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An employer’s AI policy for workers’ compensation claims should say which tools and tasks are covered, who is accountable, what the tools may and may not do, and how people will check, document, protect, and challenge their outputs. Treat AI as support—not a substitute for qualified human judgment—when an output could affect claim handling, benefits, medical review, work restrictions, accommodation, or return-to-work decisions. There is no single federal checklist in the sources discussed here; the policy must fit the employer’s role, state law, and claims arrangement.
Start by defining what the policy covers
Write down the systems used in the claim lifecycle, including employer-built tools, vendor products, automated decision systems, analytics, and generative AI. Include tools used by claims, human resources, risk, safety, and information technology staff, as well as tools used by a third-party administrator or other vendor on the employer’s behalf.
For each tool, record its permitted purpose, the workflow in which it is used, the information it receives, who can access it, and whether its output is advisory or can influence an action. Specify that unapproved tools may not be used for claim work. In particular, prohibit entering identifiable claim or medical details into a public AI service unless the use has been approved and its privacy, security, and data-use terms have been reviewed.
Set boundaries according to the consequences of use
Administrative assistance and claim-affecting recommendations do not carry the same risk. The policy should classify each use and set controls accordingly. The examples below are illustrative; an employer should classify its own tools based on what they actually do.
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| Use category | Illustrative tasks | Policy boundary |
|---|---|---|
| Administrative assistance | Organizing records, routing a document, or drafting a routine communication for staff review | Define the permitted task and require a person to check important information before it is sent, filed, or relied on. |
| Recommendation | Summarizing claim information or suggesting a next step for a claims professional | Require a qualified reviewer to verify the material facts, identify uncertainty, and decide whether to accept, reject, or escalate the suggestion. |
| Decision support with potential claim impact | Producing an output that could influence claim handling, benefits, medical review, work restrictions, accommodation, or return-to-work status | Do not let an unreviewed output determine or materially drive an action. Require meaningful human review, a documented rationale, and an escalation route for disputed or uncertain results. |
A review is meaningful only if the reviewer has suitable expertise, access to the relevant information, and authority to question or override the system. The policy should identify which roles may review which outputs, what they must verify, and when they must stop and seek additional review.
Protect claim and medical information
Set rules for data minimization, permitted purpose, role-based access, secure storage and transfer, retention and deletion, and incident reporting. Keep claim medical information separate from ordinary personnel records, consistent with applicable ADA requirements, and limit access to people who need it for an authorized purpose. Establish how workers can request access to or correction of information when applicable.
Do not assume HIPAA either always applies or never applies. HHS explains that the HIPAA Privacy Rule generally does not apply to an employer, workers’ compensation insurer, or administrative agency unless that entity is otherwise a covered entity. Covered health care providers may disclose protected health information for workers’ compensation purposes as authorized by state or other law and subject to applicable limits. The specific data flow and legal basis should therefore be reviewed for the employer’s role and the relevant state law. (HHS OCR, Disclosures for Workers’ Compensation Purposes; minimum-necessary FAQ.)
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For vendors, specify that claim information may not be reused for unrelated purposes or model training unless the use is expressly approved and legally permitted. Require vendors to explain their data practices, protect the information, support review and audits, disclose material system or model changes, and cooperate with incident response. Keep the employer’s own responsibility clear even when a third party supplies or operates the tool.
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Preserve ADA safeguards in claim-related workflows
Workers’ compensation administration and ADA obligations can apply to the same situation. The EEOC’s guidance on workers’ compensation and the ADA says that injury-related questions or examinations should be tied to the specific injury and its effect on work or workers’ compensation eligibility—not used to open an unrelated or excessive medical inquiry. It also says claim-related medical information must be kept separately and confidentially, subject to specified disclosures. The guidance was issued in 1996, before the ADA Amendments Act of 2008, so employers should apply it alongside current law and advice appropriate to their circumstances. (EEOC, Enforcement Guidance: Workers’ Compensation and the ADA.)
AI does not remove discrimination or accommodation duties. The EEOC and Department of Justice have warned that employment algorithms can screen out workers with disabilities, fail to accommodate them, or require disability-related information in ways that raise concerns about medical inquiries or examinations. For claim-related tools, the policy should prohibit using AI to infer unrelated health conditions or to expand medical inquiries beyond their lawful scope. It should provide an accessible non-automated route where needed and a process to request accommodation when the tool or workflow creates a disability-related barrier. (EEOC and DOJ, May 12, 2022 announcement.)
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Require validation, monitoring, and a response to problems
Before deployment, document the tool’s intended purpose, data sources, model or system version, validation method, known limitations, and the standard for acceptable performance. Assess whether error patterns or outcomes indicate unfair bias or disability-related effects. Repeat the assessment periodically and whenever a material change to the model, vendor, data, or workflow could change its behavior.
Record significant reviewer actions, incidents, and corrective measures. Define who may pause or suspend a use and what triggers that response—for example, a material concern about accuracy, privacy, security, or fairness. If a worker or reviewer disputes a material output, provide a route to raise the issue, correct relevant information, obtain human reconsideration, and document how it was resolved. Do not treat the system’s output alone as an adequate explanation for a consequential action.
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Assign ownership and train the people involved
Name an accountable policy owner and designate who approves new tools and uses. Claims, HR, risk, and IT teams should know the permitted uses, data-handling rules, review duties, escalation route, and incident process. Approval should cover the actual workflow and information used, not merely the product name; a new feature or changed use may require a fresh review.
Give staff a practical way to identify AI-generated or AI-assisted material where that matters to verification, and train reviewers to check source information rather than accept plausible-sounding output at face value. Vendors and administrators should provide enough system documentation for the employer to evaluate intended use, limitations, data practices, and material changes.
Make the policy specific to state law and the employer’s role
Workers’ compensation rules differ by state, and insurance bulletins may apply to regulated insurers and their agents rather than every employer. Maintain a state-by-state review process that considers workers’ compensation rules, insurance unfair-claims or unfair-discrimination requirements, privacy and security obligations, ADA duties, records rules, and relevant AI laws or regulator guidance. Review the rules for the entity actually making or supporting the decision, including a carrier, administrator, agent, or vendor.
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WCRI’s 2025 report on AI in workers’ compensation discusses governance, validation, documentation, monitoring, transparency, privacy, and security. It reports that its authors were not aware of workers’ compensation-specific AI laws at the time of their research, while noting broader insurance oversight and NAIC principles and model guidance. That is a dated research finding, not a definitive legal conclusion for 2026. (WCRI, Artificial Intelligence in Workers’ Compensation.)
Quick Recap
Turn the policy into an operating checklist
- Inventory: List tools, vendors, workflows, intended purposes, input data, access roles, and output types.
- Classify: Mark each use as administrative assistance, recommendation, or claim-affecting decision support; define prohibited uses.
- Approve: Assign an owner and require review of legal scope, privacy, security, accessibility, fairness, and validation before use.
- Review outputs: Identify qualified reviewers, verification steps, override authority, escalation triggers, and worker correction or reconsideration routes.
- Document and monitor: Keep records of versions, validation, limitations, material review actions, incidents, changes, and remediation.
- Reassess: Revisit approval after material changes, a significant incident, or a change in law or regulatory guidance, and conduct periodic review.
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