This study explores the integration of generative artificial intelligence (AI) into the pedagogical design of a hybrid practical work (PW) course in Animal Biology, addressing the challenges posed by the increasing number of students in higher education. Traditional teaching methods often struggle to meet the diverse learning needs of a growing student body, leading to overcrowded classes, insufficient equipment, and difficulties in retaining experimental procedures. Generative AI tools, such as ChatGPT, MidJourney, and Synthesia, offer innovative solutions by creating audio-visual learning resources, personalizing study paths, and providing interactive learning experiences. This research adopts the Successive Approximation Model (SAM) to design a hybrid learning environment that integrates AI-generated videos, filmed laboratory manipulations, serious games, and AI-generated quizzes. The study aims to enhance student engagement, understanding, and motivation by allowing autonomous preparation before in-person sessions. The results indicate that the hybrid approach significantly improves student engagement, comprehension of experimental procedures, and overall satisfaction compared to traditional methods. The findings suggest that the integration of AI in hybrid learning environments can effectively address the challenges of massification in higher education, making practical work more accessible, engaging, and effective.