Artificial intelligence tools that analyze photographs and drone imagery to generate preliminary damage estimates are being adopted at a rapid pace across the restoration industry, with a 2026 R&R Magazine survey finding that 88 percent of restoration businesses have adopted at least one AI-powered tool.
The tools work by applying computer vision and machine learning algorithms to images of damaged structures, identifying affected materials, estimating quantities, and generating preliminary scope of work documents that can be refined by human estimators. Several platforms integrate directly with Xactimate, automatically populating line items based on the AI analysis.
Early adopters report significant reductions in estimating time. One large regional restoration firm reported that AI tools reduced the time required to generate a preliminary estimate from four hours to 45 minutes, allowing estimators to handle more jobs and respond more quickly to time-sensitive insurance deadlines.
Accuracy has also improved in some scenarios. AI tools are particularly effective at estimating damage to standard residential structures with common materials, where training data is abundant. They are less reliable for unusual structures, specialty materials, or complex damage scenarios that fall outside the training data.
Insurance carriers have been watching AI estimating adoption closely. Several carriers have begun accepting AI-generated preliminary estimates as the basis for initial claim payments, with human review reserved for complex or disputed claims. This approach has the potential to significantly accelerate claim processing times.
The rapid adoption of AI tools is also raising questions about the future role of human estimators. Industry leaders generally view AI as a tool that augments human expertise rather than replacing it, but acknowledge that the skills required of estimators are evolving.
