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Artificial intelligence is becoming a practical operating tool across insurance. Carriers, third-party administrators (TPAs) and other claims organizations are using it to review submissions, summarize claim files, support customer service, identify claims requiring attention and detect duplicate payments.
AI can process large volumes of information, reduce the time required for routine tasks and help insurance professionals focus on work requiring greater judgment. Publicly reported examples point to shorter processing times, increased review capacity, faster assignments and earlier intervention.
But speed is not the same as accuracy, and an alert is not the same as a sound claim decision. Independent expertise is still needed to determine whether the documentation is complete, a reserve is adequate, a litigation strategy is appropriate or a reported performance improvement is producing better outcomes.
Key Takeaways
- AI is improving workflow performance. The most established applications involve intake, summarization, document review, customer service, claim triage and payment controls.
- Operational gains do not automatically produce better claim outcomes. Faster processing has value only when the work remains accurate and leads to appropriate decisions, escalation and follow-through.
- Independent oversight remains necessary. Experienced review can test whether AI-supported workflows are improving claim outcomes, controlling costs and strengthening performance without weakening professional judgment.
Where AI Is Improving Insurance Workflows
Current applications are concentrated in high-volume activities involving repeated steps, large amounts of information or identifiable patterns. The following examples are drawn from public industry disclosures.
Company names have been omitted from the table to keep the focus on how the technology is being used rather than on individual organizations.
Examples of How AI Is Improving Insurance Workflows
| Activity | How AI is being used | Reported or expected benefit |
|---|---|---|
| Underwriting intake | Reviews submissions, extracts information and supports coverage analysis. | One carrier reported reviewing more than 370,000 submissions in 2025, a 26% year-over-year increase, and a 35% improvement in submit-to-bind performance.1 |
| Customer service | Answers routine questions and assists with policy and billing communications. | A carrier reported that AI supported 46 million customer interactions and contributed to an approximately 45% reduction in policy and billing inquiries.2 |
| Medical review | Organizes medical information for review. | Approximately 50% less time reported for certain medical-report reviews.3 |
| Claim reporting | Captures first-notice-of-loss information and supports intake calls. | One carrier reported that AI-supported workflows reduced first-notice-of-loss processing time from days to hours.1 |
| Claim-file review | Summarizes medical records, correspondence and other unstructured material. | Faster review and reported summarization accuracy above 98% in one pilot.4 |
| Early intervention | Identifies claims that may benefit from clinical or other specialized attention. | One claims organization reported 53% faster case assignment, a 27% reduction in case duration and a 14% higher return-to-work success rate.5 |
| Payment integrity | Identifies duplicate bills and patterns associated with fraud, waste or abuse. | One program flagged an average of 6.2% of submitted workers' compensation bills as duplicates.6 |
| Claim triage | Segments claims and recommends routing based on severity, complexity or risk indicators. | One claims organization reported that AI-supported triage can coordinate a network-wide response within minutes of an incident, while related automation can remove days or weeks from the claim lifecycle.7 |
| Adjuster support | Drafts communications, recommends workflow steps and surfaces relevant file information. | One carrier reported that AI reviews or generates 100% of its claim-adjuster emails. The disclosure demonstrates broad use but does not quantify time savings, accuracy or effects on claim outcomes.2 |
| Distribution and agent support | Uses customer and contextual information to support product selection, quotes and policy inquiries. | A carrier is rolling out an AI assistant across an agent network of more than 19,200 offices serving over 96 million policies and accounts. The carrier expects faster access to quotes and policy information.8 |
AI can accelerate insurance work, but independent expertise is still needed to determine whether the results are accurate and producing better outcomes.
Why AI-Supported Performance Still Requires Oversight
Faster processing does not necessarily produce better claim or financial outcomes. A claim summary may omit a material fact, a duplicate-payment alert still requires validation, and a risk score cannot determine the appropriate reserve, settlement or litigation strategy.
AI creates greater value when it expands professional capacity, supports earlier action and reduces administrative expense. The key question is whether AI-supported work is accurate, properly reviewed and producing better claim and operational outcomes.
How Alan Gray Can Help
AI can improve the speed and reach of insurance reviews, but experienced judgment is still needed to interpret complex claim facts and evaluate reserve, litigation and payment decisions.
Alan Gray can provide an independent layer of review to determine whether AI-supported processes are accurate, properly controlled and producing measurable results through the following services:
- Claim-file and process reviews: Determine whether AI-generated summaries and recommendations are supported by the underlying documentation and lead to appropriate action.
- TPA and vendor oversight: Evaluate service levels, exception handling, performance reporting and reported technology benefits.
- Litigation and legal-spend analysis: Assess whether technology-supported processes are controlling legal costs, supporting claim strategy and identifying leakage.
- Performance validation: Establish baselines and determine whether faster processing increases capacity, reduces costs and improves claim outcomes.
AI can accelerate insurance work. Independent review helps determine whether the results are accurate, properly controlled and improving claim outcomes.
Citations
- American International Group, Inc. 2025 Annual Report. AIG, 2026.
- The Allstate Corporation. Third Quarter 2025 Earnings Call Presentation. Allstate, 2025.
- Aviva. "Aviva Extends Industry-First AI Underwriting Tool to Critical Illness Cover." 18 Mar. 2026; Aviva. Annual Report and Accounts 2025. 2026.
- Sedgwick. "Sedgwick Enters Next Phase of AI Technology Development to Transform the Claims Industry." 2 May 2024.
- Enlyte. "GenexEngage." 2026.
- CorVel Corporation. Elevating Bill Review to Fight Fraud, Waste, and Abuse. 2025.
- Crawford & Company. Tariffs and Claims Inflation. 2025.
- State Farm. "Our Next Gen Good Neighbor Customer Experience." 12 May 2026; "State Farm Advances AI Vision Through Collaboration with OpenAI." 5 Feb. 2026.
