English Class: The Art of Prompting in Claims & Risk Management

The Trained A-Eye

Back to School with Prompts – with Dr. Claire Muselman 

Welcome back to class! In English, we learned that the words we choose matter. They carry tone, shape meaning, and influence how others respond. The same holds true in the world of artificial intelligence, where prompting determines the quality of the results. Prompting is the way we phrase our requests to AI tools. The words we choose to use with AI matter. For workers’ compensation, where communication can make or break trust, prompting is more than a tech skill. Words, phrasing, and prompting are literacy we all need to master. 

This project is inspired by my professor friends Chris Snider and Christopher Porter, known as the Innovation Profs, who created the AI Summer School series. Their exploration of prompting made me wonder how this skill translates into workers’ compensation, where communication is at the heart of everything we do. The connection is powerful because prompting is essentially about clarity, tone, and purpose which are the same ingredients that shape great claims notes, supportive return-to-work letters, and policies people can understand! Ironic, don’t you think? By bringing this framework into our space, we are sharpening our pencils and learning how to write with intention, both for AI and for the people we serve. 

Defining Prompting in Our World 

Prompting can be defined as the process of guiding AI to generate relevant, accurate, and useful results. Think of it like drafting a claims note: if you write “employee hurt at work,” you are not saying much. You have barely scratched the surface. We need clarity and specificity versus vague language and jargon. In contrast, if you write “employee slipped in the warehouse on wet flooring, sustaining a left ankle sprain, light duty requested,” you have now provided context that helps the next reader act quickly and appropriately. AI functions in the same way. The clearer the input, the more valuable the output.  

The BRIEF Framework 

The Innovation Profs shared a simple yet powerful framework called BRIEF. BRIEF is a prompting framework which stands for background, role, instructions, examples, and format. Inspired by the Innovation Prof’s AI Summer School, we can bring BRIEF into our workers’ comp classroom. This approach helps us remember the five elements that turn a vague question into a strong prompt. Think of it as the grammar of AI, giving structure to our digital conversations. 

B = Background 

Background is where everything starts. Just as a claim file is incomplete without the injury details, jurisdiction, and employer information, a prompt is incomplete without context. If you tell AI, “Write a letter,” the response will be generic and impersonal. But if you provide background to create context “Write a letter to an injured worker at a Midwest manufacturing company in Iowa who sprained their back, explain next steps, and emphasize empathy”, suddenly the AI has the framework to build something useful. Context is the difference between a half-filled form and a detailed, actionable claim. 

R = Role 

Role is equally important. In workers’ compensation, we rely on specialized perspectives. A nurse case manager communicates differently than a risk manager, and a claims adjuster has a different tone than an HR trainer or one of our friends from the finance department. When you tell AI what role to assume, you are shaping its voice and lens. Where you stand says a lot about what you see and defining a role can shape this perspective. If you say, “Act as a workers’ comp adjuster writing to an injured worker,” you will get something more tailored than if you simply ask, “Write me a letter.” Defining roles ensures that tone, expertise, and focus are aligned with your audience. 

I = Instructions 

Instructions are the meat of the prompt. Workers’ compensation professionals know the value of clarity. Imagine a supervisor telling an employee, “Come back to work soon.” Compare that with, “Report to the warehouse Monday at 9 a.m. for modified duty, with lifting limited to ten pounds.” Which sets expectations better? AI thrives on specificity. “Summarize this statute in three sentences highlighting expectations and parameters for the claims adjudication process so a fifth grader could understand” will produce something far more actionable and readable than “Summarize this.” Clear instructions reduce trial and error and make AI a true collaborator. Plus, AI can break concepts down for easy consumption and in workers’ compensation, we are trying to make things consumable for different audiences. Simplicity and specificity coupled with brevity are where the magic happens! 

E = Examples 

Examples strengthen prompts by giving AI a model to follow. Think about how we train new adjusters: we show them examples of strong letters and then ask the adjuster to create their own version of a letter stating a claim has been found non-compensable. AI learns in the same way. If you paste a sample communication and say, “Model the style and tone of this letter,” you will get results closer to your organization’s voice. (Think mission, vision, values… this should come across in ALL aspects of communication.) Examples are the bridge between theory and practice. They tell the AI, “This is what good looks like.” 

F = Format 

Format is the final step, and it closes the loop. In claims, we communicate in a vast arena. We write diary notes, policy summaries, letters, or flash. notices each with its own format. AI needs the same direction. If you tell it to “Draft a table of restrictions” or “Write a short paragraph in plain language,” you will get content that fits your purpose. Without format, you may receive something accurate but unusable. By shaping the container for the content, you make AI an efficient partner. 

A Workers’ Comp Example 

To see BRIEF in action, let us walk through a work compensation example together. Imagine you need to communicate modified duty to an injured worker. Your prompt might look like this: “Background: A manufacturing employee has sprained their back and is worried about returning too soon. Role: You are a claims adjuster writing in a supportive and empathetic tone. Instructions: Explain modified duty, emphasize that it supports healing, and invite the worker to reach out with questions. Examples: Here is a supportive line we have used before: ‘We are here to make sure you heal while staying connected to the workplace.’ Format: Draft a short letter, no more than 150 words.” With this prompt, AI is far more likely to produce a letter that reassures the worker, supports recovery, and reflects the values of your organization. 

Please note: Be aware of what you are putting into the prompts and please abide by your organization’s AI philosophies, policies, and parameters. As you can see in the example, no personal information has been provided. You can achieve positive results without giving away unnecessary information. 

Why Prompting Matters 

The beauty of BRIEF is that it is flexible. You do not always need all five elements, but the more information you provide, the better the response. Sometimes Background and Role are enough. Other times, Format becomes the deciding factor. The framework is a memory tool, reminding us that good communication is intentional, thoughtful, and structured regardless of if being complied by a person or a machine. It is about clarity. 

Prompting as a Time Saver 

Strong prompting makes the most of your time and focus. Work smarter, not harder! Workers’ compensation professionals spend countless hours drafting letters, summarizing notes, and rewriting policy updates, let alone figuring out how to communicate with a variety of different people for their audiences. With stronger prompts, AI can handle the heavy lifting of first drafts, freeing us to refine and personalize. If AI can support work on this front, the human side can spend more time listening to injured workers, more time strategizing return-to-work programs, and more time building healthier workplace cultures. Prompting becomes a skill and a way to elevate the human side of our work. 

Class Takeaway 

English class always ended with an essay, and here is ours: prompting is the literacy of AI. The words we choose shape the quality of our results, both in technology and in people. Just as clear claims notes lead to better outcomes, clear prompts lead to better AI collaboration. For your homework, I challenge you to take one piece of your own writing and reframe it as a BRIEF prompt. Try using a standard claims letter or a safety reminder. See what AI gives back. Then ask yourself: how can this tool give me back ten minutes today, an hour this week, or even a day this month? The more we practice, the more fluent we become. Again, check with your organization with their philosophies, policies, and procedures to stay in alignment. 

Class dismissed. ✨ 

Next week: Library Day – Building a Prompt Library for Adjusters & Employers. 

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