I grew up on my grandfather’s farm in a small town called Molo, Kenya. Every day started before sunrise. There were chores in the morning and more waiting when I got home from school.
Homework came last, which meant that by the time I sat down to study, I was often exhausted. Most days, I went to school feeling unprepared. But for some reason, math came easy. Even without studying, I could see the logic. It just made sense.
That’s where it started, this deep connection to numbers, problem-solving, and precision.
Years later, while studying at Georgia State University, I went to the dean for guidance on what I should major in. I remember saying something like, “I love math, and I want to work in business. Is that possible?”
He asked me a question about derivatives. I answered it. Then he said, “Then you could major in actuarial science…”
I had no idea what that meant, but I said yes.
My first job was at Deloitte, working on pension valuations, figuring out how much companies needed to set aside for their employees’ retirement. That’s where I learned the power of accuracy. One small mistake could ripple across millions of dollars. It shaped how I think: verify the data, understand the formula, and never assume.
Over time, I moved from pensions to health and welfare plan design, and eventually into HR technology, helping organizations connect their benefits strategy, HR operations, and technology systems.
Lately, I keep coming back to one question:
With all the progress we’ve made in HR tech, why does benefits still feel behind, especially when it comes to AI?
I started wondering what it would look like to unpack how benefits came about – the stakeholders, the regulations, and the dependencies – and explore how AI could actually fit in. Where might small wins start to show up? What would it take to make real change?
That’s what this new series, Benefits × AI: Solving for the Human Variable, is about. Each week, I’ll unpack how benefits got here, why it’s so complex, and what it would take for AI to finally make an impact.
I’d love for you to join me — to share your experiences, your insights, and your ideas — as we explore this together.
Next up: Why Is AI Lagging in Benefits?
Question for you: What early experiences shaped how you think about precision, systems, or data?
