By focusing at the strategy level, carriers and brokers can optimize AI beyond efficiency enhancements or cost reduction objectives. At Securian, initial AI integrations have been applied across underwriting, enrollment, claims processing and customer service.

“Thinking about the customer journey as a whole helps us see that AI isn’t something you just bolt onto an existing process,” explains Aaron Reihl, AI Senior Product Consultant at Securian. “AI has ripple effects throughout an entire workflow. That means being upfront about our objectives and impacts during the discovery and information-gathering phases.”

Approaching AI as a component of larger strategies that span the entire customer journey has enabled Securian to effectively integrate AI where it’s most impactful, including:
◆ Capabilities that significantly streamline request for proposal (RFP) responses and underwriting processes by sorting, extracting, and organizing data and requirements support quicker responses to the market. Digital assistants that help customers explore their coverage options and provide personalized decision support, enabling confident benefit elections.
◆ Intelligent document processing that normalizes scanned information to expedite claims processing and improve accuracy while keeping a human in the loop.
◆ Advanced customer sentiment analysis that proactively identifies opportunities for service enhancements or detects fraud.

Deploying AI responsibly

Implementing AI requires careful attention to ethical and regulatory considerations, particularly around data privacy, decision transparency and bias mitigation. The rapid evolution of AI capabilities can create uncertainty and reservations about how AI is used and the safeguards in place.

Today, many insurance regulators focus on the use of AI in three primary areas:
◆ Underwriting processes
◆ Claims decisions
◆ Hyper-personalized marketing 

To address these concerns, carriers and brokerage firms must establish rigorous governance practices to evaluate, implement and monitor AI, whether it’s developed in-house or by a third party.

“For us, we have an AI governance process that involves folks from our technology, product, compliance and legal teams,” Gandhi says. “Every AI use case goes through the process, giving us a 360-degree view from expert perspectives. Before we put anything into place, we have examined the risk and thought through the mitigation.”

AI governance best practices

Having a robust governance process is critical for AI optimization. Gandhi and Reihl recommend three key elements for effective governance.

1. Humans in the loop: Ensure that humans engage throughout the entire life cycle of AI deployment, from vetting tools upfront to engagement and monitoring once the project is deployed. When it comes to decision-making, AI can provide support, but human experts should have oversight and make final decisions.

2. Cross-functional involvement: Effective AI governance requires input from IT, legal, compliance, data science and product teams to ensure all perspectives – and potential risks – are considered.

3. Workforce education: Responsible use of AI requires the engagement and understanding of the entire workforce. Committing to ongoing training to keep associates up to speed on the rapidly evolving technology and how it might impact them, like the recent emergence of Agentic AI, is critical.

As AI continues to transform employee benefits processes and customer experiences, optimizing the technology hinges on the carriers’ and brokers’ ability to balance strategic implementation with responsible use and governance.

Securian is in the news leveraging AI with their medical claims integration partnership: Securian Financial and Reclaim Health Join Forces on AI-Powered Claims Analytics | Securian Financial

Ann Clifford is a freelance writer who translates her background in financial services marketing into specialized content focused on employee benefits and small business topics.