Exploring the perceptions of engineers regarding Al capabilities at a South African multinational oil and gas company

Abstract

This study explores the perceptions of engineers regarding the capabilities of artificial intelligence (AI) within a South African multinational oil and gas company. Guided by Social Cognitive Theory, the research investigates how engineers engage with AI in their daily workflows, the concerns they raise about its implementation, and the contextual and organisational factors that influence its adoption. A qualitative approach was incorporated in the study. Semi-structured focus groups, comprising engineers from various disciplines within the innovation and engineering division of the organisation, were used. The data were analysed using reflexive thematic analysis, attempting to identify emerging patterns and conceptual insights. According to findings, while engineers argue for AI being able to bring about improvements in the working methods, diagnostic accuracy, and strategic decision making processes, they do find the issue of over-reliance, lack of human oversight, opacity, and unclear accountability distressing. Contextual barriers such as unreliable infrastructure and low digital maturity were also found to influence the integration of AI. Despite being faced with such challenges, participants showed resilience and adaptability, modifying their working practices according to the constraints of the system. Besides these, organisational enablers such as leadership endorsement, training, and feedback mechanisms were perceived as vital for the successful adoption of AI. The study contributes to the literature by documenting context-specific evidence in an industrial setting in the Global South, thus bringing to light the complex interplay between technological capability, human agency, and environmental constraints within the implementation of AI. The study provides suggestions for practice, theory, and future research.