AI Usage and Its Correlation with Work-Life Balance and Efficiency Among BPO Employees in Ortigas Center - Galindo, Mark Gerald (International Journal of Sustainability and Advanced Integrated Research, 2026)
This study examined the relationship between artificial intelligence (AI) usage, work-life balance, and perceived work efficiency among Business Process Outsourcing (BPO) employees in Ortigas Center, Pasig City. As AI technologies continue to transform BPO operations, employees are increasingly expected to use digital tools such as chatbots, workflow automation, predictive analytics, and other AI-supported systems in managing daily tasks. Guided by the Job Demands–Resources (JD-R) model, the study treated AI as a possible workplace resource that may reduce repetitive work, support faster decision-making, and improve task performance, while also recognizing that AI adoption may create adjustment demands, training needs, and technological pressure. A quantitative correlational research design was used, with data gathered from 300 respondents across five selected BPO companies. A structured questionnaire measured the respondents’ level of AI usage, perceived work-life balance, and self-reported work efficiency. The data were analyzed using descriptive statistics, Pearson correlation, regression analysis, t-tests, and ANOVA to determine the strength and significance of the relationships among the variables. Findings showed that employees reported high levels of AI usage and generally perceived themselves as efficient in performing work-related tasks. However, inferential results revealed no statistically significant relationship between AI usage and work-life balance, nor between AI usage and work efficiency. Work-life balance also did not significantly differ when respondents were grouped according to their level of AI usage. These results suggest that AI usage alone does not directly explain differences in employee efficiency or work-life balance. The study concludes that responsible AI integration should be supported by organizational practices such as employee training, workload management, leadership support, wellness initiatives, and clear implementation guidelines to maximize the benefits of AI while protecting employee well-being.