Consumers Increase Support for AI in P&C Insurance
Insurity's 2026 AI in Insurance Report finds a rapid uptick in consumer familiarity and conditional support for AI in property and casualty insurance. 84% of consumers use AI tools at least occasionally and 27% use them daily. Support for insurers using AI to improve services rose to 39% in 2026, up from 20% in 2025, while the share of consumers less likely to buy from an insurer that publicly uses AI fell from 44% to 36%. Consumers accept AI for routine, low-risk tasks like generating quotes and tracking claim status, but comfort drops sharply for autonomous, decision-making actions such as filing claims or canceling policies. For insurers and ML teams, the report signals an opening to expand augmentation use cases while prioritizing transparency, human-in-the-loop controls, and explainability for decisions that materially affect customers.
What happened
Insurity released its 2026 AI in Insurance Report showing a substantial shift in consumer sentiment toward AI in property and casualty insurance. Insurity reports 84% of consumers use AI at least occasionally and 27% use AI daily. Aggregate support for insurers using AI to improve services increased to 39% in 2026, nearly double the 20% recorded in 2025. Resistance to insurer AI usage declined from 44% to 36%.
Technical details
The survey breaks consumer comfort into task types, revealing a clear tolerance boundary between assistance and autonomy. Consumers are relatively comfortable with AI handling routine, informational workflows but become wary when AI takes autonomous action on policyholder accounts. Key comfort metrics include:
- •46% willing to let AI generate a quote
- •39% comfortable with AI tracking claim status
- •38% comfortable using AI to update personal information
- •22% comfortable with AI filing a claim on their behalf
- •16% comfortable with AI canceling or renewing a policy
The press release does not supply granular methodology, sample size, or demographic breakdowns, which limits statistical interpretation. For ML and product teams, that means treating these percentages as directional signals rather than precise effect sizes.
Context and significance
This shift aligns with broader consumer normalization of AI across search, productivity, and financial services. For insurers, the result validates prioritizing augmentation use cases that improve speed and convenience while preserving human oversight for adjudication, fraud decisions, and policy-enforcement actions. Practically, insurers should treat this as permission to expand AI-powered quoting, status updates, and personalization, while investing in audit trails, explainability, and easy escalation paths for consumers.
What to watch
Insurers that push for deeper automation without clear opt-in, recourse mechanisms, and transparent decision explanations risk reversing the trust gains. Expect vendors and carriers to emphasize hybrid workflows, human-in-the-loop guardrails, logging for regulatory audits, and UX patterns that surface when AI is acting versus when a human intervenes.
Scoring Rationale
The findings are notable for product, risk, and ML teams in insurance: they validate expanding AI for routine workflows but underline limits on autonomous decisioning. The story is industry-relevant rather than a frontier-model or infrastructure milestone, so it rates as a solid, actionable signal.
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