A Conceptual Framework for Identifying Risks of AI Integration in Higher Education

The integration of Artificial Intelligence (AI) into Higher Education (HE) presents a dual-edged sword, offering transformative potential while introducing significant risks.This paper synthesizes existing literature to examine the multifaceted challenges associated with AI adoption in academic settings, including threats to academic integrity, algorithmic biases, data privacy concerns, and the erosion of critical human skills.This paper proposes the HE AI Risk Ecology (HE-AIRE) model, a conceptual framework that categorizes these risks into four interconnected layers: pedagogical, technological-ethical, institutional-operational, and socioeconomic-cultural.By highlighting systemic interdependencies, the model underscores the need for holistic strategies to mitigate risks while harnessing AI's benefits.The study calls for robust ethical frameworks, equitable implementation, and proactive policy interventions to ensure AI aligns with the core values of HE.