A qualitative study on the influence of organisational readiness and socio-technical alignment of AI integration within the downstream oil and gas supply chain risk management

Abstract

The downstream oil and gas supply chain industry is becoming more and more vulnerable to unplanned disruptions that have already proven to threaten efficiency, resilience and continuity. While artificial intelligence has surfaced as a promising tool that can enhance operations through predictive analytics and data-driven decision-making support, the implementation within downstream oil and gas supply chains has been underwhelming. The Socio-Technical System theory guides this qualitative study as it explores how organisational readiness and socio-technical alignment can be leveraged to achieve effective AI integration in downstream SCRM. Semi-structured interviews were performed with 12 individuals who occupy relevant roles in supply, trading, risk management and digital operations in the industry. The thematic analysis reveals three interconnected themes that represent factors that need to be improved for an organisation to achieve operational readiness. These factors include barriers to AI adoption, operational inefficiencies and cultural and general tensions. A further four themes emerge as invaluable enabling factors that can be leveraged to assist with achieving socio-technical alignment. These include organisational foundations, workforce capability and engagement, alignment strategies and leadership as a driver. Ultimately, this research culminates in a conceptual framework that converges organisational readiness with socio-technical alignment to provide a roadmap for downstream O&G SC organisations and leaders to use as a guide to achieve adaptive AI-enabled SCRM.