Stephen Koepp introduced a session on leading transformation in 2026, focusing on Pacesetters’ change agility. Rebecca Warren and Kathi Enderes discussed the shift from individual productivity to system-level transformation, emphasizing the concept of “Super-Organizations.” They highlighted the importance of using AI tools not just for cost-cutting but for growth and organizational performance. Kathi introduced the AI maturity journey, from individual productivity tools to cross-functional AI agents. They also discussed talent density, focusing on capability over headcount, and the need for agile change management. The session concluded with advice for leaders to treat AI transformation as a people and culture transformation.

Leading the next Wave of transformation: Introduction and context

• Stephen Koepp introduces the session titled “Leading the Next Wave of Transformation: How Pacesetters Will Win in 2026.”
• The session aims to explore how Pacesetter organizations are creating a culture of change agility.
• Rebecca Warren and Kathi Enderes are introduced as the session leaders, with Rebecca emphasizing the shift from individual productivity to system-level transformation.
• Kathi Enderes explains the concept of “Superworkers” and “Super-Organizations,” emphasizing the use of AI tools for people empowerment rather than cost-cutting.

Understanding Superworkers and Super-Organizations

• Kathi Enderes defines “Superworkers” as employees who use AI tools to enhance productivity and performance.
• The concept of “Super-Organizations” is introduced, where AI tools are integrated into every job, not just HR.
• Pacesetters are identified as companies with the best financial performance, customer delight, great workplaces, innovation, and faster innovation.
• The focus is on using AI tools as organizational amplifiers rather than individual productivity tools.

AI maturity journey and super agents

• Kathi Enderes outlines the AI maturity journey, starting with individual productivity tools and moving to cross-functional AI agents.
• An example of a claims agent at Allianz is provided, illustrating how AI can automate entire business processes.
• The impact of AI on job roles and organizational performance is discussed, emphasizing the creation of new value for customers.
• Rebecca Warren highlights the importance of innovation across the entire organization and the visibility of work being done.

Talent density and changing hiring strategies

• Rebecca Warren and Kathi Enderes discuss the concept of talent density, focusing on capability rather than headcount.
• The “4R framework” is introduced, which includes recruit, retain, re-skill, and redesign strategies.
• The importance of retaining existing talent and re-skilling employees with adjacent skills is emphasized.
• The discussion includes examples of how companies like Panasonic and Netflix approach talent density and team fit.

Agility and change management

• Rebecca Warren and Kathi Enderes discuss the shift from traditional change management to agility.
• The concept of “change ability” is introduced, emphasizing the need for bottom-up, continuous improvement.
• The role of leaders is redefined as “learn it all,” focusing on bringing together the smartest people for the best outcomes.
• The importance of curiosity and collaboration with AI is highlighted, ensuring humans remain in the lead.

Practical steps for Pacesetter trajectory

• Rebecca Warren asks Kathi Enderes what action leaders should take to get onto the Pacesetter trajectory.
• Kathi Enderes advises treating AI transformation as a people and culture transformation rather than a tech project.
• The importance of benchmarking against Pacesetter practices and starting with a specific problem is emphasized.
• The session concludes with a focus on amplifying potential, flexibility, and agility, encouraging continuous learning and iteration.

Stephen Koepp 00:24 Okay, well, our next session coming up right now is a thought leadership spotlight. It’s titled, “Leading the Next Wave of Transformation: How Pacesetters Will Win in 2026.” So here’s the question: How do you build a business that thrives on change? While many companies still rely on top-down change management for every new technology, a select group of Pacesetter organizations are creating a culture of change agility—an operating model that adapts in real-time. Drawing on insights from The Josh Bersin Company’s “Pacesetters in the Superworker Era” report, this session explores what comes next. We’ll examine how the six secrets of Pacesetters are evolving from best practices into business imperatives that define high performance in 2026. Leading this session will be Rebecca Warren, Director of Talent-Centered Transformation at Eightfold AI, and Kathi Enderes, the SVP and Global Industry Analyst at The Josh Bersin Company. Rebecca, Kathi, welcome back. You always have fresh data and insights, so it’s great to hear what you have to say, and I will turn it over to you.

