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How insurers can leverage the power of generative AI

The game-changing technology stands to reshape the entire industry.

In brief
  • What are insurance industry use cases for generative AI?
  • What are the main objectives?
  • How can insurers get started?

The world of artificial intelligence (AI) continues to evolve rapidly, and generative AI in particular has sparked universal interest. This is certainly the case for the insurance industry, where generative AI is fundamentally reshaping everything from underwriting and risk assessment to claims processing and customer service.

The transformative power of this technology holds enormous potential for companies seeking to lead innovation in the insurance industry. Amid an ever-evolving competitive landscape, staying ahead of the curve is essential to meet customer expectations and navigate emerging challenges. As insurers weigh how to put this powerful new tool to its best use, their first step must be to establish a clear vision of what they hope to accomplish.

The role of generative AI in insurance

Generative AI, as its name suggests, generates content. Because its algorithms are designed to enable learning from data input, generative AI can produce original content, such as images, text and even music, that is sometimes indistinguishable from content created by people.

Models such as GPT 3.5 and GPT 4 present opportunities to radically improve insurance operations. They have the potential to automate processes, enhance customer experiences and streamline claims management, ultimately driving efficiency and effectiveness across the industry.

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Use cases come into focus as more insurers adopt generative AI

Within the industry, usage of the technology indicates three main objectives.

As the number of companies exploring generative AI multiplies, so will industry use cases. Recently, four patterns have started to emerge among insurers: 

  1. Summarize policies, documents and other unstructured forms of content
  2. Synthesize summarizations to create new content.
  3. Answer questions based on what it has learned from summarizing and synthesizing.
  4. Translate between natural languages, such as English and Italian, as well as computer code, for example, translations that yield new modern code that can run on the cloud.

Three primary objectives

Insurers are seeking to leverage these expanded patterns to address three main objectives:

  1. Improve experiences for customers, agents, agency staff members and employees by deploying a generative AI virtual assistant or virtual agent. Insurance companies can use generative AI to reinvent their approach to providing customer service and creating new products. Individualized and empathetic human interactions, for example, become easier to achieve when generative AI removes mundane processes from insurance professionals’ workload. 
  2. Heighten productivity and efficiency by deploying this technology alongside insurance industry knowledge workers, such as underwriters, actuaries, claims adjusters and engineers. Efficiency benefits include summarizing and synthesizing large volumes of content gathered during the claims lifecycle, including call transcripts, notes, and legal and medical paperwork, which is particularly useful in property and casualty insurance. Companies can compress the claims lifecycle dramatically. Particularly in the life insurance industry, there is significant interest in using generative AI for automation and decision-making in underwriting processes and policy issuance to a broader range of customers without the need for, say, in-person medical exams.
  3. Manage compliance and mitigate risks, which are key concerns in this highly regulated industry. Automated compliance monitoring, fraud detection, and even generating content in the form of training materials and interactive modules for staff to stay current on the latest regulations are areas that companies are starting to explore.
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Three steps to help insurers get started

Insurers can improve outcomes if they also optimize their existing processes.

To drive better business outcomes, insurers must effectively integrate generative AI into their existing technology infrastructure and processes. Generative AI is a tool within a broader set of techniques and technologies. Accordingly, insurers should improve existing processes and optimize them in parallel to achieve the maximum benefits of generative AI. The big win often involves combining multiple AI technologies to address different aspects of a project, such as semantic searching or language capabilities.

For insurers who are not yet using generative AI, these three initial steps are recommended: 

  1. Establish a multidisciplinary team of businesspeople, IT specialists and data scientists to embark on the generative AI journey, focused on adapting generative AI solutions to the unique requirements of the organization. 
  2. Identify the operating model that best fits the organization, not only in terms of experimenting with the technology but also to deploy it safely, successfully and in a scaled fashion. 
  3. Develop the requisite expertise and capabilities by beginning with low barrier use cases and gradually fine-tuning models based on domain knowledge and data sources.

With AI’s potential exceedingly clear, it is easy to understand why companies across virtually every industry are turning to it. As insurers begin to adopt this technology, they must do so with a focus on manageable use cases.

Risks and human oversight

While generative AI is valuable for identifying risks that humans overlook, the technology itself carries associated risks. These involve elements such as intellectual property, corporate-level reputation and bias, and information security. To mitigate such risks, insurers must embrace accountability and have control procedures and compliance frameworks in place. To ensure ethical and nondiscriminatory generative AI models, responsible AI methods that include human oversight are essential. 


Generative AI has the power to transform the insurance sector by increasing operational effectiveness, opening up new innovation opportunities and deepening customer relationships.

But it is essential that insurers proceed mindfully, with the right guardrails in place to manage the risks associated with the technology. Firms that adopt responsible AI practices and avail themselves of leading industry insights will be well positioned to seize opportunities as they arise amid the evolving AI landscape.

How insurers can leverage the power of generative AI

In this webcast, EY US and Microsoft leaders discuss how generative AI can fundamentally reshape the insurance industry, from underwriting and risk assessment, to claims processing and customer service.


Insurers must take an intentional approach to adopting generative AI, introducing it to the organization with a focus on use cases. Because generative AI carries potential risks, such as bias, human oversight plays a key role in its responsible deployment.

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