Key Takeaways

• Contested terrain is the map CHROs need right now: Prasad Setty defines contested terrain as the set of open questions about AI's future where credible experts hold divergent views. Understanding that landscape, rather than waiting for certainty, is what lets operating leaders act without paralysis.
• Practice leads theory in the AI era: Because AI in the workforce is moving faster than academic research can follow, the Valence Research Initiative prioritizes applied, lived lessons from real organizations over theory alone.
• Every AI interaction develops people or creates dependency: Setty argues that CHROs, CEOs, and the C-suite must intentionally design environments where AI contributes to individual development, since the alternative is dependency by default.
• AI adoption is a choice, not a foregone conclusion: Parker Mitchell notes that leaders choose the types and purposes of AI they bring into their companies. Asking "how can AI help us flourish?" leads further than asking "what is easiest to automate?"
• Power users of Nadia improved at every performance level: Early research codified Nadia usage into a power user index measuring frequency, regularity, diversity of requests, and cognitive engagement. Power users saw a lift regardless of where they started: lower performers moved toward the middle, middle performers became high performers, and top performers were more likely to stay at the top.

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Defining "Contested Terrain" in the Age of AI

[00:00:02] Parker: Prasad, I am so excited to kick off these conversations with you. We've been talking about this idea, a term of yours, called the contested terrain. And I just think it is a great concept for what CHROs are facing today in this age of AI. Maybe you could kick it off by sharing with our audience: what do you mean by the term contested terrain?

[00:00:25] Prasad: To me, contested terrain is all of those possibilities where different people who are thinking about the future unfolding in different ways have a wide variety of divergent opinions. That can be very paralyzing for people who are in operating roles and need to take action. What I was thinking we'd explore is: which of those divergent paths that different people are speculating about are the ones that we might want to take a bet on? And do we even understand that landscape, so that we don't feel like we know all the answers, but we do understand the terrain, and we know how to explore it?

What "Contested Terrain" Means for CHROs

"Contested terrain" describes the wide field of divergent, often conflicting predictions about how AI will reshape work. According to Prasad, chair of the Valence Research Initiative, the risk for leaders is paralysis: so many credible but competing views that operators freeze. The goal is not to predict the future perfectly but to understand the landscape well enough to explore it and place informed bets on which paths are worth pursuing.

Launching the Valence Research Initiative

[00:01:08] Parker: We are launching the Valence Research Initiative, and we are so proud to have you as the chair. Can you share a few words about why you think this is an exciting initiative at this moment in the conversation about AI in the workforce?

[00:01:23] Prasad: There are many questions that people are struggling with and thinking through. What I'm hoping the Research Initiative comes out with is good options and views on how to manage the chaos and the noise we see around us when it comes to AI in the workforce — to really tease out the signals, and to explore what is common ground and what is contested terrain. In this era, because things are moving so quickly, practice leads theory. So I'm looking for not just research in that sense, but research that is truly applied. It's truly lived lessons and learnings.

What the Valence Research Initiative Is

The Valence Research Initiative is an applied research program, chaired by Prasad, focused on AI in the workforce. Its purpose is to cut through the chaos and noise around AI at work and tease out reliable signals — distinguishing common ground from "contested terrain." Because the field moves so fast that practice leads theory, the initiative prioritizes applied, lived lessons from practitioners over purely academic research.

How CHROs Choose the Purpose of AI at Work

[00:02:07] Parker: AI will automate some parts of work, and the CEO and media narrative is around that. But we all have choices. As individuals, we have choices. CHROs have choices about the types and purposes of AI that we bring into our company. That is going to reflect both the priorities and the path. If we ask ourselves, "How can AI allow us to be the best versions of ourselves? How can we flourish as individuals and as collections of people?" we will make more progress down that path than if we just ask, "How can AI automate the parts of the job that are easiest to automate?"

How HR Leaders Should Decide Which AI to Adopt

HR leaders can choose the types and purposes of AI they bring into their organizations — and that choice shapes the outcome. Parker argues that leaders who start from "How can AI help our people be the best versions of themselves and flourish?" make more progress than those who only ask "What is easiest to automate?" The purpose behind adoption, not just the technology, determines the path an organization takes.

Development vs. Dependency: Designing AI Environments

[00:02:50] Prasad: I fully agree. Every AI interaction either leads to individual development or creates dependency. The more that we can be intentional as individuals — and the more we can rely on our organizations, and this is where the CHRO, the CEO, and the C-suite all come together — to intentionally design environments that contribute more to development rather than dependency, then we all win. That's exactly the future I'm hoping for.

Does AI in the Workforce Develop People or Create Dependency?

Every AI interaction either develops the individual or creates dependency, according to Prasad. The outcome is a design choice, not a given. When organizations — with the CHRO, CEO, and C-suite aligned — intentionally build environments that favor development over dependency, both the employee and the company benefit. This framing positions AI coaching as additive to human capability rather than a crutch that erodes it.

Early Research: Power Users of Nadia and Performance

[00:03:25] Parker: One of the reasons we're launching the Valence Research Initiative is not just to explore concepts like the future of work or the future of the organization, but really the support of the individual. You've been leading research with some of our partners. What are some of the early indicators around Nadia adoption and its impact?

[00:03:47] Prasad: Behavior with Nadia was codified into a power user index that took into account not just the frequency but the regularity of the interactions, whether people came to Nadia with diverse requests and questions, and also the cognitive engagement. All of that was codified into a power index. What we found was very compelling: wherever you were in your prior performance curve, once you became a power user of Nadia — compared to those who were not — you saw a lift. The lowest level of performance had a much higher propensity, much higher odds, of getting to be more in the middle range of performance. Those in the middle range tended to become high performers. And the highest performers in their distribution obviously couldn't go any higher than their highest category, but we could see that the highest performers stayed high performers, more so if they were power users of Nadia.

Does AI Coaching Improve Employee Performance?

Early Valence research indicates that becoming a power user of the AI coach Nadia is associated with measurable performance gains at every level. Prasad reports that lower performers had much higher odds of moving into the middle range, mid-range performers tended to move into the high range, and top performers were more likely to stay top performers. The effect held regardless of where an employee started on their prior performance curve.

What Makes Someone a "Power User" of an AI Coach?

Valence defines a power user of Nadia using a "power user index" that goes beyond raw usage. According to Prasad, the index captures the frequency of interactions, the regularity of those interactions, the diversity of the requests and questions a person brings, and their cognitive engagement. In Valence's early research, employees scoring high on this index saw the strongest performance lifts.

Why Practice Leads Theory in the Age of AI

[00:04:56] Parker: I had not heard that expression before — "practice leads theory." But in this era it is more true than ever, because collectively we're on this journey. The community we're going to bring together as part of the Valence Research Initiative, and the conversations across it, are going to be part of the richest benefit. I am so lucky to get to have these conversations with you. This is the first of many. I'm so lucky we're going to be able to bring other thinkers, practitioners, and trailblazers into this conversation. Thank you for kicking this off today with me, Prasad.

Why "Practice Leads Theory" With AI at Work

In fast-moving fields like AI in the workforce, practice leads theory — meaning real-world experimentation by operators produces usable lessons faster than formal research can. Parker and Prasad frame the Valence Research Initiative around this idea, convening practitioners, thinkers, and trailblazers so that lived, applied learnings become the primary source of signal for HR and business leaders.