Balancing Human Touch & AI in Insurance: 6 Key Strategies

This article was originally published in Rough Notes Magazine.

Artificial intelligence (AI) has completely transformed how we do business—now it’s time for AI to shine its light on insurance. From underwriting and claims processing to customer service and risk assessment, AI promises increased efficiency and accuracy. However, as we embrace these technological advancements, maintaining the human element and nurturing relationships are the backbone of the insurance industry.

Understanding the Human Element

Regardless of technology, people are at the center of the insurance industry. Whether providing coverage for individuals or businesses, the personal relationships agents and brokers cultivate are invaluable. Clients trust their insurance professionals for their expertise, understanding, empathy, and support. AI can enhance these relationships by taking over routine manual tasks, allowing professionals to focus on what they do best—connecting with people.

In this largely digitized world, a 2021 study conducted by Accenture asserts that 49% of insureds want to speak with a human advisor when they need to file a claim. Only 12% would file a claim with an automated phone, email, or web service, and still fewer, at 7%, would initiate an insurance claim with a chatbot¹. This only strengthens the fact that people still very much want to work with people to get a job done—especially when their money's on the line.

6 Strategies for Effective AI Integration

To achieve harmony with cutting-edge technology and the essential human element in the insurance industry, here are six strategies for professionals that leverage AI to enhance rather than replace human capabilities, ensuring that relationships and personalized service remain at the forefront of the insurance experience:

Strategy 1: Integrate AI to Enhance, Not Replace

The key to a successful AI strategy is integration. AI should be seen as a tool that complements and enhances human capabilities rather than replacing them.

Implementation Steps:

• Leverage AI for Routine Tasks: Use AI to automate repetitive and time-consuming tasks such as data entry, document processing, and basic client inquiries. For example, implementing AI-driven chatbots can efficiently handle initial client interactions, freeing up people to address more complex and emotionally nuanced issues.
• Augment Decision-Making: AI can assist in data analysis, helping agents make more informed decisions. For instance, predictive analytics can identify patterns and trends in client behavior, enabling agents and brokers to address potential issues and offer tailored solutions proactively.
• Support, Not Supplant: Ensure that AI tools are designed to support agents and brokers rather than replace them. For instance, AI can be used to suggest coverage options based on client risk data, but the final decision and personal touch should come from the agent.

Strategy 2: Training and Development

For retail agents and others along the insurance chain, ongoing training and development are essential. Understanding AI and its applications enables professionals to use these tools effectively.

Implementation Steps:

• Comprehensive AI Training: Develop training programs that cover the fundamentals of AI, its benefits, and its applications within the insurance industry. This should include both technical training on how to use AI tools and strategic training on how to incorporate AI insights into daily operations.
• Continuous Learning: Establish a culture of constant learning where employees are encouraged to stay updated on the latest AI advancements. This could involve regular workshops, webinars, and access to online courses.
• Hands-On Experience: Provide hands-on training sessions where agents can interact with AI tools in a controlled environment. Training helps build confidence and ensures they understand how to integrate AI into their workflow without losing the human touch.

Strategy 3: Foster Transparency and Trust

One concern with AI is the perceived lack of transparency. Clients may be wary of decisions made by algorithms they don’t understand.

Implementation Steps:

• Explain AI Usage: Communicate how AI is used in the decision-making process. For instance, when using AI to assess risk or determine premiums, explain the factors the AI considers and how it benefits the client.
• Transparency in Algorithms: Ensure that the algorithms used are transparent and can be easily explained. Avoid using black-box models that are difficult to interpret.
• Client Education: Educate clients about the role of AI in enhancing their service. For example, create informational materials that outline how AI can lead to faster claims processing and more accurate risk assessments, ultimately benefiting the client.

Strategy 4: Personalize Client Interactions

AI can gather and analyze customer data to provide deeper insights into client needs and preferences. This data can create highly personalized interactions, enhancing the customer experience.

Implementation Steps:

• Data-Driven Insights: Use AI to analyze client data and generate insights that inform personalized communication. For example, AI can identify significant business events that might necessitate coverage updates, such as a company expanding its operations, entering a new market, or acquiring another business. Analyzing client data enables agents to proactively reach out with relevant offers and advice, ensuring clients have the appropriate coverage for their evolving business needs.
• Tailored Communication: Leverage AI to segment clients based on their preferences and behaviors. This allows for personalized communication strategies, such as tailored email campaigns or policy recommendations.
• Enhanced Client Profiles: Maintain detailed profiles that include AI-generated insights. Agents can use these profiles to provide more relevant advice and build stronger client relationships.

Strategy 5: Human-Centric AI Design

A human-centric design approach is essential when developing AI tools. This means creating AI systems that prioritize user experience and are intuitive for clients and insurance professionals.

Implementation Steps:

• User Involvement: Involve end-users (agents and clients) in the development process to gather feedback and ensure the AI tools meet their needs. This can involve beta testing, focus groups, and regular feedback loops.
• Intuitive Interfaces: Design AI interfaces that are easy to use and understand. For instance, AI dashboards for agents should present data in a clear, actionable format, while client-facing tools should be user-friendly and accessible.
• Empathy and Support: Ensure AI interactions reflect empathy and support. For example, a chatbot handling a claim should be programmed to express understanding and offer reassurance rather than just processing information.

Strategy 6: Emphasize Relationship Building

Despite AI's efficiencies, relationship-building should remain a top priority.

Implementation Steps:

• Proactive Engagement: Use AI to identify opportunities for proactive engagement. For instance, AI can alert agents when it’s time for a policy review or when a client’s needs may have changed, prompting timely and relevant interactions.
• Personalized Touchpoints: Ensure that AI tools support personalized touchpoints, such as sending birthday wishes or congratulatory messages for life milestones. These small gestures help maintain strong personal connections.
• Feedback and Improvement: Regularly gather feedback from clients about their experiences with AI tools and use this feedback to make continuous improvements. Improving based on client feedback shows clients that their opinions are valued and helps build trust.

Striking a Balance for Success

AI in the insurance industry is an exciting new chapter, offering significant improvements in efficiency and accuracy across various operations, from underwriting and claims processing to customer service and risk assessment. However, the true potential of AI lies in its ability to work alongside human capabilities rather than replace them.

As we navigate the evolution of AI, the human touch remains the foundation of this relationship-centric industry. By implementing strategies that focus on enhancing human interactions, fostering transparency, personalizing client interactions, and emphasizing continuous learning and relationship building, insurance professionals can leverage AI to deliver superior service without compromising the personal relationships that clients value. AI should be viewed as a powerful tool that supports agents and brokers, allowing them to dedicate more time to understanding and meeting the unique needs of their clients.

Ultimately, the successful integration of AI in insurance is contingent upon a balanced approach that prioritizes human elements and technological advancements. This careful balance enables retail agents, wholesalers, MGAs, MGUs, and program administrators to thrive in an AI-enhanced future, delivering exceptional service and forging stronger, more resilient client relationships while growing their businesses.

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References:

Accenture. (2021). Accenture Insurance Consumer Study 2021. Retrieved from https://www.accenture.com/content/dam/accenture/final/accenture-com/document/Accenture-Insurance-Consumer-Study-2021.pdf ​​