AI for Writing Teaching Case Studies

A teaching case is a narrative that presents a situation, relevant context, and a decision or problem for learners to analyze. Case methods often ask students to reason from the information available to decision-makers at a particular point, rather than reveal the conclusion first. Good questions focus discussion on evidence, tradeoffs, and alternatives. AI can help brainstorm a scenario, organize background information, create role perspectives, or draft a set of discussion prompts. It can also invent organizations, dates, citations, legal rules, or clinical facts. Treat its output as a draft. If the case uses a real person, company, patient, or event, verify the details, protect confidential information, and obtain permission where needed. If the scenario is fictional or combines elements from multiple sources, label it clearly. An effective workflow begins with learning objectives and a decision point. Tell the tool what concepts students should apply, what background they already have, and what constraints the case should include. Review whether the scenario contains enough evidence for more than one plausible response. Remove irrelevant details that distract from the intended learning, and check that the case does not reward guessing a hidden answer. For specialized fields, ask a subject-matter expert to verify technical claims. A nursing case needs clinical review; a policy case needs accurate dates and context; a business case needs defensible numbers. Do not use AI-generated citations unless every source is checked. Avoid reusing copyrighted cases or confidential classroom work without permission. Before teaching, pilot the case with a colleague or small group. Review discussion questions, timing, accessibility, and what misconceptions may arise. The instructor should prepare follow-up questions and a teaching plan. AI can speed drafting, but learning value comes from careful alignment, evidence, and facilitation.