How AI is transforming property restoration—and why insurers should care

Editor's Note: This is the first in a multi-part series that examines the use of AI in the claims space.

The insurance and restoration industries have long operated in parallel, connected primarily through the claims process. But as both sectors embrace new technologies—particularly artificial intelligence (AI)—that relationship is quickly evolving. Restoration companies are no longer just service providers; they are becoming data-rich, tech-enabled partners capable of transforming how insurers manage claims.

AI is already reshaping key aspects of property restoration, from initial assessment to project management, documentation and even customer communication. As insurers evaluate digital tools to streamline claims, reduce fraud, and improve policyholder satisfaction, understanding how restorers are deploying these technologies is crucial.

Accelerating claims through AI-driven assessments

One of the most time-consuming aspects of the claims process is the initial inspection and scoping of property damage. Traditionally, adjusters and restoration contractors conduct manual assessments—often duplicating efforts. Today, restoration companies are using AI-powered tools, including image recognition and 3D modeling, to capture and analyze site conditions more accurately and efficiently.

For example, mobile apps now allow technicians to capture photos and videos that are automatically analyzed by AI algorithms. These systems can detect damage types, generate preliminary estimates and flag anomalies for review. This not only reduces the time needed for inspections but also provides insurers with consistent, structured data early in the claims cycle.

Enhancing transparency and data sharing

Another benefit of AI and related technologies is the ability to streamline data exchange between restoration firms and insurance carriers. Cloud-based platforms can now integrate directly with insurers' claims management systems, enabling real-time updates on job status, documentation uploads and cost tracking.

Machine learning models can also be used to predict job timelines based on project complexity and historical data. For insurers, this means improved transparency and better forecasting of claim durations—key metrics in customer satisfaction and cost control.

Improving accuracy and reducing disputes

Discrepancies between adjuster estimates and restoration invoices are a persistent pain point. By using standardized, AI-assisted scoping tools, restoration firms can align more closely with insurer expectations from the outset. Some tools even cross-reference pricing databases like Xactimate or Symbility in real time, reducing the likelihood of disputes over labor or material costs.

This level of standardization also benefits the policyholder. When both parties—insurer and contractor—are working from the same data and using similar tools, it creates a smoother, more transparent experience during what is often a stressful time.

The role of predictive analytics

Beyond individual claims, restoration companies are beginning to use predictive analytics to anticipate trends and allocate resources. For instance, AI models can analyze weather data, historic claim volumes, and geographic risk patterns to forecast demand for services like water mitigation or fire cleanup. This helps companies prepare response teams and inventory in advance—improving responsiveness and reducing delays for insureds.

Insurers can tap into these insights as well, using shared data to predict potential loss events and proactively communicate with policyholders. In the near future, partnerships between insurers and tech-forward restorers may even enable pre-loss mitigation efforts—turning the claims process from reactive to proactive.

Ethical use and human oversight

Of course, as with any emerging technology, the use of AI comes with responsibilities. Restoration firms must ensure that AI systems are being used ethically, that they do not reinforce bias, and that human oversight remains central. While automation can accelerate decision-making, critical judgments—especially those involving customer well-being or significant financial impact—must still be made by experienced professionals.

A call for collaboration

As insurers continue to modernize their claims infrastructure, they should consider restoration companies not just as vendors but as technology partners. By aligning around shared goals—speed, accuracy, transparency, and customer care—both sides can benefit from the efficiencies that AI and other digital tools offer.

Ultimately, the rise of AI in restoration is not about replacing people; it's about empowering them with better tools and more accurate data. And for insurers looking to stay competitive in a digital-first world, understanding and embracing these changes is not optional—it's essential.