Legacy mindset holding insurers back on implementing AI, expert says

EXL exec Sumit Taneja says for many insurers, a legacy mindset is what is holding the industry back from making rapid strides in implementing AI.

Taneja, EXL’s SVP and global head of AI consulting and implementation, noted that some companies have implemented individual use-cases for AI, but many still struggle to see a bigger-picture view. He explained that EXL last year held a few AI sessions with American insurers where this issue became evident.

“We could see the insurers almost switching off because they just could not relate to where this will go and is it practical also. So, we had to actually tone down some of that and suggest more incremental steps where there will be a vision to reach in two, three years,” he said.

Insurers ‘think very linearly’

In his opinion, this is because many insurers still “think very linearly” due to the way workflows and processes in the industry have been historically designed and utilized for years. He suggested insurers pivot away from this mindset and instead think about how they can embed AI in their day-to-day working instead of just having one standalone application that’s not part of their core workflow.

“They just can’t think multiple things will happen in parallel… It will probably take much longer to get people out of that thinking that multiple things you used to do can actually happen now in parallel,” Taneja said.

Legacy systems, data limitations

Foundational challenges like multiple legacy systems and unstructured data also are limiting American insurers’ ability to adopt and scale AI, according to Taneja.

“Not that they are not keen to do it, but there are many foundational problems that the insurance companies have, which limits them to accelerate. One is the multiplicity of admin systems, and second is their data landscape is still very siloed. Unstructured data has not been managed properly, so using some of that data for AI is still a few months or maybe a year away,” Taneja said in an interview with InuranceNewsNet.

He noted that many insurers have yet to realize the full extent of what AI can do for them, with most using it for simple automation or marketing. This aligns with the results of EXL’s recently released 2025 Enterprise AI Study, which found the U.S. insurance industry has increased adoption of machine learning but still lags behind when it comes to generative AI.

“I think we are still scratching the surface of what AI can deliver to insurance. At the same time, I will caveat it out and say the adoption with respect to GenAI and Gen Tech is still early days,” Taneja said.

Study finds slow adoption

The EXL Enterprise AI Study surveyed C-suite and senior executives in insurance, banking and finance, retail, utilities and healthcare around the world. That included 50 U.S. insurance executives and decision-makers.

Looking at the U.S. results alone revealed a disconnect between how insurers think they are doing with AI and how they measure up to other industries. While 24% of American insurers surveyed said they believe they are “far ahead” of peers with AI adoption, only 10% were actually considered AI leaders when compared to other industries.

Fifty-eight percent of U.S. insurers surveyed have started using machine learning AI solutions. This kind of AI is typically used for solutions like claims automation or fraud detection. However, only 38% reported adopting GenAI — the lowest adoption rate among all industries surveyed. GenAI is the type of technology used for chatbots or simulating customer service interactions.

Just under 90% of insurers acknowledge that scaling AI is “very important,” with 60% planning to pilot GenAI claims in the future and 46% actively rolling out GenAI pilots in underwriting.

“I’ve not seen a lot of AI at end-to-end being deployed as of now. There are enough bigger companies who we are helping; you’re seeing them moving in that direction. But it’s still maybe a couple of years away where we will see a large underwriting area or a large claims area has been completely transformed,” Taneja said.

Foundational challenges

Aside from understanding the scope of what AI can achieve, Taneja emphasized that insurers must address the issue with legacy systems and data silos if they hope to increase their adoption.

“The legacy systems they have in their ecosystem and the data silos are limiting their ability to scale faster, and I don’t see that changing very soon,” he said.

As an example, he mentioned one insurer that has 28 policy admin systems, none of which support the infrastructure needed to implement AI.

“I don’t know how they can even think of reimagination unless they get to a migration from their 28 to two or three admin systems over the next three, four years before they will really see value,” Taneja said.

Similarly, having that many legacy systems impacts data being readily accessible by AI because even just one customer exists in multiple different systems.

For insurers like this, he said, they would have to first invest in data warehouses and platform modernization before being able to implement and scale AI solutions — and that could be “very limiting for large insurers.”

EXL Service is a global data analytics and digital operations and solutions company based in New York. Founded in 1999, it now has a team of 1,500 data scientists and operates in a wide range of industries.

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