HUMAN-ARTIFICIAL INTELLIGENCE SUPERVISION AND INSPECTION PERFORMANCE OF OIL AND GAS FIRMS IN NIGERIA
DOI:
https://doi.org/10.65336/WJAEL.2026.31002Keywords:
Human-Artificial Intelligence Supervision, Inspection Performance, AI tool adoption Level, Human Supervisor Competence, Inspection Accuracy, Operational Efficiency.Abstract
The study was on the relationship between Human - Artificial Intelligence supervision and inspection performance of oil and gas firms in Rivers State, Nigeria. AI tool adoption Level and Human Supervisor Competence were used to operationalised Human - Artificial Intelligence supervision and inspection accuracy and operational efficiency were used to measured inspection performance. Technology Acceptance Model was underpinned the study. Cross-sectional survey design was used in data collection at a spot. The accessible population was 1,800 individuals and the sample size was 317 respondents at a 95% confidence level and a 5% margin of error from the accessible population of 1,800. Partial Least Squares Structural Equation Modelling (PLS-SEM) was employed to analysed the hypotheses. The findings revealed that there is a significant influence of Human - Artificial Intelligence supervision on inspection performance of oil and gas firms in Rivers State, Nigeria. The study concluded that Human-Artificial Intelligence supervision had positive impact on inspection performance of oil and gas firms in Rivers State, Nigeria. The study suggests that AI technology should not be treated as a substitute for human supervision. Oil and gas firms should pursue an integrated approach in which AI provides analytical and predictive capabilities, competent human supervisors provide contextual judgement and accountability, and organisational factors provide the infrastructure and management support necessary for the two to work effectively together.
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