Is Automation Anywhere the future of insurance claims?
Automation Anywhere is carving out a clear role in insurance claims automation by combining RPA with agentic AI that handles end-to-end workflows. U.S. carriers facing longer cycle times and rising leakage are testing whether its platform can move from pilot to production without the brittle scripts of earlier RPA. The question matters now because May 2026 platform updates and pre-built autonomous agents are already shipping.
Platform roots and timing
Automation Anywhere launched in 2003 as an RPA vendor and has since layered document AI and goal-driven agents on top of its cloud core. The current release, rolled out in 2026, adds a Process Reasoning Engine trained on more than 400 million interactions. That engine lets agents decide next steps across intake, triage, and payment without constant reprogramming.
Insurance teams have watched similar updates from UiPath and others, yet Automation Anywhere’s emphasis on governance and audit trails appeals to carriers that must document every decision for regulators. The timing coincides with renewed pressure on loss-adjustment expense after several quarters of elevated claims volume.
Early adopters report that the newest agents can classify documents, extract data, and route work in a single pass, cutting the hand-offs that once stretched simple claims across multiple systems and desks.
Claims workflow coverage
The platform automates first notice of loss intake, document classification, coverage verification, fraud scoring, adjuster assignment, and final payment. Each step runs under human-in-the-loop controls that flag exceptions for review rather than halting the process.
Because the agents operate across legacy policy systems and modern cloud portals, carriers avoid the rip-and-replace projects that often stall automation programs. The same orchestration layer also logs every action for compliance audits.
Insurers that still rely on manual routing see the largest immediate lift, since the agents collapse the multi-day queue that once sat between document receipt and adjuster assignment.
Document handling and accuracy
Document automation remains the heaviest lift in claims, and Automation Anywhere’s extraction models now pull structured data from emails, scanned forms, and mobile uploads. Accuracy rates above 95 percent on standard forms reduce the re-work that drives leakage.
Carriers testing the tools note that the models adapt quickly when a new state form appears, because the underlying reasoning engine can reference prior examples rather than requiring new scripts. That flexibility matters for multi-state writers that process hundreds of form variants each quarter.
Reduced manual re-entry also lowers the error rate that triggers secondary audits, a cost center that one U.S. commercial carrier trimmed by 80 percent after deployment.
Measured outcomes in production
A U.S. property and casualty insurer reported a 60 percent drop in average handling time and 100 percent accuracy on workers’ compensation files once bots took over routine steps. The same deployment cut audit volume because every decision carried an immutable log.
EXL, working with multiple carriers, moved end-to-end claims from multi-day cycles to same-day resolution by embedding the agents inside existing adjuster queues. Productivity gains above 40 percent appeared within the first four months of rollout.
These results sit inside the broader industry range of 30 to 70 percent time reductions cited in recent vendor benchmarks, yet they come with documented governance layers that some competing platforms still lack.
Agentic shift versus legacy RPA
Traditional RPA required fixed scripts that broke whenever a portal changed. Agentic automation instead receives a goal, such as “resolve this claim under policy limits,” and selects the next action from available tools and data sources.
Automation Anywhere’s May 2026 release added pre-built autonomous solutions for finance and IT that carriers are now adapting for claims sub-processes. The shift reduces the maintenance burden that once consumed 30 percent of automation budgets.
Teams that previously spent weeks mapping every exception path now spend days defining guardrails, then let the agents surface edge cases for human review.
Market positioning today
Automation Anywhere competes most directly with UiPath on insurance use cases, yet it differentiates through deeper document AI and a cloud-native architecture that scales without on-premise servers. Pricing comparisons often favor the San Jose vendor when operating cost per claim is modeled over three years.
Analyst notes from mid-2025 placed both vendors in the leader quadrant for insurance automation, but buyers increasingly ask for side-by-side pilots rather than relying on published benchmarks alone. The deciding factor tends to be how cleanly each platform sits inside a carrier’s existing claims management system.
Neither vendor claims to be the sole future of claims automation; both position their tools as accelerators that still require skilled adjusters for complex files.
Integration and change management
Successful rollouts begin with narrow scope, typically auto or workers’ compensation first notice of loss, then expand once the first agents prove stable. Change-management playbooks emphasize that adjusters move from data entry to exception handling, a shift that improves retention when communicated early.
IT teams value the platform’s APIs that connect to Guidewire, Duck Creek, and home-grown portals without custom middleware. Security reviews focus on the governance console that enforces role-based access and produces regulator-ready reports.
Training time for claims staff averages two weeks when the rollout includes side-by-side shadowing of the agents on live files.
Risks and guardrails
Over-reliance on automation can mask upstream data-quality issues that only surface after go-live. Carriers that invested in clean policy data before deployment saw faster stabilization than those that automated around legacy inconsistencies.
Model drift remains a concern when new fraud patterns emerge; Automation Anywhere mitigates this with continuous feedback loops that retrain agents on flagged cases. Still, human oversight of high-severity claims stays non-negotiable.
Budget owners also track total cost of ownership, including the licensing model that charges per bot hour rather than per user, to avoid surprise line items in year two.
Next deployment steps
Carriers evaluating automation anywhere should run a four-week proof of concept on a single claim type, measure cycle time and accuracy against a control group, then scale only after the governance framework is approved by compliance. The May 2026 agent updates make this timeline shorter than it was twelve months ago.
Those that complete the pilot phase report clearer ROI models that factor both direct savings and improved customer retention from faster settlements.
Forward trajectory
Automation anywhere is not the only path to automated claims, yet its current combination of agentic orchestration, document accuracy, and measurable production results positions it as a leading option for U.S. carriers ready to move beyond pilots. The next twelve months will show whether broader adoption follows the early documented wins or whether competing platforms close the gap on governance and integration speed.
