The strongest use cases are rooted in participant experience, operational efficiency, and outcomes that can actually be measured
One of the biggest mistakes organizations make with AI is starting with the technology instead of the problem. The conversation often begins with questions like: “Where can we use AI?” or “What should we automate?”
I think the better question is: “Where are people struggling today?”
When evaluating AI opportunities, I look for three signals: First, the process creates significant operational cost. Second, it generates friction for customers or users. Third, the process depends on repetitive analysis or decision-making that can be improved through automation. When those three conditions exist together, AI can often be a powerful tool.
That’s exactly why Alegeus prioritized areas like claims adjudication and HSA onboarding.
Claims processing represents one of the largest operational challenges facing many benefits administrators. Teams are managing increasing claim volumes, more complex plan designs, and rising expectations for speed and accuracy. Participants want immediate answers, while administrators need confidence that decisions align with plan requirements. AI helps address both needs, but only because there was a clearly defined business problem to solve.
Just as importantly, we believe adoption should be flexible. Organizations aren’t all starting from the same place, and they shouldn’t be forced into the same AI journey. Some partners may begin with AI-assisted claim extraction to simplify submission and improve participant experiences. Others may choose to introduce automated eligibility determination, while maintaining human review for every approved claim. Still others may gradually expand automation as they build confidence in the results.
The goal isn’t to create an all-or-nothing decision. It’s to provide an easy path to adoption, giving partners the ability to choose where AI creates value, maintain control over the process, and evolve at a pace that works for their business.
The same is true for customer identification and verification. We observed thousands of support interactions tied to document verification workflows. Participants were abandoning the process. Operations teams were spending valuable time reviewing documentation manually. The opportunity wasn’t “let’s add AI.” The opportunity was reducing friction in a process that wasn’t serving anyone particularly well.
Importantly, not every problem requires full automation. Some of the most effective AI solutions augment human expertise rather than replace it. In our claims strategy, AI is designed to help determine eligibility and accelerate review, while administrators maintain control over approval thresholds, review percentages, and escalation paths. Humans remain in the loop because trust matters.
Organizations that see the greatest success with AI don’t chase every possible use case. They focus on a handful of meaningful problems, measure outcomes carefully, and expand from there.
AI isn’t the strategy. Solving customer and operational challenges is the strategy. AI is simply one of the tools that can help us get there.
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Arjun Srinivasan is the Chief Product Officer at Alegeus, leading the company’s Product Management organization to deliver product solutions that create compelling outcomes for Alegeus partners, their customers, and healthcare consumers. With more than 25 years of experience, Arjun brings a proven track record of building and scaling market-leading digital products.