Writing accurate Xactimate estimates has always been one of the most time-consuming and skill-dependent tasks in insurance restoration. A single estimate can take hours to complete, requiring deep knowledge of line items, pricing, and the specific requirements of different carriers. AI-powered estimating is changing this equation dramatically.
The Traditional Estimating Bottleneck
In a typical restoration company, estimating is a bottleneck. Experienced estimators are expensive and hard to find. Training new estimators takes months or even years. And even experienced estimators make mistakes — missed line items, incorrect quantities, and inconsistent pricing can all impact recovery rates and profitability.
The traditional workflow involves manually reviewing property documentation, identifying the scope of work, selecting appropriate Xactimate line items, entering quantities based on measurements, and then reviewing the entire estimate for accuracy. This process is repeated for every job, with limited ability to leverage historical data or automate repetitive tasks.
How AI Is Changing the Game
AI-powered estimating platforms analyze property scans, damage documentation, and historical data to automatically generate scope of work recommendations and suggest appropriate Xactimate line items. The AI can identify damage patterns, recommend line items based on similar past projects, and flag potential supplements that might otherwise be missed.
This does not replace the estimator — it augments them. The AI handles the repetitive, data-intensive work of initial scoping and line item selection, while the estimator focuses on the judgment calls that require human expertise. The result is estimates that are completed faster, with fewer errors, and with more consistent pricing.
From Scan to Estimate in Minutes
When AI estimating is integrated with LiDAR scanning, the entire workflow from property documentation to completed estimate can be compressed from hours to minutes. The scan provides accurate measurements and spatial data. The AI analyzes the scan alongside damage documentation to generate a scope of work. Xactimate line items are suggested with quantities pre-populated from the scan data.
The estimator reviews the AI-generated estimate, makes adjustments based on their expertise, and submits. What previously took three to four hours now takes 30 to 45 minutes, with improved accuracy and consistency.
Impact on Recovery Rates
Faster estimating means faster submissions to carriers, which means faster approvals and faster payment. But the impact goes beyond speed. AI-powered estimating also improves recovery rates by identifying line items and supplements that human estimators might miss. The AI learns from thousands of past estimates to recognize patterns and opportunities that would be difficult for any individual estimator to track.
Companies that have adopted AI-powered estimating report recovery rate improvements of 10 to 15 percent on average, driven by more complete initial estimates and more effective supplement identification.