AI Phone Agent for Insurance Policyholders: Why Self-Service Calls Are Falling Short

Why Are Insurance Policyholders Still Making Calls Rather Than Using Mobile Apps?

Calls from policyholders continue to occur because there are some times when apps aren’t able to support customers. Here are some things carriers and insurance agencies need to know about this situation.

According to JD Power’s latest claims satisfaction survey (JD Power, 2026), mobile claims apps have been getting better in terms of user experience. However, their adoption varies widely by age group and type of claim.

Specifically, what carriers see on their side is more precise: calls related to checking statuses and requesting an ID card occur predominantly within the first 48 hours after filing a claim and around the time of renewals – no matter how advanced the mobile app gets.

When searching for “State Farm customer service” or “Liberty Mutual customer service,” people expect to hear a voice rather than looking at more screens in an app. Moreover, claim call volume can be seasonal and weather-related – catastrophes lead to massive spikes in both claims and call volume for days or weeks. (JD Power, 2024)

If you cannot track the weekly volume of ID card or status-check calls to your front desk, you lack the baseline needed to evaluate AI phone call ROI. 

NOTE

While most carriers monitor app download rates, not calls per insured person. If you cannot say how many ID card or status calls you get to your front desk weekly, this is the first audit to perform before even thinking about evaluating any AI vendor.

Industry Benchmark: What the Data Reveals About Live Deployments

Aggregate benchmark is a real-life average derived from AI phone agents’ live deployments in insurance, not a vendor estimate. Here is the range.

For the observed policyholder-facing deployments, the average hold time on status check calls is reduced by approximately 35-40% as soon as an AI phone agent starts resolving calls in the first place and routing exceptions to a human agent, while ID card requests take less than 45 seconds to be fulfilled end-to-end, including identity verification.

Accuracy of FNOL capture is the metric to focus on. Structured FNOL intake (matching fixed fields to the claims system’s database) always leads to a lower number of missing field callbacks by adjusters than free-form FNOL scripts, although the extent of reduction varies across lines of business and depends on the intake criteria of your claims system rather than being a fixed value.

PRO TIP

Ask for de-identified call logs from a similar line of business from any vendor before accepting a benchmark number. A 40 percent reduction in hold times on automated FNOL will not apply to commercial property claims.

The above numbers should not be taken as contractual; factors such as call type mix, claims system latency, and insured demographics all skew the actual number. 

What Should Insurers Look for in an AI Phone Agent for Policyholders?

An AI call assistant for policyholders is software that verifies the caller’s identity, retrieves policy data in real time, and takes care of standard tasks through voice. The following are some of the requirements for buyers.

ID Card/Proof of Insurance Requests

In this case, the agent should verify the identity using either the policy number or date of birth and send the ID card via email or text within the course of the phone call. This use case alone handles most of the front desk inbound volume.

Claims Status Check

The agent requires a live connection to the claims management system, be it Guidewire, Duck Creek, or an in-house carrier platform. Stale read replica and latency greater than a few seconds is all it takes for the agent to repeat a stale status and lose trust quicker than not having an answer at all.

Payments and Billing

If the policyholder calls regarding their billing or a failed attempt at autopay, the customer must be provided with the ability to pay via telephone in a PCI-compliant way. The agent must escalate all overdue accounts to a human collection team, rather than deal with it themselves.

First-Notice-of-Loss (FNOL) Capture

FNOL is the most critical call type because the early information dictates the whole claim. It should capture the loss date, location, people involved, and the initial description, and then immediately put the claim into adjuster queue.

However, what carriers and agencies of scale face in reality is that most call volume comes from ID cards and status checks, while FNOL calls are infrequent but very expensive when mishandled.

An effective AI phone agent should have confidence in handling high-frequency interactions while being careful when handling high-stakes interactions, escalating any FNOL edge cases to a licensed adjuster instead of relying on assumptions.

How Does Integration Actually Work? API Latency, Security, and Conversational Design

Integration is the collection of technical connections that allow the AI phone agent to access the live policy data during a phone conversation. This is how this works.

API Latency and Real-Time Data Access

The latency of the round trip of information from the voice layer to the policy and claims management system should not be long enough for the caller to sense any delay. Anything higher than about 1-2 seconds of latency becomes a noticeable wait time on a phone call and is quite different from the patience of someone seeing a loading spinner on a web application. The carriers who still use the policy systems built upon the legacy mainframes require the caching layer.

Webhook Security and Authentication

The status update or payments confirmation are usually sent via webhook. This means that the integration requires the signed payload, allow-listed IPs and short-lived tokens.

The webhook endpoint itself must be considered a public attack surface, as in many ways, it actually is.

PII Masking and Data Processing

Policy numbers, birth dates, and claims information are all examples of sensitive data, which means that the call transcript or log must have PII masking applied prior to storage or QA review. It’s as important for internal access control as it is for external data breaches – all employees who can hear the call recording do not necessarily need to see the unmasked policy number.

SOC 2 Compliance

SOC 2 Type II compliance shows that the vendor’s security practices remain consistent over time, beyond just a point-in-time audit. For all AI phone agents that process the PII or payment information of policyholders, SOC 2 Type II should be the standard.

Conversational Flow Design

Conversational flow design refers to the design of prompts, fall backs, and escalation triggers.

Flows that are not properly designed have a tendency to circle the user back through authentication routines or quietly fail on any vague request; flows that are designed correctly clearly define exit conditions for all branches, even the situation where the claim system itself fails.

Integration Middleware

Where there is no API in place on legacy carrier systems, data may be pushed through middleware such as MuleSoft, or even lightweight automation solutions such as Zapier for smaller carriers who need less compliance.

Buy vs. Build: A Decision Matrix for Insurance AI Agents

Buy versus build is the core tradeoff between licensing an existing AI phone agent platform and engineering one internally. Here’s how the two compare on the dimensions that actually matter for insurance.

For most regional insurers and independent agencies, it’s difficult to justify the build option against the continuous compliance and maintenance costs. The approach makes sense mostly if a company already has its own conversational AI team for other solutions.

A deeper breakdown of integration requirements and vendor evaluation criteria is covered in the AI phone call automation buyers guide, and the financial side of that decision is modeled in the AI phone call ROI and payback period guide.

What Will Change If an Insurance Company Deploys an AI Phone Agent?

The deployment is the stage at which the number of calls will transition from people queue to AI agent handling the routine queries. And here are the changes that insurers and agencies will observe.

There will be less need for front desk or call center employees to answer the same old questions regarding status and ID cards. They can handle renewals, retention, and complicated claims that require some level of reasoning.

Holding time will decrease during disasters as there is no need to recruit more employees. The AI phone agent will immediately adjust to threefold increase in the number of calls.

Complaint trends also have their relevance. Policyholder service-related complaints, which include coverage complaints and non-response complaints, comprised almost one-fifth of the total NAIC complaints closed in 2024 based on ValuePenguin’s analysis of NAIC complaint statistics (ValuePenguin, 2025). Faster and more efficient phone resolution helps address this complaint trend directly.

NOTE

Perform a baseline audit of call volumes by type, ID card, status, payment, FNOL, before assessing any vendor’s claims. The ROI equation does not work if the baseline is not accurate.

Should you make the switch? In cases of agencies receiving hundreds of ID card and status calls per week, the decision becomes rather obvious: reduced number of abandoned calls, less pressure on staff during claims spike periods, and improved speed in capturing FNOL data leading to quicker involvement of adjusters. Pricing depends on call volumes and can be found on the AI phone call software pricing page.