Most organizations now have an AI strategy. Very few have a plan for the workforce that has to deliver it. We work on the layer in between: what the work actually becomes, what the roles become, and who owns getting there.
"What does your workforce need to look like in three years, and who owns getting you there?"
Most leaders answer the first half in detail. They can describe the tools, the pilots, the roadmap, the vendor decisions. The second half is usually where it goes quiet.
That silence is not a failure of leadership. It is a gap in the org chart. The technology strategy has an owner. The workforce consequences of that strategy do not. So the tools go in, the work quietly changes underneath them, and the roles, the levels, and the pay bands keep describing an organization that no longer exists.
An AI strategy converts into results only as deep as the lowest layer that has an owner. The organizations pulling ahead right now are not the ones with better tools. They are the ones who went below the first layer while everyone else was still buying.
Every engagement runs the same five moves. We call it FRAME. It scales from a three-week diagnostic to a full operating model redesign, and each move ends in a decision rather than a deck.
The work as it actually runs today. Workflows, systems, roles, decision points, and the outcomes leadership is genuinely measured on.
Every workflow scored for value at stake, repeatability, complexity, data readiness, and risk. Most should be left alone, and saying so is part of the work.
The redesigned human and agent workflow, with decision rights named, data requirements specified, and success agreed before anything is built.
Adoption designed rather than hoped for. Oversight model, escalation paths, change leadership, and a named owner at every handoff.
Business outcomes, not usage statistics. Learning loops, and explicit criteria for what earns the right to scale and what does not.
Most teams start with the diagnostic. It is deliberately small, and it is designed so that the decision about what comes next is obvious by the end of it.
Where your AI strategy stops converting, and what it will take to go deeper. Run against the five layers with your executive team.
Take two or three high-value workflows and rebuild them for human and agent collaboration, with the role and governance consequences designed in rather than discovered later.
The three-year workforce blueprint. What the organization needs to look like, and the sequence and governance that gets it there without breaking trust on the way.
Engagements are fixed scope and fixed fee. Pricing follows the shape of the problem rather than an hourly rate, and you will have a number before you commit to anything.
Human architecture is the design of how people, roles, and organizations are structured to do work that AI has changed. It is a discipline, not a project, which is why it is built to be taught as well as delivered.
Advisory engagements with executive teams. Diagnosis, redesign, and scale-up, delivered directly.
The five-layer framework used in every engagement. Published openly, because the value is in the redesign, not in withholding the map.
A practitioner program for internal leaders and independent advisors who want to run the method inside their own organizations. Registration opening in due course.
For fifteen years I built and led people functions at an elite academic institution, which meant owning the unglamorous machinery most AI conversations never reach: job architecture, levels, compensation design, capability building, and the governance that keeps all of it defensible. I am a Certified Compensation Professional, which is a dull sentence describing the exact expertise that Layer 4 requires and that almost no AI advisor has.
Then I went and got fluent in the technology itself, because the advice being given to executives was being written by people who understood the models but not the org chart, or the org chart but not the models.
That combination is the whole offer. I am not here to explain what a large language model is, and I am not here to run a change management program around a decision someone else already made badly. I am here for the layer in between, where the work is redesigned and the organization has to actually become something different.
I wrote Know Your Worth, Get Your Worth: Salary Negotiation for Women, which was about the same underlying question this practice asks at organizational scale: what is this work actually worth, and who decides?
If the second half of it is harder to answer than the first, that is the conversation worth having. Thirty minutes, no pitch, and you will leave with a clearer read on where your own gap sits.