Michael Pines | July 27, 2026 | Personal Injury
Quick Insights
- Insurance companies increasingly use artificial intelligence to organize records, evaluate damage, identify suspected fraud and recommend settlement ranges.
- Automated systems may score a claim based on medical treatment, diagnostic codes, gaps in care, accident photos, prior claims and comparisons with historical cases.
- AI can process information quickly, but it may fail to appreciate chronic pain, unusual injuries, delayed symptoms or the personal effect an accident has on someone’s life.
- A missing record, inconsistent description or unexplained treatment gap could influence an automated assessment even when there is a reasonable explanation.
- Accident victims should preserve comprehensive medical, employment, photographic and personal-impact evidence rather than assume the insurer has the complete story.
- An AI-generated claim value is not the same as an independent legal evaluation of what a case may be worth.
- Before accepting a settlement, speak with a personal injury attorney who can identify overlooked damages and challenge unsupported assumptions.
Artificial intelligence is changing the way insurance companies process personal injury claims.
A claim that once required an adjuster to manually review hundreds of pages may now be screened by software capable of scanning medical records, analyzing photographs, detecting patterns and comparing the case with large databases of previous claims. The National Association of Insurance Commissioners reports that insurers use AI in areas including claims handling and fraud detection, while image-recognition tools can help estimate property damage from photographs.
These systems can make claims processing faster and more consistent. However, speed and consistency do not necessarily mean that an injured person is being offered full and fair compensation.
Personal injury claims are highly individual. Two people involved in similar collisions may have very different medical histories, occupations, recoveries and long-term limitations. An automated system built around averages and historical patterns may have difficulty accounting for those differences.
For accident victims in San Diego, understanding how AI may influence a claim can help prevent important evidence from being ignored or misunderstood.
How Is AI Used in the Insurance Claims Process?
“Artificial intelligence” is a broad term. Insurers may use machine learning, predictive analytics, image recognition, natural-language processing and automated decision-support tools at different stages of a claim.
AI does not always make the final decision. In many cases, it sorts information, assigns scores or recommends an outcome for a human adjuster to review. In other situations, automated tools may handle substantial portions of a relatively routine claim with limited human involvement.
The NAIC’s model bulletin on insurer use of artificial intelligence recognizes that AI systems may be used throughout the insurance life cycle, including claims administration and fraud detection. It also states that decisions supported by AI must comply with applicable insurance laws and should be subject to governance, testing and risk-management controls.
Common applications in personal injury and automobile claims may include:
- Extracting information from medical records
- Categorizing injuries and treatment
- Reviewing accident photographs
- Estimating vehicle repair costs
- Identifying potential inconsistencies
- Predicting the expected duration of treatment
- Comparing a claim with prior claims
- Flagging possible fraud
- Recommending settlement ranges
- Prioritizing files for additional investigation
- Drafting communications to claimants
The technology may be presented as a tool for efficiency. From the injured person’s perspective, however, the key question is whether the information being analyzed accurately reflects the full extent of the loss.
Automated Claim Scoring
One way insurers may use AI is through automated claim scoring.
A scoring system reviews selected data points and places a claim into a category or assigns it a numerical risk or value score. Depending on the program, the score might be used to estimate claim severity, predict litigation, recommend how closely the file should be reviewed or suggest a potential settlement range.
Factors analyzed by claim-scoring software may include:
- The type of collision
- The severity of vehicle damage
- Diagnosed injuries
- Medical billing codes
- Length of treatment
- Frequency of appointments
- Gaps in medical care
- Prior injuries or claims
- Whether surgery was recommended
- The claimant’s age and occupation
- Geographic settlement data
- Whether an attorney is involved
- How similar claims were previously resolved
A score can influence how an adjuster approaches the claim before the injured person has had a meaningful opportunity to explain what happened.
For example, a system may classify a collision as low severity based on visible vehicle damage. That classification could affect the value assigned to the bodily injury claim, even though exterior damage does not always reveal the forces experienced by the occupants or the severity of an individual person’s injuries.
An algorithm may also treat a delay in treatment as evidence that an injury was minor. It may not know that the person could not immediately obtain an appointment, lacked transportation, had difficulty finding a specialist or attempted to work through the pain before symptoms worsened.
AI-Assisted Medical-Record Analysis
Personal injury claims often involve extensive medical documentation. A single case may include emergency department records, imaging reports, specialist consultations, therapy notes, prescriptions, operative reports and years of prior medical history.
