AI-driven environmental management in oil and gas industry: developing a framework for sustainable operations and stakeholder value creation

Abstract

The oil and gas industry faces growing pressure to improve environmental performance while maintaining operational efficiency and stakeholder legitimacy. Although artificial intelligence (AI) is increasingly applied in emissions monitoring, predictive maintenance, compliance support, and sustainability reporting, the literature remains fragmented and lacks an integrated managerial framework linking AI adoption with environmental governance and stakeholder value creation. This study develops the AI-Enabled Value Creation and Management (AI-EVCM) framework through a mixed-methods design combining a PRISMA-based systematic literature review, an original cross-national practitioner survey, and cross-case analysis of four major oil and gas companies. The systematic review followed PRISMA 2020 guidelines and synthesized 170 peer-reviewed English-language journal articles identified through Scopus for the period 2021–2025. The empirical component includes 121 survey responses from oil and gas professionals across multiple regions, complemented by cross-case evidence from Shell, BP, Chevron, and ExxonMobil. The findings indicate that although AI adoption is expanding, practitioners report persistent deficits in governance, accountability, transparency, and environmental value realization. In response, the study proposes a three-layer framework linking sensing capabilities, adaptive governance, and stakeholder value loops. The paper contributes to the literature by integrating AI, environmental management, and stakeholder-oriented value creation into a coherent framework for sustainable operations in the oil and gas industry.