Economics Class: Implementing AI for Efficiency, Savings, and Smarter Spend 

The Trained A-Eye

Welcome back to class, classmates! We studied ethics, reasoning, and deep research. Now I welcome you to Economics Class, where we talk about what everyone secretly loves to measure: time and money. In workers’ compensation, both are precious resources. We are always looking for ways to streamline processes, reduce costs, and improve outcomes. We don’t do this just for efficiency’s sake, we do this so we can spend more time where it matters most: helping people heal and thrive. This week, we are learning how to implement generative AI directly into our daily work for smarter spend, higher productivity, and more peace of mind. 

This project continues to be inspired by my professor friends Chris Snider and Christopher Porter, the Innovation Profs, who created the AI Summer School series. Their lesson on implementing AI at work made me think about how perfectly this applies to workers’ compensation. Our world runs on repeatable processes from claims documentation, to compliance, from safety training, to reporting. What is great about these processes is that they are all ripe for automation when used thoughtfully. Chris and Chris focused on a tool called JobsGPT, which analyzes job roles and shows how AI can streamline daily tasks. I thought: what if we had the same concept for claims professionals, HR leaders, and risk managers? The result could change not only how we work, but how we feel at work. 

Where to Begin: Breaking Down the Job 

Start by brainstorming the tasks that fill your day. Claims professionals spend hours writing letters, summarizing medical notes, documenting conversations, and preparing reports. HR leaders write policies, update training manuals, and handle employee communication. Safety managers collect data, review incident reports, and conduct investigations. These are all areas where generative AI can help when used with structure and care. The first step is identifying which tasks are repetitive, time-consuming, or require the same pattern of logic each time. Those are your entry points. Once you list them, think about whether AI could assist with drafting, summarizing, analyzing, or communicating. Start small. Identify one task that drains time every week. Maybe summarizing telephone conversations, reviewing provider notes or incident reports, or writing return-to-work letter. Begin there. That is your opening door to efficiency. 

Quick Wins: Do These Now 

Quick wins are tasks AI can help with right away. These are low-risk, high-reward activities that do not touch private data or sensitive information. For example, you can use AI to draft first-pass content such as employee newsletters, safety bulletins, or training outlines. It can also be used to summarize lengthy meeting notes into clear action steps or help you reframe meetings that could have been an email. J AI can also help you brainstorm ideas for conference presentations, program names, or claims communication campaigns. These quick wins free up time immediately. They are your “instant ROI” projects that typically take thirty minutes but now take five. That time savings improves your calendar and your clarity. Instead of rushing from task to task, you can slow down long enough to think strategically about your team, your claims, or your client relationships. Efficiency creates space for humanity. 

Definite Don’ts: Keep These Human 

Not everything belongs in AI’s hands. Some tasks are too sensitive, nuanced, or personal to delegate. Anything involving confidential information including but not limited to claim details, medical records, or personal employee data should stay within your secure systems. Check your organizations policies on AI use. The same goes for decision-making around ethics, performance management, or return-to-work accommodations. Why? Tone and judgment are still human art forms. AI can draft, but it cannot discern emotion. AI does not sense when a worker is scared about surgery or when a supervisor feels frustrated but misunderstood. That is where your leadership and empathy shine. Think of AI as your assistant, not your replacement. You lead the conversation, and let AI take notes. 

In-Between Cases: Test and See 

The in-between category is where things get interesting. These are tasks that might benefit from AI, only after experimentation. This is your testing ground for growth. You might try using AI to generate first drafts of policy updates, training quizzes, or standard letters, then compare those to your current process. You could test how AI analyzes large amounts of data, like loss run summaries or survey responses. Run side-by-side trials. Compare quality, accuracy, and time savings. Some outputs will amaze you while others will need major revision. Experimentation is where the magic happens. Create your own AI playbook, the set of tools and prompts that make your work better, faster, and more enjoyable. Again, check your organization’s policies first!  

The 70/20/10 Rule for Implementation 

Once you start experimenting, use the 70/20/10 rule. Let AI handle 70% of the work such as the drafting, summarizing, or analysis. You take 20% to refine, edit, and ensure accuracy. Then use the final 10% to add your personal touch: empathy, tone, or strategy. This balance ensures that your communication stays human while your workload stays light. Imagine AI drafting a complex return-to-work plan. It structures the timeline, references modified duty tasks and writes the base letter. You then review, add empathy-driven phrasing, and ensure it aligns with your company’s voice. The end product? Professional, efficient, and heartfelt in less than half the time. 

Why This Matters for Workers’ Compensation 

Generative AI helps with precision, consistency, and better human outcomes. In our industry, speed is important and also, accuracy and tone are everything. Using AI strategically can reduce administrative friction and increase emotional bandwidth. Adjusters can spend more time talking to injured workers instead of typing. HR leaders can focus on culture instead of clerical work. Safety managers can prioritize prevention instead of paperwork. There is also a financial upside. Of course there is, this is an effective business strategy! When communication improves, litigation drops. When training is consistent, injury frequency declines. When return-to-work is personalized, claims close faster. Each of these results translates to measurable savings. Implementing AI thoughtfully can generate compassion-based ROI with a return on integrity as well as investment. 

Building Your Implementation Plan 

Where to begin? Start with small steps to implementing AI in your job: 

Step 1: Map your tasks. List everything you do in a typical week, from claims documentation to internal communication. 

Step 2: Label each as a Quick Win, Don’t, or Test & See. Be honest about what drains your time and what requires your expertise. 

Step 3: Pilot one or two quick wins. Track time saved, quality of results, and your overall workload balance. 

Step 4: Establish guardrails. Protect data privacy, maintain ethical standards, and clearly define what AI can and cannot do in your role. Double check your organizational specifications around AI. 

Step 5: Share your results. Bring what you learn to your team or leadership. Show how AI can enhance the human side of work by working smarter, not harder. 

Leadership Lessons from Implementation 

Leaders set the tone for how technology is received. When you model responsible experimentation, you empower your team to do the same. Encourage questions, celebrate small wins, and share best prompts in your team’s prompt library. Remember that change fatigue is real, and we are changing at a rapid pace in our present environment. For some people, AI feels intimidating or even threatening. Approach those feelings with empathy and reassurance. Make it clear that the goal is enhancement, not replacement. When people feel safe to learn, they innovate faster. This is how we future proof the workforce with one conversation, one tool, one confident experiment at a time. Teach yourself something new, and then go share it with someone else. 

Class Takeaway 

AI implementation is a human project involving reclaiming time, amplifying expertise, and creating space for what truly matters. The tools are ready. The guardrails are clear. The opportunity is enormous. When we align AI with our values of empathy, ethics, and excellence, everyone benefits. 

Your homework: Pick one “quick win” from your job this week and let AI help. Time yourself. Review the result. Then share what you learned with a colleague or your team. Innovation spreads faster when it is shared, and in workers’ compensation, collaboration is the best currency we have. 

Class dismissed.  

Next week: Economics, Part II – Implementing AI at the Organizational Level. 

Share This Article: