementation, Decision Support Systems, Nigerian Oil and Gas, Predictive Analytics, Robotic Process Automation.

Abstract

This study examines the relationship between artificial intelligence (AI) and change management implementation in the Nigerian oil and gas business environment. Focusing on three dimensions of AI (predictive analytics, robotic process automation, and AI-enhanced decision support systems), the study investigates how these technologies influence the effectiveness of change management initiatives within the Nigerian upstrea petroleum sector. Anchored in the Technology Acceptance Model (Davis, 1989) and the Dynamic Capabilities Theory (Teece et al., 1997), the research adopts a cross-sectional survey design, drawing data from 98 valid respondents comprising managerial and technical employees across 15 oil and gas firms in Rivers State, Nigeria. Using Pearson Product-Moment Correlation Coefficient (PPMC) and Multiple Regression Analysis, findings reveal strong, positive, and statistically significant relationships between all three AI dimensions and change management implementation. AI-enhanced decision support systems and predictive analytics emerged as the strongest predictors of change management outcomes. The regression model accounts for 64.3% of the variance in change management implementation, underscoring the substantial explanatory power of AI technologies in organizational transformation. The study recommends that Nigerian oil and gas firms strategically invest in AI infrastructure, build AI-competent workforces, and align AI deployment with their change management frameworks to enhance transition effectiveness and sustain competitive advantage in a rapidly evolving industry.

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