The rapid integration of Artificial Intelligence (AI) into education necessitates a re-evaluation of teacher professional development (TPD) paradigms, particularly for pre-service teachers (PSTs) at the threshold of their careers. This paper explores new pathways for TPD through a case study focused on PSTs’ utilization of AI tools for two fundamental pedagogical tasks: lesson planning and teaching reflection. The study investigates how engagement with selected AI applications, such as those designed for generating lesson frameworks and facilitating reflective practice, influences PSTs' skill acquisition, pedagogical thinking, and overall professional growth. Key findings from the synthesized case study reveal that while AI offers considerable benefits—including enhanced efficiency in planning, the generation of novel instructional ideas, and more structured, data-informed reflection—PSTs also encounter significant challenges. These include navigating the variable quality of AI-generated outputs, developing the critical AI literacy and prompt engineering skills required for effective use, addressing ethical considerations, and achieving deep pedagogical integration beyond superficial task completion. The study underscores the importance of AI-related Technological Pedagogical Content Knowledge (AI-TPACK) and suggests that AI can foster a cycle of continuous pedagogical improvement. The implications of these findings point towards a need to reimagine TPD, embedding AI literacy and critical engagement with AI tools within teacher education curricula to prepare PSTs for an AI-augmented educational landscape. This paper contributes to the field of Artificial Intelligence Education Studies by providing empirical insights into the practical application of AI in foundational teacher training and by proposing more dynamic, personalized, and practice-oriented professional development pathways.
Yong Ding (2025) studied this question.