How insurers can leverage the power of generative AI

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.

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. 

Conclusion

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.