AI can scan these materials far more quickly than a person. It may identify diagnoses, treatment dates, reported pain levels, preexisting conditions and references to earlier injuries. In complex claims, software may also summarize records or identify passages for an adjuster to examine more closely.
This can improve organization, but medical-record analysis is only as reliable as the records and instructions given to the system.
Automated tools may place significant weight on:
- Inconsistent descriptions of pain
- Different injury dates
- References to previous symptoms
- Missed appointments
- Treatment gaps
- Normal imaging findings
- Notes indicating improvement
- Lack of a specialist referral
- Disagreements among medical providers
- Statements taken out of context
Medical records are not written to tell the complete story of a legal claim. They are primarily created to document clinical care and billing. A brief note saying that a patient is “doing better,” for example, does not necessarily mean the patient has fully recovered or can return to every activity performed before the accident.
Similarly, a normal X-ray does not rule out many soft-tissue, neurological or pain-related conditions.
An experienced personal injury attorney can review the broader medical history, consult the appropriate providers and explain why isolated entries should not determine the value of a claim.
Analysis of Accident and Vehicle Photos
Computer-vision systems can analyze photographs of damaged vehicles and property. Insurers may use these tools to identify affected parts, estimate repair costs and classify the apparent severity of a collision.
Photographic analysis can be useful in straightforward property-damage claims. Problems may arise when conclusions drawn from property damage influence the bodily injury evaluation.
Visible damage does not always correspond directly with the physical forces transmitted to an occupant. Vehicle design, the angle of impact, seat position, occupant characteristics and other factors may all influence the risk of injury.
Photographs also have limitations. They may not show:
- Damage hidden beneath body panels
- Seat or restraint-system damage
- Frame or structural deformation
- The full angle of impact
- Damage that was repaired before inspection
- Movement of occupants inside the vehicle
- The claimant’s symptoms after the collision
Accident victims should preserve photographs from multiple angles, repair estimates, inspection reports, dashcam footage and any other available evidence. When appropriate, an attorney may work with accident-reconstruction or biomechanical experts to provide context that an image-analysis system cannot supply on its own.
Fraud Flags and Automated Suspicion
AI is also used to detect patterns associated with possible insurance fraud. The software may compare a claim with known fraud indicators or identify combinations of facts that it considers unusual.
Possible flags could involve:
- A recent policy change
- Multiple prior claims
- Delayed reporting
- Treatment from certain providers
- Similarities to previously investigated claims
- Inconsistent statements
- Unusual billing patterns
- A lack of objective diagnostic findings
- Social media content
- Relationships among drivers, passengers or providers
Fraud detection serves a legitimate purpose. Insurance fraud increases costs and can undermine the claims system. However, being flagged by an automated program does not prove that someone has done anything wrong.
A legitimate claim may appear unusual for many innocent reasons. A person with a chronic condition may have extensive prior treatment. Someone involved in multiple accidents may simply have been unfortunate. A delay in reporting may result from hospitalization, confusion about coverage or an initial belief that the injuries would resolve.
Once a claim is flagged, it may receive greater scrutiny, additional document requests or referral to a special investigations unit.
Accident victims should not guess, exaggerate or attempt to make their claim appear more persuasive. Accuracy and consistency are essential. When a fact could be misunderstood, supporting records and a clear explanation may prevent an automated concern from shaping the entire claim.
AI-Generated Settlement Recommendations
One of the most significant uses of claims technology is the generation of settlement recommendations.
Software may compare the claim with historical outcomes involving similar diagnoses, treatment patterns, jurisdictions and accident types. It can then suggest a range that an adjuster may use during negotiations.
This process can make the insurer’s evaluation more standardized. It may also anchor negotiations around a number produced before all relevant damages have been fully documented.
A settlement recommendation may consider:
- Medical expenses
- Duration of treatment
- Type of injury
- Whether surgery occurred
- Lost income documentation
- Prior settlement data
- Geographic trends
- Comparative fault
- Policy limits
- The likelihood of litigation
- The expected cost of defending the claim
Historical databases are not neutral simply because they contain large amounts of information. Their results depend on what data was collected, which cases were included and how previous outcomes were categorized.
