AI in insurance is here, but is it helping users or only businesses?

When artificial intelligence started its subtle but incremental arrival in the insurance industry, it was sold as the solution to age-old inefficiencies: cumbersome forms, impenetrable product information, and inflexible underwriting practices. Now, AI pledges personalisation, velocity, and transparency. But beneath efficiency and innovation is the higher question. Who really wins from this AI transformation in insurance: the end-user, or the business?

Let's turn back the clock

For years, the purchase of insurance was a confusing, transactional affair. Sellers, under quotas or incentives, pushed customers toward products that more often benefited the company than the consumer. Policyholders had no clue what they were purchasing until claim time, a time too late. This gap of trust persisted for years, and digital transformation, driven by AI, was to remedy it. And, in a sense, it has.

AI is increasingly being applied to tailor insurance policies to income, geography, credit history, and even life aspirations. It can analyse thousands of pieces of data in a matter of seconds and spit out policy options that suit a person's profile. For tech-literate city professionals, this is a refreshing break from boilerplate products and stingy fine print shocks.

But there's a catch

Underlying the promise of personalisation is a business model still driven by commissions, cross-sell opportunities, and monetisation of user data. Even as some sites proudly proclaim their AI-facilitated neutrality, delivering best policy choices based on performance, not payment, the business as a whole too often operates in obscurity. Is the suggestion really in the user's best interest, or nudge-optimised for profitability?

The line is thin, and increasingly, it’s being tested

Consider claims processing, still another field that AI has transformed. Intelligent algorithms are capable of detecting suspicious claims with high accuracy, allowing insurers to cut costs and be more efficient. But there's a downside, too: increasingly, the fear of false positives, instances where legitimate claims may get turned down because algorithms are too strict or too obscure. For a family waiting on a prompt reimbursement, this's not a technical error; it's an emergency.

Even customer support, formerly a human function, is being increasingly AI-driven. Voice assistants and chatbots can lead customers through the labyrinth of policy information or claim submissions. In theory, this cuts down on agent reliance and allows for on-demand help. But in reality, customers get stuck in endless loops of canned responses, finding it difficult to access a human voice when it is most crucial.

Not that AI is not valuable to customers. For sites that are actually transparent and customer-focused, however, AI can be a game-changer. Take newer players who centre their models around user trust, providing unbiased counsel, free consultations, and the option to avoid human involvement altogether. These sites aren't employing AI to eliminate people from the equation but to provide users with more power over how much engagement they desire.

The risk is scale

As these models expand, so does the pressure to cut corners. Insights derived from data can be hijacked for marketing, cross-selling, or retargeting. Insurer partnerships, vital to platform monetisation, can start to decide which products receive more exposure. In time, the distinction between "smart suggestion" and "subtle steering" can become blurred.

This is where public awareness and regulation need to change. Just as banking services were brought under control to avoid predatory lending or covert fees, the insurance industry funded by AI requires clear guardrails. Sites need to reveal not only what they're suggesting, but why. Users have a right to know if their financial choices are being driven by algorithms acting in their best interests, or somebody else's.

Transparency, explainability, and accountability have to become the non-negotiable foundations of AI in insurance. Users do not need a more "intelligent" or faster process; users need a fair one.

The future is not dark. It's actually full of promise. Consider AI systems that learn and adapt constantly from user input, rather than from engagement rates alone. Consider platforms that teach users with every suggestion, helping them better know their own needs over time.

Consider insurance as a lifetime planning companion working behind the scenes, never cajoling.

But for that future to be a reality, we need to pose the tough questions now.

AI in insurance is no longer some promise for the future; it's today's reality. But if it's to really be about the user, not the business, then it has to be more than efficiency and incorporate empathy, ethics, and transparency.

Until such time, the question remains: Is AI in insurance here to serve us, or serve itself?

(Vaibhav Kathju is Founder and CEO of Inka Insurance.)