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.