AI Dependence and its Impact on Human Decision-Making Quality and Supply Chain Efficiency

Authors

• Jesus Salazar, St. Mary's University
• Leonardo Fabbri, St. Mary's University
• Axel Villegas, St. Mary's University

Files

Contributor

Swain, Ajaya (Faculty Mentor)

Digital Publisher

Digital Commons at St. Mary's

Publication Date

Spring 2026

Keywords

Artificial Intelligence (AI), Supply Chain Management, Efficiency

Description

• Artificial Intelligence (AI) is transforming supply chain management by enabling:
  • Data-driven decision-making
  • Improved forecasting accuracy
  • Enhanced operational efficiency (Choudhary et al., 2023; Ivanov & Dolgui, 2021)
• AI applications such as predictive analytics support:
  • Inventory optimization, Logistics planning
  • Procurement decisions in real time
• However, increasing reliance on AI introduces risks:
  • Automation bias (over-trusting AI outputs)
  • Reduced human critical thinking
  • Overdependence on algorithmic recommendations (Raisch & Krakowski, 2021)
• This study examines the dual impact of AI dependence on:
  • Decision-making quality
  • Supply chain efficiency
• Objective:
  • Identify whether AI improves performance or reduces human effectiveness
  • Determine the optimal balance between AI support and human judgment

Format

PDF

Size

1 poster

City

San Antonio, Texas

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.