Writing Harvard Business School-style case studies is both a science and an art form. Personally, my favorite part is crafting a compelling narrative that immerses students in a real-world business dilemma, forcing them to analyze, debate, and decide. However, for many faculty, the most challenging and time-consuming part isn’t writing the case—it’s the teaching note.
Teaching notes serve as a roadmap for instructors which include key learning objectives, offer a structured way to guide classroom discussions, and anticipate student responses. Developing a strong teaching note demands deep pedagogical thinking, scenario planning, and articulation of insights in a way that is both comprehensive and adaptable. This is where generative AI has become an important research assistant for me, as I dig myself out of a backlog of lingering and not-yet-finalized teaching notes.
The Bottleneck in Case Writing
Traditionally, after completing a case study, I teach it two to three times before considering the case content “final” and attempt to craft the accompanying teaching note. Writing and refining the teaching note is a process that I dread because quite often, I’m ready to move on to the next case—the next new thing—and I am slightly tired of the case that needs me to sit down and do the pedagogical thinking required for a teaching note. Even with my deep familiarity with the case, translating its nuances into a crisp, instructor-friendly note requires additional cognitive effort and a significant time investment.
How Generative AI Accelerates the Hardest Part
Inspired by Matthew Schonewille’s September 2024 presentation about using AI to support case writing, I decided to try leveraging generative AI tools to help me conquer four teaching notes. Rather than staring at a blank page, I can now prompt AI with the key elements of the case—its protagonist, dilemma, main themes, and intended learning outcomes—and let it generate structured content that serves as a first draft. The AI can quickly produce:
- Suggested discussion questions, ordered by complexity
- A logical session flow, including cold-call prompts and pivot points
- Summary insights that instructors can use to reinforce takeaways
- Alternative angles for framing the case in different classroom settings
- References to relevant academic theories and frameworks
From First Draft to Final Product
Of course, AI-generated content is not a perfect, plug-and-play solution. It still requires human oversight and refinement. Because I’ve taught the case two to three times, I have plenty of ideas of my own that I want to add to what AI produces or use to re-direct AI’s suggestions. However, what once took weeks to structure and draft now takes days. Instead of spending my time on the mechanics of writing, I can focus on refining insights, enhancing clarity, and ensuring the teaching note is tailored to the specific nuances of the case. Beyond efficiency, AI has also helped generate alternative discussion paths and sparked ideas I might not have considered on my own.
The Future of Case Writing with AI
Generative AI is not replacing the skill of case writing—it is enhancing it. By accelerating the most labor-intensive part of the process, AI allows me to focus on my preferred activity: crafting rich, thought-provoking cases that shape the next generation of business leaders. I can confidently say that AI has turned my biggest case-writing bottleneck, the teaching note, into an opportunity for deeper impact and creativity. For anyone struggling with the teaching note development process, I suggest leveraging AI as your assistant, not your replacement.