Rebecca Warren 01:35 All right. Excited to be here. Kathi, good to see you again. Always learning new things each time. So today—and I know we don’t have a ton of time, so I’m going to try to jump right in—we’re going to talk about some super stuff today, right? We’re going to be super. So I love talking with you about the Superworker, right? What does that mean to elevate that role? But we now are starting to think about the Super-Organization, so I want to dig into that. And how are we thinking about our Pacesetters moving from individual productivity into now system-level transformation or disruption? Let’s talk a little bit about that switch from individual to the organization.

Kathi Enderes 02:26 Sure. Well, first I want to decompose all of these buzzwords. We’re talking about Superworkers. We’re talking about Super-Organizations. We’re talking about Pacesetters. So what do we mean by that? Just really quickly, because I know not everybody is maybe familiar with that. So Superworkers is something actually very positive that we coined, that we’ve been talking about all year long with organizations and with our clients. It’s how you’re using the AI tools, not just as a technical tool, but really as a people empowerment tool—not just as a cost-cutting tool. So rather than thinking about “how can we do more with less”—which, I kind of hate that notion; why would we want to do more with less?—how can we work less and maybe accomplish more? And that’s kind of flipping that switch or flipping the coin here, thinking about that. And so using AI tools to elevate every employee’s productivity and performance helps them do much more meaningful work. How can we think about that? So that’s the Superworker.

Super-Organizations, we think, is the next stage. Because as we’re thinking about how do we put these AI tools to work in every job—not just in HR, but in every job, in sales and marketing and in software engineering—how can we as an organization capture those productivity and performance impacts company-wide? So that’s the organization, right? So that’s what we’re thinking about in the Super-Organization.

And Pacesetters are those companies that we identified who are leading the industry. It’s the five to 10% of companies that are having the best financial performance. They also delight their customers constantly. They are great places to work. They are leading on people innovation, people practices, and they’re also innovating much faster. So the question that we’ve tried to approach is: how do these Pacesetters turn the AI tools not just into individual performance tools or productivity tools, but organizational amplifiers? So that’s kind of what we mean by the Super-Organization.

And these Pacesetters do things completely differently. The first one has to do with shifting that mindset from using AI as a tool for cost control, for cutting, for having less basically and doing “more with less,” to how can we actually accomplish more? How can we use AI as a tool for growth, organizational performance, and creating new value?

Most companies are kind of stuck in the lower two levels of our AI maturity journey. I’ll go through that model just really quickly to explain. That first stage is basically using AI tools as assistants. So you use it individually for your job, basically to write better emails, get better meeting notes, all of those kind of things—individual performance tools, productivity tools. Really good. We’ve done this for the last three years, right? But not that transformative for the company.

The second stage is when you use AI agents that actually automate some specific tasks that you’re doing. So if you’re, for example, a marketing person, maybe it’s going to help you write better campaigns or something like that. Or if you’re a recruiter, maybe it’s going to help you automate the interview scheduling process. Helps you be more productive as an individual, but still doesn’t change your role, doesn’t take the company that much forward.

And then there’s a huge shift to where you’re thinking about, as an organization, how can we string all of these individual productivity tools and agents together in order to have kind of cross-functional agents, or what we call the “Super Agents.”

Rebecca Warren 07:30 Another super!

Kathi Enderes 07:32 Another super, exactly, and it’s going to be a super-powered time for us. But these Super Agents basically do things for the organization. So they do an entire workflow, they’re doing an entire process, and then basically everything changes, because then you really get fundamentally different outcomes in HR, but in other processes too.

For example, one agent I always like to talk about is a claims agent at Allianz, the German insurance company. Very large German insurance company, global company. They have a claims agent where, basically, you as a customer can take a picture and then you submit it, and then in the background it kicks off all the claims—categorizing, processing, saying if it fits neatly into one area, or if it needs to be escalated. Maybe it’s just somebody who assesses all of those kind of things. I’m not an insurance expert, of course, I don’t know exactly what happens, but basically, it helps with the entire business process end-to-end.

But then we have to think about, what does it mean for the people that used to process the claims, that touch those claims? If somebody gets escalated, how does it change their jobs? How does it actually not just make things faster, but create entirely new value for the customer? Because maybe they get not just faster answers, but better answers, the right outcomes, all of that. So that’s what we mean by thinking about not just for individuals, for Superworkers, but really for Super-Organizations.

