The latest survey of AM Best, a global credit rating agency specialising in the insurance sector, found that 60% of its respondents (carrier companies and managing general agents) anticipate AI materially reshaping their business models within the next one to three years.
However, the AM Best study also highlights obstacles like data readiness, cybersecurity and privacy concerns, preventing the technology’s widespread adoption. The difficulty of integrating AI with legacy systems also proved to be another headache for industry players.
The survey, titled “Artificial Intelligence Appears to be Ready, But Most Insurers Are Not,” covered responses from more than 150 insurers and MGAs with a Best’s Performance Assessment. While industry-scale adoption is already underway, with 41% of organisations confirming active use of AI in core business functions, around one in five respondents stated that their organisations have reached an advanced stage of implementation.
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Some participants even indicated that insurance industry players have a formal AI policy. As per AM Best, insurers appear less concerned about organisational resistance or third-party model risk but continue to view system vulnerabilities and data quality issues as key challenges.
“AI systems are heavily dependent on high-quality, clean and well-structured data. 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 Many of these legacy systems are outdated and store data in inconsistent formats lacking standardisation,” commented Kaitlin Piasecki, Industry Research Analyst at AM Best.
Sridhar Manyem, senior director of industry research and analytics at AM Best, said, “AI systems can produce unreliable outputs when underlying data is of poor quality, fragmented across legacy systems, insufficiently governed or lacking appropriate context. Insurers that have invested in modernising their legacy systems and have robust data governance will find it easier to integrate AI into their workflow.”
According to the research, around two-thirds of respondents intend to increase their investment in AI over the next 12 to 24 months. Among the main priorities identified, enhancing employee productivity, reducing operational expenditure, and strengthening underwriting processes—particularly in risk selection and pricing—took centre stage.
“Among firms already deploying AI, 63% reported modest gains in workforce productivity and satisfaction, while 11% observed notable improvements. Overall, 31% of respondents expect no significant change in staffing levels, whereas 37% anticipate staff being reassigned to higher-value functions,” AM Best noted.
“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 materialise. Insurance roles, especially those that require judgment, critical thinking and accountability, were ones respondents felt AI wouldn’t yet be able to fully replicate,” concluded Jason Hopper, associate director of industry research and analytics at AM Best.