Equitable Integration of Generative Artificial Intelligence in Higher Education

The rapid adoption of generative artificial intelligence (GAI) has introduced both opportunities and inequities in higher education. While these technologies can personalize learning, improve administrative efficiency, and expand access to information, they also magnify long-standing digital disparities. Digital inequality, historically defined by differences in access, autonomy, skill, social support, and purpose, now extends into the realms of algorithmic fluency and tool literacy. Drawing on Bourdieu’s theory of cultural capital and Actor-Network Theory, the analysis examines how inequitable access to and understanding of GAI affect students, educators, and institutions. The discussion highlights ethical and policy challenges, including bias, privacy, and academic integrity, and proposes a framework for equitable GAI adoption centered on access, literacy, and ethics. The article concludes that higher education leaders must approach GAI integration with a focus on transparency, adaptability, and inclusion to ensure that digital transformation enhances, rather than reinforces, educational inequality.