How to Showcase AI Skills on Insurance Adjuster Resumes & Applications

Quick Answer: Should You Mention AI Skills When Applying for Adjuster Jobs?

Yes, you can mention AI experience when applying for an insurance adjuster position—but AI should not be the focus of your resume or interview.

Lead with the qualifications that show you are prepared to handle claims: licensing, claims education, estimating, investigation, documentation, customer service, communication, organization, and sound judgment.

Then, use AI experience as one additional proof point. A strong example shows that you can use an approved tool for a specific task, verify its work, protect sensitive information, and remain responsible for the final result.

You do not need an AI-focused resume or an extensive portfolio. One clear, honest example is enough.

How AI Skills Fit Into an Insurance Adjuster Application

AI is showing up in more workplaces, so it is fair to wonder whether you should mention it when applying for an adjuster position. You may also be unsure how much attention to give it without making your resume or interview sound like it is more about technology than claims.

The key is to keep AI in its proper place. Employers are hiring an adjuster, not an AI specialist. Your licensing, claims knowledge, communication skills, judgment, organization, and ability to document your work should remain the focus of your application.

At AdjusterPro, we have helped people prepare for insurance adjusting careers for decades. Because we provide licensing, career training, and continuing education, we have a clear interest in helping new adjusters succeed. We also do not want to overstate the role AI plays in getting hired. 

AI experience is not a substitute for claims qualifications, and mentioning it does not guarantee that an employer will view you more favorably. It can, however, strengthen your application when you connect it to a specific task and explain exactly what you did.

In this article, you will learn how to present AI experience on your resume, create a simple claims-related practice example, explain how you checked the results, and discuss responsible AI use during an interview.

Table of Contents

1. Lead With Claims Skills, Not AI Tools
2. Prepare One Claims-Related AI Example
3. Know When Not to Use AI
4. Explain How You Verified the AI Output
5. Use a Five-Part Framework to Explain Your AI Experience
6. Claims Knowledge and Emotional Intelligence Come First

1. Lead With Insurance Adjuster Skills, Not AI Tools

Simply listing ChatGPT or other AI platforms in a skills section does not tell an employer very much.

When hiring adjusters, employers are not hiring software users. They are hiring people who can evaluate evidence, communicate clearly, protect sensitive information, and make sound decisions when the answer is not obvious.

Deloitte’s claims research, “Reimagining Claims: Soft Skills Are the Differentiator” (By Kedar Kamalapurkar, Namrata Sharma, Sabyasachi Satapathy), says AI can support better decision-making, but it cannot replace the human skills claims work requires, including empathy, interpreting unclear coverage, and handling difficult conversations.

“AI can enable more effective decision-making, but cannot replace the human elements critical to claims work: showing empathy at some of the worst moments for an insured, interpreting ambiguity in coverage, and handling difficult customer or vendor conversations. The real differentiator often lies in the soft skills that shape key moments in the claims journey: first notice of loss, investigation, negotiation, and settlement. Yet, these capabilities have steadily eroded, and many adjusters struggle to develop or retain them.”

For a job candidate, tool familiarity does not equal claims competence. Employers still need to know whether you can catch bad output, protect confidential information, follow company policy, and take responsibility for the final work.

Your application should lead with core qualifications such as licensing, Xactimate training, and related experience. AI experience should support that larger professional story.

Instead of writing, “Proficient in AI tools and prompt engineering.”

Describe a specific task: “Completed a self-directed project using an AI tool to compare two fictional property estimates, then verified each suggested discrepancy against the original documents.”

A specific example shows how you think, verify, and take responsibility for the final work. A list of tools only shows what you have used.

2. Show AI Experience With a Claims-Handling Example

You do not need several AI projects. One thoughtful example may be enough to show how you approach the technology.

Your goal is not simply to prove that you know how to use AI. It is to show how you think as you use the technology.

Possible practice exercises include:

• Comparing two fictional repair estimates
• Organizing a mock claim report
• Reviewing a fictional photo narrative for missing details
• Summarizing public training materials
• Identifying differences between sample documents

What Should Your Example Show an Employer?

Your example should make your thinking visible. Show what you asked AI to do, how you checked its work, what you corrected, and what you completed yourself.

That division of responsibility is already taking shape in claims operations.

In an April 2026 announcement, Hippo Holdings said its AI workflow can capture and organize first-notice-of-loss information, flag inconsistencies, route claims, review documents, support customer communications, and prepare claim summaries. The company reports that initial contact now occurs in under two hours on average and expects more than 70% of its homeowners claims to be filed digitally. These are company-reported results, not findings from an independent study.

Hippo’s internal modeling also suggests that its current staffing structure could support a 30% to 35% increase in claims volume. The company’s goal is to use AI to handle more of the administrative workload so adjusters can concentrate on claims that require interpretation, empathy, and judgment.

How to Build a Simple AI Practice Example

To create a simple claims-related practice example:

1. Create two fictional estimates with planned differences in quantities, materials, labor rates, or repair methods.
2. Ask an AI tool to organize the differences into those categories.
3. Check every finding against the original estimates.
4. Record what the tool found, missed, and misunderstood.
5. Write the final comparison yourself.

