Abstract

The integration of Artificial Intelligence (AI) in education has transformed learning environments, pedagogical strategies, and assessment mechanisms. However, this digital shift also presents critical ethical challenges related to bias, privacy, and the integrity of educational processes. This paper examines how institutions can balance innovation with ethical responsibility by promoting transparent data governance, equitable algorithmic design, and learner-centered AI applications. Through an interdisciplinary lens, it explores the potential risks of algorithmic discrimination, surveillance concerns, and the erosion of academic integrity while emphasizing frameworks for responsible AI adoption. The study advocates for policy interventions, ethical literacy, and stakeholder collaboration to ensure that AI in education remains inclusive, fair, and trustworthy.