Rebecca Warren and Kathi Enderes discussed the impact of AI on workforce productivity and the concept of Superworkers. They highlighted the Global Workforce Intelligence Project, which analyzed various industries’ skills and roles over four years. The project identified Pacesetters that focus on skills velocity, enabling rapid skill acquisition and adaptation. They emphasized AI’s role in enhancing human potential rather than just cutting costs. The conversation also covered the four stages of AI adoption in organizations, stressing the need for a growth mindset and cultural shift to leverage AI effectively. Practical steps include encouraging experimentation and fostering a learning culture.

Introduction

• Stephen Koepp introduces the session, emphasizing the impact of new technologies on workforce productivity and efficiency.
• Rebecca Warren expresses excitement about discussing the Pacesetters Report and the global workforce intelligence project.
• Kathi Enderes introduces herself and her role at the Josh Bersin Company, focusing on HR and technology vendors.
• Kathi highlights the Pacesetters research and its significance in understanding industry changes and organizational solutions.

Global Workforce Intelligence (GWI) Project overview

• Rebecca Warren discusses her role at Eightfold and the importance of focusing on people rather than jobs.
• Kathi Enderes explains the Global Workforce Intelligence Project, which started four years ago to analyze industry skills and roles.
• The project covers various industries, including healthcare, pharmaceutical, consumer banking, automotive manufacturing, insurance, and consumer packaged goods.
• Kathi emphasizes the importance of data-driven insights to understand business problems and industry changes.

Impact of AI on workforce and Superworker concept

• Rebecca Warren and Kathi Enderes discuss the impact of AI on workforce productivity and efficiency.
• Rebecca highlights the goal of AI in enhancing human potential rather than just cutting costs.
• Kathi introduces the concept of the Superworker, where AI and humans complement each other to achieve greater organizational value.
• Examples of Superworkers in their organization are shared, illustrating how AI can help employees focus on more creative and valuable tasks.

Defining Pacesetters and skills velocity

• Rebecca Warren asks Kathi to define Pacesetters and discuss the concept of investing in efficiency and human potential.
• Kathi explains that Pacesetters are industry leaders in customer satisfaction, financial performance, innovation, and people factors.
• The Pacesetters research identifies common themes in AI transformation, focusing on skills velocity rather than just skills depth or availability.
• Skills velocity refers to the ability of organizations to quickly enable employees to acquire and transition to new skills.

Redesigning workflows and roles

• Rebecca Warren and Kathi Enderes discuss the concept of productivity-based work redesign and the stages of AI adoption.
• Kathi outlines the four stages of AI transformation: using AI assistance, automating parts of jobs, using multi-functional cross-functional agents, and fully autonomous agents.
• The discussion emphasizes the need for productivity-based job redesign to create higher-order roles and enhance organizational productivity.
• Rebecca highlights the importance of leading with outcomes and focusing on work that adds value rather than job titles.

Challenges and barriers to AI adoption

• Rebecca Warren asks about the challenges and barriers to achieving higher levels of AI adoption.
• Kathi Enderes identifies change agility, mindset shift, and organizational culture as key barriers.
• The conversation touches on the fear and intimidation employees feel when using AI tools.
• Rebecca suggests moving from a culture of fear to a learning culture, encouraging experimentation and curiosity.

Practical steps for building a Superworker organization

• Rebecca Warren asks for practical steps organizations can take to start building a Superworker organization.
• Kathi Enderes emphasizes the importance of shifting the mindset from cost-cutting to growth opportunities.
• Encouraging early adopters to experiment with AI tools and share their experiences is recommended.
• Rebecca highlights the need for guided tours and bite-sized learning to build confidence and reduce fear.

Conclusion 

• Rebecca Warren and Kathi Enderes wrap up the discussion, emphasizing the importance of the Superworker concept.
• Kathi reiterates the need for a growth mindset and collaboration around AI tools.
• Rebecca suggests finding early adopters and encouraging them to test and learn.
• The session concludes with mutual appreciation for the insights shared and the importance of continuous learning and adaptation.

