Insurance Appraisers, Auto Damage

Auto-damage appraisers normally inspect wrecked cars, figure repair costs, and fill out claim forms ^[1]. Today, insurers are starting to use AI to help with some of these steps. For example, the insurtech Tractable works with a UK insurer (Ageas) to let AI “see” crash photos and instantly generate a repair estimate ^[2].

Similarly, a Deloitte team built a deep-learning model that “recognize[s] car damage” and then looks up parts and labor in seconds, instead of a person manually checking manuals ^[3]. In short, tasks like examining damage and estimating parts and labor can now be partly automated by smart software. One industry article notes that this “visual intelligence” makes damage assessments faster and more consistent from photos ^[4] – for example, shops can upload images to the claim and AI checks that no fixes are missed, so there’s less back-and-forth ^[4].

However, the more judgment-based tasks still rely on people. Deciding if a car should be totaled or negotiating final repair costs (for example, if a shop disagrees) involve experience and communication. Even experts point out that AI “isn’t the same as an educated collision repair professional” ^[5], so appraisers still play a key role in final reviews and agreements.

Why might insurers adopt these tools quickly or slowly? On one hand, the technology is already available and promises big gains. Carriers see that faster claims save money and improve service.

In fact, insurers report that using AI “accelerates every part” of the claims process and creates efficiencies (faster settlements, fewer delays) ^[2]. Customers like speed, too: a JD Power study cited by analysts shows customer satisfaction drops sharply if people have to submit multiple damage photos (a score of 875 with one photo fell to 806 when three or more were needed) ^[4]. Quick AI estimates on the first try could avoid that frustration.

Also, claims have been taking longer – one report says the average repair cycle is now 23 days (up from 12 days before the pandemic) ^[4] – so cutting that time is a big incentive.