This workshop proposal aims to inform the design of teacher training on equity in the use and teaching of AI. AI is transforming both teaching practices and student learning environments and learning content. Teachers are increasingly using AI tools for course planning, some AI-based tools are being integrated into schools (e.g., for language learning), and educators are also responsible for teaching AI concepts. While equity has been recognized as a critical concern, potential equity issues are complex and depend on various factors, including school level, student demographics, the type of AI used (generative or predictive), and whether AI tools support student learning or assist teachers in planning and assessment. Additionally, inequities may emerge when teaching AI. A comprehensive understanding of equity issues is essential to inform teacher training that provides teachers with equity issues that emerge in their specific context and equips them with the necessary skills to use AI responsibly in the classroom. This workshop aims to develop such an overview by bringing together a multidisciplinary group of researchers and practitioners with experience with AI education, professional development, AI fairness, predictive and generative AI biases, and inequities in digital education. Through case studies and discussions, the workshop will identify and categorize various equity challenges, laying the foundation for future research on AI teacher training and informing the development of context-specific guidelines for equity for AIED.