Building a robust AI foundation

Evaluate current technology

Some of the technology you’re currently using may already be evolving to include AI. For example, Microsoft products now have add-on generative AI capabilities with CoPilot. Do your research, contact your vendor reps to understand what may be available.

Technology paired with AI

Phone: AI-powered phone solutions analyze speech patterns, context and sentiment and offer agents a recap of their discussions with prospects and clients to help formulate next steps. Cloud solutions like Gong have grown in popularity across industries because of their ability to help businesses drive productivity as well as assist with more predictable revenue and pipeline growth.

Texting: AI-driven chatbots engage in conversations and provide automated responses to client inquiries. These chatbots help streamline communication processes, enhancing engagement and client satisfaction. Zendesk, Intercom, Birdeye and others have developed solutions to append to a company’s user interface to support the beginning of simple digital engagements before introducing a human representative to dive deeper. Again, keep a close awareness of any disclosures required by your jurisdiction.

Email: AI-powered email platforms can help personalize emails using agent-generated content prompts, improving engagement and conversion rates as well as the quality of messaging. We have witnessed Microsoft’s launch of Copilot for its 365 apps to assist an employee while putting together professional documents like presentations, summarizing Teams meetings and writing responses to customer inquiries.

Forms: AI-enabled form completion tools leverage natural language processing to predict and autofill form fields based on user inputs and historical data that expedite data collection and processing. We see popular personal and commercial lines rating platforms use data aggregation and connectivity with third-party data providers. This assists consumers and agents with the completion of form fields that advance the progression of rating without requiring a human for each and every step.

Marketing communication: AI-powered marketing automation platforms utilize machine learning algorithms to segment audiences. By analyzing client preferences, these systems deliver targeted messages and enhance campaign relevance. This process is usually accomplished through the connectivity of the agency management system (AMS), customer relationship management (CRM) platform and marketing automation solution. By sharing data and empowering logic, communications preferences can be adhered to by client so the right messages get to the right person at the right time.

Social media: AI algorithms integrated into social media platforms analyze user interactions and preferences to deliver personalized content curation. LinkedIn has integrated AI into its recruiting, coaching and campaign tools as well as post responses, suggesting what the author could say based on the context of a respondent’s comments. This is a way to expedite the development of text while still requiring the oversight of the agent to ensure nothing is lost in translation.

Prepare your tech stack

• Consider AI chatbots on your website to handle simple queries, freeing up your team to focus on more complex client needs.
• Think about using machine learning algorithms to analyze data, uncovering patterns and insights to refine your marketing automation and prospect management strategies.
• Potentially utilize AI and machine learning to streamline your prospecting management, identifying high-quality leads.
• Consider using AI to analyze online sentiment about your agency, aiding in reputation management by providing real-time feedback on client perceptions.
• Approach integrating AI into your texting platform to automate responses to common inquiries, ensuring timely and efficient communication with clients.

Training your staff

As insurance companies integrate AI into their operations, it’s vital to invest in continuous workforce training. For those that are working with gen AI, it’s important for them to understand how they work, and their limitations. Consider these change management best practices.

Upskilling employees with the necessary skills not only maximizes the benefits of AI but also cultivates a culture of responsible use within the organization. You may also consider future skillsets focused to look for when hiring new talent.

Using AI responsibly

Along with the enthusiasm and promise any new technology brings, it’s important to not let that get ahead of the need to be safe and ethical. Especially when it comes to regulatory compliance, AI presents new challenges and regulations have yet to catch up with the technology. To ensure responsible use, it’s important to stay current with these concerns. For example, from the early adoption of generative AI, the bias in some algorithms has been documented, emphasizing the need to have human review to avoid discriminatory practices.

To guide your decisions and use, consider documenting your guiding principles when it comes to using generative AI. These could include:

Regular audits and monitoring: Regular audits should be conducted to monitor the performance and behavior of AI systems. This oversight ensures that AI continues to operate within ethical and legal boundaries, and that any issues are identified and addressed promptly.

Accountability: Providing opportunities for feedback, including regular measurement of the tools you’ve adopted and asking employees to weigh in.

Transparency: Sharing with customers and employees how AI is used at the agency can provide reassurance about the integrity of the technology, and convey its benefits.

By considering implementing these best practices, insurance professionals can harness the power of AI while maintaining the trust of their clients and meeting the high standards the industry demands.

At Nationwide, we’ve created an enterprise-wide steering committee to help guide our ethical practical uses of generative AI.

“Additionally, we have what we’re calling a Blue/Red Team risk approach. Our “Blue Team” explores how we can use this technology to benefit Nationwide, the ways we can harness its power to help our associates be most productive, provide better customer service to our members and uncover new uses cases to support our business. Our “Red Team” anticipates the risks and vulnerabilities of this technology. They consider issues like cybercriminals misusing the technology, unethical use for malicious purposes, and how to prevent bias from affecting decisions or work driven by the technology.”

-Jim Fowler, Nationwide’s Chief Technology Officer