Dental education has significantly evolved, transitioning from traditional lectures to interactive, student-centered approaches such as team-based learning (TBL) and artificial intelligence (AI) integration. Traditional lectures efficiently deliver content but foster passive learning, limiting critical thinking and practical skill development. Problem-based learning (PBL) promotes active inquiry but faces resource limitations. TBL addresses these challenges, offering a structured, collaborative learning environment that enhances critical thinking, clinical reasoning, and student engagement through immediate feedback and shared accountability. Recent advancements in generative AI, including tools like ChatGPT, further enrich dental education by providing personalized, adaptive learning experiences. AI-driven simulations allow students to engage with realistic clinical scenarios safely, enhancing their decision-making and practical skills. However, integrating AI introduces ethical and practical concerns, notably data privacy, transparency, and algorithmic biases. Empirical studies affirm TBL’s effectiveness in boosting academic performance, engagement, and satisfaction. Integrating TBL with AI creates a potent educational model, bridging theoretical knowledge and clinical practice effectively. Globally, institutions increasingly adopt this combined approach, resulting in improved clinical competence and enhanced student preparedness. Effective implementation demands well-aligned curricula, comprehensive faculty training, strategic resource allocation, structured facilitation, and ongoing evaluation. This chapter explores theoretical foundations, compares educational models, addresses ethical considerations, and offers practical implementation guidance. Embracing TBL and AI integration enables dental educators to significantly improve learning outcomes and effectively prepare graduates for contemporary clinical and professional challenges.