Will AI Replace Insurance Agents? The Work Is Splitting

Agencies are adopting AI quickly, and the occupation is still projected to grow. Both of those are on the record, and holding them together is most of the answer to whether AI will replace insurance agents.

AI is already doing parts of the job and it will do more. Routine work moves first. Who answers for the advice does not move with it, though direct channels and automated recommendations can still take particular services away from agents entirely.

Inside a working agency today

Walk into a working agency today and the AI is quieter than the headlines suggest. It quotes. It reads a submission and pre-fills the forms. It drafts the follow-up email. It answers “what is my deductible” at 9pm so a person does not have to. Producer services sit inside the same AI governance perimeter as underwriting and claims, and on the same business-line map, even when the tooling looks like office software.

By one industry survey, 64 percent of US agencies now use AI in at least one workflow, up from 38 percent two years earlier, with quoting the most common use.¹ That figure comes from a vendor’s report rather than a regulator, so treat the exact number with care. But the direction is not in dispute: the routine, high-volume tasks are the ones getting automated first, because they are the easiest to automate and the least fun to do.

None of that is the part of the job clients actually pay for. They pay for someone who knows which coverage they need, who picks up the phone when a claim goes wrong, and who is on the hook if the advice was bad.

One projection, and the claim it can test

One employment projection cannot isolate AI from retirement, channel shifts, economic growth, and changes in the mix of captive and independent agents. It can still test the strongest claim, which is that the occupation is about to disappear.

The US Bureau of Labor Statistics projects employment of insurance sales agents to grow about 4 percent from 2024 to 2034, roughly the average for all occupations, with about 47,000 openings a year over the decade.² That is a government projection made with full knowledge that AI and online self-service exist. The same outlook notes that online research and direct purchase reduce demand for some agent services, and that independent agents are expected to fare better than captive ones as carriers push distribution costs down.²

Read together, the message is narrow and useful. Simple products and routine service face pressure from direct purchase and automation. Advice remains part of the projected demand. A projection is not a promise, and this one cannot tell you whether your own segment holds. It can say that the aggregate is not collapsing.

What stays human

It helps to separate the job into tasks and ask which ones a model can actually own.

A model can quote. It can compare options against a rule set. It can summarize a policy. It can route a simple service request. These are pattern tasks, and pattern tasks are what AI is good at.

A model can simulate a coverage conversation and surface useful questions. It does not hold the producer license, absorb professional liability, or become the person a regulator identifies when advice was improper. Those stay with the human and the firm no matter how much of the interaction the software takes.

The line that matters runs between performing a task and answering for the result. Pattern work will keep crossing it, at a pace that differs by product and by agency. Accountability does not move merely because the workflow does.

Competition arrives through agents and direct channels

Volume is where the pressure lands first, and it comes from another producer using automation to carry more of it. Direct digital channels create a second pressure, especially in simple products where advice adds less visible value.

When quoting and intake are automated, the agent who adopts the tools handles more clients with the same hours and spends the saved time on advice and relationships. The agent who does not adopt them does the same volume by hand and slowly loses on price and speed. The vendor report behind that adoption figure makes the same argument from the sell side, and it frames the cost of waiting as lost quotes rather than lost jobs.¹ Discount the source and the point survives, because it is the one claim in a sales document that does not require you to buy anything.

So the nearer contest is between agents. The software just sets the pace.

The part most coverage skips: your own AI use

When an agent or agency starts using AI to do more than answer questions, the same rules that govern carriers can start to reach the agency. Whether they reach a firm your size is its own self-check. The narrower question here is what pulls a producer in.

The mechanism is duller than it sounds, and it is worth knowing exactly. The unfair trade practices act your state runs on does not say “insurer.” The NAIC model text makes it an unfair trade practice for “any insurer, health insurance lead generator, or person engaged in the business of insurance” to commit the practices it lists, unfair discrimination among them. A producer, the same act says, is a person licensed to sell, solicit, or negotiate insurance.³ Your license is what puts you inside the statute the NAIC bulletin points examiners at.

The trigger is a tool with a say in who gets offered what. A lead-scoring or recommendation engine can produce proxy discrimination with nobody intending it, and licensing the engine from someone else does not move the license. How the channel gets governed as a whole is worked through in AI in insurance distribution.

Quoting and service tools often carry less fair-treatment exposure than lead scoring or recommendations, but they are not outside privacy, security, licensing, recordkeeping, or misrepresentation rules. Once a tool starts deciding which prospects hear about a product at all, testing becomes more urgent. If you license one, ask the vendor what evidence shows that outcomes do not skew by protected class. An assurance without the method and results leaves the agency unable to evaluate the answer.

AI returns hours. Quoting, paperwork, and the after-hours deductible question never needed a license, and moving them to software frees time that has to go somewhere. An agent who spends it on more processing has adopted the technology without collecting what it was for.

FAQ

Will AI replace insurance agents? Current evidence does not show the profession disappearing. BLS projects the occupation to grow about 4 percent through 2034.² That aggregate outlook can coexist with fewer roles in particular products or channels.

Which parts of an agent’s job is AI taking over first? The repetitive, low-judgment tasks: generating quotes, reading submissions, drafting routine correspondence, and answering common service questions. None of that work depends on a relationship, which is why it moves first.

Should independent agents worry more or less than captive agents? The official outlook expects independent agents to fare better, because insurers are leaning more on brokerages and less on captive agents to control costs.² The bigger variable for any agent is whether they adopt the tools at all.

Does using AI create compliance risk for an agency? It can, once the tool starts shaping the offer rather than describing it. Tools that only quote or answer questions carry little exposure. Lead-scoring and recommendation engines raise fair-treatment questions, and the agency that deployed one is inside the answer.

Footnotes

1. Perspective AI, “AI for Insurance Agents in 2026: Adoption Hit 64%,” 2026: https://getperspective.ai/blog/ai-for-insurance-agents-2026-64-percent-adoption-industry-data . Vendor-published survey; the adoption figures are self-reported industry data, not a regulatory statistic. ↩ ↩²

2. US Bureau of Labor Statistics, “Occupational Outlook Handbook: Insurance Sales Agents.” Employment “is projected to grow 4 percent from 2024 to 2034, about as fast as the average for all occupations,” with “about 47,000 openings … projected each year, on average, over the decade”; the outlook also states that “many clients do their own research and purchase insurance online, which reduces demand for an insurance sales agent’s services” and that “employment growth will likely be strongest for independent sales agents as insurance companies rely more on brokerages and less on captive agents in an effort to control costs.” https://www.bls.gov/ooh/sales/insurance-sales-agents.htm ↩ ↩² ↩³ ↩⁴

3. NAIC, Unfair Trade Practices Act (MDL-880), Spring 2024 edition. Section 3: “It is an unfair trade practice for any insurer, health insurance lead generator, or person engaged in the business of insurance to commit any practice defined in Section 4 of this Act”; Section 2.K defines “producer” as “a person required to be licensed under the laws of this state to sell, solicit, or negotiate insurance”; Section 4.H is the unfair discrimination provision, reaching anyone “making or permitting” it. This is the model text; each state enacts its own version, and the UTPA is one of the two acts the NAIC AI Model Bulletin rests its authority on. https://content.naic.org/sites/default/files/model-law-880.pdf ↩