This study explores the capabilities and perceptions of undergraduate business administration students regarding artificial intelligence (AI) and its potential to address sustainable development challenges. The research aims to identify suitable pedagogical solutions to enhance knowledge and understanding in these areas. The study employed a workshop-based approach, including introductory lectures, surveys, questionnaires, group discussions, and reflective narratives. Data analysis was conducted using an abductive qualitative methodology. Key findings include: 1. **Students' Current Knowledge and Perceptions**: Students had limited knowledge about AI and its applications, with many lacking a deeper understanding. They recognized the importance of AI but acknowledged their own limitations. 2. **Workshop Impact**: The workshop helped students understand the potential of AI in sustainable development, though they struggled with linking AI to specific sustainable development goals (SDGs). Group dynamics showed that deeper understanding among group members improved overall comprehension. 3. **Challenges and Pedagogical Solutions**: Students identified a lack of prior introduction to AI and sustainability topics, as well as unclear instructions and questions. They suggested more in-depth lectures and clearer examples to enhance learning. The study also developed a taxonomy of AI literacy in sustainable development, which can serve as a reference for course planning and learning tasks in higher education. The study concludes that AI literacy is crucial for sustainable development, and higher education institutions play a significant role in integrating AI and sustainable development into curricula. The findings provide insights into pedagogical models that can effectively promote AI literacy in higher education.This study explores the capabilities and perceptions of undergraduate business administration students regarding artificial intelligence (AI) and its potential to address sustainable development challenges. The research aims to identify suitable pedagogical solutions to enhance knowledge and understanding in these areas. The study employed a workshop-based approach, including introductory lectures, surveys, questionnaires, group discussions, and reflective narratives. Data analysis was conducted using an abductive qualitative methodology. Key findings include: 1. **Students' Current Knowledge and Perceptions**: Students had limited knowledge about AI and its applications, with many lacking a deeper understanding. They recognized the importance of AI but acknowledged their own limitations. 2. **Workshop Impact**: The workshop helped students understand the potential of AI in sustainable development, though they struggled with linking AI to specific sustainable development goals (SDGs). Group dynamics showed that deeper understanding among group members improved overall comprehension. 3. **Challenges and Pedagogical Solutions**: Students identified a lack of prior introduction to AI and sustainability topics, as well as unclear instructions and questions. They suggested more in-depth lectures and clearer examples to enhance learning. The study also developed a taxonomy of AI literacy in sustainable development, which can serve as a reference for course planning and learning tasks in higher education. The study concludes that AI literacy is crucial for sustainable development, and higher education institutions play a significant role in integrating AI and sustainable development into curricula. The findings provide insights into pedagogical models that can effectively promote AI literacy in higher education.