Enhancing Supply Chain Resilience Through Artificial Intelligence: Developing a Comprehensive Conceptual Framework for AI Implementation and Supply Chain Optimization
Open accessAbstract
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.
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Embedding AI in supply chain management helps reach sustainability targets by minimizing operational costs and enhancing organizational performance.
“The embedding of AI in supply chain management aids in the reaching of sustainability targets because it minimizes operational costliness and enhances organizational performance53,54.”
From A decision-support framework for evaluating AI-enabled ESG strategies in the context of sustainable manufacturing systems (2025) · cites this paper as [54]
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Pampa, I. L. P., Rosales, L. B. R., & Atúncar, G. S. (2025) · Research Square · doi:10.21203/rs.3.rs-7336582/v1 · Cited by 1 · see citing works
The Modern Framework of Digital Supply Chain Management: A Systematic Literature ReviewPreprint
ali, A. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5180627
Navigating AI Adoption: The Role of Organizational Culture Under Disruption Severity
Morshed, N., Rahman, M., & Anzum, K. M. T. (2024) · International Conference on Industrial Engineering and Operations Management (IEOM) · doi:10.46254/ba07.20240219
Li, J., Sun, Y., Wang, J., Cui, L., Chu, H., & Su, L. (2025) · International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) · doi:10.1109/icdcece65353.2025.11035829
AI as a Catalyst for Sustainable Supply Chains
Meziane, B., Alla, L., & Bentalha, B. (2025) · IGI Global eBooks · doi:10.4018/979-8-3373-3012-9.ch001
Linking Supply Chain Resilience to Artificial Intelligence: A Systematic Literature Review
Sahab, S., & Oulfarsi, S. (2025) · International Colloquium on Logistics and Supply Chain Management (LOGISTIQUA) · doi:10.1109/logistiqua66323.2025.11122852
Ruiz, F. E. A., Beltrán, P., Tejera, E., Landázuri, A. C., & Álvarez-Suárez, J. M. (2025) · ACS Agricultural Science & Technology · doi:10.1021/acsagscitech.5c00706
The Contribution of Artificial Intelligence in Transforming Supply Chain Ecosystem
Eletter, S. F. K., Refae, G. A. E., Shaikh, Z., Yaseen, S. G., Yasmin, T., & Athamena, B. (2025) · Studies in systems, decision and control · doi:10.1007/978-3-031-90271-0_56
Ethical AI in the Supply Chain
Bentatou, N., & Lemqeddem, H. A. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-3104-1.ch007
Socio-Technical AI Maturity in Supply Chains: Insights from the Pulp and Paper Sector
Freitas, F., Zimmermann, R., Freires, F. G. M., Couto, F. A. P., Fontes, C. H., Soares, A. L., Dalmarco, G., Rhodes, D. H., & Gomes, J. (2025) · IFIP advances in information and communication technology · doi:10.1007/978-3-032-05673-3_11
Nguyen, L., Mayet, O., & Desai, S. S. (2025) · Logistics · doi:10.3390/logistics9040154
AI and Big Data Analytics for Management of Nutraceuticals
Almoselhy, R. I. M., Usmani, A., Rajendran, R., & Thomas, S. (2025) · Springer eBooks · doi:10.1007/978-3-030-69677-1_50-1
Nithin, O. V. S., Shashwath, S. H., Gothe, S. S., Singh, A. K., Chandra, A., & VijayKumar, M. N. (2025) · International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS) · doi:10.1109/csitss67709.2025.11294222
Singla, L., & Lad, M. (2025) · International Conference on Artificial Intelligence, Blockchain, and Internet of Things (AIBThings) · doi:10.1109/aibthings66987.2025.11296198
AI-Driven Economic Intelligence for Adaptive Supply Chain Ecosystems
Foukolaei, P. Z. (2025) · IGI Global eBooks · doi:10.4018/979-8-3693-4525-2.ch007
KnoChain: Knowledge-Aware Recommendation for Alleviating Cold Start in Sustainable Procurement
Li, P., Ma, Y., Hou, K., & Li, S. (2026) · Sustainability · doi:10.3390/su18010506
The smart supply chain management: Huawei's innovative approach
Benahmed, S., Benkhira, M., & Hansal, A. (2026) · European Journal of Management Studies · doi:10.1108/ejms-03-2025-0028
Retracted: The Role of AI in Enhancing Supply Chain and Operations Management
Krishna, S. H., Anumula, S. K., Thakur, R., Sharma, Y. K., Sharma, P., & Tewari, P. C. (2025) · International Conference on Digital Innovations for Sustainable Solutions (ICDISS) · doi:10.1109/icdiss68238.2025.11320742
RetractedA Multi-Objective Framework for Inventory Digitalization Using AI and IoT
