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Artificial Intelligence (AI) is revolutionizing the insurance industry by driving advancements and efficiencies. But do you know the pitfalls to look out for?
Published on July 8, 2025
By April Minkus, Esq.
Executive Claims Examiner/Counsel, Management Liability Claims
And Keith Rahman, Esq.
Sr. Claims Examiner, Management Liability
2-minute read
As AI usage grows, the legal landscape has been playing catch up, leading to more lawsuits and pressure on lawmakers to provide clearer guidelines. To address these challenges, the insurance industry should adopt proactive risk mitigation strategies to secure the responsible and ethical use of AI technologies. Here are the top 10 insurance industry risk mitigation strategies related to AI to keep in mind:
#1 Establish diversity in AI development teams: A diverse team can help identify and mitigate biases in AI systems, leading to more equitable outcomes. Biased algorithms can lead to unfair treatment of policyholders.
#2 Regularly audit AI systems: Continuous monitoring and evaluation of AI outputs can help detect and correct biases and inaccuracies. Insurance companies should regularly review claims processing algorithms to validate they are not unfairly denying claims or increasing premiums for certain groups.
#3 Maintain human oversight: Use AI as a tool to assist, not replace, human decision-making to prevent errors and biases. Human intervention is crucial to override AI decisions when necessary, affirming fair and accurate outcomes. For insurance companies, this involves having human adjusters review AI-generated decisions on claims and underwriting.
#4 Don’t substitute data for on-the-ground knowledge, specifically, leveraging relationships with your trading partners. Open communication between underwriters and brokers is key to keeping pulse on market shifts and how others are responding. In fact, the information received from trading partners is effectively the most updated data we could ask for. If we could capture it as quickly as our partners notice it, we would!
#5 Comply with privacy laws: Verify that AI systems handle personal data in accordance with privacy regulations to avoid legal risks. This is particularly important when handling sensitive health and financial information.
#6 Understand third-party vendor practices: Evaluate the privacy practices of third-party vendors and include contractual protections to help limit risk. If your company is using third-party AI tools for claims processing and underwriting, it's essential to confirm these vendors comply with privacy laws.
#7 Be careful when AI systems are part of a product offering: Product liability claims could hold developers and manufacturers accountable for defects in an AI system that is utilized as part of a product, such as part of a vehicle’s autopilot system. Owners may be vicariously liable for their AI systems’ actions.
#8 Implement ethical guidelines: Document and follow ethical guidelines for AI development and deployment to establish responsible use. Have clear policies on how AI can be used in underwriting, claims processing, and customer interactions.
#9 Stay informed about regulatory compliance: Keep up-to-date with relevant laws and regulations governing AI to avoid legal risks. This is crucial if you operate in multiple jurisdictions with varying regulations.
#10 Engage stakeholders: Involve users, developers, and policymakers to verify AI systems meet needs and address concerns. For insurance companies, this means engaging with policyholders, regulators, and industry groups to confirm AI systems are fair and transparent.
