A critical review and actionable framework for integrating generative AI into teacher professional development

Abstract Generative Artificial Intelligence (GenAI) is increasingly influencing teacher professional development, yet systematic understanding of its pedagogical affordances and implementation strategies remains limited. This critical review synthesizes 20 peer-reviewed studies (16 empirical and 4 conceptual) published between 2023 and 2025, examining GenAI framework development, implementation strategies, and affordance analysis in teacher professional development contexts. Our analysis identifies four affordance categories: functional (content co-creation, instructional design), cognitive (higher-order thinking, knowledge construction), social (human–AI partnership models), and reflective (self-efficacy building). While constructivist principles appear in approximately two-thirds of studies, fewer than one-third explicitly engage with the TPACK framework, highlighting theoretical gaps. Implementation challenges include limited prompt engineering training and variable ethical framework development. We propose the GenAI-Enhanced Teacher Professional Development (GenAI-TPD) framework comprising five core competency domains and four progressive developmental stages, operationalized through testable propositions and observable indicators that provide actionable guidance for researchers and practitioners.