AI and quantum computing for carbon-neutral supply chains: a systematic review of innovations
Abstract
The urgent global imperative to mitigate climate change has brought carbon-neutral supply chains to the forefront of sustainability and operations management discourse. As organizations strive to meet net-zero emission targets, technologies such as Artificial Intelligence (AI) and Quantum Computing (QC) have emerged as powerful enablers of this transformation. This systematic literature review investigates the roles of AI and QC in achieving carbon-neutral supply chains, examining how these technologies optimize forecasting, logistics, procurement, emissions monitoring, and real-time decision-making across diverse industrial contexts. By following the PRISMA 2020 methodology, a total of 87 peer-reviewed articles published between 2015 and 2025 were identified, screened, and synthesized from databases including Scopus, Web of Science, IEEE Xplore, ScienceDirect, and Google Scholar. The review reveals that AI significantly enhances operational sustainability through intelligent demand forecasting, inventory optimization, carbon footprint assessment, and green procurement decision-making. Quantum computing, while still in its early stages of maturity, offers high-potential applications in solving complex optimization problems such as vehicle routing, energy grid balancing, and low-emission manufacturing simulation. The integration of AI and QC—especially when combined with technologies like digital twins and blockchain—was found to support advanced sustainability modeling,…
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Evidence Hub reads this as a systematic review. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.
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