The Department of Veterans Affairs is deploying artificial intelligence to screen Disability Benefits Questionnaires (DBQs) — the medical forms at the heart of veterans' disability claims — with the stated goal of catching fraudulent claims representatives, according to Small Wars Journal.
The algorithm's logic is drawing scrutiny. It automatically flags any DBQ where the examining doctor's address is more than 100 miles from the veteran's home. Small Wars Journal notes that this criterion directly penalizes rural veterans, who routinely travel long distances to reach specialized care — making them appear suspicious through no fault of their own.
The AI push comes alongside other contested VA policy moves. The agency had proposed amending federal regulation 38 CFR 4.10 to require examiners to factor in the "semi-corrective effects" of medication when rating disabilities — a change critics feared would shrink benefits for many veterans. Over 20,000 public comments opposed the rule, and the VA rescinded it on February 27, 2026.
Lawmakers are pushing back with the proposed FRAUD in VA Disability Exams Act, which would require an actual criminal conviction before the VA could reduce a veteran's benefits on fraud grounds.
AI systems are prone to hallucinations, data bias, and pattern-matching errors, according to Small Wars Journal, and the black-box nature of these tools makes it hard for veterans to challenge wrongful decisions. Recommended safeguards include mandatory human review before any AI flag affects a claim, independent auditing, and clear appeals pathways.
With millions of veterans' disability ratings — and the income tied to them — on the line, deploying opaque AI to police those claims without robust oversight risks automating injustice at scale.