Simon Glairy has spent the better part of two decades at the intersection of traditional underwriting and cutting-edge digital transformation. As an expert in Insurtech and risk management, he has observed the industry’s evolution from a period of skeptical experimentation to one of disciplined, strategic integration. Glairy understands that the current landscape is no longer about whether a piece of software can identify a risk, but whether that software can survive the rigorous transition from a controlled lab environment to the messy, high-stakes reality of global insurance markets.
The following discussion explores the pivotal shift from invention to adoption that is currently defining the industry. We delve into how carriers like Lloyd’s and The Hartford are prioritizing risk mitigation over simple risk transfer, the growing importance of hyper-local data in the face of escalating natural catastrophes, and the practical hurdles that prevent even the most well-funded startups from achieving market-wide scale. Glairy provides a roadmap for how the “next chapter” of insurance innovation will be written through collaboration, workflow integration, and a relentless focus on measurable resilience.
Many insurtech initiatives successfully prove technology works in isolated trials but struggle with wider market adoption. From your perspective, why has the industry shifted its focus from proof of concept to proof of adoption, and what does that mean for the next generation of startups?
For the last ten years, the insurance sector was essentially obsessed with proving that new technology could actually function within its ancient architecture. We’ve moved past that now; we know the tech works, and that realization has brought us to a much more difficult hurdle: scaling these solutions across an entire market. This shift toward proof of adoption is born out of a newfound selectivity among carriers who are no longer distracted by the mere pace of invention. They are looking for tools that don’t just sit on a shelf but become embedded in the daily lives of underwriters and brokers. For a startup, this means the “wow factor” of a demo is no longer enough to secure a long-term partnership. You have to prove that your solution can handle the weight of a massive enterprise without breaking the existing culture or slowing down the pipeline.
We are seeing a move away from the traditional model of simply paying out after a disaster toward actively preventing those losses from happening in the first place. How is this prevention-first philosophy reshaping the relationship between carriers and their policyholders?
This is perhaps the most exciting transition I’ve witnessed because it fundamentally changes the carrier-policyholder relationship from a reactive one to a proactive partnership. Leaders at The Hartford have noted that we now have the data sources and analytics to identify hazards before they turn into claims, which is a significantly better outcome for everyone involved. When an insurer can work with a business to strengthen its resilience against infrastructure deterioration or wildfire, the policy becomes more than just a financial safety net; it becomes a service of constant vigilance. This creates a deeper sense of trust, as the customer feels the carrier is invested in their survival rather than just waiting to settle a loss. It turns insurance into a value-added service that operates 365 days a year, not just on the day a disaster strikes.
With the increasing frequency and severity of natural catastrophes in the United States, there seems to be a tension between traditional catastrophe modeling and new, granular data streams. How are underwriters balancing these two worlds without discarding the systems that have worked for decades?
It is a common misconception that granular, real-time data is meant to replace traditional catastrophe modeling, but the reality is much more about layering. As Dawn Miller from Lloyd’s has pointed out, the growing demand for local-level insights is a recognition that our risk environment has become incredibly complex and interconnected. In the U.S., where wildfires and floods are becoming more frequent, underwriters need to supplement their broad models with real-time environmental monitoring to address widening protection gaps. This isn’t about a shift away from established models but about adding a high-definition lens to a map that was previously too blurry at the street level. By layering this granular information, insurers can make more impactful decisions and offer placements that are both more accurate and more efficient.
Integration seems to be the graveyard of many great ideas in the insurance space. When you look at how AI and new data sources are being tested today, what are the specific practical filters that a technology must pass to prove it can actually function within a carrier’s existing workflow?
The real bar for any new technology, especially AI, is whether it fits seamlessly into the existing workflows of brokers, carriers, and customers. You can have a tool that accelerates claims processing by fifty percent, but if it requires an underwriter to log into a separate portal and manually transfer data, it will eventually be abandoned. We look for solutions that produce measurable improvements in safety and resilience while addressing an identifiable business problem that existing systems cannot solve. At The Hartford, the focus is on testing these products in structured, real-world settings through pilots that mimic the daily grind of the office. Innovation only creates value when it is practical enough to be adopted at scale, meaning it must feel like a natural extension of the professional’s hand rather than a foreign object forced into their routine.
The collaboration between Lloyd’s Lab and U.S.-based tech firms has been particularly fruitful, with forty-seven startups raising more than $600 million. What does this massive influx of capital into specific areas like cyber threats and infrastructure tell us about the future of the industry?
That volume of capital—over $600 million—is a loud signal that the industry is finally putting its money where the most complex risks are. We are seeing a concentrated effort to tackle exposures like hurricanes and cyber threats that have traditionally been difficult to price and manage. Through initiatives like Syndicate 1221, which has provided eleven mentors to fifteen different accelerator teams, we are seeing a bridge being built between specialized tech expertise and deep insurance knowledge. These startups are developing tools to monitor everything from flood exposure to the structural integrity of aging bridges, which are exactly the kinds of actionable insights the market is starving for. However, even with all that funding, the ultimate test remains: can these companies move from gaining commercial traction to becoming a standard part of the global market infrastructure?
What is your forecast for the evolution of the carrier-insurtech partnership over the next five years?
My forecast is that we will see a “great thinning” where the industry moves away from a thousand separate point solutions toward a few deeply integrated platforms that prioritize risk mitigation over everything else. We will stop talking about “Insurtech” as a separate category and simply view these advancements as the standard way insurance is conducted. The winners will be the companies that can prove consistent results beyond a controlled pilot environment and show they can actually reduce the frequency of claims through real-time data and AI-driven insights. Ultimately, the next five years will be defined by a shift from the novelty of invention to the utility of scale, where the impact of a technology is measured by how quietly and effectively it disappears into the background of a more resilient global economy.
