TOWARDS A GLOBAL AI-ENABLED FOURTH GENERATION DIGITAL TRANSFORMATION MODEL FOR OPERATIONAL EXCELLENCE

The study examined how artificial intelligence-driven digital transformation reshapes organizational performance across multi-country settings. Using secondary data from 218 global firms between 2020 and 2024, the research applied Structural Equation Modeling and multilevel regression to test the predictive link between AI integration, digital capability, innovation adoption, and performance outcomes. The findings revealed a strong positive association, where automation efficiency increased proportionally with AI diffusion following the model A = 0.32D + 0.47, signifying a measurable gain in operational excellence and decision accuracy. The results demonstrated that digital maturity enhanced efficiency by 38 percent and reduced costs by 31 percent, confirming that integrated data ecosystems and predictive analytics strengthen firm resilience. This research contributes to theory by extending the Technology Adoption Theory (Straub, 2009) through the inclusion of adaptive learning and AI integration as new factors, thereby broadening its explanatory scope and offering a refined framework for understanding intelligent transformation in global digital economies. The study bridges global debates on sustainable digitalization, providing insights for firms, policymakers, and researchers on how intelligent systems drive transformation in volatile markets. It recommends promoting human-machine collaboration and ethical AI governance to achieve balanced technological advancement.