The insurance industry is at a pivotal moment in embracing generative AI. According to the ISG Pulse Check State of the European Insurance Industry 2024, insurance firms are actively engaged in generative AI transformations and currently comprise nearly a quarter of all generative AI use across various industries.

This transformative technology is helping insurers unlock value and innovation, gain deeper insights into their clientele, enhance the precision of risk assessments, and elevate the quality of offerings. Insurance firms in the EMEA region (Europe, the Middle East and Africa) see their top priority for generative AI as customer service delivery and claims management, followed by customer personalization, employee productivity, insurance operations delivery, policy administration and upselling/cross-selling.

While the potential of generative AI has positioned it as a key investment priority for insurance firms, ISG research finds the prevalent trend in the insurance industry right now is experimentation and enthusiasm, despite still-elusive outcomes. Five percent of EMEA insurance firms currently have no investment in GenAI, while 32 percent are pursuing exploratory initiatives, 36 percent are running isolated projects, 25 percent have transformation work in progress, and only 2 percent are moving to steady state.

For insurance firms that are yet to explore this technological frontier, a window of opportunity exists to bridge the gap and stay abreast of competitors before the landscape evolves further.

How Generative AI Will Impact Insurance Firms

Generative AI has the potential to transform every facet of the insurance value chain, from initial customer interaction to claims resolution and beyond. For example, unlike conventional claims processing methods, which rely heavily on manual intervention and predefined rules, GenAI leverages advanced algorithms to generate insights autonomously. This enables organizations to expedite the claims processing cycle, optimize resource allocation and mitigate operational risks.

According to ISG analysis, European insurance firms are poised to experience significant operational efficiency and service quality enhancements, with potential improvements in claims handling efficiency and quality ranging between 40 and 60 percent. This is coupled with a notable 30 to 40 percent boost in customer satisfaction and cost reductions of up to 50 percent thanks to generative AI technologies.

Insurance firms can only fully realize these benefits if they adopt and seamlessly integrate generative AI throughout their value chain. By leveraging this innovative technology, insurers can unlock new avenues for growth, streamline processes, and ultimately, deliver unparalleled value to their stakeholders.

How Insurance Firms Should Implement Generative AI

Today, enterprises are starting with specific generative AI use cases to test and demonstrate tangible value and win buy-in from internal stakeholders. These test cases often focus on enhancing day-to-day operations, leveraging AI for tasks like coding assistance or deploying chatbots as knowledgeable assistants. Next, insurers are shifting to comprehensive transformation initiatives aimed at reshaping end-to-end processes like automated claims processing or personalized marketing strategies to enhance efficiency and customer experience.

However, a more comprehensive strategy that considers the broader organizational landscape and aligns generative AI initiatives with the overarching business objectives, AI strategy, operating model, ecosystem and sourcing model would boost an organization’s chances of realizing substantial and sustained value from generative AI implementations.

To create a robust framework that elevates generative AI from a tool into a strategic enabler that revolutionizes business operations and drives sustainable growth, insurers should build:

• A strategy that starts with the C-suite’s vision and acts as the spearhead for all other discussions. The success of any generative AI integration requires senior leadership guidance and buy-in.
• The cognitive infrastructure that forms the base technology foundation on which everything else is built. This is a conceptual infrastructure, filled with hybrid cloud technology platforms, security policies, edge computing, and any other purpose-built assets that serve and enable generative AI.
• The AI control pane, with measures and mechanisms to ensure ethical, secure, compliant, reliable implementation and operation of generative AI, and a method for tracking its impact.
• The data layers of all the structured and unstructured data owned by the organization, mechanisms to transform the data and generative AI models.
• The operational functions that serve the functional activities, such as intelligent AI chatbots for customer service. This is where the vision and value of generative AI is executed and realized.

Strategically adopting generative AI requires a meticulous approach. This framework fosters cohesion among diverse business functions, enhances operational efficiency, and acts as an instrument for pre-emptively resolving and troubleshooting issues. It also serves as a compass for identifying capability gaps and facilitating targeted interventions to bridge these gaps effectively.