Purpose Over Speed: How Carriers Will Win With Ai

Insurers may have been spared a landfall hurricane in the U.S. in 2025, but the spring and summer severe weather and tornado outbreaks accounted for a record 21 billion-dollar disasters. And with tornadoes already wreaking havoc this early in the storm season, it is likely that above-normal severe weather events can be expected again this year.

Carriers have more tools than ever before to help them prepare, including artificial intelligence. But before any AI tool is implemented, insurers must ask a fundamental question: What problem are we looking to overcome?

Optimize AI tools for the best value

There are many ways AI can be used, from predicting where storms are more likely to hit based on historic data and current weather patterns, to identifying damage in photos and videos uploaded by customers. But not every AI application is right for every insurer. Implementing an AI solution simply because competitors and other industry players are doing so will result in little value.

For example, using AI to streamline First Notice of Loss reporting following a catastrophic event can help customers begin the claims process sooner without having to wait to speak with their agent or a call center representative. AI can filter the spike in claims faster than a human by analyzing photos and videos almost instantly. It can flag more complex claims or instances of extreme damage and total loss for immediate further investigation. Insurance companies can prioritize the time adjustors have available to serve those with the greatest need most efficiently.

This type of AI tool can be an effective time saver for insurers managing high-frequency claims. The AI tool can easily be trained to recognize common damage scenarios. However, an insurer with specialized policies may not reap as many benefits from this solution because the time and effort required to build an AI tool capable of accurately analyzing claims will outweigh the results.

AI works best when it is an integrated part of the process. For AI to deliver meaningful results, it must be designed into the flow, from the start. That’s when it becomes additive: keeping the full picture of the claim in view, flagging issues a human might miss and supporting faster, more accurate decisions.

First: Define the problem

Success starts with three things:

• A clear problem definition
• A defined owner
• A shared vision for success

What are we trying to win? What are we willing to lose? Initiatives fail without this foundational clarity. Tools rushed in without a plan, or force-fit into a part of the organization that didn’t ask for it, often fail.

AI isn’t a magic button. It’s an operating model shift; one that works only when leaders approach it with clear goals, tight controls and a long-term view.

The carriers who will win with AI are those who prioritize purpose over speed. When implemented with that level of intent, AI doesn't just improve speed or cost efficiency. It unlocks higher-order outcomes: better decision-making, more consistent service, and new space for human involvement to shine.

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