A client who needs proof of insurance at 9 p.m. is the easiest case for an AI assistant, because the answer sits in a record and software can fetch it. Here, an AI assistant means software that carriers and agencies run, such as a chatbot or a voice system. The insurance virtual assistants we recruit are people, as our definition of what an insurance virtual assistant is explains, and they often work next to these tools.
Key Takeaways
- AI assistants can answer account questions at any hour from the policy record, and a person handles anything that needs judgment.
- Software can flag a possible coverage gap, but recommending coverage is licensed work and a licensed agent makes the call.
- In claims, AI tools sort documents, route files and flag unusual ones for review, and the carrier's adjusters still decide.
- Natural language processing lets software read a question in everyday words, and it works best on narrow topics such as billing dates and document requests.
- Machine learning scores risk and spots patterns at carriers, and regulators expect insurers to govern how they use it.
Giving Customers Real-Time Information
Picture a policyholder who wants to know on a Sunday morning when the next premium is due. A portal or chatbot can look up the policy and answer in seconds, and nobody at the agency has to be on call. That is the strongest case for AI in service: a question with one right answer, held in a record.
A chatbot answers at any hour, which also helps a client whose time zone differs from your office. The answer is only as good as the record, though. When the record is wrong, the software repeats the error faster, and chat tools stumble on questions that need judgment, such as whether a particular loss is covered.
Personalized Recommendations for Enhanced Insurance Experience
Software can compare a client's policy with what it knows about them and flag gaps: a new driver who is not listed, or a business that opened a second location. A flag is a prompt. Advising a client on coverage is part of selling, which the NAIC's Producer Licensing Model Act reserves for licensed producers by defining negotiating to include offering advice on a contract's benefits, terms or conditions. A licensed agent decides what to recommend.
Intelligent Claim Processing and Automation
Several vendors that serve carriers describe AI tools for intake and sorting. Cognizant describes software that identifies, sorts and routes the documents behind underwriting, claims and policy administration, and Capgemini says it embeds AI in claims workflows from intake and triage to decisioning and settlement. Wipro's claims pages mention fraud scanning with machine learning.
A fraud flag is a reason for a person to look closer, and nobody should deny a claim on a flag alone. At an agency the effect is indirect, since a carrier portal that updates faster gives your assistant fresher status to pass to the client.
Using Natural Language Processing for Intuitive Interactions
Natural language processing, or NLP, is software that reads and writes ordinary language. It lets a client ask a question the way they would ask a person. The table shows what such tools are built to do, and how well they do it depends on the product and the data behind it.
| Text-based | Voice-based | |
|---|---|---|
| Understanding the request | Reads the message and the customer's policy record to find the answer | Turns speech into text, then works out what the caller wants |
| Documents and images | Accepts photos and documents, such as a picture of damage or a policy page | Reads out policy dates and claim status from the record |
| Staying consistent | Gives the same answer on the website, in the app and by text | Gives the same answer on the phone as in chat |
Machine Learning for Optimized Insurance Operations
Machine learning is software that finds patterns in past data. Insurers use it for tasks such as scoring risk and spotting unusual claims, and regulators have taken notice. The NAIC adopted a model bulletin on insurers' use of AI systems in December 2023, and its page on artificial intelligence says decisions made or supported by AI must comply with insurance laws.
The agency side of this is smaller. A tool trained on messy records gives messy answers, so the assistant's work keeping the management system accurate is the groundwork. For more on routine work that can move to a person, see how virtual insurance assistants improve workflow efficiency.
Enhancing Customer Satisfaction Through AI-Powered Assistance
Clients like fast answers at odd hours, and they dislike a loop of canned replies. Give every chat a clear way to reach a person during office hours, and have your own assistant return those requests the same day.
Satisfaction also depends on what happens after the handoff. A message that arrives with the client's name, policy number and question already filled in spares them from repeating it, and that is where a human assistant and a chatbot work well together.
Driving Innovation in the Insurance Industry With Virtual Assistants
An agency could add tools like these without changing its staff:
- Software that reads incoming documents and files them, with the assistant checking the matches.
- A website chatbot that answers billing-date and document questions and has a button to reach a person.
- A call-summary tool that drafts notes for the assistant to correct.
- A report that flags policies near lapse, which the assistant works through with reminders.
For where this is heading, read our piece on future trends in insurance virtual assistant outsourcing.
Final Thought
AI tools are likely to keep getting better at the narrow, repetitive parts of insurance service. An agency does best when it gives software the lookups, keeps people on the judgment calls and checks the work.