SustAI-SCM: Intelligent Supply Chain Process Automation with Agentic AI for Sustainability and Cost Efficiency

Batin Latif Aylak ()
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Batin Latif Aylak: Department of Industrial Engineering, Turkish-German University, Sahinkaya Caddesi 106, Beykoz, Istanbul 34820, Turkey

Sustainability, 2025, vol. 17, issue 6, 1-24

Abstract: Sustainable supply chain management (SCM) demands efficiency while minimizing environmental impact, yet conventional automation lacks adaptability. This paper presents SustAI-SCM, an AI-powered framework integrating agentic intelligence to automate supply chain tasks with sustainability in focus. Unlike static rule-based systems, it leverages a transformer model that continuously learns from operations, refining procurement, logistics, and inventory decisions. A diverse dataset comprising procurement records, logistics data, and carbon footprint metrics trains the model, enabling dynamic adjustments. The experimental results show a 28.4% cost reduction, 30.3% lower emissions, and 21.8% improved warehouse efficiency. While computational overhead and real-time adaptability pose challenges, future enhancements will focus on energy-efficient AI, continuous learning, and explainable decision making. The framework advances sustainable automation, balancing operational optimization with environmental responsibility.

Keywords: agentic AI; sustainable supply chain; transformer model; automation; cost optimization; green logistics (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:6:p:2453-:d:1609861

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