The goal is not to prove that AI can do claims work for you. It is to show that you can use AI to organize information, catch its mistakes, explain your corrections, and remain accountable for the final result.

Note: For a practice project, use fictional documents or public training materials. Never upload a real claim file, policyholder information, photographs, estimates, or internal documents to a tool you selected on your own.

3. Know When Insurance Adjusters Should Not Use AI

Responsible AI use includes knowing when not to use it.

Be prepared to avoid AI use when:

• The employer has not approved the tool
• The information is confidential or protected
• You do not understand how the platform stores submitted data
• Company policy prohibits its use
• You cannot independently verify the response
• The task requires authority or expertise you do not have

A company-approved AI system may help organize information, compare documents, create an initial summary, or highlight areas that need further review. But a general-purpose AI tool should not be treated as the sole or final authority on coverage, causation, scope, payment, or claim denial.

Responsible AI use begins with knowing when the tool does not belong in the work.

4. Verify AI-Generated Claims Information

The strongest part of your example is how you checked the AI tool’s work.

AI can miss details, make unsupported assumptions, or produce incorrect calculations. 

Explain exactly what you verified, such as:

• Names and dates
• Totals and calculations
• Quantities and line items
• Information from the original documents
• Missing details
• Unsupported conclusions

Check the Evidence Before Trusting the Answer

In a recent interview with AdjusterPro, veteran adjuster Jim Cresse described an auto claim involving two nearly identical photographs of the same vehicle. One showed an undamaged car. The other showed heavy damage along its side.

The assigned adjuster noticed that the supposed damage photo appeared to have been taken at the claimant’s home rather than at the reported loss site. An in-person inspection confirmed that the vehicle did not have the damage shown in the submitted image.

Cresse described the warning sign this way:

“It’s almost exactly the same photo, only now it has a dent in it.”

Before even turning to AI, you need to verify that your information and data is complete, accurate, and real.

Compare AI Outputs for the Same Estimate

Cresse also tested ChatGPT and Claude by giving both tools the same photo narrative and asking each to prepare a repair estimate.

Both estimates appeared detailed and useful. But one came back about 15% below the estimate Cresse had prepared in Xactimate, while the other came back about 15% above it.

The tools helped him produce a starting point quickly, but their conflicting results could not both be treated as correct. His claims knowledge and his original estimate gave him the baseline needed to evaluate them.

5. Use a Five-Part Framework to Explain Your AI Experience

When presenting your example, organize your answer around five points:

1. Problem: What were you trying to accomplish?
2. Tool: How did AI assist?
3. Verification: How did you check the response?
4. Responsibility: What did you correct or complete yourself?
5. Takeaways: What worked, and what would you do differently next time?

Together, these five points show what you did, how you evaluated the result, and what you learned from the process.

Show How You Questioned the AI’s Output

Verification is not saying, “I looked it over.” It’s knowing you can defend your decision. 

In “The Adjuster’s Year Ahead: What AI Will and Won’t Change About the Job,” forensic biomechanist and expert witness Rami Hashish argues that automation is concentrating claims work around interpretation and defensible judgment. AI may prepare much of a file before an adjuster reviews it, but the adjuster must still test whether the facts fit together, decide when the system is wrong, and document the reasoning behind the final decision.

Hashish describes this skill as learning to “interrogate AI”—not simply operate it. An adjuster should be able to explain why an output was accepted, rejected, or overridden and identify the evidence supporting that decision. In other words, explain your reasoning. 

This point gives candidates a useful model: do not stop at saying you checked the answer. Show how you reached your conclusion.

How to Present Your Example in an Interview

Here is how you could explain the fictional estimate-comparison project:

Name the mistake. 

Show how you found it. 

Explain why you changed it. 

State what you would improve next time.

That is professional adjuster judgment.

Put Claims Knowledge and Emotional Intelligence First Before AI

AI can support research, organization, comparison, drafting, and review. It does not replace foundational knowledge of inspection, estimating, investigation, documentation, communication, coverage, causation, or licensing requirements.

Without that knowledge, it may be difficult to recognize when an AI response is inaccurate or inappropriate.

The strongest candidate is not the person who can name the most AI platforms. It is the person who can apply claims knowledge, use approved technology responsibly, and defend the final work.

Lead your application with your licensing, training, experience, and claims-related skills. Then use one clear example to show that responsible AI use is another capability you bring to the role.

Get Ready for the Next Step in Your Adjuster Career

Before you focus on adding AI experience to your application, make sure the rest of your qualifications are in place.

If you have not earned your adjuster license yet, find out what is required in your state, and start there. You cannot handle claims in states or positions that require a license without the proper credentials, regardless of which technology you know how to use.

Already licensed? Focus on building the certifications, practical knowledge, and resume that will help you prepare for adjuster opportunities.

Ready to apply and get hired? Use AdjusterPro’s Adjuster Ready Scorecard to evaluate your hiring readiness, identify gaps in your preparation, and decide what to work on next.