Sustainable design principles, including circular design and life cycle assessment (LCA), are increasingly vital in architecture and product design education, yet they remain challenging to teach with traditional methods. This paper proposes a practical pedagogical framework that integrates artificial intelligence (AI) tools – specifically a knowledge-based system (KBS) combined with a large language model (LLM) – to enhance the teaching of circular design and LCA. It justifies the use of AI in sustainability-focused design curricula, highlighting how AI-driven tools can provide interactive, real-time feedback and expert knowledge to students. The environmental footprint of generative AI is reviewed, addressing energy use, carbon emissions, water consumption, material resources and electronic waste, with up-to-date data from 2019–2025. The study discusses how the educational benefits of AI can outweigh these environmental costs when sustainable AI practices are applied. The proposed AI-KBS + LLM framework is presented as a conceptual prototype: the KBS component supplies domain-specific LCA data and design heuristics, while the LLM offers natural language interaction and contextual reasoning, enabling students to receive tailored sustainability advice during the design process. The study outlines the framework’s components and workflow. Potential pedagogical benefits – from democratising access to sustainability expertise to fostering iterative, reflection-driven design – are analysed alongside ethical considerations, such as managing AI’s biases and environmental impact. The paper concludes that, with mindful implementation, AI-augmented learning can empower future designers to create more sustainable, circular solutions while the AI’s own footprint is mitigated through responsible practices.