%20(1).png)
TPAs are essential to modern claims administration. Insurance organizations rely on them for claims capacity, operational support, and specialized expertise. That role is becoming more demanding as claim files grow harder to manage, document, and explain.
Claims professionals are also facing heavier reporting, compliance, data, and legal spend requirements. In response, many organizations are introducing artificial intelligence into claims workflows to reduce manual work, organize information, and identify files that may require closer attention.
AI may improve efficiency, but it does not resolve the underlying challenges in complex claims. Fragmented systems, inconsistent documentation, unclear reserve rationale, and incomplete litigation data can limit the usefulness of automated analysis. For higher-severity files, technology still needs to be supported by experienced judgment, technical review, and effective oversight.
TPA Growth and Workflow Complexity Create Capacity Pressure
How Complex Claims Strain Standard Workflows
Claims involving disputed liability, multiple parties, medical complexity, high-risk venues, reserve uncertainty, or excess and reinsurance exposure often require more frequent review and deeper analysis. For TPAs managing large claim inventories, these files can place added pressure on standard workflows. They may require:
- More detailed documentation of liability, reserves, and settlement rationale.
- More frequent client reporting on legal spend, reserves and emerging severity.
- Closer review of litigation budgets, invoices, and defense strategy.
- Additional coordination with excess carriers, reinsurers, and other stakeholders.
These demands can reduce the time available for the judgment and analysis that most directly influence claim outcomes.
Where AI May Help—and Where It May Not
Within claims workflows, AI may be most useful when it helps professionals organize information, identify exceptions, and focus attention on files that warrant deeper review.4
Potential Benefits Include:
- Preparing an initial claim chronology from notes, reports, and litigation updates.
- Flagging files with rising legal spend but no current litigation budget.
- Identifying reserve changes that lack clear supporting documentation.
- Organizing information before a large-loss review, client meeting, or reserve discussion.
- Reducing routine work so claims professionals can focus on files requiring judgment and technical review.
Potential Limitations Include:
- Producing a summary that appears complete even when important liability facts are missing.
- Identifying a legal spend increase without showing whether the work was necessary.
- Relying on outdated, inconsistent, or incomplete claim information.
- Generating conclusions that are not supported by the underlying file.
- Overlooking emerging exposure when claim coding or documentation is weak.
AI can make information easier to process, but it cannot independently determine whether a litigation strategy is appropriate, a reserve is adequate, or a settlement opportunity should be pursued. Those decisions still require context, judgment, and accountability.
AI can help organize claim information, flag unusual legal spend or reserve activity, and reduce routine work. It cannot independently determine whether liability is adequately assessed, a reserve is appropriate, litigation strategy is sound, or a settlement opportunity should be pursued.
Why Legal Spend Deserves Closer Review
Legal spend can reveal whether defense activity is aligned with the claim's exposure and resolution strategy. Rising costs, outdated litigation budgets, or weak links between counsel activity and claim strategy may signal that the file needs closer review. Analytics can help identify unusual billing patterns and budget variances, but those indicators still need to be evaluated in context. Liability, venue, procedural posture, expert needs, and settlement strategy all affect whether legal spend is appropriate.
Where Alan Gray Can Provide Additional Support
TPAs may benefit from additional support on high-severity claims, rising legal spend, legacy files, excess or reinsurance issues, unclear settlement posture, or matters identified through automated review.
Alan Gray can provide independent claim and legal spend review to clarify exposure, assess strategy, strengthen reporting, and support better-informed decisions, including evaluating whether automated summaries or alerts accurately reflect the claim file and whether gaps in documentation, coding, or data are affecting the review process.
Alan Gray's role is not to displace the TPA or its technology, but to provide additional technical depth and independent visibility when complex claims require more focused attention, helping TPAs and their clients align around claim strategy, reserve rationale, legal spend drivers, reporting obligations, and resolution opportunities.
Citations
- IBISWorld. "Third-Party Administrators & Insurance Claims Adjusters in the US—Market Size and Industry Statistics." IBISWorld, 2026.
- Mordor Intelligence. "Insurance Third Party Administrators Market Size and Share." Mordor Intelligence, 16 Jan. 2026.
- Demski, Jennifer. "Workers' Compensation Industry Faces Administrative Overload as Technology Transformation Lags." Risk & Insurance, 11 Aug. 2025. The article cites Rising Medical Solutions' Workers' Compensation Benchmarking Study.
- Luckman, Nina. "From Automation to Augmentation: How AI Reshapes Workers' Compensation." Risk & Insurance, 29 May 2026.
-2.png)
.png)