Rebecca Warren 08:09 Yeah, I love that, because you’re thinking about innovation not just happening with people, but it’s across the entire org, and there’s more visibility then to who’s doing what and how it’s all happening. And when we think about those agents getting work done behind the scenes—and I took that note on what you said there about “work less and do more,” I like that idea. Let’s not get more with less; let’s work less and do more. I love that because all of that work can happen potentially simultaneously, whereas before, maybe it was in a very isolated project, right? This step has to go, then this step has to go. So, exactly broader work getting done, more visibility across the organization, and really evolving, I think, more towards that broader business strategy, instead of thinking about individual talent strategies or departmental strategies.

Kathi Enderes 09:02 Totally, totally. And starting with the outcome, right? Because when you’re thinking about activities, then you’re not really thinking, “maybe we don’t need any of these.” Some of these activities you might not need anymore. And for example, when you think about using AI in the recruiting process—because I know many of you might be thinking about that—well, if you just say, “here’s all the processes that we do today, and then we’re going to AI-enable this, that and the other,” you might miss the point that maybe you don’t have to do this process anymore at all. Maybe you don’t need to interview every single person.

I just talked with a big retail company that said for staffing up for the holiday period, for example, they don’t interview every single person. They have some roles where there’s such fast turnover, where they need to fill them so quickly, they basically do a really high-powered, finely tuned AI assessment, and then they have them start the next day, basically. And it’s actually been shown that the people that were assessed by the AI stay on average 2.5 times longer. So not only could the AI assess the fit much better for these really volume retail people that just come in basically to work the registers or support the customers, because it can assess much better: “Is that person going to be able to deal with this high volume, high pressure environment?” So they see, not just do I get people in faster, but they stay much longer, which means, basically, it’s a better job for them. It’s a more appropriate job. And if you think about the impact that that has on that retail business—when people stay longer—of course, it has a direct impact on the bottom line for retail businesses, certainly.

Rebecca Warren 10:47 Yeah, so that gets me thinking here. So I know one of the things that we have talked about in the past is Talent Density, right? Looking at capability instead of just headcount. So as you’re thinking about changing hiring strategies, talk to me a little bit about thinking about that capability instead of just bodies in seats.

Kathi Enderes 11:11 Yeah. I mean, it’s really that Talent Density approach is really changing the recruiting function—and actually all of us in HR, but really recruiting specifically — from this “fulfillment center,” Amazon fulfillment center of jobs waiting, where we just get requisitions in and we just basically try to fill them as fast as possible, to thinking about: How can you actually get the right capabilities, the right skills, into the organization, and make every person count much more?

And maybe that’s not to do with hiring at all. Maybe you don’t need to hire at all. And we have this framework, we call it the “4R Framework,” where you’re thinking at the same time when you need to fill a certain capability — for example, for the business, they say, “we need, I don’t know, 15 people in Houston, Texas with these AI capabilities,” and you in recruiting scratch your head and say, “we won’t find them,” right? So rather than saying, “well, we won’t find them,” or “we can do it,” or “do your best to do it,” maybe think about: Well, do we need to hire them all as 15 FTEs? Or maybe we can think about how we retain people that we already have in the organization. So that’s the second R, from Recruit to Retain. Basically, we have people with the right capabilities already. How can we retain them differentially so we don’t lose more of them and need to hire even more?

Then when you think about the third R, which we call Reskill: How can we find people with adjacent skills, with complementary skills, that we could uplevel and train for that and reskill them, and then move them around internally?

And then the last one is the Redesign. So maybe we can redesign the job with AI at the table so we don’t need so many of these people. Or maybe we can find a different employment model where we are saying maybe some of them are full-time FTEs, but maybe some of them are projects, some of them are outsourced to contractors or consultants, because we might not need that capability all that long.

So it really flips the mindset from just basically reactive hiring to proactive workforce planning, strategy, all of that. And all with the notion of Talent Density, where you’re saying every person has to count, and every person basically that you bring into the organization has to amplify the rest of the team and not bring them down. Because sometimes when you hire more people, you’re actually getting less productive, because maybe you introduce kind of duplication or unclarity or bureaucracy into the team.

