Why I built
JR Key Advisory.

The gap between mandate and progress.

As AI has become a strategic priority, I’ve watched familiar organizational patterns emerge with new urgency. Mandates without strategy. Strategy without alignment. Alignment without ownership. Pilots that succeed technically but fail to create meaningful business value. Organizations treating AI as primarily a technology initiative when it is equally a leadership, workflow, and organizational challenge.

Those patterns aren’t unique to AI. They’re the same challenges I’ve encountered throughout my career helping organizations navigate change at the intersection of technology, products, and the people who use them. AI has simply made them more visible—and more consequential.

At McKesson, I led the research and design behind a pharmacy intelligence product that contributed to approximately $97 million in first-year savings across 85 customer organizations. At Fisher Investments, I helped design concepts for integrating AI services into internal products. More recently, I presented to more than 140 members of Exiger’s staff on the uniquely human advantage in the age of AI—why judgment, collaboration, and shared understanding become more valuable, not less, as AI becomes embedded in everyday work.

The throughline was never the technology. It was the people doing the work, the customers they served, and the context in which both had to succeed.

That’s why I founded JR Key Advisory.

Technology moves faster than strategic clarity, organizational alignment, and shared ownership. Agents amplify whatever direction they’re given. When that direction is fragmented, AI scales fragmentation. When leadership establishes a clear, owned strategic mandate, AI can scale meaningful business progress.

JR Key Advisory exists because closing the gap between AI mandate and AI progress requires strategic and organizational work, not just technical implementation.

Why this work fits my background.

I’ve worked in environments where technology decisions had to account for real business constraints, complex stakeholders, regulated contexts, and the way people actually do their work.

That includes experience across training, software development, UX program leadership, product strategy, and cross-functional facilitation. Across roles, my work has often been to enter complex environments, understand the context quickly, and help teams create practical clarity. A development background also lets me speak fluently with technical teams: I know what’s actually possible, what’s genuinely hard, and what’s vendor positioning.

AI strategy now requires that same combination: business judgment, human-centered understanding, technology fluency, and disciplined facilitation.

What I believe about AI progress.

I measure AI progress by whether it helps the business become more effective: better decisions, stronger workflows, increased capacity, improved customer value, and more useful work for the people inside the organization.

It’s less about doing the same work with fewer people and more about how we expand and grow with the people we have.

That is why my work starts with leadership decisions before implementation. The goal is to clarify where AI belongs, what is worth investing in, and what evidence should guide the next step.