Senator Schiff Brings Back Idea of Federal Reinsurance Program  August 19th 2025

Insurer in Full: AI investment lags ambition of insurance leaders as savings so far prove elusive

As insurance leaders enthusiastically advocate AI adoption, some in the industry highlight a mismatch in investment, which they put down to a lack of clarity on how the technology can deliver significant savings.

Searches by The Insurer of more than a dozen company reports and filings show little evidence of large financial commitments so far. The Insurer also asked 11 of the industry's largest carriers and brokers how much they have spent on AI adoption. All either declined to comment or did not respond.

Tom Spier, chief commercial officer of reinsurance broking platform Supercede, told The Insurer he had spoken to reinsurers with “extremely large innovation budgets that largely remain unspent".

Spier said this was because "they simply don't have the confidence on where to place those bets", adding that he was sceptical of investment claims: "They can't be. Otherwise, the sector would be bigger than it is … It just doesn't add up."

Kristy Lovegrove, group head of technology at the live and legacy business outsourcing firm Pro Global, also said that uncertainty around costs explained a “lack of budget representation for AI”.

Joe Brace, operations director at the Lloyd's Market Association, said: "Direct spend on AI companies, consultancies, products, it's in the single figure (percentage of GWP). It's going to be low at the moment."

Brace said that as the industry moves into a soft market there will be a focus on expense ratios, which will lead to a small uptick in AI investment as companies seek to cut costs via automation, however he doesn’t believe it will “move the dial”.

Several senior executives said the industry is still at the experimentation stage in AI and nothing specific to processing insurance transactions has been deployed at scale, while practical applications remain limited.

The next phase of insurtech will modernize with trust, not disruption

Up until about 20 years ago, the insurance industry evolved gradually, mostly through regulation, precedent, and relationships.

But that changed in the mid-2000s, with the rise of insurtech. In the era of “move fast and break things,” more than one tech founder decided they could remake the insurance industry from the ground up, eliminating its inefficiencies in the process.

Many big names of that era eventually flopped. Insurance, it turns out, is harder than it looks. More than that, though, it’s meant to provide stability. It’s built on trust, and its product is essentially a promise: if something goes wrong, the insurer will offer compensation.

But that doesn’t mean the insurance industry can’t benefit from technology like AI. It just means that the AI tools that transform insurance have to be built on a framework of trust—not just speed and automation. This is especially true in knowledge-intensive areas like underwriting, claims, and coverage analysis.

So how do we get there? By building AI systems that complement human expertise rather than seeking to displace it. Let’s examine what that looks like.

AI thrives at transactional tasks, not complex judgment work Much of the early hype around AI in insurance focused on automation: faster processing of applications, quicker FNOL intake, reduced human intervention in workflows. That’s because AI systems excel at transactional tasks with clearly defined inputs and outputs.

Where AI struggles is in the gray areas: interpreting policy language, assessing liability, and navigating the nuance of coverage positions across jurisdictions.

These scenarios—like trying to determine whether a complex claim is covered—aren’t simple matters of processing data to get an answer. They require nuanced judgment calls. Those calls can only be made by someone with the necessary context, experience, and professional skepticism—all traits that AI systems can’t replicate.

Dan Schuleman is the co-founder and CEO of Qumis

AI in Underwriting Report 2025

*New survey reveals 77% of underwriters see AI as the biggest opportunity to boost performance and profitability in the next 12 months — here’s what they’re doing about it...

According to Intelligent Insurer’s brand new “AI in Underwriting Survey” (sponsored by Send) a strong 77% of respondents agree that AI presents the greatest opportunity to improve underwriting performance and profitability over the next 12 months – a notable rise from 65% in 2024. This upward shift could reflect growing confidence in AI's ability to streamline workflows, enhance risk selection, and support better decision-making.

The numbers say it all…

Last year, almost half of the underwriters we surveyed (48%) hadn’t touched AI, today that’s down to 19%. The rest are either piloting, deploying, or scaling AI, and the momentum isn’t slowing.

There is simply no other technology, or methodology, being deployed in the short-term that has the potential to exact this level of profitable change in underwriting. For underwriters, AI is no longer a nice-to-have or a pilot project, it’s a reality.

The choice is clear: Invest and adapt, or risk losing your competitive edge.

Download the full survey results here.

This special provides exclusive data directly from the mouths of underwriters to help inform your own strategy and benchmark against the wider industry.

You’ll discover unique insights to help you:  Gauge where the market really stands on AI: Discover how underwriters expect AI to reshape their roles in the next 2–5 years, and how quickly organisations are moving from exploration to implementation.

For any queries:

Debbie Atwell, Senior Conference Producer – Intelligent Insurer, Newton Media Ltd.; Direct: +44 (0) 203 301 8252; Email: datwell@newtonmedia.co.uk

Harnessing AI for Insurance Innovation: Strategies for Effective Pilots | Insurance Innovation Reporter

The insurance industry has long recognized the potential of AI and machine learning to enhance efficiency and improve the customer experience.

Despite the complexity and time required to integrate these technologies, the urgency is clear—with 80 percent of insurance executives noting the growing inseparability of business and technology strategies.

To meet evolving needs, carriers should streamline technology pilots by engaging non-business partners early, clearly identifying success metrics, and working with AI champions.

From the nascent phase of AI and machine learning programs to the final stage of implementation, it is critical to engage broader stakeholders at every step.

The first step is consulting a wide range of stakeholders to identify the need or use case for AI or machine learning pilots, which is ideally tied to firm-wide priorities. For many, these needs could include processing an ever-increasing amount of unstructured and structured data sources—in turn driving efficiencies, identifying risk signals and links between data, and supporting programmatic auditing capabilities.

During the pilot phase, even if this period can sometimes involve lower levels of production scrutiny, teams should gather full requirements and stand up a governance protocol on the assumption that the pilot will be successful and deploy broadly.

ANDREW HOLSHOUSER is the Head of Underwriting Transformation for individual life and disability products at The Guardian Life Insurance Company of America

Captive owners turn to AI to combat nuclear verdicts

Captive owners and risk managers should embrace AI tools and predictive analytics as they look to mitigate the effect of nuclear verdicts on their insurance programs, experts say.

As jury awards exceeding $10 million become more frequent and severe, such technologies can identify high-risk claims early on and provide strategies to curb rising legal payouts.

Communication and early intervention are key to preventing large verdicts, the experts said during a panel session at the 40th annual Vermont Captive Insurance Association conference last week.

Actively communicating with actuaries, reinsurers and other stakeholders about emerging casualty claims is essential, said Melissa Hollingsworth, deputy chief risk officer of the Los Angeles Unified School District.

“You can’t sweep it under the rug. You have to be proactive and make sure you get it on people’s radars. I’m a big fan of communication. It goes a long way with helping mitigate these types of losses,” Ms. Hollingsworth said.

Reserving is crucial, she said. “Working with your actuary to predict and project out potential losses that are incurred but not reported, that IBNR, that’s really going to help, particularly with mitigating the impact on your captive,” she said.

In the first seven months of 2025, there were 70 verdicts of $10 million or more in the U.S., with an average payout of $238 million, said Denise Tyson, La Jolla, California-based CEO of Schaefer City Technologies, an insurtech that provides AI products meant to help guard against such verdicts.