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

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  • Batin Latif Aylak

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

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.

Suggested Citation

  • Batin Latif Aylak, 2025. "SustAI-SCM: Intelligent Supply Chain Process Automation with Agentic AI for Sustainability and Cost Efficiency," Sustainability, MDPI, vol. 17(6), pages 1-24, March.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:6:p:2453-:d:1609861
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    References listed on IDEAS

    as
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    2. Ilya Jackson & Dmitry Ivanov & Alexandre Dolgui & Jafar Namdar, 2024. "Generative artificial intelligence in supply chain and operations management: a capability-based framework for analysis and implementation," International Journal of Production Research, Taylor & Francis Journals, vol. 62(17), pages 6120-6145, September.
    3. Alexandra Brintrup & Edward Kosasih & Philipp Schaffer & Ge Zheng & Guven Demirel & Bart L. MacCarthy, 2024. "Digital supply chain surveillance using artificial intelligence: definitions, opportunities and risks," International Journal of Production Research, Taylor & Francis Journals, vol. 62(13), pages 4674-4695, July.
    4. Plambeck, Erica L., 2012. "Reducing greenhouse gas emissions through operations and supply chain management," Energy Economics, Elsevier, vol. 34(S1), pages 64-74.
    5. Wenwen Chen & Yangchongyi Men & Noelia Fuster & Celia Osorio & Angel A. Juan, 2024. "Artificial Intelligence in Logistics Optimization with Sustainable Criteria: A Review," Sustainability, MDPI, vol. 16(21), pages 1-22, October.
    6. Nistor Andrei & Cezar Scarlat & Alexandra Ioanid, 2024. "Transforming E-Commerce Logistics: Sustainable Practices through Autonomous Maritime and Last-Mile Transportation Solutions," Logistics, MDPI, vol. 8(3), pages 1-21, July.
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    Cited by:

    1. Ren'e Bohnsack & Mickie de Wet, 2025. "AI is the Strategy: From Agentic AI to Autonomous Business Models onto Strategy in the Age of AI," Papers 2506.17339, arXiv.org, revised Jul 2025.

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