When a car crash once meant days of phone calls, inspection appointments, and back-and-forth paperwork, some insurance claims can now begin with a smartphone photo, a telematics record, or an automated estimate generated before an adjuster ever sees the damaged vehicle.
That shift is changing one of the most stressful parts of an accident: the period after the crash, when injured people are trying to document what happened, get medical treatment approved, repair or replace a vehicle, and understand what an insurer is willing to pay. In 2023, there were an estimated 6.1 million police-reported traffic crashes in the United States, resulting in more than 2.4 million people injured and 40,901 killed, according to the National Highway Traffic Safety Administration.
To better understand how claims technology is changing the experience after a crash, Law Offices of Pius Joseph, a personal injury law firm, examined federal crash data, insurance regulatory guidance, and recent consumer-protection actions involving artificial intelligence and driving data.
AI is already part of the insurance life cycle
Artificial intelligence is not limited to chatbots or customer-service tools. The National Association of Insurance Commissioners says AI is being used throughout the insurance life cycle, including underwriting, pricing, policy servicing, claim management, and fraud detection. In claims, NAIC says insurers use AI for accident image analysis, estimating ultimate claim settlement values, and fraud detection.
A 2026 NAIC Journal of Insurance Regulation article reviewing insurer surveys found that more than 70% of automobile, homeowners, and health insurers surveyed were already using, planning to use, or exploring AI. Among life insurers, 58% reported current or expected future use.
For accident victims, that can mean faster processing in straightforward cases. A damaged bumper, uploaded photos, a police report, and repair-shop data can all be routed through automated systems that identify damage, compare it with historical claims, flag inconsistencies, and generate estimates.
But claims after serious crashes are rarely just a repair estimate. They can involve medical bills, wage loss, long-term care needs, liability disputes, and questions about whether a settlement reflects the full cost of an injury. Those are the cases where speed may matter less than whether the system is accurately weighing the person’s circumstances.
Faster claims can still leave gaps
The clearest benefit of AI is efficiency. Algorithms can sort documents, read photos, identify missing information, detect duplicate bills, and route claims to the right department. For insurers handling large volumes of auto, health, property, and liability claims, automation can reduce administrative time.
That matters because crash claims are only one part of a much larger system. NHTSA’s 2023 crash data shows that millions of people each year move through some version of the post-crash process (police reports, repairs, medical treatment, and insurance filings)
However, the same tools that speed routine steps can create new problems if they are used to make or heavily influence decisions without enough human review. A model may estimate vehicle damage from photos but miss hidden structural damage. A claims tool may flag a medical bill as unusual without understanding why a specific injury required additional care. A fraud-detection system may detect a pattern that looks suspicious but has a reasonable explanation.
Insurance regulators have increasingly focused on those risks. Insurers remain responsible for complying with existing insurance laws when using AI, including rules related to fairness, accuracy, consumer protection, and the avoidance of unfair discrimination. They also emphasize that state regulators may require insurers to explain how AI tools are used in claims and other decisions.
Driving data is becoming part of the claims and pricing debate
One of the biggest changes for accident victims is that vehicles themselves can now generate data that may become relevant after a crash. Connected cars can record location, speed, hard braking, acceleration, mileage, and other driving behavior. That information may help reconstruct an accident, but it can also raise privacy and fairness concerns.
In January 2025, the Federal Trade Commission announced action against General Motors and OnStar, alleging the companies failed to clearly disclose that they collected precise geolocation and driving-behavior data and sold it to third parties, including consumer reporting agencies, without consumers’ consent.
The FTC finalized its order in January 2026. The agency said GM and OnStar would be barred for 5 years from sharing consumers’ geolocation and driving behavior data with consumer reporting agencies. The order also requires stronger consumer control, including consent requirements and the ability to access or delete certain data.
The FTC’s complaint alleged that some consumers discovered the data sharing only after adverse action notices from insurance companies indicated their coverage was denied, canceled, or their premiums increased because of driving-behavior reports.
For accident victims, the lesson is broader than one automaker or one enforcement action. A modern claim may involve more than just a police report, a witness statement, and a repair estimate. It may also involve data generated before, during, or after the crash, some of which the driver may not realize exists.
Medical claims face their own AI guardrails
Crash-related insurance claims often overlap with medical coverage. An injured person may be dealing with auto insurance, health insurance, disability coverage, or Medicare Advantage, depending on the circumstances. AI is increasingly part of those systems, too.
In February 2024, the Centers for Medicare & Medicaid Services clarified that Medicare Advantage plans may use algorithms or AI tools to assist with coverage determinations, but those tools cannot replace the required review of an individual patient’s circumstances. CMS said an algorithm’s prediction alone cannot serve as the basis for terminating post-acute care services; the patient’s condition must be reassessed before services are ended.
California has also moved to limit how AI can be used in health coverage decisions. State guidance issued in 2025 addressed the use of AI, algorithms, and software tools in utilization management following the passage of SB 1120, which requires health plans and disability insurers that use these tools to meet specific standards.
Those health-coverage rules do not govern every auto or personal injury claim. But they show the direction of policy debate: AI may assist, but regulators are increasingly wary of systems that deny, delay, or reduce benefits without meaningful review.
The claims process is becoming more technical
For accident victims, the practical result is that the claims process may feel less visible. A person may not know whether a settlement estimate came from an adjuster, a software tool, a photo-analysis model, or a combination of all three. They may not know whether a medical bill was reviewed by a clinician, an automated utilization-management tool, or both.
That lack of visibility matters because claims decisions affect real financial outcomes. A delayed approval can postpone treatment. A low repair estimate can leave a vehicle owner paying out of pocket. A denied medical claim can create debt before liability is resolved. A settlement offer based on incomplete information may not reflect future medical needs, lost income, or long-term impairment.
NAIC’s guidance emphasizes that insurers using AI should be able to govern, test, document, and explain their systems. The association says human oversight remains important in insurance decision-making, especially where AI affects consumers.
What accident victims can watch for as claims become automated
As AI becomes more common in claims handling, accident victims may need to be more careful about documentation. Photos should be complete and taken from multiple angles. Medical symptoms should be reported consistently. Repair estimates, diagnostic records, wage documentation, and correspondence with insurers should be saved.
Consumers should also pay attention to adverse action notices, denial letters, and explanations of benefits. These documents may reveal whether a decision was based on driving data, medical necessity criteria, repair estimates, or other factors. If a claim decision appears incomplete or inaccurate, the notice may also explain how to appeal or request more information.
The technology behind claims may continue to change, but the central issue remains the same: after an accident, the claim should reflect the facts of the crash, the evidence available, and the person’s actual losses, and not only what a model can infer from a photo, a form, or a data point.
