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Professor, Department of Management Studies, SRM Valliammai Engineering College, Tamil Nadu, India
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Professor and Head, Department of Management Studies, Dayananda Sagar Academy of Technology and Management, Bangalore, Karnataka, India
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Assistant Professor, Department of Corporate Secretaryship and Accounting & Finance, Faculty of Science and Humanities, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, India
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Assistant Professor, Department of Commerce, Faculty of Science and Humanities, SRM Institute of Science and Technology, Ramapuram, Tamil Nadu, India
Assistant Professor, Department of Commerce, Faculty of Science and Humanities, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, India
AI is rapidly redefining how customer-oriented companies conduct their businesses through process automation, decision-making, and improved customer service. However, the influence of AI is lacking regarding employee well-being. This paper is focused on researching the connection between AI adoption and employee well-being by assessing the effects of AI on the level of job satisfaction, work engagement, work-life balance, organizational support and overall employee well-being in an AI-enabled workplace. The unique character of this research lies in an integrated employee well-being assessment framework designed and tested in the context of customer-centric organizations, where both the adoption of AI and other critical organizational aspects are taken into account while assessing employee well-being. The data were collected through a questionnaire filled in by 350 employees working for customer-centric companies, and the quantitative research methodology was applied. Descriptive statistics, reliability analysis, Pearson correlation, and multiple regression were used for the data analysis. Experimental work has proved the high reliability of the used questionnaire with a 0.87-0.92 Cronbach's alpha coefficient. The relationship between employee well-being and AI adoption was found to be highly positive with a Pearson correlation coefficient of 0.84, whereas the regression model accounted for 71% of the modification in employee well-being with R² = 0.71. Moreover, the developed framework reached an Employee Well-Being Score of 90.1%. The findings indicate that the proper implementation of AI together with organizational efforts and an approach focusing on employees may greatly contribute to improvements in well-being, engagement of workers, and organizational performance. The conclusions obtained during the research provide valuable suggestions for organizations that need to be successful in their endeavors toward sustainable digital transformation and a healthy and productive workforce.
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