AI in life insurance: Shaping an industry in new ways

As artificial intelligence is integrated into all aspects of the insurance industry, the life insurance space is one area where it is changing the underwriting process. Digital Insurance reached out to several industry experts to learn more about how AI is being used to improve the life insurance process for customers.

AI in underwriting

"AI is reshaping underwriting in practical and significant ways," shared Banwari Agarwal, CEO of banking, financial services and insurance at Sutherland in a statement. "It is enhancing both customer and agent experiences through streamlined applications, personalized product offerings, and the ability to engage with carriers when, where, and how they prefer. It also enables carriers to differentiate themselves in the market by accelerating processes and improving risk assessment through predictive models, non-traditional data sources, and enhanced fraud detection." 

Agarwal finds that some major carriers are using AI for accelerated underwriting because the models can analyze vast amounts of information such as prescription histories, claims, and health records in an effort to determine which individuals may not need an exam before receiving coverage. "Same-day issuance for everyone isn't here yet, only low-risk applicants qualify for near-instant decisions, while complex cases still take weeks. By 2026, AI tools like automated document extraction and smarter triage will further speed approvals," he said.

Adnan Haque, vice president of integrated analytics at Munich Re Life U.S., agrees that AI is having an impact on the underwriting process for life insurers and said in a statement, "AI is changing life insurance underwriting by enabling carriers to process and interpret vast amounts of unstructured data more efficiently. One compelling use case involves the handling of medical records, which are often lengthy, complex, and vary widely in format. 

Traditionally, underwriters would manually sift through these documents to extract relevant health information, a laborious and time-consuming process. With AI, insurers can now automate the structuring and summarization of these records. The technology can identify key medical conditions, treatments, and risk factors, and present them in a concise, standardized format for underwriter review. This not only accelerates decision-making but also improves consistency and reduces the likelihood of missing critical information."

Applying AI to different policies

The integration of AI extends into a variety of life insurance policies, including both term and permanent life. Agarwal explains that the terms for these policies differ and finds that term life insurance relies on AI risk models. "More complex permanent life products use AI to support underwriting by scanning and analyzing unstructured data from sources like electronic health records (EHRs) and physician statements, extracting and organizing critical information for underwriters. AI also assists in screening applicants, determining who qualifies for accelerated paths versus who requires full medical underwriting. Larger policies still require traditional review."

Looking ahead, he says they expect to see broader AI adoption in the permanent life space, as well as more unified platforms that can support both term and permanent products. "The nature of offerings is also evolving," he adds. "For example, targeted combinations such as indexed universal life products with long-term care riders, and alternate distribution channels like life insurance embedded in wellness perks. At Sutherland, we are leveraging AI to shorten the product development life cycle by 50–70% and transition carriers to an AI-first, agile operating model that scales effectively with their business growth."

Protecting customer data

The integration of AI can provide unintended exposures of information to the technology and highlights the importance of protecting client data, but proper processes can help minimize the risk.

Brian Carey, vice president of insurance solutions engineering at Equisoft explained in a statement, "In general, there's a common misconception that implementing AI automatically weakens an organization's security and privacy, or that it's collecting your data to retrain other models. But that's simply not the case — it all comes down to maintaining a clear chain of custody for the data. The lineage must be traceable from source to destination and then verified. Every piece of data that's inputted needs to go through this process before it can be used." 

He contends that some aspects of information protection can be handled through contractual verbiage in agreements. "If you're handling any personally identifiable information (PII) or HIPAA-regulated data, the right contractual terms will put the necessary privacy safeguards in place, ensuring access controls and security as you would with any other kind of sensitive data."

Shantanu Baruah, president and global head of healthcare, life sciences and insurance at Hexaware agrees the process must be proactive in protecting customer data. "Underwriting involves highly sensitive personal and health data, so carriers must take a three-pronged approach to provide multilayered protection," he said in a statement. "First, strong cybersecurity measures are essential — using encryption, guardrails for AI use, multifactor authentication, penetration testing, and regular security audits to ensure resilience. Second, carriers must comply with strict regulatory frameworks from governments, including HIPAA in the U.S., GDPR globally, and state-specific laws like CCPA in California. Lastly, privacy by design needs to be embedded from the start, not as an afterthought. That means applying clear policies, ensuring explainable AI, and establishing traceability for how information is sourced and used."

Because AI has the ability to search through so many records as part of the underwriting process, there may be some concerns that pre-existing conditions could affect coverage, but experts say AI actually makes it easier to issue policies. 

"Overall, it's making it easier," finds Agarwal. "AI helps underwriters differentiate well-managed conditions, such as controlled diabetes, from higher-risk profiles, ensuring applicants aren't unfairly declined. Serious or unstable conditions still require full underwriting, but we are already seeing broader eligibility thanks to more nuanced risk models. By 2026, AI will further refine impaired-risk pricing, enabling products specifically designed for applicants who previously struggled to obtain coverage."

The additional information also enables carriers to address unique situations for clients. 

"For example, Sutherland helped a travel insurer create a personalized offering that launched multiple variations of their flagship product to support various pre-existing conditions at affordable price points, moving beyond the standard one-size-fits-all approach," adds Argarwal. "Our AI engine analyzed sales interactions across channels, internal risk and pricing data, and third-party sources to provide product recommendations. As a result, more people who were once denied coverage are now being insured."

The impact of health changes after binding

Another concern for some policyholders involves changes in their health after a policy is underwritten, but these situations highlight the importance of having this type of coverage. "Circumstances like this are a big part of why life insurance is so valuable," explains Haque. "Once a policy has been issued, if an individual falls ill or their health circumstances change, they continue to be covered."

Baruah concurs but also cautions that any attempts to conceal a health issue could affect coverage. He says that once a life insurance policy is written and bound, any health changes will not affect the coverage terms or pricing. However, he explains that most policies have a two-year contestability period that begins the day the policy is issued. 

"If the client passes away during this period, the insurer can investigate the medical history provided on the application. If the insurer finds evidence of material misrepresentation or fraud (such as the concealment of a major health condition that existed before the policy was bound), the claim may be contested or the policy may be voided, resulting in the denial of a claim."

AI's impact on life insurance has the potential to be far-reaching. "From what I have seen, AI is changing the way insurers engage with customers, handle claims, and manage their operations," says Baruah. "It is helping carriers adjust to a digital-first environment, where more personalized outreach and seamless onboarding are becoming essential to building long-lasting relationships with policyholders. It is also transforming the claims experience, streamlining processes that were once manual and time-consuming by simplifying forms, anticipating questions, and identifying fraud with better accuracy. It's also strengthening the internal operations of insurers by improving agent productivity and making workflows more efficient."

Carey sees AI being leveraged for internal-facing solutions, particularly when it comes to factors such as knowledge bases, knowledge transfer and knowledge management. These tools, in essence, he says, are making data and information available across organizations. 

"Looking ahead to the next year or two, I expect the life insurance industry to adopt AI and these systems more broadly. While there have been concerns around the security of this technology, those fears don't reflect the reality of how these systems operate. The intrinsic capabilities of AI have the potential to transform the industry."