Analysis of Artificial Intelligence Technology Adoption in an Educational Environment: Open AI Case Study Using the Innovation Diffusion Theory Framework (IDT)

This study aims to identify factors that influence the adoption of artificial intelligence (AI) technology, specifically the ChatGPT chatbot, in the context of higher education in Indonesia. Using an extended Innovation Diffusion Theory (IDT) framework, this study analyzed variables such as Relative Advantage (RA), Compatibility (CO), Trialability (TR), Trust (TRU), Perceived Ease of Use (PEU), Perceived Usefulness (PU), and Behavioral Intention (BI). Data were collected through an online survey from 400 college students in Indonesia and analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method. The results showed that Compatibility and Trust have a significant positive influence on Behavioral Intention, emphasizing the importance of technology compatibility with academic needs and trust in technology. In contrast, Relative Advantage and Trialability did not show significant influence, indicating that relative advantage and trialability are not strong enough to drive ChatGPT adoption. In addition, the relationship between Perceived Ease of Use and Behavioral Intention was also insignificant, suggesting the presence of other factors that are more relevant in the educational context. This research provides practical implications for educational institutions to increase student awareness of the benefits of chatbots, provide opportunities to try this technology, and build trust through assurances of safety and reliability. Theoretically, this research extends the literature on IDT by integrating additional elements such as Trust and Perceived Ease of Use, providing new insights into the dynamics of AI technology adoption in the digital era.