I have spent more than a decade sitting inside rooms where insurers, business leaders debate why life and health coverage still has not reached every corner of India. After going through all of this, my realisation is, it‘s not that people don’t want protection. People don’t understand it, don’t trust the process, they think insurance is complicated, English heavy, city thing for people who talk about tax benefits over coffee.
That’s where AI steps in. when I say AI, it’s not the sci-fi thing with robots floating around. I’m talking about the brilliant, very human feeling AI that works with our languages, our accents, our emotions, and yes, even our confusions.
So, let’s look at how data, voice bots, and vernacular AI might finally take life and health insurance to the people who’ve been left out. Whether it’s the gig workers, the farmers and yes, those quiet families in tier 3 towns who nod yes in meetings even when they don’t understand a single word. Trust me, AI might do it better.
The real barrier isn’t money. It’s understanding.
I have heard people say, “I can’t afford insurance.” What they meant is “I don’t get it”
I once tried explaining a critical illness plan to a relative in layman’s terms possible. He listened politely, nodded all the time, waited for me to finish my well-rehearsed explanation on survival benefit, then said, “… so is this health or life or something in between?”
People aren’t rejecting insurance. People are rejecting confusion. And confusion thrives where language barriers exist, where literacy varies, where processes feel intimidating, and where insurers expect everyone to magically understand actuarial logic.
This is exactly where data, voice bots, and vernacular AI come together like the perfect trio.
Voice bots make insurance less scary.
Voice bots? Really?
The kind of AI voice systems we can build today are nothing like that robotic “Press 3 to talk to a human” nightmares we’ve lived through. I’ve tested new-gen models that answer questions like an actual helpful human being with infinite patience. And the best part, there is no waiting to get in touch with a gen AI agent like we would wait for a human operator.
Imagine someone from a village in Uttar Pradesh calling a toll-free number and saying in pure Bundeli, asking about some health coverages, premiums, explanation of pre-authorisation etc. And the bot replies back in Bundeli, in plain language, without hesitation, without judgement, without putting the person on hold, and doesn’t disconnect until the person is clear.
In my work implementing AI-assisted claims systems, I saw how people opened up when communication became simple. They trusted the system more, asked more questions, and actually understood the answers. Also, the Voice bots don’t get tired or irritated. They don’t rush through conversations. They don’t assume anything about the customer. And that consistency builds trust faster than a glossy brochure ever will.
Vernacular AI speaks the language people think in.
Here’s the thing. Indians don’t think in English. As a matter of fact, even most English speakers don’t think in English. We think in our mother tongues. We translate in our heads. Insurance, until now, has been guilty of the worst sin possible: trying to convince people in a language they don’t emotionally connect with.
Vernacular AI changes that entirely. Picture this, A speaking farmer opens an insurance app, speaks in local language/accent and the bot replies in same language, with examples referencing real-life situations he understands. No corporate tone. No English jargon. No long sentences that feel like legal disclaimers. That’s not customer service. That’s dignity. And dignity creates adoption.
Data makes everything sharper, fairer, and more human.
I know it sounds strange to call data “human.” But think about it.
The more data you have, the more context you understand. And understanding context is what humans do best. In the same way, data helps AI, whether its understanding which areas lack health insurance, which professions need micro-coverage, which families require wellness nudges, which regions struggle with chronic illness patterns, which customers prefer voice over text.
And the beauty is, AI doesn’t judge. It doesn’t say “this demographic is risky because historically this group had higher claims.” Instead, AI can say “hey, this specific person has these specific needs; let’s tailor something.”
When I built fraud analytics models for a global insurer, we used advanced data clustering to identify patterns that humans could never catch manually. That same intelligence, when applied to product design, makes coverage personal in a way older systems never could. Data makes insurance fair. Fair insurance creates trust. Trust creates adoption.
The Unavoidable Mess of Policy Wording
Insurance isn’t complicated by accident. It’s complicated because life and health conditions are complicated.
Whether its policy wording, exclusions, waiting periods, claims documentation, health disclosures. I’ve sat through long discussions with underwriters arguing over a single line of wording that could change the claim outcome for thousands of customers.
AI can simplify that mess. Gen AI can rewrite entire policy documents in conversational language, highlight exclusions, translate everything, and answer questions like a seasoned advisor. AI makes insurance understandable. People trust what they understand.
AI reaches where agents physically can’t.
This is the part that excites me the most. India doesn’t lack supply. It lacks access. Agents can’t cover every village. Branches can’t reach every district. Apps can’t help people who aren’t comfortable reading.
But voice bots and vernacular AI can. AI becomes the bridge between insurers and millions of people who want protection but don’t know how to ask for it. Coverage isn’t limited by geography anymore. It’s limited only by imagination.
Last thought: AI needs guardrails. And heart.
AI is beneficial, no doubt about it, however we need strong governance. Not as a restriction, but more like a seat belt.
We need to make sure that the AI explains its decisions clearly and simply, and if it’s ever unsure about something, it has to defer to a human. It must respect the customer’s right to choose to speak with a person at any point in the process. Beyond that, the AI has to avoid any bias in things like pricing or claims, and fundamentally, it needs to remain accountable for its actions. So, the goal is to automate fearlessly, but we must supervise the whole thing wisely.
AI won’t just expand access. It’ll expand trust.
Life and health insurance should feel like a warm safety net, not a complicated exam. It all comes down to combining a few key things: the insights that data provides, the sense of comfort that voice bots offer, and the real feeling of belonging that vernacular AI can create. When these work together, they have the power to take life and health coverage from India’s big cities right down to its smallest towns, reach people in twenty-two language households instead of just English speakers, and change confusion into clarity.
The author is an insurance technology leader at PricewaterhouseCoopers (PwC), United States. Views are personal.
