This paper explores the multifaceted potential of GenAI in transforming educational practices, emphasizing its role in adaptive learning, student engagement, and administrative efficiency. By analyzing case studies and empirical research, we illustrate how GenAI tools enhance both student learning outcomes and faculty productivity through personalized interventions, real-time feedback, and automated administrative processes. However, these advancements are accompanied by significant challenges, including ethical concerns like data privacy, algorithmic bias, and over-reliance on AI tools. The paper highlights the need for a balanced approach, recommending robust frameworks for bias mitigation, ethical AI integration, and inclusivity. Key strategies such as dataset diversification, stakeholder collaboration, and transparency mechanisms are identified as essential for addressing these challenges. Furthermore, this work underscores the critical role of regulatory frameworks, AI literacy programs, and faculty training in ensuring the responsible use of GenAI in academic settings.