What's the future of property and casualty insurance?

The wildfires that tore through California and Texas in 2024 and 2025 were historic in their scale and destruction. The Smokehouse Creek Fire, which scorched more than 1 million acres in the Texas Panhandle, became the largest wildfire in state history. Just months later, California's Palisades Fire destroyed over 6,800 structures across the Los Angeles metro area, making it among the worst in state history by property loss.

Together, these events caused tens of billions of dollars in economic damage and may be seen as a turning point for the industry, where insurers began a notable shift toward more preventative approaches to risk. With catastrophe-prone markets like Texas and California under pressure, both homeowners and insurers are looking beyond traditional "repair and replace" models. To adapt and deliver greater value, insurers are embracing strategies that can both predict and prevent loss before it occurs.

For today's policyholders, expectations are changing. In an era of smart homes, real-time alerts, and accelerating climate risks, they want insurers to act more like safety partners than reactive claims payers. If a car can warn of a crash, and a thermostat can detect a fire, why shouldn't an insurance company help prevent loss?

That's exactly what forward-thinking insurers are working to deliver, through proactive, tech-enabled risk mitigation. AI can now flag wildfire risk before ignition, sensors can detect hail or water damage in real time, and connected platforms can automatically trigger alerts, dispatch services, or engage mitigation vendors. Major carriers are investing in technologies to help customers reduce risk, avoid losses, and protect what matters most. According to a June 2025 Guidewire survey, 70% of consumers want insurers to offer proactive services, not just pay claims.

For insurers bought into such a vision, three core pillars are essential for transitioning from passive coverage to more active protection:

• Intelligent infrastructure powered by AI
• A real-time data stack that senses risk early
• A governed and transparent data foundation that enables explainable decisions

Intelligent infrastructure: The AI that powers prevention

AI is foundational to next-generation, predict-and-prevent property insurance. When integrated into a modern, cloud-based infrastructure, generative AI-based risk assessment solutions mine vast internal and external datasets to help underwriters understand and accurately price risk.

Generative AI models can also identify high-risk patterns—such as vegetation overgrowth, yard debris, or hail-prone roofs—and then recommend policy adjustments, suggest new coverage options, or offer highly tailored risk mitigation measures to policyholders. GenAI can also analyze customer behavior, claims histories, economic trends, and data from solutions like HazardHub or Faura to predict risks and the likelihood of claims in milliseconds. When applied to predictive analytics and policy-generation workflows, Bain & Company estimates that Gen AI can help an insurer increase revenues by 15% to 20% and reduce costs by 5% to 15%.

With new forms of agentic AI capable of performing tasks autonomously, carriers can automate all of this at scale across their entire book of business. Together, these technologies can form a kind of central nervous system for next-gen carriers. They can continuously assess data from satellite imagery, IoT-based smart-home sensors, weather feeds, and policy terms to alert property owners of early signs of wildfire ignition or roof deterioration that could make a property vulnerable to hail or water damage.

When you consider that systems leveraging these technologies grow smarter and more effective over time, it's little wonder that 50% of insurers plan to adopt agentic AI this year. With every interaction, machine learning feedback loops refine these models, enhancing underwriting precision and enabling a future where insurers prevent losses before they happen.

A real-time data stack that sees risk coming

True prevention enabled with AI orchestration isn't possible without the visibility afforded by the kind of real-time data mentioned. P&C insurers are adopting IoT-enabled policies, enabling them to stream live data from homes, buildings, and critical infrastructure. Moisture sensors, structural vibration monitors, smoke detectors, and indoor air quality devices now feed directly into AI systems that can trigger mitigation efforts, often before a policyholder even knows something's wrong.

Geospatial intelligence elevates this further. For instance, aerial, satellite, and LiDAR data offer parcel-level visibility into roof conditions, as well as wildfire, hail, and wind exposure. Solutions like Nearmap can estimate roof age, enabling carriers to detect mispriced risks, trigger midterm endorsements, or proactively reach out to policyholders.

Meanwhile, new forms of parametric insurance are further redefining proactive disaster response and helping to insure properties that might otherwise be uninsurable. Case in point: a novel pilot policy by the Nature Conservancy and UC Berkeley. Instead of insuring individual homes, they insure 1,345 acres of shared forest land for the Tahoe Donner Homeowners' Association in California.

If a wildfire crosses a pre-defined geofence, a claim is triggered and paid automatically, no adjuster, no paperwork. But payouts and premiums are linked to mitigation efforts, such as tree thinning and prescribed burns. 

In models like this, communities collectively reduce risk, and insurers reward them for proactive land management, preventing devastating and costly wildfires before they happen. By all signs, the market approves. 

Governance That Makes It All Actionable and Trusted

Prediction without trust falls short. A recent AI sentiment survey found that only 20% of consumers trust insurers to use AI responsibly, down from 29% in 2024. This signals a growing desire for greater transparency and reassurance, as customers increasingly expect clear, understandable insights, not decisions driven by opaque algorithms. That's why leading insurers are architecting AI systems with transparency and governance built in.

Agentic platforms now routinely document decision paths, track data lineage, and generate natural-language explanations for every action taken or avoided. These aren't just intelligent tools; they're auditable assets, designed for clarity and regulatory compliance.

Data infrastructure is central to this trust framework. To that end, P&C insurers are investing in cloud-native platforms, data governance tools, and real-time analytics pipelines, according to a 2025 report from McKinsey. This isn't just IT modernization, mind you. It's table stakes for predictive, preventative insurance models, where every decision must be explainable, timely, and rooted in reliable data.

Five imperatives for predict-and-prevent leaders

With these three pillars in place, property insurers can evolve into real-time resilience networks. They can detect threats before they surface. They can create coverage that adapts dynamically to conditions on the ground. And they can shift focus beyond paying claims to preventing them. Here are five key steps to get started:

1. Embed AI in workflows: Start with underwriting, claims, fraud, and customer experience (CX). Prioritize systems that learn.
2. Invest in real-time risk data: Combine high-def data sources with models that see around corners.
3. Scale parametric models: Use them to cover the "uncoverable," pay faster and incentivize mitigation.
4. Leverage platforms that integrate best-in-class tools: Free operations from legacy limitations.
5. Treat data as a strategic asset: Govern it well, explain it clearly, and evolve it continuously.

A future where insurance protects before it pays

The California and Texas wildfires have accelerated the need for a critical shift in property insurance. As catastrophe risks and losses increase, and customer expectations evolve, the industry is moving from simply pricing risk to a more active role in mitigating it.

The path forward is clear: insurers who embed intelligent infrastructure, real-time data, and greater transparency and governance into their operations won't just process claims, they can successfully prevent them. They'll become resilience partners to their customers, offering early warnings, dynamic coverage, and mitigation services that reduce losses before they occur.

Here's one last prediction: by 2030, all of this will be commonplace. Foresight will be foundational. Prevention will be expected. And those who invest now, building the infrastructure, data pipelines, and trust required to act before disaster strikes, won't just predict and protect. They'll lead.