Hey Fellow Case Writers!

I’ve been reflecting on how tools like ChatGPT, Claude and Gemini are changing the way we teach and learn. Recently, I came across a conference paper that explored how tools like ChatGPT can change the way we design and deliver learning experiences. Specifically, it focused on using ChatGPT to create business case studies for MBA students.

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If you’ve ever worked with case studies, you know how valuable they are in business education. They help students tackle real-world problems, make tough decisions, and develop their leadership and analytical skills. But creating these case studies is no small feat. The process involves:

• Months of research and data collection.

• Collaborations with businesses to gather real-world insights.

• Fine-tuning the content to fit the course objectives.

Even after all that effort, case studies can quickly feel outdated in today’s fast-changing world. Students might lose interest if the material doesn’t align with current trends or challenges.

A Fresh Approach with ChatGPT

The paper detailed how educators used ChatGPT to create a case study for a company called RedLine. RedLine is a mobile firefighter turnout gear cleaning service started by a firefighter who wanted to reduce cancer risks for his peers. Their innovative approach involves using Mobile Extraction Units (MEUs) to clean gear on-site within 48 hours, compared to traditional cleaning methods that can take days.

Here’s where ChatGPT came in: The researchers used it to help analyze franchise opportunities for RedLine. By feeding it well-crafted prompts and refining its responses through an iterative process, they developed a comprehensive and engaging case study. The case study It included:

• Market entry strategies for RedLine’s franchise model.

• Insights into using technology, like predictive maintenance, to improve operations.

• Ethical considerations, such as balancing automation with the human touch in customer service.

The Benefits of Using Generative AI

This process highlights how AI can enhance education by offering new ways to approach tasks like writing case studies. While the use of AI isn’t a guaranteed success, it has meaningful impacts that deserve consideration. Although the case study reviewed wasn’t particularly impressive, it does showcase a method and framework for creating case studies. The value ultimately depends on the quality of the data and the effectiveness of its delivery. However, this process enables writers to craft meaningful cases with the right guidance and experience. Below are some key advantages to note:

1. Incredible Efficiency: Creating a case study from scratch often takes months. With ChatGPT, the researchers were able to develop one in a fraction of the time. This frees up educators to focus on teaching rather than content creation.

2. Customizable Content: The AI generated content specific to the needs of the course, making it much more relevant for students. It tailored insights for the firefighting industry and franchise expansion challenges.

3. Dynamic and Up-to-Date Learning: Because AI pulls from a broad dataset, it can incorporate real-world trends, making the material feel fresh and applicable to today’s business environment.

Challenges and Ethical Considerations

Of course, it wasn’t all perfect. The paper emphasized the importance of human oversight when using AI-generated content. While ChatGPT can generate coherent and relevant text, it’s up to educators to:

• Ensure the content is accurate and aligned with the course’s goals.

• Address any biases or gaps in the AI’s responses.

• Uphold ethical standards, such as protecting data privacy and ensuring transparency in the AI’s use.

One of the more thought-provoking discussions in the paper revolved around finding the right balance between automation and the human touch. While generative AI is a powerful tool, students still need mentorship, real-world experience, and opportunities to develop soft skills like empathy and communication.

Lessons Learned from RedLine

The RedLine case study also highlighted some specific lessons:

• Iterative Prompting Matters: The quality of AI-generated content depends heavily on the prompts provided. By iterating and refining their prompts, the researchers guided ChatGPT to produce highly tailored outputs.

• AI Enhances Strategic Thinking: The inclusion of generative AI helped students think critically about integrating technology into traditional industries.

• Franchise Development Insights: The study provided a roadmap for expanding a small business into a franchise while maintaining consistent service quality—a real-world challenge for many entrepreneurs.

My Experimentation

Many of you know that I have been doing a variety of tasks with the use of AI in my attempt to see where this “tool” fits in my workflow and what limitations it has. That process has lead to well over 15,000 conversations with AI and over 30,000 interactive prompts via my interactions. The bigger picture….. If we can use generative AI to create case studies, what else can we do and in what way should we be using it? Below are just a few possibilities in education (spoiler, I have done these already):

• Designing interactive coursework that adapts to student needs in real-time.

• Simulating complex business scenarios for students to analyze and solve.

• Generating detailed lesson plans or assignments for educators, saving countless hours of preparation.

At the same time, we need to be careful. As the paper pointed out, AI is a tool, not a replacement. It’s here to assist educators, not take their place. The human element—the ability to mentor, inspire, and connect—is irreplaceable.

A Final Thought

Generative AI is opening doors we never imagined just a few years ago. It’s exciting to think about the possibilities, but it also raises important questions. How do we use this technology responsibly? How do we ensure that it complements, rather than replaces, the human touch in education?

Citation: Singh, J., Samborowski, L., & Mentzer, K. (2023). Developing Case Studies with Generative AI. Proceedings of the ISCAP Conference, Albuquerque, NM.

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Matthew