Ever thought you understood the terrain and then realized you were stepping into something completely new?
That’s exactly how I felt in this photo at Lake Naivasha, Kenya, headed on a walking safari – something I’d never even heard of. Funny how that same feeling shows up in work, too.
I’ve been thinking a lot about why AI seems to be moving faster in every other area of HR except benefits.
We’ve seen real progress in recruiting, learning, and performance, but benefits technology still feels stuck. And that made me want to dig deeper in this series.
Benefits is inherently complex. Stakeholders include insurance carriers, consultants, employees, healthcare providers, pharmacy benefit managers, and claims administrators. The list honestly goes on and on. It’s also highly regulated. It touches HIPAA laws that protect participant privacy, enrollment file formats that are government-mandated, and annual filing requirements. And it’s deeply personal. All these things make benefits tech complex, and innovation that much more difficult.
But I think there’s another thing that makes benefits tech especially challenging.
When I transitioned from benefits plan design to administration, I started noticing a pattern: systems kept breaking. Something would work fine one day and be broken the next. Each time, the tech team would dig into the code to troubleshoot. But my first question was always, “Where’s the plan document?”
Because to me, you can’t fix what you don’t understand. The system can only do what it was configured to do — but the plan document tells you what it was actually intended to do. Unless you understand that intent, you’re just fixing symptoms, not causes.
That’s when I realized the disconnect. The people configuring benefits systems are brilliant engineers and data scientists, but they’re not always benefits experts. And that’s not a criticism or a fault – it’s just how this space works. Two different skill sets that have to work in sync.
So maybe the gap in benefits tech innovation isn’t just technical. It’s contextual.
This series will explore how benefits evolved, why it’s so complex, and what it would take for AI to truly make an impact.
My hope is that this becomes a conversation. I don’t have all the answers, but maybe together we can start asking the right questions.
A Couple of Questions For You:
Have you ever had a light bulb moment where you realized something wasn’t what you thought it was (personally or professionally)?
Do you think it’s possible to bridge these two distinct domains, or will they always need to collaborate separately?
Next Up: Where It All Began – how history still shapes the systems we use today.
