What motivates academics in Egypt toward generative AI tools? An integrated model of TAM,SCT,UTAUT2,perceived ethics,and academic integrity

Abstract

In recent years, the adoption of AI technologies in academia has increased, prompting a need to explain factors driving scholars to adopt or plan to adopt AI technologies in research routines. This study integrates three models into one integrated model: TAM, UTAUT, and SCT. These three models are combined to understand how GenAI self-efficacy, perceived ethics, academic integrity, social influence, facilitating conditions, perceived risks, ease of use, and perceived usefulness influenced the participants’ intention to adopt GenAI in research. Following this, data were collected from Egyptian academics linked to Egyptian universities. There were 742 responses to this question. Data were analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The paper's results showed that GenAI self-efficacy, social influence, and perceived ethics are significantly related to perceptions of ease of use, usefulness, and intention to use GenAI. Facilitating conditions have a negative effect on perceived ease of use, and perceived risk does not affect perceived usefulness or intention to use significantly. Notably, the result found that ethics and academic integrity affect perceptions of GenAI's usage and utility. This guide illustrates how universities must take proactive steps to influence how AI will be used and reinforces the importance of using these tools within an ethical lens. This paper emphasizes the need to balance the use of generative AI and ethical practices. It examines the role of ethics and academic integrity in perceptions that influence attitudes toward the use of generative AI. They represent a step forward in our understanding of how to induce AI adoption–in this case, in the academic context, and specifically in Egypt. Additionally, it places sound emphasis on the role of AI technology and how it can be beneficial whilst advocating for a sensible approach in that application, which includes ethical principles.