Panasonic, for example, they did a study where they saw the exact right team size that they needed to have on their production line. And they found out that having more people on that production team, basically, of these batteries, was actually counterproductive. So they saw the exact right team size for that, for this particular scenario. And then they said, “Well, we shouldn’t have…” because their managers were drowning, basically. They said, “Oh, we have so much work to do. We have so much demand. We need to hire.” And so then they basically established how can you get the exact right amount of people with the right skill set on the team. So thinking about that team fit, not just individual role fit, all of that figures into Talent Density.

Rebecca Warren 14:29 So it takes away the idea of a body count, right, or a number of hires. Let’s think about the work that needs to get done, the skills that we need, and then potentially using AI, which enables maybe smaller teams to be more capable, and they can outperform those that are larger, that maybe have more folks, but maybe don’t have that same alignment of skills or abilities to take on more work.

Kathi Enderes 14:57 That’s right, exactly. I mean, Netflix is such a great example, and they coined the term of Talent Density. So we borrowed it from them, because they are a fairly, fairly small organization — I mean, compared to maybe other media companies or something like that. But they are so, so agile in their thinking and their business model. But then they also have things like talent practices, like what they call the “Keeper Test.”

So the Keeper Test goes like this: for every manager — they don’t do regular performance reviews — but they say every manager has to think about all of their team members in this way to say, “What if this person was going to tell me they’re going to quit? How far would I go to keep them?” And if they would say, “Absolutely, do whatever I could. I’d offer them more money, I’d triple their salary, I’d give them basically the career choices that they want”—that’s one answer. But if they’re saying, “Oh, actually, I would be a little bit relieved, because maybe they’re bringing the rest of the team down, or maybe they’re not in the right role, and we need to be more aligning them to the right role” — that gives you another answer as well.

So they’re thinking about their teams like sports teams. And you can’t have somebody who is not high performing on your sports team, right? You’re going to find them another position, if they’re in soccer, for example, or in basketball. If they’re not performing in that role, you’re going to find them another role. It’s going to be really clear. So thinking about it like that too, that all has to do with Talent Density.

Rebecca Warren 16:22 And so what I’m hearing you talk about, as well, is agility of organizations to figure out, how do we do things differently? You know, we’ve talked a lot about change management and change management plans, and they’re very organized, right? You’ve got this step-by-step: you do this, and then when the change management plan is complete, you check the box and you move on. But that’s not how the world is working today. That’s not how organizations are working, right? It’s that continual complex processes that you can’t just check a box. You have to continue to solve through them to become more flexible, because work doesn’t put itself into a change management plan. So let’s talk a little bit about that — like, how can we think about organizations thinking through agility, as opposed to a set change management plan? How are you thinking about agility?

Kathi Enderes 17:19 Yeah, I mean, we’ve been talking about that. We identified that these Pacesetters actually don’t do change management for the AI transformation, because change management is in its traditional sense like project management, right? It’s maybe a sibling or brother or sister of project management. You can manage the change if you know exactly what’s the deadline, and then you know exactly your activities. You’re going to do training, you’re going to do communication, you’re going to do stakeholder management, you’re going to do change leadership, all of those things. And there’s many, many different approaches out there, and they’re all good for that kind of step change, where you know exactly what’s the start point, what’s the end point, moving people from A to B. Basically great approach on change management, but that assumes it’s kind of a point in time—you’re implementing an ERP system, and you know exactly when it got cut over. And then you know exactly are people actually using it, and if they’re not using it, you’re gonna kind of cut off their old access, whatever it is, right? So you know exactly it’s like a very finite thing.

But in the AI transformation, if you look at the AI tooling, every day something new comes around. I mean, you can’t even keep up. Every day tools can do it only every day, and I’m trying to keep up. But of course, it’s impossible, right? It’s impossible what all of these tools can do every single day and doing something new. So you can’t say “we’re going to train people on it, and we’re going to communicate it,” because it is changing every single day. If you’re moving towards a moving target, we call this “Change Agility.” And so we’re saying this can’t be this organized project management approach, but this needs to be much more bottom-up, much more tapping into the ingenuity, into the ideas of every single person to say, “What do we need to do? How can we experiment?” Helping people also have that psychological safety, basically, to tell leadership and their manager or their team something is not working, it’s actually not the right approach. And so that kind of bottom-up change management, change agility approach, all of that figures into that.

