Understanding the Different Generational Motivations and Adoption of AI in Families: Integrating Technology Acceptance and Uses and Gratifications Theory

Abstract

This study examines AI adoption within families through a generational lens, revealing how age-related motivations shape AI engagement across generations. By integrating the Technology Acceptance Model (TAM) and Uses and Gratifications (U&G) theory, this research explores extrinsic and intrinsic drivers of AI use, uncovering how factors influence AI adoption among adolescents and parents. Surveying 120 families, including 200 adolescents and 160 parents, we employed SEM-PLS to validate our model, revealing distinct patterns in AI preferences across age groups. Findings indicate that while ease of use, usefulness, and socialization consistently drive AI engagement, personal integrative factors are especially impactful within the Iranian context. Our results highlight intergenerational differences that inform family-centered AI design and policy, offering a culturally nuanced framework for AI development that bridges generational divides. This study delivers insights for policymakers, and researchers, providing a roadmap for inclusive AI adoption strategies that honor cultural and generational needs within families.