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Case study 03  Deep dive

AI Insurance Quote

B2C, direct to customer  Individuals and businesses buy insurance online

A price from one sentence, not five pages. An AI-first way to buy auto, home, life and business insurance, where the application fills itself and the customer stays in control.

It started from an industry signal. In February 2026 insurers began offering quotes inside ChatGPT, and insurance stocks fell on the news. I asked what buying insurance should feel like when the first touchpoint is a conversation, not a form.

Role
Solo UX design, concept and prototype
Scope
10 screens, 5 lines of insurance, 1 AI assistant
Domain
Insurance distribution, conversational AI
Status
Concept  clickable prototype, not user-tested

At a glance

The case in seven answers

Client
Northstar (anonymized)
What was the problem?
A personal auto quote asks about 24 fields across five pages, including a license number and part of an SSN, before the customer sees a price. Commercial renewals repeat dozens of unchanged answers every year.
Why did it matter?
Customers do the insurer’s data entry before they get any value, and the front door is moving into AI assistants, where a five-page form cannot live.
What research was done?
A field-by-field audit of a personal auto application, a real seven-page healthcare renewal form with identifying details removed, an industry analyst note on AI-led buying, and assumption-based personas that are not yet validated.
What constraints existed?
Carriers still need a complete, structured application. Prices come from the carriers’ rating engines, identity and payment are required to buy, and commercial renewals need a licensed broker’s review.
What decisions did I make?
I chose agentic AI for the front door: it reads free-form requests, fills what it can, and decides which question to ask next, asking only what changes the price. Every answer is labeled by source, sensitive data comes last, and the full form or a licensed agent is always one click away.
How did engineering shape it?
The AI fills the application, but the carriers’ rating engines set the price, so the AI never invents a number. The form stays behind the conversation because carriers need structured data. In the prototype, simple rules stand in for the language model and the rating systems.
What changed after launch?
It has not launched. It is a concept with a clickable prototype. Next, I would test with recent buyers and measure quote started, price seen and policy bought, plus how often people change what the AI filled.

01  Problem

Five pages before a price

Buying insurance online still works like a paper form moved onto a screen. A typical personal auto quote asks for about 24 fields across five pages, including a driver license number and part of a Social Security number, before the customer sees a single price.

Commercial insurance is heavier. A real healthcare association renewal application I worked from runs to seven pages: general information, liability and employees, services and licensed beds, medical services and abuse protocols, directors and officers, crime, and a statement of values for up to ten locations. Most of it is “any changes?” questions the organization already answered last year.

The customer does the insurer’s data entry, and only then learns the price.

Meanwhile, the front door is moving. In February 2026 a digital insurer and an insurance comparison platform launched quoting apps inside ChatGPT, and insurer and broker stocks fell in Europe, the US and Australia on fears of disruption. Industry analysts described it as a reset of insurance distribution: people getting personalized quotes inside AI assistants they already use.

The problem, stated plainly

  • Too much before the price. About 24 fields and five pages for a personal auto quote.
  • Sensitive data too early. License and SSN are asked before the customer has any reason to trust the site.
  • Most answers are already knowable. Vehicle safety features, a home’s year built and roof, or last year’s renewal answers.
  • Renewals repeat everything. Commercial customers re-answer dozens of unchanged questions every year.
  • The channel is shifting. Customers will increasingly start in an AI assistant, and a five-page form cannot live there.

02  Impact

Outcomes, business impact and learnings

This is a concept, so the business impact is modeled from the prototype and the real application it is based on, not measured. I have marked which is which.

Outcomes

What I delivered

  • Ten screens and a clickable prototype covering auto, home, life and small-business quotes, plus a commercial healthcare renewal.
  • A source-labeled application model: every answer is marked You said, You answered, Looked up, Assumed or If you buy.
  • A renewal-by-exception pattern that turns a seven-page form into six change checks and a broker review.

Business impact

Modeled, not measured

  • Price first: 24 fields before a price become one sentence and two or three questions.
  • Renewals: 64 answers become 6 checks, and the broker receives only flagged changes to review.
  • Conversion: fewer fields before the price is the lever most likely to lift quote completion. Measure quote started, price seen and policy bought.
  • Channel readiness: the same understand, ask and quote engine can serve customers inside AI assistants, where analysts expect buying to move.

Learnings

What I took from it

  • The form doesn’t disappear; it moves behind the conversation. Carriers still need structured answers.
  • Trust is earned in order: value first, identity later.
  • An invisible assumption is a wrong price waiting to happen, so assumptions are the first thing we show.
  • Next: test with recent buyers, and measure how often people change what the AI filled and where they switch to the form or an agent.

Designed outcomes, not measured results

This is a concept with a clickable prototype, not yet tested with customers. In the prototype, simple rules stand in for a language model and for carrier rating systems. Carriers, prices, records and organizations are sample data, and the healthcare renewal is modeled on a real application with all identifying details removed.

03  Product

The quote comes first. The form fills itself.

Carriers still need a complete application, so the form doesn’t disappear. It moves behind the conversation. The customer says what they need in one sentence, and the AI does the data entry, visibly, field by field.

