Browsing by Author "MUHAMMAD ASIM SOHAIB"

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    AI-DRIVEN WORKLOAD OPTIMIZATION TO ENHANCE ECONOMIC SUSTAINABILITY:
    (umt.lahore, 2025) MUHAMMAD ASIM SOHAIB
    The application of Artificial Intelligence-Driven Workload Optimization is reshaping the management of operations in organizations, but still little is understood about its overall effects on sustainable performance.
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    Ai-driven workload optimization to enhance economic sustainability:
    (UMT Lahore, 2025) MUHAMMAD ASIM SOHAIB
    The application of Artificial Intelligence-Driven Workload Optimization is reshaping the management of operations in organizations, but still little is understood about its overall effects on sustainable performance. The current study would test the direct effects of Artificial Intelligence-Driven Workload Optimization on Economic Sustainability and test the mediating effects of Employee Well-Being and Employee Productivity. The study seeks to furnish an integrative theory of interaction between the implementation of artificial intelligence and humanistic-oriented variables that would foster a sustainable business result. A sample size of 380 structured questionnaires was sent to the various professionals in the HR, operations, sales and marketing department of various public and private organizations but 265 were analyzed. The findings of the study confirmed that Artificial Intelligence-Driven Workload Optimization produces a substantial positive impact on Economic Sustainability using Partial Least Squares Structural Equation Modeling (PLS-SEM). Also, Employee Well Being and Employee Productivity were identified to partially mediate it, and the same underlines the fact that AI technologies provide the best outcomes when they may be aligned with employee’s well-being and performance-enhancing strategies. The results contribute to the theoretical knowledge of AI incorporation in the concepts of sustainable businesses as it shows that not only a technological adoption has an impact on Economic Sustainability, but also organizational investment in human capital. This paper demonstrates the importance of synchronizing AI-based plans and employee-oriented programs, which supports the notion that successful results should be based on strikes a balance between innovation and employee well-being. The findings provide practical implications to business professionals and policymakers who want to derive the positive dynamics of applying AI and develop a productive and resilient organizational culture.