Leveraging AI in insurance: Unraveling its benefits and opportunities

In the dynamic landscape of the insurance industry, agents face a multitude of challenges and opportunities driven by shifting market demands and evolving client expectations. The current hard market conditions, coupled with the emergence of new coverages, have led to a surge in client requests, requiring a delicate balance between acquiring new sales and nurturing existing client relationships. Independent agents find themselves juggling multiple appointments and brand affiliations, requiring the unique ability to manage various risk appetites and communicate effectively at scale across diverse portfolios. In light of these complexities, the consideration of integrating AI into the agent’s toolkit emerges, offering a transformative solution to meet the heightened expectations of clients and navigate the ever-evolving insurance landscape.

When it comes to client expectations, the demand for greater personalization in all communications stands out as a pivotal requirement in today’s insurance industry. AI not only enables agents to tailor their interactions to individual client needs but also ensures speed and accuracy in delivering information and services. Drawing parallels from other industries such as online retail, AI offers innovative applications that can be seamlessly translated into the insurance realm, enhancing client experiences and operational efficiencies. By leveraging AI, agents can provide a level of support that complements their work rather than replacing it, fostering stronger client-agent relationships and driving business growth.

Benefit: Increased productivity  — Think about repetitive tasks or ways employees spend time. Some of these may not be necessary to express empathy, or be particularly complex. With the ability to process and make sense of data quickly, AI can speed up intricate operations, freeing employees to spend time on more interactions that matter most.

Opportunity: Through some online meeting platforms, there are AI systems that can actively listen to the entirety of a meeting, discern the crucial points, and generate concise, accurate summaries. This helps share key insights and decisions are shared with those who couldn’t attend and allows participants to focus more on the discussion. The summaries can be archived, simplifying the search for and retrieval of information about past meetings, enhancing organizational knowledge and decision-making processes. Just as you would in recording a meeting, it’s important to inform all attendees that this function is being used.

Benefit: Optimized client experience — AI can tap into online knowledge bases (i.e., CRM, learning management systems, etc.) specific to the agency and provide general information and answer straightforward questions. For more complex issues, AI can direct customers to agents and ensure that the advice given is always compliant.

Opportunity: AI-powered chatbots can mimic helpful sales assistants who know just what you need, and text integration means they can reach clients wherever they are. However, this type of tech is complex and constantly changing. Using it in a regulated insurance industry means implementation plans should include consulting with legal counsel to better understand your jurisdictional landscape and developments.

Benefit: Lower costs — With processes sped up, the cost to perform each task decreases. Plus, employee satisfaction increases when they can focus on less mundane tasks.

Opportunity: Ask staff to generate a list of their time-consuming, repetitive tasks and look for patterns.  Consider how AI may aid in speeding up some of the tasks.

Understanding the limitations of AI in the insurance industry

The insurance sector has been increasingly integrating AI into its daily operations, aiming to streamline processes and enhance client experiences. While AI presents remarkable capabilities, it’s equally important to acknowledge its limitations, especially in an industry that heavily involves decision-making, personal interactions, and evolving regulations. Insurance agents equipped with an understanding of AI’s strengths and weaknesses can better integrate this technology into workflows.

What AI can’t do

• Make ethical decisions: When talking about ethics, AI systems don’t have that human knack for grasping the moral consequences of their actions. They might recommend decisions based on data, but they can’t fully get the ethical ins and outs in challenging insurance situations.
• Replace human empathy: AI can mimic conversational nuances but can’t genuinely empathize with customers. Your experience and expertise is crucial in dealing with sensitive issues, providing emotional support, and fostering long-lasting customer relationships based on trust and empathy.
• Guide through uncertain situations: With frequent unique scenarios in the industry, AI might face challenges with ambiguity and situations demanding a profound grasp of context, societal norms, and unspoken cues – all crucial areas where human judgment plays a pivotal role.
• Establish personal connections: Though AI can enhance efficiency, it cannot replace the personal connections you establish with clients. Meaningful conversations and connections that foster customer loyalty still heavily rely on personal interactions.
• Exhibit creativity: AI lacks creativity in problem-solving and approach. Unique, out-of-the-box solutions, especially in complex claims or novel policy development, require human ingenuity and creative thinking.
• Check its own work: AI can offer mistaken answers, or even “hallucinate” facts that don’t exist. It’s vital to keep a human in the loop to validate AI-generated answers and content.

While AI can significantly augment the capabilities of insurance agencies, it should be regarded as an assistant rather than a replacement. Balancing AI’s analytical prowess with human emotional intelligence and ethical judgment will pave the way for a more resilient, responsive, and customer-centric insurance industry.

“AI could be a customer service superpower if used the right way – providing faster, more personalized experiences. But a human must remain in the loop. There is still risk and incorrect information in these tools. A human brings judgement, empathy, reason and critical thinking skills to the AI task.”

-Jim Fowler, Nationwide’s Chief Technology Officer

Dos and Don’ts of risk management in gen AI

When it comes to managing risks with generative AI, it’s crucial to establish guidelines around data privacy, transparency, inclusivity and regulation compliance.

Ensure data privacy

• Do implement robust data encryption techniques to protect personal and sensitive data.
• Do understand what each Gen AI tool will do with prompts and other submitted data. Avoid inputting sensitive data if it’s not fully secure.
• Do conduct regular audits to ensure compliance with data protection laws.
• Don’t collect, store, or process more personal data than is necessary for the operation of your systems.
• Don’t ignore the importance of securing consent from users before their data is used in any form with gen AI models.

Maintain transparency

• Do document and communicate the design, purpose, and operation of gen AI models to employees clearly and comprehensively.
• Do create understandable and accessible terms of use and privacy policies for end-users interacting with gen AI products and ensure compliance with any local regulations.
• Don’t withhold information about the limitations and potential risks associated with the use of gen AI technologies from users and stakeholders.

Promote Inclusivity

• Do involve a diverse group of employees in the planning, testing and adoption phases of gen AI projects to minimize biases.
• Do consistently test and reevaluate your gen AI technologies to ensure fairness and inclusivity across varied demographics.
• Don’t rely on homogenous data sets that reinforce stereotypes and propagate biases in gen AI outputs.

Comply with regulations

• Do stay informed about and adhere to existing and emerging legislation pertaining to AI and its applications.
• Do cooperate with regulatory bodies and contribute to the development of ethical guidelines and standards for gen AI.
• Don’t view compliance as a checkbox exercise; it should be an ongoing effort that evolves with your technology adoption process.