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Towards a Decision-Support Framework: AI Applications in Supply Chain Optimization

Year: 2025

Type: article

Abstract: : The complexity of modern supply networks requires decision tools that combine predictive power with human judgment. This paper presents a synthesized, original framework for integrating artificial intelligence into supply chain decision making. It examines AI applications in demand forecasting, inventory control, logistics, supplier risk evaluation, and production scheduling, then proposes a four-layer decision-support architecture that balances automated analytics with managerial oversight. The framework emphasizes explainability, data governance, and workforce readiness to mitigate ethical and operational risks. Practical recommendations guide organizations seeking resilient, sustainable, and transparent AI-assisted supply chains. Keywords: Artificial Intelligence; Supply Chain Optimization; Decision Support Framework; Ethical AI; Resilience.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.18678150

Authors: LAVANYA N KARTHIK, SHUBHA K S, BINDUSHREE R

Language: English

Topic: Impact of AI and Big Data on Business and Society

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W7130364174

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