Artificial Intelligence as a Catalyst for Strengthening the Strategic Value of Quality Management

Document Type : Original Article

Authors

1 Assist. Prof., Dept. of Strategic Management, Faculty of Management and Industrial Engineering, Malek Ashtar University of Technology, Tehran, Iran.

2 Ph.D., Dept. of Aerospace Engineering, Faculty of Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

3 Assistant Professor of the Faculty of Electrical and Computer Engineering, Malek-e-Ashtar University of Technology, Tehran, Iran

10.22091/jdaid.2026.15903.1049

Abstract

This study proposes a comprehensive vision for integrating Artificial Intelligence (AI) into quality management practices, emphasizing its strategic contributions to organizational performance, process reliability, and continuous improvement. To evaluate this impact, we conducted a systematic review of recent literature combined with a simulation-based evaluation. This research specifically explores how AI technologies enhance critical quality functions, such as automated inspection, predictive auditing, and real-time performance monitoring.Our results, supported by regression and correlation analyses, indicate a significant positive association between AI implementation and key performance indicators, specifically in defect reduction, process optimization, and adherence to quality standards. However, the effective adoption of AI also presents notable hurdles. Challenges regarding data quality and integrity, algorithmic transparency, and the need for greater organizational readiness remain critical considerations. Addressing these factors is essential for ensuring reliable and responsible implementation. Ultimately, this study introduces a strategic framework designed to assist organizations in adopting AI-driven solutions. This approach allows businesses to harness the power of intelligent systems while maintaining ethical principles, ensuring that their quality management practices remain sustainable and effective in an increasingly digital environment.

Keywords

Main Subjects

References

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Journal of Data Analytics and Intelligent Decision-making
Volume 2, Issue 3 - Serial Number 6
September 2026
Pages 122-141

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