What Are We Building?
Carolyn Buck Luce, Ellen McGirt, and Jennie Glazer on people, power, AI, and the choices shaping the next workplace
As the Center for Talent Innovation enters its next chapter, we invited co-founder and board chair Carolyn Buck Luce, board member Ellen McGirt, and board member & CEO Jennie Glazer to contemplate a shared set of questions: What have we learned about people and organizations? What remains unfinished? And what do those lessons demand as work changes again?
Their reflections were gathered separately and edited and sequenced here as a roundtable conversation to let three distinct vantage points challenge and extend one another.
What did we actually learn?
CAROLYN: The work has always been about the dominant enterprise conditions.
We looked at the people with the greatest differences from the dominant culture because their experiences were signals. They helped us see something larger about the organization.
Was it our systems? Was it middle management? Was it how we measured talent? Was it what we reinforced about what leaders look like, act like, behave like?
The question was: What is it that we haven’t yet addressed?
You don’t solve only for the particular symptom. You solve for the dominant conditions because everyone will benefit.
And underneath all of that was a very simple idea. Equal opportunity does not mean everyone is the same. The goal is for people to have an equal opportunity to work at the level of their skills, ambitions, talents and dreams.
ELLEN: I would argue that the project of DEI was, in many ways, a cake that was taken out of the oven before it was baked.
What was beginning to emerge was something much bigger than a collection of programs. It was a deeper understanding of the connection between people, perspective and how organizations perform. Underneath that was something even bigger: human transformation.
Great leadership happens every day in the conversations we have with other people. That’s where innovation lives. That’s where problems and opportunities surface.
And there are only so many efficiencies you can bring into a workplace before you start taking away something important about being human.
JENNIE: That is the part I don’t want us to lose as the conversation moves toward AI.
We spent decades learning that systems aren’t neutral. The last thing we should do now is encode the same blind spots into the next generation of them.
The questions we’ve spent years asking still matter: Who gets heard? Who gets access? Who gets the opportunity? Who experiences the system differently? Where is bias hiding?
Those are now AI questions. They’re organizational design questions. They’re talent questions.
What is actually new?
ELLEN: AI is obviously new. But I worry about getting mesmerized by the technology.
The pressure to move quickly is enormous. And chances are, organizations are going to invest in some of the wrong things.
So get very good at imagineering. Understand the difference between a forecast and a scenario. Bring together people with genuinely different perspectives and imagine several futures.
Where could this technology help? Where could we make expensive mistakes? What might the human costs be? What are we not seeing?
Business likes to know where it is going before it sets out. Imagination asks you to relinquish some of that control.
Fine. Call it scenario planning if that makes it sound more official.
But make it a practice.
CAROLYN: That is where the bridge matters.
We have a whole set of best practices we’ve learned. We also have a responsibility to build next practices.
You can’t just jump the timeline. You have to understand what the earlier work taught us and then ask: What’s still true? What is genuinely new? And what bridge do we need to build between the two?
“What’s still true” can’t mean the way we did it. It has to mean the essential issues.
The work now is building that bridge into next practices.
What are our decisions around AI actually building?
JENNIE: We spend an enormous amount of time asking, “What can AI do?”
I think we are underasking: What are our decisions around AI building?
Organizations rarely announce, “Today we’re going to redesign our entire talent system.”
Instead, we automate this task. We flatten this layer. We rewrite this job. We change this promotion process.
Each decision can look perfectly reasonable on its own.
Then you zoom out and realize you’ve changed how people learn, who gets visibility, who gets sponsored, where judgment gets built and what the leadership pipeline looks like.
Organizations are being redesigned one “reasonable” decision at a time.
Take entry-level work. If AI takes the work that used to teach you how to work, where does the learning happen?
If teams get flatter, where do future managers learn to manage?
If the career ladder becomes a jungle gym, who gets access to the moves that actually build a career?
And one I’m slightly obsessed with: What happens when the people who used to sponsor you leave, reorganize, or disappear in another transformation?
Those are second-order effects. Nobody necessarily chose them. But somebody has to be looking for them.
CAROLYN: And that’s where the old learning becomes useful.
The differences are signals.
Don’t just ask what happened. Ask: How did we create the conditions in which it happened?
Was it the system? Was it the manager? Was it how talent was evaluated? Was it what the organization rewarded?
The technology changes. The discipline of asking what haven’t we yet addressed? still matters.
What are we in danger of optimizing away?
JENNIE: Judgment is the capability I worry about most.
Judgment is annoyingly inefficient to build.
It comes from doing things. Getting things wrong. Watching someone more experienced. Asking dumb questions. Seeing consequences. Trying again.
There is no elegant shortcut.
If we automate away every messy learning experience, we may wake up with very efficient organizations and a thinner bench of people who know what to do when the situation stops looking like the playbook.
Efficiency is seductive because you can put it in a spreadsheet. What is much harder to count is the learning that disappears with the task.
ELLEN: And that’s why I think we need to broaden what we mean by innovation.
When people hear “innovation” right now, they understandably think technology.
I hear something else, too.
The workplace is one of the places where we spend most of our lives. It can be a place where people continue to learn and grow—to become the next best version of themselves.
Leaning into the innovation piece of what it means to be human at work is the brightest hope I see for a world that works for everyone.
The human part isn’t sitting beside the transformation.
It is the transformation.
Can you prepare for a future you can’t predict?
ELLEN: I think we have to become much more comfortable with imagination.
If you work on a future problem with a sense of cautious adventure, it brings you into proximity with people who are different from you.
Even if you don’t come up with the answer, it changes your experience. You begin to understand what animates people, what frightens them, what challenges them.
The process by which you develop the playbook has to be different now.
The lifespan of the playbook has to be different now.
JENNIE: My father worked at NASA, and at one point his job was connected to the manned mission to Mars in the '90s.
I remember asking him: How do you manage a project when the technology you need to complete it doesn’t even exist yet?
His answer was basically: You figure out what has to become possible.
I think about that all the time.
I’m deeply suspicious of anyone who tells me they know exactly what jobs will look like ten years from now.
Prediction isn’t the job. Preparation is.
Can your people learn? Can they question? Can they collaborate across difference? Can they use technology well? Can they make a judgment call without waiting for a perfect answer?
Can your organization see what is happening early enough to adapt?
CAROLYN: And that brings us back to the bridge.
We know things now that we didn’t know thirty years ago about systems, opportunity, difference and the conditions organizations create for people.
We shouldn’t leave those lessons behind.
But we also can’t mistake what we did before for what we need to do next.
We have to discern what is essential, understand what is new, and build the bridge between them.
That is how you get to next practices.
JENNIE: The question I hear constantly is: “What jobs will AI replace?”
I would ask a different one:
What kind of organization are our AI decisions creating?
What happens to learning? What happens to judgment? Who gets opportunity? Who gets left out? Where does bias show up? What happens to managers? What happens to careers?
And do we actually like the organization we are building?
Because organizations are already being redesigned—one reasonable decision at a time.
The harder question is: