Florida Moves to Rein In Insurance AI Amid Fears of Unfair Claim Denials

Florida lawmakers probe insurer AI use, pushing guardrails, human review, and fairness. Carriers should keep humans on adverse decisions, document models, and test for bias.

Categorized in: AI News Insurance
Published on: Oct 10, 2025
Florida Moves to Rein In Insurance AI Amid Fears of Unfair Claim Denials

AI in Florida Insurance: Guardrails, Fairness, and What To Do Now

Florida lawmakers are scrutinizing how insurers use artificial intelligence across underwriting, claims, and customer service. The message was clear: AI is already embedded in operations, and carriers are still on the hook for compliance and outcomes.

A recent U.S. Senate report projected major labor shifts from AI over the next decade. Against that backdrop, a Florida House subcommittee dug into whether new rules are needed to protect consumers while enabling efficiency gains.

What lawmakers asked

Legislators pressed on a core concern: Can AI be the sole basis for denying a claim or declining coverage? Rep. Hillary Cassel cited allegations of a 90% error rate when AI alone evaluated certain claims and asked what Florida law bars AI-only denials.

Industry voices stressed that existing statutes requiring fair claim settlement still apply. "At the end of the day… the insurance company is always responsible," said Thomas Koval, a retired executive and current FCCI Insurance Group board member.

Where AI is already used

AI is not theoretical. The state's Department of Financial Services reported its consumer chatbot handled 13,000 interactions since October 2024. Carriers are using AI to surface fraud indicators, assess property risks, and deploy drones to survey damage and proximity to hazards.

Speed and pattern recognition are delivering faster triage and more consistent workflows. The question is how to keep those gains aligned with Florida insurance code and consumer fairness expectations.

Guardrails and accountability

"An AI system has to have guardrails," Koval told lawmakers. He emphasized human intervention on the front end and algorithms built to comply with existing insurance regulations.

Koval also pushed for safeguards that prevent consumer harm: compliance-first model design, monitoring for errors, and clear accountability. The principle stands: whether a platform is automated or human, the insurer is responsible for the decision.

Fairness concerns: AI-only denials

Cassel pressed on whether Florida law explicitly bans AI as the sole basis for a denial. The panel noted that current statutes on fair claims handling already bind insurers, but did not cite a specific prohibition on "AI-only" decisions.

Practical takeaway for carriers: treat AI as decision support, not decision maker, on adverse actions. Ensure human review, documentation, and appeal paths.

Pricing, selection, and market access

Lawmakers also flagged a risk: if AI identifies more micro-risks, will fewer people qualify for coverage? Rep. Nathan Boyles asked how to avoid over-targeting that erodes access.

"Companies that don't pay claims and don't write new policies will not be in business for long," said Paul Martin of the National Association of Mutual Insurance Companies. He argued AI can increase precision and make some previously "uninsurable" risks workable with better data.

Policy outlook in Florida

The panel recommended addressing specific AI problems as they appear rather than passing broad, one-size-fits-all AI laws. Expect targeted guidance and enforcement grounded in existing insurance code, with updates as use cases evolve.

What carriers and MGAs should do now

  • Adopt a "human-in-the-loop" standard for adverse actions. No claim denial, cancellation, or declination should rely solely on AI output.
  • Document model use and decision rationale. Maintain audit trails mapping inputs to actions, with explainability for regulators and consumers.
  • Build compliance guardrails into models. Encode Florida insurance code constraints, rate/rule filings, and claims standards into workflows.
  • Test for bias and error rates. Backtest regularly, track false positives in fraud models, and calibrate thresholds to reduce consumer harm.
  • Tighten vendor oversight. Require transparency on data sources, training methods, monitoring, and indemnities for noncompliance.
  • Upgrade consumer notices. Disclose when automated tools inform a decision and provide clear appeal and human review paths.
  • Train front-line teams. Claims, underwriting, SIU, and compliance need practical training on AI limits, overrides, and documentation.

Useful resources

Upskilling your team

If you're formalizing AI oversight or building model governance, align training across underwriting, claims, and compliance. A structured path helps teams apply AI responsibly and defend decisions.

Explore AI courses by job role to support adoption and accountability across your organization.

Bottom line

AI is already embedded in Florida insurance operations. The safest path is simple: keep humans in control, code compliance into the workflow, and prove fairness with data. That protects customers-and it protects your company when the questions come.