5 Ways Restoration Contractors Can Improve Their Inputs to Get Better Outputs from AI

Artificial Intelligence (AI) is rapidly transforming the insurance claims landscape, from generating estimates to analyzing job photos and parsing through project documentation. As carriers and third-party administrators adopt AI to speed up decision-making and standardize claim reviews, restoration contractors find themselves in a powerful position: the quality of your inputs directly affects the quality of AI outputs.

In other words, AI doesn't remove your voice; it amplifies it. Clear documentation, properly labeled photos, and consistent data entry can guide AI tools to produce faster, more accurate decisions in your favor. The good news? You don’t need to be a tech expert to make AI work for you. You just need to know how to speak its language.

Here are five practical ways you can improve your documentation so AI can better understand and support your work.

1. Use Consistent and Clear Terminology

AI systems that review estimates and documentation rely heavily on pattern recognition. They are trained to detect and process language that aligns with known standards. When your notes include vague, inconsistent, or overly casual language, the AI may misinterpret the information, overlook key actions, or even flag the claim for further review or denial.

Think of it this way: the clearer and more familiar your language is to the AI, the more likely it will "understand" your work and generate an accurate response or decision.

Tips:

• Use standardized terms found in platforms like Xactimate or Cotality. If the AI is trained to recognize "HEPA air scrubber," but you write "air filter thing," you’re inviting confusion and risking missed line items.
   
• Avoid slang, abbreviations, or internal shorthand. What makes sense in the field ("demo’d walls," "put fans in") may not translate well to a machine, or to the adjuster reading the output.
   
• Be precise in descriptions. For example, say:
  “HEPA air scrubber installed in living room for Category 3 loss per IICRC S500 standards”  instead of: “Machine placed in room.”
   
• Repeat key terms where appropriate. If you’re documenting drying equipment across multiple rooms, repeat the type and placement clearly in each room’s notes, rather than relying on phrases like “same setup in other areas.”
   

Clear, consistent language is one of the easiest and most effective ways to help AI interpret your documentation correctly and to minimize unnecessary delays or back-and-forth with adjusters.

2. Photograph with Purpose

Photos are no longer just supporting documentation; they’re often a primary source of truth for AI models analyzing claims. Many platforms now use computer vision to verify scope items, assess damage severity, and even determine appropriate line items. That means low-quality, poorly framed, or incomplete photos don’t just look unprofessional; they may cause AI systems to miss or misinterpret critical details, ultimately weakening your claim.

Restoration professionals should approach photography as a form of storytelling: your photos should guide someone through the job site as if they were there.

Tips:

• Capture wide-angle shots to establish context. Don't just show a damaged wall, show the room it’s in. Help the AI (and adjuster) understand scale and surroundings.
   
• Document all phases of the job:
   
  • Before mitigation (initial damage and cause)
     
  • During mitigation (equipment setup, demo, containment)
     
  • After mitigation and rebuild (completed work)
     
• Include scale in your photos. Use a ruler, gloved hand, or common object (like a clipboard) to show the size of damage, especially for microbial growth, staining, or impact points.
   
• Highlight special circumstances that justify your scope:
   
  • Limited access areas (e.g., crawlspaces or attics)
     
  • Safety hazards (e.g., live wires, mold exposure, biohazards)
     
  • Structural instability or unusual materials
     
• Maintain clarity and lighting. Avoid blurry or dark images. Good lighting can make a significant difference in what AI detects.
   
• Label or sort photos when possible. If your system allows it, organize photos by room or job phase to further support clarity and credibility.
   

The bottom line? Every photo should have a purpose; whether it’s to confirm a scope item, justify an estimate, or tell the story of the work completed. The better your visuals, the better the AI’s interpretation, and the stronger your case for faster claim approvals.

3. Write Strong, Structured Notes

AI systems reviewing job documentation, just like adjusters, look for clarity, logic, and completeness. These models are trained to detect specific patterns, keywords, and sentence structures to determine what work was done, why it was necessary, and whether it aligns with standards and scope.

Clear, well-organized notes not only help AI interpret your documentation more accurately, but they also reinforce your professionalism and credibility when the claim is escalated to human reviewers.

Tips:

• Use bullet points or numbered lists to clearly separate tasks performed. This improves readability for both AI and humans.
   
• Include the “who, what, when, where, and why” in your daily job logs. For example:
  “Technician John Smith removed non-salvageable drywall in the basement on 7/12 due to saturation from Category 3 water intrusion.”
   
