How AI is Changing Underwriting and Claims in Insurance — and What Remains Constant
Artificial intelligence is becoming a bigger part of the insurance industry, helping to speed up and improve processes while keeping human judgment central. Although AI tools are powerful, they come with risks and limitations that insurers must manage carefully.
Data Collection, Aggregation, and Summarization
Insurance companies process vast amounts of data daily. AI has made the biggest difference by automating the collection and analysis of this information, which helps speed up both underwriting and claims.
Modern AI systems can go beyond just scanning documents. They use large language models (LLMs) to extract key information from medical records, claims documentation, and other sources, reducing manual processing from days to minutes. This boosts efficiency and frees up staff for more complex tasks.
Underwriters who once spent hours reviewing submission files can now rely on AI-powered data scraping tools to get a clear picture in minutes. Additionally, AI may soon assist in summarizing conversations during risk assessment meetings, although caution is needed to avoid inaccuracies.
AI can also pull in financial and other third-party data to provide a fuller risk profile quickly, especially for publicly traded companies.
Risk Stratification and Claim Triage
AI doesn’t just gather data; it can also help classify risks or claims based on company criteria. For example, it can suggest risk categories by comparing data against predefined acceptable ranges, similar to how lab results are interpreted.
In claims management, predictive models flag high-risk cases that might need extra attention, such as complex workers’ compensation claims. This helps claims professionals focus resources where they’re most needed.
Still, AI is a support tool. It provides recommendations but does not replace human decision-making. Underwriters and claims specialists remain the final authority.
Straight Through Processing: A Limited Outlook
AI might handle simple, straightforward claims end-to-end, particularly in personal insurance lines. However, for complex commercial risks, full automation is unlikely. Regulatory rules and the need for nuanced judgment mean human oversight will stay essential.
The real value of AI lies in automating routine tasks that lead up to decisions, helping insurers respond faster and more efficiently without removing human expertise.
Addressing Bias and Fairness Risks
AI depends heavily on the quality and fairness of the data it processes. Bias or errors in data can lead to unfair or incorrect decisions, raising legal and ethical concerns.
Insurance is highly regulated, and any AI-driven errors can cause significant financial penalties and damage to client trust. Lawsuits related to AI use in claims have already appeared, often driven by misunderstandings but still posing challenges for the industry.
To manage these risks, insurers need strong monitoring, regular audits, and transparent communication with clients about how AI influences decisions. Some states have begun requiring insurers to disclose AI use and implement governance frameworks. For instance, New York’s Department of Financial Services introduced standards aiming for fairness and clarity in AI-driven underwriting and pricing.
Strategies for Managing AI Risks
AI’s input should fit within existing risk management frameworks. Both humans and AI can make mistakes, so checks and balances are essential regardless of who or what makes the recommendation.
Close supervision of AI systems is critical to prevent bias or performance drift. Underwriters still review and approve decisions, especially for complex commercial risks, maintaining collaboration and oversight.
Keeping Humans at the Center
Looking ahead, AI will likely improve data handling and decision support, freeing insurance professionals to focus on higher-value activities. This can mean more time for client engagement and relationship-building, which remain the core of insurance business.
Clients expect knowledgeable experts, not just automated answers. For complex risks, human judgment and personal interaction cannot be replaced by AI.
In claims, AI can speed up workflows and reduce errors, allowing claims professionals to spend more time on complex or sensitive issues. This leads to better client experiences and stronger trust, even when claim outcomes are difficult.
However, the industry must be cautious about over-relying on AI recommendations. Human critical thinking and oversight remain essential to catch errors and avoid automation bias.
AI is a tool to assist insurance professionals, not replace them. Those who balance technology with human insight will deliver the best results for their clients and organizations.
For insurance professionals interested in learning more about how AI tools can augment their roles, exploring specialized AI courses can be a practical step. Resources like Complete AI Training offer focused options tailored for different job functions.
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