Arora, M. M. L., Sethi, S., Ahluwalia, A., Udayai, K., Aggarwal, N., & Ahmad, V. (2025) · IEEE International Conference on ICT in Business Industry & Government (ICTBIG) · doi:10.1109/ictbig68706.2025.11323600
Kalia, A., & Sreelakshmi, M. V. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-40387-3.00004-0
Praveen, R., Aida, R., Rambhatla, A. K., Trakroo, K., Maran, M., & Sharma, S. (2025) · International Conference on Communication and Electronics Systems (ICCES) · doi:10.1109/icces67310.2025.11336907
AI and Big Data Analytics for Management of Nutraceuticals
Almoselhy, R. I. M., Usmani, A., Rajendran, R., & Thomas, S. (2026) · Springer eBooks · doi:10.1007/978-3-031-98791-5_50 · Cited by 1 · see citing works
Exploring AI Tools and Framework for Supply Chain Management
Thamilarasi, V., Sivakumar, J., Roselin, R., Jeysankar, N., Wanjale, K. H., & Susila, S. J. G. (2026) · IGI Global eBooks · doi:10.4018/979-8-3373-9554-8.ch003
Gurav, V., Badgujar, A., & Sakhare, H. (2025) · International Conference on Electronics, Communication and Aerospace Technology (ICECA) · doi:10.1109/iceca66444.2025.11382888
Smart prosperity through smart supply chain based on using smart and intelligent technologies
Arsovski, Z., Arsovski, S., Đorđević, A., & Stefanovic, M. (2026) · Enterprise Information Systems · doi:10.1080/17517575.2026.2628647
Optimizing Supply Chain Management through Resilience and Capabilities Integration
Goyal, S., Prakash, F., Thangamani, A., Saini, R., Senthamilselvan, K., & Grover, M. (2025) · International Conference on AI-Driven STEM Education and Learning Technologies (AISTEMEDU) · doi:10.1109/aistemedu67077.2025.11403882
Modernizing pharmacopoeias with artificial intelligence
Kumar, M. P., Sahoo, S. K., Jadaun, G. P. S., & Raghuvanshi, R. S. (2026) · Computational Toxicology · doi:10.1016/j.comtox.2026.100407
Predictive Analytics and Adaptive Planning for Sustainability Resilience
Anwar, N., Talib, E. A. H., Praja, S. E., Agusalim, M., & Idrus, I. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-6645-6.ch007
Data‐driven Supply Chain Optimization
Niedbał, R., Pypłacz, P., & Khan, D. M. N. S. (2026) · doi:10.1002/9781394446117.ch9
Shah, S. Z., Liu, A., & Nusrat, A. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6418881
Tamtam, F., & Tourabi, A. (2026) · Applied Computer Science · doi:10.35784/acs_7703
Designing Just Reskilling Pathways for AI-Driven Logistics Transformation
Huynh, N. V. T. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-7826-8.ch011
Hail, C. E., Dahmane, A., & Mustapha, E. K. (2025) · IEEE International Conference on Advanced Technologies in Supply Chain Management (ATSCM) · doi:10.1109/atscm67505.2025.11473481
Digitalization and automatization of the supply chain in Morocco: an exploratory study
Ghoubach, S., & AMINE, B. E. (2025) · IEEE International Conference on Advanced Technologies in Supply Chain Management (ATSCM) · doi:10.1109/atscm67505.2025.11473550
Lasri, H., & Ouabouch, L. (2025) · IEEE International Conference on Advanced Technologies in Supply Chain Management (ATSCM) · doi:10.1109/atscm67505.2025.11473512
Kobbi, M., & Lamrabet, H. (2025) · IEEE International Conference on Advanced Technologies in Supply Chain Management (ATSCM) · doi:10.1109/atscm67505.2025.11473677
- Authors
- Riad, M., Naimi, M., & Okar, C.
- Affiliations
- Université Hassan 1er (MA)
- Abdelmalek Essaâdi University (MA)
- Corresponding author
- Riad, Meriem
- Venue
- Logistics
- Publisher
- MDPI AG
- Published
- 2024-11-06
- Volume
- 8
- Issue
- 4
- Pages
- 111
- ISSN
- 2305-6290 (ISSN-L)
- OpenAlex
- W4404110879
- Cited by
- 146
- References
- 52
- Citations by year
- 2026: 76 · 2025: 66 · 2024: 4
- FWCI
- 49.23
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Logistics (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Strategy and Management › Supply Chain Resilience and Risk Management
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Social Sciences › Business, Management and Accounting › Management Information Systems › Supply Chain and Inventory Management
- Keywords
- supply chain resilience, artificial intelligence, supply chain management, AI implementation, supply chain optimization, demand forecasting, inventory management, real-time visibility, supply chain risk management, operational efficiency, automation and robotics, data sharing
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