This study aims to investigate the ethical and unethical use of Generative AI (GenAI) in academia. Specifically, it examines Kuwait University faculty members’ perceptions of GenAI use among them and their students with respect to academic integrity.
A mixed-methods approach was used using an online semi-structured survey administered via the Qualtrics platform. Descriptive analysis was applied to the quantitative items, and thematic analysis was conducted on the qualitative open-ended responses.
Faculty responses revealed uneven awareness of GenAI and widespread uncertainty regarding appropriate and inappropriate uses in teaching and research. Participants emphasised two priority needs: structured GenAI literacy initiatives and clear institutional policies defining ethical and unethical GenAI practices. Drawing on these findings and building on the AI4People ethical framework proposed by Floridi et al. (2018), the study introduces “AI4Academia” as an emerging model for guiding the ethical integration of GenAI in higher education. The model supports governance development, faculty training and student guidance, and may be transferable to comparable contexts.
This findings of this paper contributes to the emerging body of literature on GenAI in higher education by providing an empirically grounded model (AI4Academia) that integrates faculty perspectives based on their actual experiences and challenges into the discourse on AI adoption. It extends existing work by linking technology with academic integrity and governance considerations, offering a conceptual bridge between innovation adoption and ethical oversight in educational contexts.
The findings highlight the need for higher education institutions to adopt a coordinated approach to GenAI integration, focusing on literacy programmes, clear policies and ongoing faculty development. The AI4Academia model offers a structured framework to support governance, teaching practices and training, ensuring ethical and transparent use. The study also contributes practical and scholarly value by informing institutional and policy strategies, particularly in non-Western contexts, and emphasises the importance of transparency and accountability in AI adoption.
The study contributes novel empirical evidence from a non-Western higher education context and extends the AI4People framework into the academic domain through the development of the AI4Academia model. By grounding ethical principles in faculty perspectives, the model bridges the gap between abstract AI ethics and practical policy design, offering a data-driven and empirically grounded framework for responsible GenAI adoption while safeguarding academic integrity.
