ARTIFICIAL INTELLIGENCE ADOPTION AND QUALITY OF LIFE: A STRUCTURAL EQUATION MODELING APPROACH USING PLS-SEM

Abstract

Artificial intelligence has become a central component of contemporary digital transformation, influencing social interactions, access to information, and decision-making processes across multiple domains. As intelligent technologies become increasingly integrated into everyday activities, understanding their implications for human well-being and quality of life has become an important research priority. The present study examines the structural relationships between artificial intelligence adoption, perceived benefits of artificial intelligence, life satisfaction, and psychological well-being.

A quantitative and cross-sectional research design was implemented using a survey-based data collection procedure. The measurement instrument included reflective indicators measured on a five-point Likert scale. The proposed theoretical model was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) through the SmartPLS software. The analysis followed a two-step procedure consisting of the evaluation of the measurement model and the structural model. Reliability and validity were assessed through indicator loadings, composite reliability, Cronbach’s alpha, and average variance extracted. Structural relationships were examined using path coefficients, coefficients of determination, and bootstrapping procedures to determine statistical significance.

The results indicate that artificial intelligence adoption significantly influences perceived technological benefits and life satisfaction. Additionally, perceived benefits of artificial intelligence contribute positively to individuals’ evaluations of their life conditions. Life satisfaction was found to be a strong predictor of overall well-being, highlighting the role of subjective evaluations in shaping psychological outcomes. The structural model demonstrated substantial explanatory power for life satisfaction and well-being, indicating that perceptions related to artificial intelligence technologies are relevant predictors of quality-of-life indicators in digital environments.

These findings contribute to the growing interdisciplinary literature connecting technological innovation with human well-being. The study highlights the importance of designing artificial intelligence systems that enhance accessibility, efficiency, and user-centered experiences. Understanding how individuals perceive and interact with intelligent technologies is essential for ensuring that digital transformation contributes positively to human development and social well-being.