And it also touches on the role of the leader. So the leader is no longer the “know-it-all,” but it’s the “learn-it-all,” as Microsoft calls it, and I love it. So you’re not supposed to be the smartest person in the room. You’re supposed to be the person that brings the smartest people together to get the smartest outcome. So you don’t have to lead by doing this, but by tapping into people. It’s a different approach.

Rebecca Warren 19:53 Yeah, and I think about that in terms of curiosity, right? You need to be less of a knowledge holder or an expert in something; you need to have that curious learner, that curiosity to say, “What am I going to continue to learn?” So you go from being a gatekeeper of knowledge to being the one that says, “we don’t know, let’s figure it out and let’s learn together.”

Kathi Enderes 20:17 Yeah, no, absolutely. Because the best ideas come from the frontline. They usually don’t come from the top. In the AI transformation, it certainly doesn’t come always from the leaders, right? A lot of times you might have a great idea that comes from somebody who is actually doing the work, and they’re saying, “Look what we’re doing here and how we’re using these AI tools.” So tapping into that constantly is really important. And then people also won’t resist it, because if it’s their solution, you’re not trying to push it on them.

Rebecca Warren 20:48 So that’s collaboration. I continue to talk about how we have to collaborate with AI instead of competing with it. We don’t have to integrate, but we have to use that—keep our humans in the lead, make sure that we’re thinking about things the right way. But when you collaborate and you pull people in and have those stronger conversations, it really shifts how people look at their jobs, the work, and the organization.

Kathi Enderes 21:11 Yeah, no, absolutely, exactly, yeah. And I love how you say that: keeping the humans in the lead.

Rebecca Warren 21:18 That’s right, yeah. Okay, so I’m watching time. I don’t know how this has gone so fast, so I’m skipping over a bunch of other stuff that we could have talked about, but here’s where I want us to land. So when we think about that Pacesetter trajectory and where that’s going, and people who want to be in the lead as their organization, both with people and tech, if leaders here today took one action to get onto that Pacesetter trajectory for next year, what’s that one action they should take to get them started?

Kathi Enderes 21:54 Yeah, I would say you start thinking about AI transformation not as a tech project, but really as a people and culture transformation. I think then everything will be much better, and you’re going to go into that direction of the Pacesetters. So what this looks like is, basically, you can look at—and I know we’re probably going to share the Pacesetter research — to benchmark your own actions and how you think about AI transformation, how you work on AI transformation, against what the six practices are. And I know we didn’t cover all six, but we’ll have more to read basically against what the Pacesetters are doing. So thinking about: How can you treat AI transformation as a people and culture transformation, not just as a tech transformation? And look at how the Pacesetters are doing it, benchmark against them. And pick one thing that you want to work on. Break down those boundaries. Basically work together across the HR team, if you are in HR, or work together with the business too. So pick one specific problem. That’s what you can do, basically — and just start working. You don’t need to wait for your organization to necessarily give you permission. Just get started somewhere where the business has a problem, where there’s some opportunity, and try it out. And that’s kind of the Change Agility mindset.

Rebecca Warren 23:16 I love that. So the words that I heard: amplify, elevate potential, flexible, agile… like there’s so many great things in there. So we’re going to leave you with those last words of what is the potential that you can do. Just start somewhere, keep learning, keep growing, keep iterating. All right, Steve, you’re going to have to yank us off the stage. We’re going to have to go back to you before we start talking again.

Speaker 1 23:43 Well, hello there, Rebecca and Kathi. That was a wonderful conversation. Thank you for sharing your thought leadership on our stage today. We really enjoyed that. And up next, we will be having our workshops. Today I’m Kaylin Clemens, Vice President of Talent Engagement at From Day One, and I’ll tell you a bit about each session and how to navigate to them from here. The first option that we have that’s happening now is titled “Financial Wellness: A Core Benefit, A Win-Win for Business and Employees.” Financial stress is one of the top distractions for U.S. workers, and companies that address that see measurable gains in retention, engagement, and productivity.