Indian consumers have already folded conversational AI into the way they handle money. ServiceNow’s Customer Experience Report found that 80% of Indian consumers use AI chatbots for tasks such as checking the status of a complaint, getting product recommendations and accessing self-help guides. More tellingly for financial services, 78% said they use AI chatbots when reviewing investment options. Car insurance is now being drawn into the same habit.

That matters because third-party motor insurance is one of the few financial products every vehicle owner in India is legally required to buy, and among the least understood. The question is no longer whether customers will consult an AI tool before renewing, but what they do with the answer.

Trust, Not Technology, Decides the Habit

The evidence from India is early but pointed. A 2026 study in the International Journal of Bank Marketing  based on survey data from 245 experienced insurance-chatbot users in India, examined what drives both first-time adoption and sustained use. Trust in the chatbot significantly shaped both. Ease of use and perceived usefulness predicted adoption intentions, with consumers placing particular value on convenience and being able to reach the service across multiple channels.

The more interesting finding concerns risk. Perceived risk reduced trust, but did not stop people using the tools, a pattern the authors characterise as a calculated, risk-tolerant mindset. Indian customers are broadly aware a chatbot may be wrong and are using it anyway, which places the burden of verification on them at exactly the moment they are least equipped to carry it.

What People Are Actually Asking

Service teams across the industry tend to field the same queries, and they are definitional rather than about price: what Insured Declared Value means and who sets it, the difference between third-party and comprehensive cover, whether engine damage caused by waterlogging is included, what happens to a no-claim bonus after a small claim, and whether a particular add-on justifies its cost.

These are precisely the questions that have historically gone unasked. Insurance vocabulary in India is dense, agents tend to be consulted at renewal rather than during research, and few buyers read a policy wording end to end. A chatbot removes the social cost of asking a basic question, and it answers at eleven at night.

Where AI Helps, and Where It Stops

It helps most with decoding jargon. Explaining depreciation, IDV or a total-loss threshold in plain language is exactly what these tools do well, and a customer who understands those three concepts negotiates a renewal far better than one who does not.

It stops at anything specific to the individual policy. An AI tool does not know a customer’s no-claim bonus, claims history, geographic zone classification or an insurer’s currently filed rates. It can describe an add-on category accurately and still be wrong about a particular document, because add-on names and inclusions are not standardised across insurers in India. A general answer about engine protection cover says nothing about the exclusions printed in a specific wording.

There is a subtler issue too. Because these tools draw on publicly available material, the answer a customer receives may reflect whichever insurer’s content is most visible online rather than whichever product suits them.

Gaurang Thosani, Head – Digital Marketing & eBusiness at Royal Sundaram, noted: “Customers are arriving at the renewal conversation far better informed than they were years ago, and they are arriving with sharper questions. That is good for the industry. Our job is to make sure the answer they get from us matches the policy document, because the document is what outlines what the claim will actually cover.”

The Regulator Has Started Writing the Rules

On 18 June 2026, IRDAI constituted a seven-member working group on artificial intelligence, chaired by Sandeep K. Shukla, Director of IIIT Hyderabad. Its mandate is to assess how far regulated entities have already deployed AI and then build the sector’s first formal governance framework, covering ethical, transparent and explainable use, with claims processing and fraud detection named as priority areas.

One limitation is worth stating plainly. That framework will govern how insurers themselves deploy AI. It does not extend to the third-party chatbots a customer consults independently before buying a policy. For now, that verification gap sits with the buyer.

A Practical Way to Use It

●      Use AI to build questions, not conclusions. It is a research assistant, not an underwriter.

●      Verify every specific claim against the policy wording and schedule, not a brochure or a comparison summary.

●      Check the IDV on the quote yourself. It drives both the premium and the payout, and a low premium often reflects a low IDV.

●      Confirm anything price-bearing, such as no-claim bonus, deductible and add-on inclusions, directly with the insurer before buying.

Gaurang Thosani, Head – Digital Marketing & eBusiness at Royal Sundaram, added: “An AI tool can explain what zero depreciation means. It cannot tell you whether your specific policy includes it, what your no-claim bonus is worth this year, or how your claim will be settled. Those answers sit in your policy schedule, and that is still the document customers should read.”

Taking the Next Step

The useful conclusion for car owners is not that AI should be avoided, but that it should be used for what it is genuinely good at, understanding the product, rather than for what it cannot do, which is confirming the terms of an individual contract.

Insurers such as Royal Sundaram publish policy wordings and add-on details alongside their car insurance quotes, which makes that verification step quick. As conversational tools become a standard part of how policies are researched, the buyers who benefit most will be those who use them to ask better questions before signing.