Understand

The AI reads one sentence, works out the line of insurance, and fills every field it can: from the customer’s own words, from records, and from sensible defaults it labels as assumptions.

Ask

Only questions that change the price, one at a time, with answer chips or free text. Usually two or three. Everything else waits.

Quote

Carriers’ rating engines price the filled application. The AI recommends a plan, says why, and shows what moves the price.

You decide

Identity, payment and consent come only now, after a price. The AI never buys on the customer’s behalf.

Where this sits on the autonomy spectrum

Across my three case studies, the AI’s freedom follows who bears the cost of a mistake. In Claims Adjuster Copilot a licensed adjuster approves every AI proposal. In Enterprise Tool Governance an agent acts inside limits admins set. Here the AI does all of the paperwork, but the customer makes the decision, and for commercial renewals a licensed broker reviews everything before insurers see it.

The journey

One sentence, five steps, ten screens

From a single sentence to a policy, plus the same idea applied to a commercial renewal. Select a screen to jump to it.

  1. Tell

    Describe what you need in your own words, or pick a line of insurance.

    01 Home
  2. Understand & ask

    The AI fills the application and asks only what changes the price.

    02 Conversation10 Full form
  3. Quote

    Three plans, a recommendation with a reason, and the price explained.

    03 Quotes04 Review
  4. Decide

    Identity and payment only now, then the policy is issued.

    05 Decide06 Issued09 Agent
  5. Renew

    For businesses, last year’s answers carry over and a broker reviews the changes.

    07 Renewal08 Broker

The screens

From one sentence to a policy

Select any screen to view it full size. Carriers, prices, records and organizations are all sample data.

02

Conversation

The centerpiece. From “Auto insurance for my electric SUV in LA. I commute to work.” the AI picks up location, vehicle and use, fills 15 fields and asks only two questions: the driver’s age and driving record. On the right, the carrier’s five-page application fills itself, color-coded by where each answer came from, so the customer can see exactly what the AI did.

Ask only what changes the price
03

Quotes

Three plans from sample carriers, with an AI pick and a plain reason, such as “battery repairs are expensive, so collision cover matters.” Deductible and limits re-price instantly. “What moves your price” shows each factor’s effect in dollars, based only on the customer’s own answers.

Explain the price
04

Review what the AI filled

Every answer by page, with its source and a way to change it. Assumptions are the first thing to check, because if an assumption is wrong, the price is wrong. Nothing goes to a carrier until the customer buys.

Show every assumption
05

You decide

The first time the site asks who you are. Name, license, SSN and payment appear only here, after a price, and the customer confirms the AI’s answers are accurate before “Buy” is enabled.

Sensitive data last
01HomeOne prompt box, example requests, or pick a line of insurance. A side-by-side sets the promise: five pages the usual way, one line this way.
06Policy issuedThe policy is issued, with the proof of the idea on screen: time to first price, questions answered and fields filled for you.
09Talk to a licensed agentA licensed agent with the full picture. No repeating yourself: the agent sees the conversation, the answers and the quotes.
10The full formThe same application as a familiar form, already filled and fully editable, for anyone who would rather not chat.

Business insurance

Renewal by exception

The same idea, applied to the seven-page healthcare renewal I started from. Most answers don’t change from one year to the next, so the AI carries them over and asks only what might have changed. A licensed broker reviews anything flagged before insurers see it.

For the customerTraditional renewalRenewal by exception
Pages to complete7None. Review is optional
Answers to give64, most of them unchanged6 change checks, plus 2 signatures
What the broker receivesA full form to re-read line by lineThe same full form, with changes flagged
Who decidesThe customer and the brokerStill the customer and the broker. The AI prepares

Counts come from the prototype’s sample renewal, modeled on the real application. They are not measured results.

07

Healthcare renewal

Last year’s 64 answers are carried over across seven pages. The AI checks six things that might have changed: services, staff and volunteers, funding, incidents, planned changes and the liability limit. Each page turns green as it is confirmed.

Carry over, then confirm
08

Broker handoff

The renewal lands with the broker, not directly with insurers. What changed is flagged, an indicative premium range is shown with its assumptions, and a timeline makes the human steps clear: broker review, insurers, terms, signature.

A person reviews before insurers see it

04  Experience

Get a quote yourself

Type your own request, or pick a scenario. Answer with the chips or in your own words, change the coverage, review the answers and buy. The bottom bar jumps to any screen, and “Reset demo” starts over. All data is sample data.

AI Insurance Quote  prototype Open full screen ↗

The prototype is a desktop-sized app, so it opens best in its own tab.

Open the prototype ↗

How I got here

The design process, in one document

This page shows the problem, the impact, the product and the experience. The thinking behind them is in a 23-slide presentation: discovery, research materials, personas, journey maps, ideas, user flows and a validation plan.

  • Discover
  • Research materials
  • Personas
  • Journey maps
  • Ideas
  • User flows
  • Screens, annotated
  • Validation plan
View the design process 23 slides  view only

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