If earlier claims involving certain injuries were routinely undervalued, an algorithm trained on those outcomes may repeat the pattern. If a database does not adequately record loss of independence, cognitive fatigue, disrupted relationships or career consequences, those harms may receive little weight in the recommendation.
A computer-generated settlement range should therefore be viewed as an insurer’s internal evaluation – not an objective measure of what an injured person deserves.
Why AI May Undervalue an Unusual or Complicated Injury
Algorithms generally perform best when a new case resembles the examples in their data.
Personal injury claims often do not fit neatly into standard categories.
An unusual or complicated injury may be undervalued when the system cannot find enough comparable cases or does not recognize how multiple conditions interact. Examples may include:
- Complex regional pain syndrome
- Mild traumatic brain injuries with normal imaging
- Post-concussion syndrome
- Chronic pain without a single visible structural injury
- Aggravation of a preexisting condition
- Psychological trauma after a serious crash
- Injuries affecting a person with a highly specialized occupation
- Conditions involving delayed or fluctuating symptoms
- Multiple injuries that create a greater combined limitation
- Rare complications following surgery or treatment
Consider a musician who suffers reduced finger dexterity, a contractor who can no longer lift safely or a business owner whose post-concussion symptoms interfere with executive decision-making. Medical bills alone may not capture the injury’s effect on that person’s livelihood.
AI can identify patterns, but it may not understand why a seemingly modest physical limitation has major professional consequences.
It may also struggle to value experiences that are inherently personal, such as:
- The inability to care for a child
- Loss of independence
- Fear of driving
- Sleep disruption
- Cognitive fatigue
- Social withdrawal
- Changes in intimate relationships
- Loss of hobbies and recreation
- Ongoing uncertainty about recovery
These losses require context, testimony and persuasive documentation. They cannot always be reduced to a diagnostic code.
Small Details Can Have an Outsized Effect
Automated systems can process thousands of data points, but they may not distinguish between a genuinely damaging inconsistency and an innocent difference in wording.
For example, an emergency record may describe pain as beginning “today,” while a later specialist says symptoms began “after the accident.” A software program might flag the entries as inconsistent even though both statements describe the same event.
Other details that could be interpreted negatively include:
- A missed medical appointment
- A delay in filling a prescription
- A temporary return to work
- A social media photograph taken during recovery
- A note that the patient exercised
- A physician’s reference to a prior injury
- A short interruption in physical therapy
- An incomplete employment record
- A discrepancy in mileage or repair estimates
These facts do not automatically defeat a claim. The danger is that they may influence an automated score without the surrounding explanation.
Comprehensive documentation helps place each fact in context.
What Accident Victims Can Do to Protect Their Claims
You may never know exactly which software an insurance company uses or how heavily it influences the adjuster. You can still take practical steps to create a complete and accurate record.
Seek Appropriate Medical Care
Prompt medical attention helps protect your health and establishes a record connecting the symptoms to the accident.
Follow reasonable treatment recommendations, attend scheduled appointments and tell your providers about all relevant symptoms. Do not minimize an injury because you hope it will disappear, but do not exaggerate it either.
Explain Gaps in Treatment
There may be legitimate reasons for interrupted care, such as:
- Appointment availability
- Insurance authorization delays
- Transportation problems
- Childcare responsibilities
- Work demands
- Illness
- Financial hardship
- A provider’s recommendation to pause treatment
Tell your attorney why the gap occurred and preserve any documentation that supports the explanation.
Keep Medical Records Complete
Make sure your providers know how the injury affects your work, mobility, sleep and daily activities. A medical chart cannot reflect limitations the patient never reports.
You may also need records from specialists, therapists, pharmacies and prior providers to distinguish new injuries from preexisting conditions.
Document Lost Income Carefully
Preserve:
- Pay stubs
- Tax returns
- Employer statements
- Work schedules
- Disability records
- Commission histories
- Business financial documents
- Records of missed opportunities
For self-employed individuals and people with variable compensation, lost-income claims may require more detailed financial analysis.
Preserve Photographs and Video
Keep photographs of the accident scene, vehicles, visible injuries, medical devices and the progression of bruising or swelling. Save dashcam footage, surveillance video and relevant mobile-phone records before they are deleted or overwritten.
Maintain a Personal Recovery Journal
A journal can document changes that may not appear in medical billing records, including:
- Pain levels
- Sleep difficulties
- Medication side effects
- Missed family activities
- Driving anxiety
- Difficulty performing household tasks
- Cognitive or emotional symptoms
- Activities you can no longer perform
Keep the entries truthful and specific. Assume that anything created in connection with a claim could eventually be requested or reviewed.
