Mike McGavick, the former chief executive of XL Group and Safeco Insurance, sees exciting possibilities ahead for AI to refocus the insurance industry on the problems it is designed to solve.
But today, the industry is falling short, he says.
“There is unbelievable opportunity, and unbelievable need for us to play our role with AI,” McGavick told a group of actuaries at the Casualty Actuarial Society Seminar on Reinsurance this week.
“Our whole purpose in life should be to look at society and the risks it really faces and to do everything we can to create products that can transfer that risk so that people can focus on their lives and creativity and all the solutions that come from this massive change in society,” he said. He offered this view near the end of a presentation that started with the veteran executive describing repeated patterns of technology adoption he’s observed over the course of more than three decades in the industry. He also punctuated his remarks with a challenge to actuaries to embrace their roles as model arbiters to pave the way forward.
In the end, he said the insurance industry exists “to take on what government can’t and to try to do it in an extremely economic and efficient way and make the world better—make the world take the risks that keep humanity improving. That’s our job. And yet right now, we aren’t doing it,” he said, offering an example of the industry’s role in cyber risk transfer to support his view.
Specifically, McGavick cited figures that put cyber insurance premiums at about $30 billion and the total amount of cyber crime globally at $10.5 trillion. Noting that cyber insurance loss ratios are roughly 50 cents on the dollar, the industry is, at most, addressing $15 billion of that.
(Editor’s Note: In a report last year, Munich Re put cyber insurance premiums at roughly $16 billion in 2025, projecting a $30 billion figure by 2030: “Cyber Insurance: Risks and Trends 2025.” The $10.5 trillion is a commonly cited figure from Cyber Ventures “Cybercrime Cost Predicts 2025 to 2031.”)
“We’re doing the stuff we know and are comfortable with” while risks are growing, he said. “The challenge is how to get out in the open on the horizon of opportunity—make the difference we’re called upon to make in society and to really do our jobs,” he said.
Patterns Repeat
While McGavick also highlighted the level of inefficiency that persists in the industry, he was overwhelmingly enthusiastic about the promise of AI agents to address it and the role of actuaries at the center of change, influencing trust in AI models.
“This is the sexiest spot in insurance,” he said as he opened the talk. “I believe fundamentally every day that moves forward, actuaries become more important in the entire insurance ecosystem because there is no other group prepared and trained to continue to add trust to a world that is already distrusted and now, as it begins to use its AI journey, will be even more distrusted.”
“This is a huge moment. We know [what’s] coming is massive. But we just ain’t there yet,” McGavick told the actuaries assembled in a Philadelphia conference room, going on to describe the industry patterns that will repeat to shape how AI comes into the property/casualty insurance sector.
“Every day that moves forward, actuaries become more important in the entire insurance ecosystem. There is no other group prepared and trained to continue to add trust to a world that is already distrusted and now, as it begins to use its AI journey, will be even more distrusted.” Mike McGavick
“How do we react to tech in the insurance industry? No. 1, exclude it. No. 2, try to harness it and eventually get greedy and figure out how to insure it.” Breaking the last two parts down further, he said insurers first attempt to harness technology to lower their own costs. Then they try to refine core insurance processes to be more effective: “We try to rethink how underwriting might be done with this tool at hand, how claims handling might be done.”
The third step involves starting to think about new risks that might need insuring—but the growth ambition comes after attempts to lower costs and refine processes.
“We’re genuinely at the beginning,” he said, suggesting that the actuaries already know this to be true. “When you watch your companies make announcements about AI work, I’m sure you snicker a little because you know it isn’t that much yet… Often, it’s a case of the leadership team doing a deal with an LLM and saying, ‘We’ve got it licked,’ when in reality, the actual processes that you engage in to create a trusted product are unchanged, largely.”
’I Lent My Reputation to It’
Before elaborating on why the industry’s repeating pattern always starts with cost cutting, McGavick explained why he feels qualified to deliver any predictions about AI, describing two levels of involvement: as a hedge fund executive investing in AI, and as non-executive chair of a company that delivers insurance-specific agentic AI to tackle process improvement.
After retiring from the insurance industry, McGavick served as co-chair of the operating board of directors for Bridgewater Associates at a time when the large hedge fund was positioning itself as the lead thinker around AI in the investing world, having made early investments in OpenAI and Anthropic. “They already have multiple billions of dollars being managed by AI by itself with some guardrails around it for regulatory purpose,” he added.
At Bridgewater, McGavick recalled sitting in on a meeting where participants argued about the future of language models—whether the Anthropics and OpenAIs of the world would ultimately prevail across all industry sectors, or whether smaller domain-specific language models would operate sector by sector. At the same time, XL Catlin’s former leader of IT, Martin Henley, had McGavick’s ear, asking for help with a new company he had been working to set up for several years. The company, mea Platform, is premised on the idea that the domain-specific language model construct makes more sense for insurance.
To McGavick’s mind, there’s going to be a meeting in the middle. “The LLMs are trying to boil the whole ocean of language to find learning and then are drilling down toward the ocean floor where the actual economic activity takes place. … They’re going to cover the ocean—a handful of them because there’s not enough money, not enough energy, not enough resources for there to be more than a handful…
“But down where the economic activity is handled—by people like us trying to create insurance products that help people—[the LLMs] lose their way. They can’t use the language we use. Our language is harnessed for specific purpose,” he reasons.
“Small language models, specific to industry sectors, are going to grow up from the ocean floor. They’re going to meet the LLMs somewhere and they’re going to be very profitable.”
Offering proof of how strongly he believes this, McGavick said, “I lent my reputation to it” through a role as advisor and non-executive chair on the AI-powered insurance workflow automation platform mea. “I’m fully invested. I think this is a cool thing.”
’We Should Be Ashamed’
Returning to his discussion of insurance industry patterns, McGavick gave his take on why insurers attack cost structures first when they react to new tech. “I believe that’s in part because we’re ashamed—and we should be,” he said, reporting that operational costs have represented 12 to 14 cents of every premium dollar for years.
Citing a figure from an Accenture report, McGavick noted that operational inefficiency costs the insurance sector about $32 billion a year. (Editor’s Note: McGavick cited the high end of a range presented in the 2022 Accenture report, “Poor Claims Experiences Could Put Up to $170B of Global Insurance Premiums at Risk by 2027,” which found that underwriters grappling with aging systems and inefficient processes spend 40% of their time on non-core and administrative activities—an annual efficiency loss of between $17 billion and $32 billion.)
“That is all money that should be going into the clients by virtue of loss costs, or into our underwriting functions to discover new products. There’s so much we should be doing with that and we aren’t. We’re wasting it.”
As insurers fight for cost advantages by launching big IT projects and hiring new workflow vendors “over and over and over,” McGavick said, “we’re running in place… because of the complexity of our product… We disappoint ourselves over and over.”
“We’re going to see real change because AI against the sector’s useless procedural projects is a no-brainer,” McGavick said.
Optimistically, he predicted that “this time is going to be different” because AI attacks the problem of complexity in an effective way. “My expectation is that two or three platform providers are going to emerge who use AI just to run operations. None of the underwriting, none of the claim standards … They’re just going to” handle the operational complexity that has long burdened the industry.
