What a Time essay on AI and trust means for insurance

What do artificial intelligence and trust mean for insurance? (AI-generated image)

By Jonas Roeser

Tiffany Xingyu Wang raised a troubling question in her recent TIME essay, “AI Arrived at the Worst Possible Moment”: What happens when a technology capable of producing persuasive answers arrives when people are less certain about establishing what is real?

In insurance, that question has a human face. Someone asks an AI assistant to find an agent who can help their mother choose Medicare coverage, protect the family business or decide what to do with a life insurance policy. The assistant returns a name, a polished summary and perhaps a few reasons the agent appears qualified. Before that person makes a call, there are questions the answer may not address. Is the agent who they claim to be? Is their license current? Did they earn the designation listed in their biography? Are the reviews attached to the right professional?

The insurance industry has always depended on trust. Agents are invited into conversations about illness, retirement, death and family finances. Much of that trust is built in person, over time. But the first introduction now often happens online, and increasingly it may come through an artificial intelligence answer assembled from information scattered across the internet.

That information varies enormously in quality. A professional biography may be written by the agent. A credential may appear without a link to the organization that awarded it. A licensing record may be current while a directory listing is years old. A strong review may tell a consumer something useful about an experience without answering whether the professional is qualified to handle a particular need.

Wang writes about the loss of shared ways to determine what deserves belief. In insurance, we can address one small but consequential part of that problem. We can make the claims attached to a professional easier to check and keep checking the facts that can change.

I think of this as a trust stack. Identity is one layer. Licensing and professional standing are another. Education and earned designations add context. Reviews help a consumer understand what working with an agent may be like. None tells the whole story, but together they offer a fuller picture than a search result or a polished profile can provide on its own.

Many agents and agencies are asking how to appear when someone searches through an AI assistant. It is a fair question. But being mentioned is only the beginning. If an AI system surfaces an agent, the consumer should be able to look beyond the summary and examine the professional information behind it. No profile can promise that an agent is the right fit. Verification does not measure judgment, compassion or the quality of advice. It can answer basic questions that a consumer should not have to leave to guesswork. It can also help an honest professional distinguish earned qualifications from claims anyone could type onto a website.

Insurance media and professional organizations have a part to play. Publications help readers understand complex products and emerging risks. Associations and course providers establish standards and award credentials. Agencies know their professionals and their areas of practice. When those sources make their information clear and current, they give consumers something useful to examine. They also improve the information AI systems may draw upon.

Wang’s essay is a warning about the conditions in which AI is arriving. It also points toward work we can do now. We cannot control every answer an AI assistant gives. We can improve the evidence available when someone asks whether the person in that answer is real, qualified, and currently authorized to do the work.

Google indexed websites. AI increasingly assembles answers from them and other sources. In insurance, the next step is to make trust easier to inspect.

TIME and Tiffany Xingyu Wang do not discuss or endorse Agent Review in the referenced essay.