AI in life and health: Poised for a 2026 breakthrough?

By Will Wood

With compelling use cases emerging across the life and health sector, the age of artificial intelligence is here. Although AI adoption in life and health insurance may not be as widespread as in other industries or insurance lines, advisors in life and health are eager to revel in its efficiencies.

A recent BCG survey demonstrates that while insurers seem to be sticking more than a toe in the water when it comes to AI, the real progress has only just begun. BCG found that more than half of the insurers surveyed - 67% - had tested generative AI programs, but only 7% had successfully scaled them.

When will AI truly make its mark on the life and health sectors? The honest answer is this year. Advisors will see it happen in the two areas most ripe for automation: medical underwriting and claims assessment.

The future of medical underwriting

Data-heavy processes with repeatable decision-making create the biggest opportunities for AI, which is why powerful medical underwriting use cases will emerge this year.

AI will ingest all the data underwriters previously gathered by hand. This can include medical reports from providers, laboratory bloodwork, and even conversations between providers and patients inside a person’s home. The AI engine can then summarize the data using tailored prompts.

To see how this will work, consider using AI to assess an individual’s smoking status. With the right prompt, AI can surface key information — including the person’s start and end dates, nicotine levels, and types of tobacco use — so underwriters can determine whether the person meets eligibility criteria. Multiply this example by the thousands of applications and quotes produced each year by agents, and the time savings will be massive.

The future of claims assessment

We’re also seeing promise that claims assessment, which is also data-intensive, is ripe for AI adoption. Claims professionals will use AI to compile structured and unstructured data regarding critical illness or permanent disability filings and ask for a summary, helping to determine how and if the claim should proceed.

While time savings is the primary advantage, modern AI claims platforms can also prevent waste, fraud and abuse by analyzing claims in real time and searching for anomalies and inconsistencies. Claims flagged by AI can be routed for investigation before payout is made, creating potentially significant cost savings.

Overcoming barriers to AI adoption

AI is indeed primed for wide-spread adoption across the life and health sector, but what could slow us down? After all, AI alone is not the solution. Rather, embedded AI that is tailored to specific, critical workflows that offer value will lead to success if we also consider and work to avoid potential roadblocks.

First, data must originate from a single, trusted data source. If data is scattered and AI tools must pull information from multiple sources, hallucinations may result, creating errors that erode trust among staff and customers.

Second, carriers must perform due diligence when evaluating AI underwriting and claims tools. Before adopting these tools, the user must ask how a vendor will use proprietary data. If it is used to train an AI model that also serves competitors, the tool could create incorrect recommendations that do not align with the carrier’s policies. It could also expose valuable information, such as historical claims decisions and medical risk thresholds, to other carriers.

Third, advisors should choose carriers using proven AI solutions. Today’s AI landscape is similar to the early days of insurtech. Many so-called disruptive startups faded away, while only a few were built to last. In the same way, upstart solutions, especially those not purpose-built for life and health insurance, will not survive into the 2030s and beyond.

Next steps for advisors

Younger, digital-native clients expect efficiency, speed and frictionless interactions. They do not want to spend hours filling out applications or wait weeks for a claims decision. To meet these expectations, advisors must think strategically about with whom they align, favoring carriers who are integration-ready, AI-enabled and committed to continuous modernization.

As AI becomes embedded ever deeper into medical underwriting and claims assessments, advisors should prioritize partnering with carriers whose agile ecosystems can seamlessly integrate modern AI solutions at a foundational level. Carriers should focus less on the shiny new AI tool itself, and more on whether their foundational architecture is agile enough to integrate it.

No-code platforms allow carriers to build innovative, agile programs into existing ecosystems quickly, creating additional efficiencies and frictionless user experiences across applications and claims processes, and more intelligent data exchange. Those carriers that redesign their workflows with strong technology foundations for AI implementation, rather than wrapping it around legacy systems, will see true business transformation. AI agents will collect data, and coordinate action across systems while ensuring a human-in-the-loop component where underwriters and claims handlers serve as check points. This will translate to improved efficiencies for the advisor as well as enhanced customer experience while building a foundation for broader transformation.

This is an exciting time for those of us working in the life and health sector. We will likely see insurers largely move from AI pilot programs into full-scale production this year, following the lead of property/casualty insurers. Automating data-heavy processes such as medical underwriting and claims assessment with AI will likely bring the biggest upsides, giving advisors who work with AI-enabled partner carriers more space to build trust with clients and grow business.