ABSTRACT Background This study explored the factors that influence the balance between academic integrity and the effective use of GenAI tools in higher education. It focused on the role of institutional guidelines in enhancing the responsible use of GenAI technologies to enhance academic integrity. Objectives The study was theoretically grounded in the Technology Acceptance Model and the Theory of Planned Behaviour to investigate the factors that promote academic integrity in using GenAI tools (RQ1), their impact and institutional strategies to effectively mitigate ethical risks (RQ2) and the model practices to support the ethical and effective use in higher education (RQ3). Methods The PRISMA framework was used to systematically review and thematically synthesise the results of 213 peer‐reviewed articles published between January 2021 and May 2025. Results Finding indicates that academic support, defined by structured training, technical scaffolding, and perceived usefulness, is critical to enabling ethical GenAI use. Additionally, student self‐regulation, as influenced by behavioural control and goal setting, was associated with greater academic integrity in GenAI‐mediated learning. Whereas institutional policies varied widely, those with transparent, adaptive and discipline‐responsive governance frameworks more effectively mitigated academic misconduct. Indeed, the model practices included GenAI ethics committees, interactive GenAI literacy modules, and the developer‐educator collaborations to promote algorithmic transparency. Conclusions A comprehensive systems‐based approach that encompasses academic support, self‐regulation and ethical guidelines is critical for the responsible use of GenAI tools in education. Hence, to preserve academic integrity while nurturing innovation, institutions should integrate GenAI ethics into curricular design, faculty development and cross‐sectoral policy frameworks. Future research may expand into multilingual and longitudinal analyses to support equitable and sustainable GenAI integration across diverse educational settings.
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