This paper presents a multi-institutional interview study involving 12 instructors from Australia, Finland, and New Zealand to explore their perceptions and planned adaptations regarding the use of AI code generation tools in computing education. The study aims to understand how instructors with varying experiences plan to integrate these tools into their teaching practices and address the associated challenges and opportunities. The research questions focus on the threats and opportunities for learning programming, teaching and assessment, and the necessary changes in programming education. The study employs a phenomenological approach to gain deep insights into instructors' experiences and attitudes. Data was collected through semi-structured interviews, and thematic analysis was used to identify key themes. Key findings include: 1. **Learning Programming**: Instructors noted that AI tools can enhance learning by providing examples and explanations, but they also expressed concerns about students over-relying on these tools, missing out on essential learning processes, and lacking trust in the accuracy of AI-generated solutions. 2. **Teaching and Assessment**: Instructors discussed the efficiency gains in preparing learning and assessment tasks, but also highlighted the challenges of assessing students' understanding when AI tools are used. They proposed various strategies to address these issues, such as clear guidelines, invigilated assessments, and unique project assignments. 3. **Future of Programming Education**: Interviewees agreed that the advent of AI tools will significantly change programming education, requiring a rethinking of course content and assessment methods. They emphasized the importance of teaching students how to effectively interact with AI tools and integrate them into their learning. The study concludes that while AI tools present both opportunities and challenges, educators need to adapt their teaching practices to ensure students develop a deep understanding of programming fundamentals and can effectively use AI tools in a responsible manner. The findings highlight the need for further research and collaboration between researchers and educators to develop best practices and pedagogical strategies for integrating AI code generation tools into computing education.This paper presents a multi-institutional interview study involving 12 instructors from Australia, Finland, and New Zealand to explore their perceptions and planned adaptations regarding the use of AI code generation tools in computing education. The study aims to understand how instructors with varying experiences plan to integrate these tools into their teaching practices and address the associated challenges and opportunities. The research questions focus on the threats and opportunities for learning programming, teaching and assessment, and the necessary changes in programming education. The study employs a phenomenological approach to gain deep insights into instructors' experiences and attitudes. Data was collected through semi-structured interviews, and thematic analysis was used to identify key themes. Key findings include: 1. **Learning Programming**: Instructors noted that AI tools can enhance learning by providing examples and explanations, but they also expressed concerns about students over-relying on these tools, missing out on essential learning processes, and lacking trust in the accuracy of AI-generated solutions. 2. **Teaching and Assessment**: Instructors discussed the efficiency gains in preparing learning and assessment tasks, but also highlighted the challenges of assessing students' understanding when AI tools are used. They proposed various strategies to address these issues, such as clear guidelines, invigilated assessments, and unique project assignments. 3. **Future of Programming Education**: Interviewees agreed that the advent of AI tools will significantly change programming education, requiring a rethinking of course content and assessment methods. They emphasized the importance of teaching students how to effectively interact with AI tools and integrate them into their learning. The study concludes that while AI tools present both opportunities and challenges, educators need to adapt their teaching practices to ensure students develop a deep understanding of programming fundamentals and can effectively use AI tools in a responsible manner. The findings highlight the need for further research and collaboration between researchers and educators to develop best practices and pedagogical strategies for integrating AI code generation tools into computing education.