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Enhancing Supply Chain Resilience Through Artificial Intelligence: Developing a Comprehensive Conceptual Framework for AI Implementation and Supply Chain Optimization

Author

Listed:
  • Meriem Riad

    (National School of Applied Sciences AMSAD Laboratory, Hassan 1st University Settat, Berrechid 26100, Morocco)

  • Mohamed Naimi

    (National School of Applied Sciences AMSAD Laboratory, Hassan 1st University Settat, Berrechid 26100, Morocco)

  • Chafik Okar

    (National School of Applied Sciences MCSDM Laboratory, Abdelmalek Essaâdi University Tetouan, Tetouan 93002, Morocco)

Abstract

Background : Amid growing global uncertainty and increasingly complex disruptions, the ability of supply chains to rapidly adapt and recover is critical. The incorporation of artificial intelligence (AI) into supply chain management represents a transformative strategy for enhancing resilience. By harnessing advanced AI technologies, such as machine learning, predictive analytics, and real-time data processing, organizations can more effectively anticipate, respond to, and recover from disruptions.AI improves demand forecasting accuracy, optimizes inventory management, and increases real-time visibility across the supply chain, reducing the risks of stockouts and surplus inventory. Furthermore, I-driven automation and robotics enhance operational efficiency by minimizing human error and streamlining processes. Methodology/Approach : This paper proposes a conceptual framework for strengthening supply chain resilience through AI integration. The framework leverages AI technologies to improve key aspects of supply chain resilience, including risk management, operational efficiency, and real-time visibility. Result/Conclusions : Additionally, it underscores the importance of collaborative relationships with supply chain partners, enabled by AI-powered data-sharing and communication tools that foster trust and coordination within the network. Originality/Value : This comprehensive framework offers a strategic approach to integrating AI into supply chain management, highlighting its potential to significantly enhance resilience, operational efficiency, and sustainability, thereby empowering organizations to navigate the complexities of modern supply chains more effectively.

Suggested Citation

  • Meriem Riad & Mohamed Naimi & Chafik Okar, 2024. "Enhancing Supply Chain Resilience Through Artificial Intelligence: Developing a Comprehensive Conceptual Framework for AI Implementation and Supply Chain Optimization," Logistics, MDPI, vol. 8(4), pages 1-26, November.
    • Handle: RePEc:gam:jlogis:v:8:y:2024:i:4:p:111-:d:1515022
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    8. Rangga Primadasa & Elisa Kusrini & Agus Mansur & Ilyas Masudin, 2026. "Evaluation of Resilience-Sustainable Supply Chain Management (RSSCM) Performance Indicators in SMEs: An AI-Driven-CRITIC-ISM-MICMAC Hybrid Framework," Circular Economy and Sustainability, Springer, vol. 6(2), pages 1-41, April.
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