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Across CX operations, enterprises are facing a familiar set of challenges, including rising service expectations and increasingly complex interactions. And now, the question of how humans and AI can work together to deliver smarter, faster, and more trusted support also takes center stage. For Assurant, the answer wasn’t a quick fix or a point solution. It was a strategic shift—rethinking how AI could enhance both the customer journey and the agent experience in tandem.
That mindset has guided their multi-year journey with generative AI.
In a recent webinar hosted by ASAPP, Chris Arnold (VP of Customer Experience Strategy at ASAPP) sat down with Nikki Schmidt (Director of Technology Services) and James Dill (Digital & AI Transformation Specialist) from Assurant to explore how the company is applying generative AI across its CX operations—and moving toward agentic AI. Their conversation touched on data and organizational readiness, how to identify high-impact use cases, and why human-in-the-loop design is key to building trust and delivering results.
Read on for highlights from the webinar, or watch the full conversation below.
Starting with strategy
Assurant’s journey began like many enterprises: legacy systems, customer data in silos, and a growing desire to improve both the customer and agent experience. Nikki, who started her career as a contact center agent, described how their thinking evolved—from evaluating “just another chat solution” to investing in a more intelligent, scalable approach to customer engagement.
When Assurant began looking for an AI partner, they weren’t just shopping for features. They needed a partner that could keep pace with their strategy, flex across multiple business lines, and offer deep expertise in contact center operations. ASAPP stood out for its ability to embed AI capabilities across the entire customer journey—not just for customer-facing interactions, but for the agent experience and backend systems as well.
Just as important is that the relationship didn’t end at implementation. “ASAPP’s there every step of the way,” said James. “It’s not just holding our hand. It’s getting us to the finish line and then staying with us.”
Realizing the ROI of AI
Both Nikki and James emphasized that the driver for AI wasn’t just cost efficiency. It was about agent empowerment and experience quality. By using ASAPP’s tools, Assurant improved self-service, reduced customer friction, and gained actionable insights to refine their workflows.
“We’re able to be proactive, not reactive,” James shared. “And, we've been able to leverage it not only to increase our customer experience, but also improve our employee experiences because when customers ultimately get to our agents, they know what the problem that they're trying to solve is.”
The rise of agentic AI
As generative AI continues to advance, it’s becoming capable of managing the kind of complexity that once required multiple agents, systems, and handoffs. “Agentic AI, provided it has the proper documentation and APIs to answer customer questions—the capabilities are really endless,” James explained. For Assurant, this evolution isn’t just about operational efficiency, but about meeting rising expectations for fast, seamless support. “Our objective at the end of the day is always a seamless customer and employee experience,” James said.
That means the significant potential to reduce friction wherever possible. “You talk about an interaction that might entail three different departments today—transferring a call three times after you spend a couple minutes in the IVR,” he added. “You go from a 20-minute interaction to a five-minute interaction with an AI agent.” With the move toward agentic AI, Assurant is increasing its rate of first-touch resolution—eliminating unnecessary steps, speeding up service, and delivering a better experience for customers and employees alike.
Human in the loop and human-AI collaboration
One major theme throughout the discussion was the importance of human-AI collaboration when it comes to agentic AI. Rather than treating a generative AI agent as a support tool or a replacement, Assurant focuses on designing systems where the two work in concert. GenerativeAgentⓇ handles routine queries and surfaces answers, while humans supervise, validate, and intervene when needed.
“Our focus is starting to become more on top engineering, human in the loop—how the technology and the people can work best together,” Nikki said. “It’s not about people or process. It’s about the right hybrid of both.”
One piece of advice Nikki shared for those early in their generative AI journey: “Bring your people with you.” “Your agents are a wealth of information. Your business partners are a wealth of information. Nobody does not have value in this discussion, and especially those who are on the front lines of your systems, your day-to-day.”
Starting small and scaling smart
When it came to selecting initial use cases, Assurant prioritized queries with high volume and clear resolution paths. Think contract FAQs, explaining terms and conditions, or claim status checks. These scenarios allow GenerativeAgent to shine while still offering a seamless handoff to a human when nuance or compliance calls for it.
James emphasized the importance of being intentional when choosing use cases. “It’s about identifying the 80% of interactions that could be addressed via the GenerativeAgent…and we’ve also considered those instances where the GenerativeAgent can help you get 90% of the way there, but a human still needs to make the final decisions about if that’s the appropriate answer to tell a customer. ”
What’s next: Voice, chat, and a unified AI experience
As Assurant looks ahead, the focus is on building intelligence that works consistently across channels—not just for customers, but for the agents who support them.
“Customers really are gonna choose whatever channel works best for them. So how do we meet their expectations there and make it a seamless experience?” Nikki said. That includes ensuring that AI can deliver the same level of support in a phone conversation as it does in a chat interaction.
“It’s hard to pick one or the other because we’re going to be focusing on both,” James added. “With ASAPP, you are able to build those GenerativeAgents, and they act the exact same in chat as they do in voice.” That flexibility is key to scaling AI effectively, while continuing to deliver personalized interactions and low-effort experiences at every touchpoint.
Takeaways for CX and Ops leaders
Here are the key takeaways from the conversation with James and Nikki.
- Data readiness matters. Clean, structured, accessible data sets the foundation.
- Human-in-the-loop is essential. Not just for safety, but for building trust.
- AI systems should evolve with your business. Look for a partner who stays engaged well beyond implementation.
- Start with high-impact use cases, but build for flexibility and growth.
- AI and people work better together. Design for collaboration, not replacement. Bring your people with you.
