The current state of generative AI, at least for insurance carriers, is hype outpacing reality. The potential of generative AI is undeniable on the consumer-facing side. It could transform the digital experience, make claims instantaneous and help customers prevent accidents before they happen.
But the current state of Gen AI—according to Corporate Insight’s new study, AI in Financial Services Today: The Opportunity, the Risk and the Emerging Reality—is that insurance customers have both a deep familiarity and an established distrust of AI. These negative sentiments put insurers in a tricky spot. Firms that move too slowly risk being left behind. But carriers that move too quickly to implement immature AI tools risk causing further distrust. Consumers are already suspicious of insurers and are concerned AI will be used to deny more claims.
Below we preview some key findings from the AI in Financial Services Report, which maps current AI positioning across every major financial services vertical, including insurance, to help firms make informed decisions about consumer-facing AI deployment. The report draws on CI’s competitive intelligence research across 21 verticals, in-depth consumer interviews, and a Q1 2026 survey of more than 2,000 U.S. adults.
The Distrust Challenge: Consumers Familiar with AI, but Dislike and Distrust Implementation
First let’s look at the reality: Consumer-facing AI applications have yet to make inroads in the insurance industry. Carriers show considerably more enthusiasm for touting AI in internal and financial professional-facing contexts, where proliferation has been substantial. On the internal side, applications tend to center on underwriting, claim processing and fraud detection. For financial professionals, the focus shifts to administrative efficiency, portfolio review and personalized client outreach.
Chatbots remain the most visible consumer-facing application, yet most are still rule-based or rely on basic NLP, a far cry from more sophisticated experiences offered by fintechs and even some large incumbent banks and brokerages. These VAs are not generative AI tools, nor are they even universal. Across the carriers CI tracks, only 61% of P&C personal lines insurers, 50% of life insurance carriers, and 39% of annuity firms have deployed a virtual assistant.
Consumer-facing AI tools are minimal to non-existent across the insurance industry—but one of the many challenges facing insurers is that customers believe the exact opposite. Our research for this study found that two-thirds of consumers already assume their financial services and insurance providers use AI—and their default interpretation is negative. They see AI as a way to cut costs, not to improve service. Consumers are more worried about AI and its effects on society than they are excited about it.
That’s a high bar for insurers to clear. Any consumer-facing generative AI tool will need to improve service and work so reliably that it overcomes consumer’s default distrust. Further complicating matters, customer expectations are formed by existing AI tools. In this case, that’s often the free versions of Claude and ChatGPT that, while impressive, remain prone to hallucinations and struggle with basic math.
Clear Identification Builds Trust (Give Your VA a Robot Name)
Clear identification of AI usage is a good first step for any insurer looking to build trust. According to our survey, when consumers interact with a chatbot and realize midway through that it’s AI, close to two thirds (57%) will immediately leave the chat, with satisfaction dropping sharply among those who disconnect.
Lemonade does well to explain how it uses AI in claims processing. The firm employs dual routing system for claims, wherein AI can unilaterally approve claims, but any claims that are not instantly approved automatically route to humans for review before a decision is made on the claim. Our IDIs (in-depth interviews) for this report found that consumers are comfortable with claim filing assistance but deeply worried AI will be programmed to deny claims. This clearly outlined process builds trust, ensuring that any negative outcome is still rooted in human review.
Another easy way to build trust in consumer-facing AI: Give any Gen AI tools a robot name. The previous generation of rules-based VAs often came with human names: Maya, Erica, AVA. Firms are now rebranding their VAs with robot names to avoid costly misunderstandings about AI.
Health insurers provide good examples of this trend, with Highmark BCBS identifying its chatbot as Mark, the Chatbot with a robot-head icon, and Arkansas BCBS giving its VA the straight-to-the-point name of ChatBot. Sparkle icons are slowly gaining traction as an AI indicator, although our research suggests firms should always label their icons.
Looking Ahead: AI Quote Journeys, Finding the Balance between AI and Human
In the insurance space, the most valuable consumer-facing AI applications will be the ones that simplify the digital customer experience. The lower-touch nature of the insurance industry means that the stakes for most customer service interactions are high. This reinforces the need for generative AI to build trust with customers by providing accurate information, being clearly identified, and including humans-in-the-loop wherever the stakes are highest.
Fifty percent of survey respondents said an easy option to switch to a human at any point in the interaction would make them more comfortable with AI. That was the top comfort driver in the survey. When AI tools hit their limit and offer no way out, consumers leave with a reinforced belief that the AI was there to avoid a conversation, not enable one. That’s a particularly bad outcome for insurance, where the moments consumers reach out are already fraught.
For carriers, the more pressing question is not whether current tools will improve (it’s safe to assume they will) but how and when to adopt these tools once they’ve improved. Traditional quote flows still hold a clear advantage in accuracy, personalization and actionability, but that gap narrows the moment carriers begin piping real-time rate data directly into AI platforms. Tracking how and where other firms are using AI, both inside and outside of the insurance industry, is the best way to ensure your organization leverages the power of AI while still preserving customer trust.
CI’s new study, AI in Financial Services Today: The Opportunity, the Risk and the Emerging Reality, covers AI deployment across every major financial services and insurance vertical, using competitive intelligence from CI’s monitor research, consumer interviews, and a 2,000-person survey.
The study includes the full report, complete survey data with age and gender cross-tabs, and a live executive presentation from CI’s subject matter experts.
To learn more or purchase the report, fill out the form below.
Justin Suter is the director of thought leadership at Corporate Insight.