• Explain any deviations from standard pricing, scope expectations, or line item choices. For example, if you used an alternative material or added labor due to limited access, state the reason explicitly.
   
• Reference IICRC or manufacturer standards when applicable. Statements like
  “Performed drying per IICRC S500 Category 3 guidelines” give both AI and adjusters confidence that your work aligns with industry best practices.
   
• Avoid vague or generic language. Instead of writing “demo completed,” say
  “Removed 32 linear feet of 2’ flood-cut drywall in hallway due to microbial growth.”
   
• Use past-tense action verbs (e.g., removed, installed, extracted, documented) to convey completed work.

Strong notes bridge the gap between the work completed on-site and how it’s understood in the claim review process. The more clearly and completely you write, the better positioned you are to defend your scope and get paid appropriately.

4. Label and Organize Your Files

Just like a messy jobsite can slow down a project, disorganized digital files can delay or derail the claims process. AI systems and human reviewers perform better when your documentation is clearly labeled and logically organized. Clean, consistent file management doesn’t just look professional; it is professional. It shows that you take your work seriously and that your documentation can be trusted.

Tips:

• Use consistent file naming conventions that include location, task, and date. For example:
  “LivingRoom_Demo_20240705.jpg” or “Kitchen_MoistureLog_20240706.pdf”
   
• Organize by category or folder structure. Group files into logical buckets such as:
   
  • Photos, Moisture Logs, Estimates, Certificates of Insurance (COIs), Work Authorizations, Daily Logs.
  • This structure makes it easier for AI systems and adjusters to locate the right files quickly.
     
• Tag files with metadata when possible. Some documentation platforms allow you to embed metadata (such as room name, date, or type of document). This additional layer of context helps AI models properly associate files with the correct scope items. For example, tagging a photo as "Kitchen – Demo – 7/17/25" helps the system connect it directly to the kitchen demolition scope, rather than treating it as a generic image.
   
• Keep version control clean. If a document is updated, mark it as such (e.g., “Estimate_v2”) and remove outdated drafts when appropriate to avoid confusion.
   
• Avoid dumping all content into one folder. This may seem faster in the field, but it creates more friction downstream, especially when systems are parsing data at scale.
   

Organized documentation is one of the simplest ways to improve claim speed and accuracy. When AI tools and reviewers can easily follow your digital trail, you're more likely to get timely approvals and fewer follow-up questions.

5. Feed the System with Accurate, Real-Time Data

AI systems are only as good as the information they’re given. Over time, these tools learn from the patterns and data they process, so the accuracy of your inputs today directly impacts the quality of recommendations and decisions tomorrow. Whether it's pricing, timelines, or equipment usage, feeding the system with clean, real-time data helps both AI and human reviewers operate with greater confidence and clarity.

Tips:

• Keep pricing and material costs up to date in your systems to reflect real-world conditions. Outdated pricing can lead to inaccurate estimates or pushback from adjusters.
   
• Use actual field data whenever possible, such as moisture readings, drying logs, or equipment runtime data. Avoid generic placeholders that reduce credibility or confuse AI systems.
   
• Track project milestones and timelines closely to ensure they align with production logs and justify your billing cycles or scope adjustments.
   
• Correct documentation errors early, especially before they’re submitted to TPAs or insurance carriers. Once flawed data is entered into the system, AI may continue referencing it in future evaluations, compounding the problem.
   

The takeaway? AI is a tool that learns from your data. When you prioritize accuracy, you’re not just improving one claim; you’re improving the entire system over time.

Final Thoughts

AI isn’t a passing trend; it’s becoming a core part of how insurance claims are reviewed, approved, and paid. But that doesn’t mean restoration professionals are at the mercy of machines. You have more influence than ever. By improving how you document, photograph, and organize your work, you're not just keeping up, you’re leading the way.

The bottom line: Better inputs lead to better outputs. And in an AI-driven claims environment, that translates to faster approvals, fewer disputes, and stronger margins for both your business and your clients.

This is an opportunity, not a threat. Restorers who take the time to adapt today will be the ones who thrive tomorrow.

Stay engaged with RIA for more resources, training, and advocacy efforts designed to help you stay ahead of technology trends and protect the future of the restoration industry. The more we learn and lead together, the more we shape how AI supports, not replaces, our work.

 

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