The introduction of Artificial Intelligence (AI) into Quality Management Systems (QMS) is causing the organizations to begin to perceive quality assurance and process improvement in a new way. The given current research focused on the investigation of the impact of three fundamental independent variables, Scalability of AI Integration, Ethical Implications of AI, and AI Integration Challenges, on the Effectiveness of AI-Driven QMS in the context of the Cost-Effectiveness analysis. There was quantitative research methodology through structured questionnaire that was conducted in different classes of industries in Pakistan. The overall valid responses collected and analyzed are 284 and this was done through the use of Partial Least Squares Structural Equation Modeling (PLS-SEM) using R programming environment. The results of structural models indicated that constructs have very significant relationships. Only the mediating effect of cost-effectiveness was positively associated with scalability and ethical practices, but AI integration challenges had a direct positive effect and an indirect effect through cost-effectiveness. The research made both theoretical and practical contributions through validation of a SEM. It provides viable recommendations to quality professionals, policymakers and institutions that aim at having scalable ethical AI practices. The next research can compare various sectors and evaluate the things in the long run to demonstrate how AI will transform the quality systems.