Artificial Intelligence Adoption in Sustainable Supply Chain Management: A Systematic Literature Review and Future Research Agenda
TL;DR
It is demonstrated that AI assists in maintaining the economy in terms of efficiency and cost reduction, the environment in terms of waste and emissions, as well as, to a lesser degree, social sustainability in terms of transparency and compliance.
Abstract
The research is a systematic literature review of the use of artificial intelligence (AI) in sustainable supply chain management (SSCM) and comes up with a research agenda. Within a systematic literature review methodology that follows PRISMA guidelines, the review synthesizes the latest peer-reviewed works that were published in 2020-2026. The results demonstrate a rapid increase in the adoption of AI in SSCM over the last several years, as machine learning, predictive analytics, natural language processing, and automation have become commonly discussed topics. The literature is primarily centered around demand forecasting, optimization of logistics, inventory planning, resilience, and traceability. It is demonstrated that AI assists in maintaining the economy in terms of efficiency and cost reduction, the environment in terms of waste and emissions, as well as, to a lesser degree, social sustainability in terms of transparency and compliance. But significant impediments are also reported in the review, such as data quality, capability gap, complexity in integrating, high cost, and governance. On the whole, the research paper has concluded that AI has high potential to revolutionize SSCM, yet more empirical, theoretical, and socially oriented studies are required to improve the situation.