Artificial Intelligence and Responsible Management for Organisational Sustainability: A Systematic Literature Review on AI Governance and Sustainable Development Goals

Artificial intelligence (AI) is increasingly transforming organisational decision-making, sustainability management, and governance structures across industries. Although AI technologies are frequently promoted as catalysts for achieving the United Nations Sustainable Development Goals (SDGs), growing concerns relating to ethical governance, algorithmic bias, energy consumption, transparency, and socio-environmental inequality raise important questions regarding the sustainability of AI-driven organisational systems. Existing studies largely focus on technical AI applications while offering limited understanding of how responsible management capabilities influence sustainability outcomes. This study addresses this gap through a systematic literature review examining the relationship between artificial intelligence, responsible management, organisational sustainability, and SDG implementation. Following PRISMA guidelines, primarily peer-reviewed studies (with limited justified exceptions) published between 2015 and 2025 were retrieved from Scopus and Web of Science databases using a structured search strategy. After a rigorous screening process, 64 studies were included in the final review and analysed through thematic synthesis and governance-oriented coding. The final sample comprises 56 peer-reviewed journal articles, four peer-reviewed non-journal sources (three conference papers and one book chapter), and four non-peer-reviewed exceptional sources (two preprints, one book, and one report). The findings identify four dominant themes: AI-enabled environmental sustainability, intelligent operational efficiency, AI-driven social sustainability, and responsible AI governance. The literature suggests that AI may enhance sustainability performance through predictive analytics, resource optimisation, smart manufacturing, intelligent healthcare systems, and sustainability monitoring. However, the sustainability impact of AI is proposed to be mediated by governance capabilities such as transparency, accountability, stakeholder inclusion, ethical oversight, and regulatory alignment. It is important to note that only 30% of the reviewed studies provide primary empirical data; thus, most reported relationships are conceptual or associational rather than causal. Drawing upon systems theory and stakeholder theory, this paper proposes a novel conceptual framework positioning responsible AI governance capability as a partial mediating mechanism between AI adoption and sustainable organisational outcomes. The study contributes to the literature by shifting the debate from technological determinism toward governance-centred sustainability management. The paper concludes by identifying major research gaps and providing evidence-informed recommendations for organisations, policymakers, and future interdisciplinary research.