Human Institutional Memory in the AI Era — And Why It Matters

After sixteen years at a company with a multibillion‑dollar market cap, I’ve realized that one of the most valuable things I bring isn’t just experience — it’s institutional memory.

Over the years, I’ve watched leadership transitions unfold: three CEOs, four CFOs, five CHROs, and seven CDIOs. Each brought something different, and being here through those changes has helped me understand how decisions evolve, how priorities shift, and how to keep teams grounded through it all.

I’ve listened to countless earnings calls, read annual reports, and followed analysts who were genuinely curious and occasionally skeptical about our direction. Those moments helped me build a deep understanding of how external expectations connect to internal strategy — and how that connection can sometimes create pressure. I’ve also seen how capital‑allocation decisions play out over time — including the recurring “one‑off” costs that quietly tell their own story. And I’ve lived through cycles of decentralization, centralization, cost discipline, and investment.

Inside the company, I’ve seen vendor selections, training programs, and new initiatives come and go. Some were transformative, some were experiments, and all of them taught me something. I’ve watched our mission and values grow in thoughtful, intentional ways, and I’ve learned how those shifts show up in day‑to‑day work. Aligning with them has helped empower me and focus on the changes I needed to make together with others.

Not all aspects of institutional knowledge are positive. When institutions become complex — sometimes unnecessarily so — that knowledge can turn into something exclusive rather than shared. Complexity can create barriers, slow down progress, and make it harder for new voices to contribute. I’ve seen how institutional knowledge can be sustained by increasing complexity, often unintentionally keeping outsiders at a distance.

That’s why I was genuinely encouraged when our recent CEO emphasized simplification. It felt like a meaningful step toward greater clarity and accessibility. And while I’ve also seen how deeply rooted systems can resist simplicity, the very act of naming it as a priority matters. It opens the door for change, even if the path forward isn’t always straightforward. These patterns aren’t just history to me; they’re context I use to navigate what’s happening now.

So when I recently compared this long arc of experience with AI’s processing power, I expected AI to have the advantage in recall. But AI couldn’t even retrieve the names of our past CDIOs from the public internet. That moment reminded me of something important: institutional memory isn’t always written down — but it’s incredibly valuable.

It helps teams avoid repeating old mistakes, recognize when a “new idea” is actually a familiar one, and understand why certain decisions were made in the first place. It creates continuity. It builds trust. And it supports better, more informed choices.

That’s the perspective I bring — a long‑view understanding of how we got here, what we’ve tried, what worked, what didn’t, and what we learned along the way.