Artificial Intelligence in Insurance: A Regulatory, Compliance, and Transactional Perspective

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Artificial intelligence is a trending topic in the insurance industry but much of the current commentary centers around litigation. That content ranges from coverage disputes and claims handling to courtroom applications and horror stories. But for insurers, brokers, agents, and their advisors, some of the most transformative uses of AI can be found outside the courtroom: in regulatory filings, compliance monitoring, contract review, and M&A transactions. Using AI in the regulatory, compliance, and transactional spaces provides opportunities like the ability to streamline tedious processes, ensure continuity across transactional documentation, and identify risks and changes in regulatory framework. With these opportunities, however, come risks, and the continued role of experienced counsel will be vital to surviving and thriving in this evolving landscape.

Benefits of AI in Regulatory, Compliance, and Transactional Insurance Work

When used properly, AI tools can deliver measurable gains across the non-litigation components of the insurance practice. For example, in contract review and drafting, AI-powered platforms can compare incoming documents against defined negotiation positions to identify any deviations, flag risk issues, and generate initial redlines. Having AI engage in these routine review tasks saves time and lets those involved focus on the human aspects of these transactions—like the critical thinking and problem-solving to address the deviations, red flags, and potential risks.

In M&A, the most visible impact of AI is on due diligence. For example, in an acquisition, AI tools can identify key contract provisions—such as change-of-control clauses, assignment restrictions, and termination rights—across an entire contract population. This facilitates an accelerated review timeline, earlier identification of material issues, and the ability to negotiate and protect interests on both the buyer and seller sides.

On the regulatory front, AI systems can review the regulatory landscape across multiple jurisdictions simultaneously. This could provide a cross-jurisdictional understanding of how different states view specific regulatory issues or kick off a 50-state survey. AI can also help draft consistently worded board resolutions, identify holes in company compliance policies and procedures, and create task charts and checklists for regulatory and compliance requirements.

Pitfalls and Risks for Users

Despite the many capabilities and advantages, AI use in these spaces carries significant risks, such as:

• Accuracy and hallucinations. It is well-known at this point that large language models may generate information that sounds accurate but is in fact incorrect. In the insurance industry, inaccuracies could be devastating. For example, inaccurate descriptions of policy coverage, exclusions, or premiums could constitute violations of state unfair trade practice laws. Similarly, an inaccurate explanation of a regulatory requirement could cause an insurer to violate a state’s insurance laws and eventually lead to a consent order.
• Data privacy and confidentiality. Transactions within the insurance industry can involve highly sensitive data such as policyholder information, proprietary underwriting models, and confidential deal terms. Companies should be evaluating and monitoring how their AI tools, or the ones used by affiliates and vendors, are handling this data given data protection regulations and cybersecurity requirements.
• Regulatory uncertainty. Most current state insurance laws were not drafted with AI in mind, and many may conflict with the use of AI in insurance industry transactions. The NAIC’s December 2023 Model Bulletin reminds insurers and insurance professionals that decisions supported by AI must comply with all applicable insurance laws, yet this is an ever-evolving framework with jurisdiction-specific obligations.
• Over-reliance on AI output. AI can be incredibly beneficial when used as a screening and prioritization layer in your workflow, but AI outputs should not be accepted as final products. Without critical human review, an AI-generated analysis risks missing nuance, strategic context, or jurisdiction-specific requirements that a machine cannot reliably provide.

The Role of Counsel

AI does not originate ideas, exercise judgment, or develop and maintain professional relationships which is why experienced insurance counsel remains essential in regulatory, compliance, and transactional insurance work. Experienced counsel will be able to deploy the AI-tools available while also providing:

• Quality control and validation. AI is successful at providing surface level or generic findings. Human eyes and understanding remain necessary to validate results, give context, and, ultimately, make decisions. For example, an AI tool may flag a contract clause as high-risk for an impending deal, but that clause or the risks inherent may be immaterial given strategic priorities or prior negotiations.
• Regulatory expertise. Insurance regulation operates state by state, demanding a nuanced understanding of each jurisdiction’s insurance laws and enforcement postures. While AI tools are great at pulling together statutory and regulatory text, much of the nuance and practical application components are only known through regulatory counsel’s learned experience and professional relationships.
• Strategic and client-specific tailoring. In M&A transactions, counsel brings judgment, strategy, risk assessment, and the ability to tailor transactions to individual clients. Whether it is advising on material representations and warranties for an insurance company acquisition or guiding a client through a multi-state compliance review, counsel is necessary to ensure that any AI-generated work product aligns with the individual client’s business goals.
• Governance and ethical oversight. As regulators increasingly expect insurers to demonstrate responsible AI governance—such as explainability, audit trails, and human oversight—counsel plays a critical role in designing frameworks, policies, and procedures that satisfy these expectations.

AI can be a tool to amplify the capacity of counsel to deliver precision, speed, and value. Law firms, insurers, brokers, and agents can all thrive by pairing AI tools with experienced counsel capable of exercising the judgment and regulatory expertise that technology alone cannot provide.

Our Insurance Regulatory team is happy to assist you to ensure that AI adoption enhances your compliance posture, transactional objectives, and long-term success. Examples of services that the Insurance Regulatory team can provide include drafting AI compliance oversight addenda for downstream vendor contracts, creating frameworks for internal AI governance, and providing training on AI best practices in the regulatory, compliance, or transactional space.