A new survey by AM Best found that while a majority of insurance carriers and managing general agents anticipate artificial intelligence will significantly reshape their operations, persistent challenges in data readiness, cybersecurity, and legacy system integration are slowing widespread adoption.
The findings appear in a Best’s Segment Report titled “Artificial Intelligence Appears to Be Ready, But Most Insurers Are Not,” based on responses from more than 150 rated insurers and managing general agents holding a Best’s Performance Assessment.
Nearly 60% of respondents said they expect AI to significantly transform their business models within the next one to three years.
At the same time, 41% reported that their organizations are already actively using AI across core business areas, and nearly 20% agreed or strongly agreed that their organizations have reached an advanced stage of implementation. A majority also said their companies have formal AI policies in place.
Kaitlin Piasecki, industry research analyst at AM Best, said legacy infrastructure is one of the most significant bottlenecks. “AI systems are heavily dependent on high-quality, clean, and well-structured data,” she said.
“Legacy systems can create significant barriers when implementing AI because they simply were not built for this type of data integration. Many of these legacy systems are outdated and store data in inconsistent formats lacking standardization.”
Approximately two-thirds of respondents said they plan to increase AI investment over the next 12 to 24 months. The leading goals cited were improving employee productivity, lowering operating costs, and supporting underwriting functions for risk selection and pricing.
Among those that have already implemented AI solutions, 63% reported a small improvement in workforce productivity and satisfaction, while 11% reported a significant improvement. On staffing, 31% of respondents said AI would bring no material change to headcount, while 37% expected employees to be redeployed to higher-value work.
Jason Hopper, associate director of industry research and analytics at AM Best, cautioned against expecting quick financial returns.
“Given that this technology is still relatively new, a return on investment in AI would be difficult to measure at this stage; the cost benefits will likely take years to materialize,” Hopper said. “Insurance roles, especially those that require judgment, critical thinking, and accountability, were ones respondents felt AI wouldn’t yet be able to fully replicate,” he added.
While respondents expressed less concern about change resistance and third-party model risk, they identified the potential for AI system breaches by bad actors and data readiness as among the most significant challenges to AI implementation.
