I’m thrilled to sit down with Simon Glairy, a trailblazer in insurance and Insurtech, whose expertise in risk management and AI-driven risk assessment has shaped the way the industry approaches technology. With a deep understanding of how data and innovation intersect, Simon offers unique insights into why insurance is at the forefront of AI adoption. In our conversation, we explore the cultural and historical factors driving this trend, the workforce’s readiness to embrace change, the challenges of modernizing legacy systems, current AI applications, and the exciting future potential of AI in addressing complex risks like climate change.
How do you see the insurance industry’s long-standing relationship with data contributing to its leadership in AI adoption today?
I think it’s rooted in the fact that insurance has always been a data-driven field. From the days of actuarial tables to modern risk modeling, we’ve relied on data to predict outcomes and protect policyholders. That foundation made the transition to AI a natural step. Unlike other industries that might be starting from scratch, insurance already had the mindset and infrastructure to analyze vast amounts of information. AI just supercharges that capability, allowing us to refine predictions and personalize services in ways we couldn’t before.
What do you believe is fueling the positive attitude among insurance employees toward AI, especially compared to other sectors?
It’s encouraging to see that 71% of insurance workers are embracing AI. I believe this stems from a people-first culture that’s deeply embedded in the industry. Insurance is ultimately about protecting people, and employees see AI as a tool that helps them do that better—whether it’s through faster claims processing or more accurate risk assessments. Unlike some industries where AI might feel like a threat to jobs, in insurance, it’s often viewed as a partner that enhances their ability to serve customers.
With such high AI adoption rates, what gaps do you see in how effectively the workforce is leveraging this technology?
Despite the enthusiasm, there’s still a learning curve. Many leaders feel their teams aren’t using AI to its fullest potential. The gap often lies in strategic skills—understanding how to interpret AI outputs, integrate them into decision-making, and apply them creatively to solve complex problems. It’s not just about using the tools; it’s about thinking critically about the insights they provide and acting on them in a way that drives real value.
How can insurance companies better support their employees in adapting to AI tools and closing these readiness gaps?
It starts with fostering a culture of continuous learning. Companies need to invest in training programs that aren’t just one-off sessions but ongoing opportunities to upskill. This could mean workshops on data analysis, simulations to practice using AI tools, or even partnerships with educational platforms. Equally important is creating an environment where experimentation is encouraged—where employees feel safe to test new approaches without fear of failure. Support from leadership in championing AI as a collaborative tool, not a replacement, is key.
What are some of the biggest hurdles insurance companies face when updating their old IT systems to support AI at scale?
Legacy systems are a huge challenge. Many insurance companies operate on IT infrastructure that’s decades old, designed for a very different era. These systems often can’t handle the data volume or processing speed that AI demands. Modernizing them isn’t just a technical issue—it’s a financial and cultural one. It requires significant investment, and there’s resistance to change when processes have worked ‘well enough’ for years. Plus, integrating AI without disrupting day-to-day operations is like trying to change the tires on a moving car.
Can you explain the role of agentic AI frameworks and how they help insurance businesses adapt to evolving demands?
Agentic AI frameworks are essentially systems that deploy intelligent agents capable of autonomous decision-making within defined parameters. In insurance, they’re incredibly useful for adapting to shifting needs—like sudden spikes in claims after a natural disaster. These agents can analyze data in real-time, adjust workflows, and even suggest resource allocation, all while keeping human oversight at the center. They bring flexibility to rigid processes, allowing businesses to respond faster and more effectively to both customer and market demands.
How is AI currently transforming key areas like risk assessment or pricing in the insurance industry?
AI is revolutionizing how we approach risk assessment and pricing by enabling a level of precision that was previously unimaginable. It can analyze massive datasets—think telematics from vehicles or weather patterns—to create highly individualized risk profiles. This means pricing can be tailored more accurately to a policyholder’s actual risk, rather than broad categories. It’s a win for insurers because it reduces guesswork, and it’s a win for customers who get fairer rates based on their specific behaviors or circumstances.
Can you share an example of how AI creates mutual benefits for insurers and customers in something like usage-based auto insurance?
Absolutely, usage-based auto insurance is a perfect case. With AI, smart devices track driving behaviors—like speed, braking patterns, or time of day. Drivers who opt in and show safer habits can qualify for lower premiums. For insurers, this data means better risk assessment and fewer claims to pay out. For customers, it’s about transparency and fairness—they’re rewarded for good driving, and they feel more in control of their costs. It’s a partnership model that aligns everyone’s interests.
Looking at the bigger picture, how does AI contribute to making insurance more transparent and equitable for policyholders?
AI helps strip away some of the mystery in insurance by basing decisions on clear, data-driven insights. When pricing or claims decisions are tied to specific behaviors or conditions—like driving habits or home safety measures—customers can see why they’re paying what they are. It also reduces bias by focusing on objective data rather than subjective assumptions, which can lead to fairer outcomes. Of course, this hinges on training AI with unbiased data, but when done right, it builds trust between insurers and policyholders.
As we think about the future, how do you envision AI reshaping the way insurance companies handle claims or develop new products?
I see AI taking claims processing to a whole new level—think near-instant assessments using image recognition for damage or predictive models to flag fraudulent claims before they’re paid out. On the product side, AI could help insurers design offerings we haven’t even imagined yet, tailored to hyper-specific risks or customer needs. With the ability to model future scenarios, like the impact of climate change, AI will enable insurers to stay ahead of emerging risks and create solutions that are proactive rather than reactive.
With climate change leading to more extreme weather events, how can AI help insurers manage these growing risks?
AI is a game-changer here. It can process vast amounts of climate data—historical patterns, current trends, and future projections—to help insurers understand and predict risks like floods or wildfires with greater accuracy. This allows for better pricing of policies in vulnerable areas and more strategic reserve planning to cover large-scale events. Beyond that, AI can support prevention efforts by identifying at-risk areas and helping policyholders take mitigating steps, ultimately protecting both the business and the customer.
What is your forecast for the role of AI in the insurance industry over the next decade?
I’m incredibly optimistic. I believe AI will become the backbone of the industry, not just in operations but in how we redefine what insurance means. We’ll see deeper personalization, where policies are almost bespoke to each individual’s life. AI will also drive innovation in managing global challenges like climate risks, creating products and strategies that keep pace with a changing world. Most importantly, I think AI will strengthen the human element—freeing up professionals to focus on empathy and connection, while the tech handles the heavy lifting. It’s an exciting time to be in this space.
