The AI-driven Decision-Making (AIDM) Framework: Integrating AHP and ChatGPT for Supplier Selection

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Authors: Negar Sadeghi, Mohammad Dehghanimohammadabadi, Nihan Kabadayi
Cited by: 2
References: 35

Abstract

Abstract The integration of Artificial Intelligence (AI) into decision-making is transforming industry norms by enabling smarter, faster, and more reliable decisions. This paper presents a novel approach for supplier selection in manufacturing by combining the Analytic Hierarchy Process (AHP) with the Generative Pre-trained Transformer (GPT). Using GPT as virtual agents to mimic expert evaluations automates the supplier selection process, significantly improving efficiency. The study demonstrates the effectiveness of large language models as virtual experts in complex decision-making, highlighting AI’s crucial role in strategic manufacturing operations. Comparing GPT’s assessments with human expert judgments confirms the model’s reliability and effectiveness in optimizing supplier selection. This approach enhances decision-making processes and emphasizes the broad utility of AI-centric methodologies in various industries.

Fields of Study & Subjects

Forecasting Techniques and Applications Digital Transformation in Industry Explainable Artificial Intelligence (XAI)

Publication details

Journal / source
Annals of Operations Research
Publisher
Springer Science and Business Media LLC
Volume
359
Issue
3
Pages
2593–2615
Publication date
12 March 2026
Language
EN