Yapay zekâ tabanli karar verme süreçleri ile kalite yönetimi yenilik yaklaşimlarinin değerlendirilmesi
An Evaluation of AI-Based Decision-Making Processes and Innovation Approaches in Quality Management

Summary/Abstract: In today's rapidly digitalizing business world, the impact of AI technologies on decision-making processes and quality management is increasing. Data-driven and predictive approaches, which are replacing traditional methods, enable businesses to make faster, more accurate, and more effective decisions while also contributing to raising quality standards and ensuring sustainability. This study aims to examine the integration of AI-supported decision-making systems into quality management processes and the strategic advantages this integration provides to businesses. Within the scope of our study, we first explain the concept of artificial intelligence, its historical development, and its relationship with decision support systems. We then examine the concept of quality management, its evolution, and the changing application forms it faces today with digitalization. We evaluate how international standards such as ISO 9001 integrate with AI-based systems. The main focus of the study analyzes the applications of AI technologies in areas such as quality control, customer feedback analysis, process optimization, and predictive maintenance, with case examples. The research examined in detail the AI-powered quality practices of leading global companies such as Siemens, General Electric, Toyota, Bosch, IBM, Amazon, and Unilever, assessing the benefits these practices offer businesses, the challenges they face, and future prospects. The findings demonstrate that AI not only improves quality but also enhances businesses' decision-making capabilities, increases customer satisfaction, and significantly increases operational efficiency.

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