Be Careful on Social Media
Insurers may review public posts for statements or images they believe conflict with the claim.
A smiling photograph does not prove that someone is pain-free, but an insurer may still use it to argue that the injury is less serious than reported. Review your privacy settings and avoid posting about the accident, medical treatment, negotiations or activities that could be misunderstood.
Do not delete existing content after a claim arises without first asking your attorney, as destroying potentially relevant evidence can create additional legal problems.
Review Every Statement for Accuracy
Recorded statements, claim forms and medical histories can be compared by automated systems. Answer carefully and truthfully.
Avoid speculation. When you do not remember a detail, say that you do not remember rather than guessing.
Do Not Accept a Fast Offer Without Understanding the Claim
Automation allows insurers to evaluate some claims very quickly. A rapid offer may arrive before the full medical prognosis, future treatment needs or income losses are known.
Once a settlement is accepted and a release is signed, the injured person usually cannot seek more compensation from the released party if the condition later worsens.
Ask a personal injury attorney to review the offer before giving up your rights.
Is an Insurer Allowed to Use AI in California?
The use of AI does not excuse an insurance company from complying with California law.
California’s Fair Claims Settlement Practices Regulations include standards for prompt, fair and equitable claim settlements. The California Department of Insurance also has emphasized that insurers must avoid unfair discrimination in claims practices, including discrimination that may result from data, models or algorithms.
National regulatory guidance similarly states that AI-supported insurance decisions remain subject to laws governing unfair trade practices and unfair claims settlement practices. Regulators expect insurers to maintain governance and controls designed to identify inaccurate, arbitrary, unfairly discriminatory or otherwise unlawful outcomes.
That does not mean every low offer involving automated analysis is illegal. Insurance carriers and injured claimants frequently disagree about liability, causation and damages.
It does mean an insurer cannot avoid its legal responsibilities simply by attributing an outcome to software.
Can You Ask Whether AI Was Used?
A claimant can ask the adjuster how the offer was calculated and what information influenced the evaluation. The insurer may not disclose proprietary software, internal scoring formulas or every data point considered.
An attorney may nevertheless challenge the underlying assumptions by requesting an explanation of the valuation, supplying missing evidence and identifying factual errors.
When litigation begins, additional information may sometimes be pursued through formal discovery, subject to relevance, privilege, trade-secret protections and court rulings.
The most important goal is not necessarily obtaining the algorithm’s source code. It is building evidence strong enough to show why the insurer’s conclusion is incomplete or unreasonable.
AI Can Assist Claims Handling, but It Cannot Tell Your Whole Story
Artificial intelligence is not automatically harmful. It can speed up administrative work, locate relevant records and help adjusters process large amounts of information. It may also reduce certain types of human error.
The concern arises when an automated recommendation is treated as a substitute for individualized judgment.
An algorithm does not experience chronic pain. It does not know what it means to stop carrying your child, abandon a career, depend on others for transportation or wake up every night because of accident-related symptoms.
Those consequences must be documented, explained and supported.
Do Not Let an Automated Valuation Define Your Recovery
Insurance companies may use AI to scan records, analyze photographs, detect fraud indicators and recommend settlement amounts. These tools can shape a claim before an injured person ever speaks meaningfully with an adjuster.
You do not have to accept an automated valuation as the final word.
The San Diego personal injury attorneys at Pines Salomon Personal Injury Lawyers can investigate your accident, gather medical and financial evidence, document the human effect of your injuries and challenge assumptions that may be lowering the insurer’s evaluation.
With more than 80 years of combined experience and over $100 million recovered for injured clients, Pines Salomon understands that no serious injury should be reduced to a score without considering the person behind the claim.
Contact Pines Salomon Personal Injury Lawyers for a free consultation before accepting an insurance company’s settlement offer.
We proudly serve San Diego, San Diego County, and its surrounding areas:
Pines Salomon Injury Lawyers – San Diego Office
835 5th Avenue #302, San Diego, CA 92101
(858) 551-2090
Available 24/7
Pines Salomon Injury Lawyers – La Jolla Office
4660 La Jolla Village Dr. San Diego, CA 92122
(858) 585-9031
Available 24/7
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