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Homeowners across the United States are facing a growing challenge: rising insurance premiums and reduced access to coverage, especially in areas vulnerable to natural disasters.
As catastrophic (CAT) events such as wildfires, floods, hurricanes, and severe storms increase in frequency and severity, insurers are reassessing their risk exposure. In many cases, they’re reducing coverage offerings or withdrawing from entire regions. At the same time, nearly one in seven homes in the U.S. is now uninsured. The industry is approaching a critical point where traditional underwriting and risk management methods are no longer sufficient.
Emerging technologies — particularly artificial intelligence (AI) and location intelligence — are beginning to offer a path forward. By providing more accurate, property-specific insights, these tools can help create a more resilient and equitable home insurance ecosystem.
Moving from broad risk pools to property-level precision
Traditional insurance models have relied heavily on aggregated data: ZIP code-level risk assessments, long-term historical trends, and generalized assumptions. While these models offer scale and simplicity, they often fail to reflect the actual condition and risk profile of individual properties.
AI-powered location intelligence is changing that. Using aerial imagery in conjunction with data points like weather history, building materials, vegetation proximity, and others, insurers can now assess risk at a much more granular level. This allows for more accurate underwriting decisions and pricing, better reflecting the true exposure of each property.
This shift toward precision comes at a time when U.S. homeowner premiums are projected to rise another 8% in 2025, following an average 20% increase over the past two years. By leveraging more detailed insights, insurers can expand their capacity in areas previously deemed too risky, offering more competitive rates, and increasing transparency in the pricing process.
Importantly, this kind of insight isn’t limited to underwriting. Property-specific data can inform risk monitoring, claims triage, policy servicing, and portfolio-level decision-making throughout the entire policy lifecycle.
Enabling proactive risk management for homeowners
Beyond improving how insurers evaluate risk, AI and location intelligence have the potential to shift the insurer-policyholder relationship from reactive to proactive. Historically, homeowners often hear from their insurer only when premiums go up or when coverage is denied. That dynamic is beginning to change.
With access to updated property data and risk indicators, insurers can now notify homeowners of issues before they result in claims. For example, overgrown vegetation might elevate wildfire risk, or signs of roof deterioration might signal future water damage. When shared in a timely and actionable way, this information allows homeowners to take preventive steps and potentially reduce their premiums.
This process is also more efficient and less invasive than traditional inspections. Aerial imagery analyzed through AI can detect roof damage or property changes without the need for in-person site visits. It also improves safety and consistency, particularly when assessing difficult-to-access features like rooftops. According to a recent survey, 66% of experienced P&C insurers agree that new technologies help lower average insurance costs by shifting higher premiums to higher-risk consumers while allowing lower-risk homeowners to benefit from more accurate pricing.
Aligning innovation with regulatory oversight
The adoption of AI in insurance is accelerating, and regulatory bodies are taking active steps to keep pace. In 2025, all 50 U.S. states, along with Washington, D.C., Puerto Rico, and the Virgin Islands, introduced AI-related legislation. Among them, 28 states and the Virgin Islands have enacted more than 75 new measures this year alone.
This growing regulatory interest underscores the importance of transparency and accountability. As insurers use AI to support underwriting, pricing, and claims decisions, the models must be explainable, auditable, and compliant with existing consumer protection standards.
When done responsibly, AI can support a more resilient insurance system. Transparent models help build trust with regulators and consumers alike. At the same time, better data and more precise pricing help insurers stay in markets they might otherwise exit, which expands access to coverage and supports greater equity.
Building a more resilient future
As climate risks continue to evolve, the insurance industry must adapt. AI and location intelligence are no longer fringe innovations. They are fast becoming essential tools to manage risk, price coverage more accurately, and enable proactive engagement with policyholders.
In the near future, technologies that once seemed cutting-edge — automated aerial assessments, predictive analytics, and dynamic property scoring — will be standard tools across the industry. To realize their full potential, the path forward requires continued collaboration between insurers, technology providers, and regulators. Responsible implementation, clear communication, and shared goals will ensure these tools benefit everyone involved.
The stakes are high. But with the right strategy, insurers can continue to offer sustainable coverage options, empower homeowners to better protect their properties, and contribute to safer, more resilient communities across the country.
Opinions shared in this piece are the author's own.
David Tobias serves as the chief product officer at Nearmap. Previously, he co-founded Betterview, the leading Property Intelligence Platform for P&C insurers, which was acquired by Nearmap in December 2023. David plays a pivotal role in driving the market strategy for Nearmap, enabling users to effectively identify and mitigate risk, enhance operational efficiency, and build a more transparent customer experience.
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