AI Innovation, Green Learning, and Sustainable Attitudes: Pathways to Green Technology Adoption in Universities

The integration of artificial intelligence (AI) into sustainability efforts has appeared as a serious pathway for fostering green practices, especially within academic institutions. This study investigates the interplay between Cognitive AI Innovation (CAII), Responsible AI Use (RAIU), Green Consciousness (GC), Green Digital Learning Orientation (GDLO), Sustainability Attitude (SA), and their collective impact on the “Adoption of Green Technologies (AGT)” through the mediating role of AI Use for Green Technologies (AIGT). Drawing on the “Theory of Planned Behavior (TPB)” and Perceived Benefit Theory (PBT), this study proposes a comprehensive model explaining the behavioral, cognitive, and technological factors influencing sustainable technology adoption. The research applied a quantitative study design in which data were gathered via structured questionnaires from 385 university students through purposive sampling. "Structural Equation Modeling (SEM)" with SmartPLS 4.0 was utilized for analysis of data and hypothesis testing. The results demonstrate that CAII, RAIU, GC, and GDLO significantly influence both AIGT and SA, while SA and AIGT positively impact AGT. Notably, AIGT emerged as a significant mediator in the model, bridging cognitive, attitudinal, and digital learning orientations with the final adoption outcome. The findings have practical implications for educational representatives and institutional leaders, suggesting that fostering AI competencies, responsible AI practices, and green digital learning can accelerate green technology integration in educational environments. Future research may explore longitudinal impacts and cross-cultural validations to enhance generalizability.