Insurance Industry Increasingly Adopting AI Technologies, Study Shows

Conning survey reveals a surge in AI adoption within the insurance industry, with large language models leading the tools being explored for sales, underwriting, and claims processing.
By: | March 14, 2024
Businessperson using AI tools

The insurance industry is embracing artificial intelligence (AI) at an accelerating pace, with 77% of respondents in a recent survey indicating they are in some stage of adopting AI in their value chain. This represents a significant jump from the 2023 survey, which showed 61% of respondents had either implemented or were in the process of implementing AI as part of their workflow, according to the study by Conning.

The survey, conducted among insurance C-suite decision-makers responsible for “greenlighting” emerging technologies, also found that 67% of companies are already piloting large language models (LLMs)—advanced AI systems designed to understand and generate natural language and other types of content to perform a wide range of tasks—a strong indicator of future adoption.

“Insurers are adapting, developing, and piloting innovative AI applications in pursuit of greater efficiency to drive customer and distributor satisfaction. In addition, insurers have access to a wider and larger selection of data than ever before and AI is a crucial technology in managing that data,” said Scott Hawkins, a managing director and head of insurance research at Hartford, Connecticut-based Conning.

The study explored AI’s impact on three key components of the insurance value chain:

  • Sales and underwriting
  • Operations and claims processing
  • Risk control and pricing

In the realm of sales and underwriting, AI algorithms are enhancing the accuracy and efficiency of underwriting processes.

“By analyzing vast amounts of data, including customer information and external factors, AI is helping insurers make better-informed decisions when assessing underwriting risks, speeding up the underwriting process, and reducing the likelihood of human error,” the survey report states.

AI-powered systems are also revolutionizing operations and claims processing by automating mundane tasks and streamlining workflows. These systems can analyze claim documents, assess damage, and calculate payouts with minimal human intervention. Moreover, AI plays a crucial role in fraud detection by flagging suspicious claims and patterns that may indicate fraudulent activities.

When it comes to risk control and pricing, AI tools are improving insurers’ ability to assess risks accurately and set prices accordingly.

“By analyzing historical data and real-time information, AI algorithms can predict future trends and potential losses more effectively,” the report explains. “This enables insurers to offer more competitive rates while maintaining profitability.”

The survey revealed several key takeaways on AI adoption, including the high percentage of LLM pilots. Additionally, the study found a high affinity for machine learning/predictive analytics (ML/PA) across the value chain, with ML/PA tied for the highest adoption rate (44%) among all technologies.

The survey excluded robotic process automation (RPA) and telematics from the study’s findings. While respondents were surveyed about RPA, the results indicated this technology was well past the mature stage and could not be considered an emerging technology, Conning stated. Telematics is an emerging technology, but respondents had found only limited applications across the value chain to date, the study noted.

Breaking down the technology adoption by value chain component, the survey found that in sales and underwriting:

  • ML/PA had been adopted by 54% of respondents, with the highest percentage of full adopters (17%) and the lowest percentage of non-consideration (11%).
  • LLMs showed the greatest potential for adoption, with 69% of respondents currently piloting the technology in this area.
  • Natural language processing (NLP) and speech recognition technology both were being piloted by 42% of respondents.

In operations and claims processing:

  • ML/PA and NLP each have been adopted by 47% of respondents.
  • Although LLMs have low overall adoption in this area, 65% reported they are currently piloting the technology, suggesting potential for wider adoption.

Finally, in risk control and pricing:

  • ML/PA has a higher overall adoption rate (35%) and the highest full adoption rate (14%).
  • ML/PA is likely to be the most adopted technology, with only 14% stating no plans to consider it.
  • LLMs have a high potential for adoption, with 62% currently being piloted.

As the insurance industry continues to adapt and find opportunities for growth and transformation, the adoption of AI technologies is expected to drive shifts in the type of staff and positions needed to run a modern insurance company. While developing and piloting these technologies will require significant investments in management time and resources, the potential benefits in terms of deeper customer insights, higher profitability, and improved operational efficiency are undeniable, according to Conning.

To purchase a copy of the report, visit Conning’s website. &

The R&I Editorial Team can be reached at [email protected].

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