How GenAI Is Transforming Insurance

10 February 2026 / 4 min read

Verisk’s experts discuss how GenAI is reshaping insurance, yet human expertise remains key to navigating its challenges.

Among the many potential uses of generative artificial intelligence (GenAI) in insurance, the technology is emerging as a solution to one of the industry’s major challenges: mastering vast volumes of fragmented and unstructured data.

At The Verisk Insurance Conference, a panel of industry experts explored how GenAI is reshaping the insurance landscape. Nutan Rajguru, Johan Larsson, Jes Westerman and Leanne Chamberlain shared practical use cases, discussed implementation challenges and offered a forward-looking perspective on AI’s role in underwriting, claims and customer service.

Tackling industry pain points with AI

Larsson explained that while insurance has always been data-driven, much of that data is scattered, hard to process, and time-consuming to manage.

“The insurance industry is driven by data. It's the fuel,” he said. “Going through data is always a challenge, especially when you find it in various formats and sources. There's also a large amount of unstructured data that a computer wouldn't normally be able to work with without help.”

However, GenAI is well-suited to overcome this issue because it excels at quickly spotting patterns in complex data, according to Larsson.

Beyond handling data, GenAI can streamline manual, time-consuming tasks that usually demand significant human effort. Westerman highlighted that in underwriting, applying GenAI in this way can drive notable efficiency gains.

“Wherever there is an extra cost and human resource used in manual processes, GenAI can fill in those gaps, improve levels of automation, and help to extract and validate data,” he said.

While this approach cuts down the time spent on manual underwriting tasks, Westerman stressed that humans should remain in the loop. Chamberlain agreed, emphasising that AI doesn’t replace humans but supports them—particularly when they’re facing “blank page syndrome,” by providing initial ideas and summarising large volumes of documentation to guide decisions.

Real-world applications already making a difference

Panellists emphasised that AI isn’t just a future possibility; there are already use cases. For example, in claims, AI tools can extract and summarise medical documentation, which can improve speed and accuracy in decision-making.

“Whenever you need to go through a medical history of a claimant and understand underlying symptoms and history, we can do that in seconds instead of days or hours,” said Larsson.

Meanwhile, in underwriting, AI is streamlining interactions between brokers and insurers, standardising incoming data and performing first-pass risk assessments.

Chamberlain added that it also improves operational efficiency through automated vehicle grouping, claim triage, and damage assessment.

Verisk’s own innovations, such as the Verisk Document Reader, illustrate these benefits by classifying, extracting, and prioritising incoming documents.

According to Rajguru, this not only accelerates workflow but also enables more strategic tasks because “things that would take years can take just weeks now and months.”

Quantifying the value

As more insurers adopt AI, they are looking for ways to demonstrate its tangible benefits. Larsson highlighted that the time and accuracy gains from AI provide clear, quantifiable value.

“The best reader in this room probably reads around 300–350 words a minute,” he said. “AI never gets tired, never emotional, so time, but also accuracy, to a large extent, is definitely quantifiable.”

But the benefits of AI aren’t just measured in numbers. Chamberlain pointed out that it also enhances employee engagement and improves customer experience.

“It's not all just about trying to save money,” she said. “Ultimately, the end goal is to give a better experience to the consumers and to make things better for the people who are interacting daily with these tasks.”

Navigating challenges

Despite its benefits, AI adoption brings it own challenges. As more insurers explore its use, fostering a culture of acceptance can be difficult, particularly when employees fear it may replace their roles.

Chamberlain references a 2024 survey showing that around a third of executives worried about losing their jobs to GenAI. Therefore, she recommended addressing these concerns by framing AI as a tool to assist humans, not replace them.

“One of the challenges is trying to give people comfort that this doesn't mean that you're going to lose your job,” she said. “This means that your job, hopefully, is going to be more fulfilling.”

Looking ahead: the future of GenAI in insurance

Looking ahead to 2030, panellists envisioned a future where AI drives straight-through processing, enhances fraud detection, powers virtual agents, and supports claims settlement.

A recurring theme was AI’s potential to transform how individuals interact with insurers, making coverage more tailored and efficient than ever before.

“Maybe you will be talking to your personal assistant and they will be sending out to a mixture of carriers and brokers,” Westerman said. “You would be able to get really good value insurance as the insurer will have fantastic understanding of your risk, because they're accessing a level of data that they’ve never accessed before.”

GenAI is moving beyond hype to become a strategic enabler in insurance. The panel’s insights underscore the importance of thoughtful implementation, ethical considerations, and a clear roadmap for integrating AI into core business processes—transforming claims, underwriting, and customer service while supporting employees and enhancing customer experience.