We tested whether ChatGPT can play a role in designing field courses in higher education. In collaboration with ChatGPT, we developed two field courses; the first aimed at creating a completely new field trip, while the second was tailored to fit an existing university module, and then compared to the human module design. From our case studies, several insights emerged. These include the importance of precise prompt engineering and the need to iterate and refine prompts to achieve optimal results. We outlined a workflow for effective prompt engineering, emphasising clear objectives, sequential prompting, and feedback loops. We also identify best practices, including highlighting the importance of collaborating with human expertise, validating AI suggestions, and integrating adaptive management for continual refinement. While ChatGPT is a potent tool with the potential to save a significant amount of time and effort in field course design, human expertise remains indispensable for achieving optimal results.