This chapter addresses the integration of AI into K-12 science education from a multifaceted perspective. First, it discusses how science teachers should be prepared for digital transformation, focusing on the concepts of AI-based technological pedagogical content knowledge model and teacher literacy. Then, ethical and pedagogical issues in AI-enabled learning environments are addressed, with an emphasis on data security, algorithmic biases, and the importance of inclusive teaching. Student modeling and learning analytics examine the role of AI in providing individualized feedback, analyzing student behavior, and interpreting learning data to inform instruction. Interdisciplinary approaches, problem-based learning, and engineering design processes are detailed within the framework of integrating AI into STEM education. Finally, the future of ethical leadership and teacher education with AI in education is discussed, and sustainability, professional development, and policy recommendations are presented in teacher training programs.