Stephen Koepp 00:00
New technologies. They’re fundamentally redesigning work, empowering their workforce, and they’re achieving unprecedented gains in productivity and efficiency. This session, led by Rebecca Warren, Director of Talent-centered Transformation at Eightfold AI, and Kathi Enderes, SVP of Research and Global Industry Analyst at the Josh Bersin Company, will give you a deep dive into the strategies of these high performing organizations. So Rebecca, Kathi, welcome. Glad you’re here. Please take it away.

Rebecca Warren 00:32
All right. Thanks, Steve. So Kathi, I’m not sure about our deep dive in 20 minutes, we’re going to have to talk really, really fast, but I think we can do it. We can probably wait a bit for the ground. Oh so good to see you today. Really excited for us to talk about the pace setters report and the research that you’re all doing. You and I have had several conversations about how amazing this research is and how it helps us think more broadly. So before we jump in, do you just want to do a quick little introduction of yourself for the rest of the group?

Kathi Enderes 01:09
Sure. Happy to and I’m really thrilled to join you here, Rebecca, and thanks for having me. I’m Kathi Andres, SVP of Research and Global Industry Analyst at the Josh Bersin Company. If you don’t know who we are, we are a research and advisory company for the HR profession, and so we work with a lot of corporate HR teams, but then also a lot of technology vendors, like Eightfold, for example, all with a focus on moving HR into this new world where we can make a bigger impact and make work better and more meaningful and get better better business outcomes on that. So I’m really thrilled to talk about what we saw here with our peace status research, because it’s part of a big Global Workforce Intelligence Project that we’re working together with. It pulled on for the last four or five years. So we’re diving deep into many different industries to understand, what are the skills, what are the roles, and what are the career pathways and organizational solutions, industry by industry in this new world.

Rebecca Warren 02:15
All right, so Rebecca Warren, I’m at Eightfold AI. I am part of our Talent-centered Transformation practice where we spend time thinking about the lens of people, as opposed to the lens of jobs. And so Kathi, we had a chance to work together on a couple of things, so let’s dive in. So before we talk about the most recent Racesetters report, Let’s chat a little bit. I love this research that you did through the Global Workforce Intelligence Project. So will you talk a little bit about that for folks who may not be familiar, and then we’ll dive into the pace.

Kathi Enderes 02:53
So we started the Global Workforce Intelligence (GWI) Project four years ago, almost four years ago, actually, exactly four years ago, working with all the data that Eightfold has to understand industry by industry, what are the skills that are rising? What are the skills that are declining in need? What are the new jobs and roles that are getting more important and less important? And what organizational solutions can companies deploy in order to make all of this happen? So we are tapping into the data of Eightfold on each of these industries, and we covered healthcare. We covered pharmaceuticals, we covered consumer banking, automotive manufacturing, insurance, so lots of different consumer packaged goods, PPG, and lots of different industries. And we wanted to see actually based on the data, so not just based on interviewing leaders in these industries, but based on the data, what’s happening in those industries. How are they changing? And how does this change? Actually, what skills and roles we need to support in HR and in that challenge. So it’s been fascinating because we get really deeper into the business problems and how these industries are changing, which is, I know every HR person is looking to get closer to the business and really understand how the business operates. So it’s been a great one.

Rebecca Warren 04:24
As you know, you look through the data in there, and I know folks can go to your website and download the report. So when you look at it, every single industry is changing, right? It doesn’t matter what industry it is. AI has affected every single one. And as we talk about, right the Superworker, what does that look like? So the goal of AI, unleashing human potential, tying those things together, it’s not just about cutting costs. And I love what Alessandro said a little bit ago. He’s like, do you sharpen the ax and do it in half the time, or do you just start hacking? Away and take, you know, a lot longer and not as efficiently. So I love the idea that AI can help enhance human potential, as opposed to just thinking about cutting costs. So let’s talk a little bit about that. What does that mindset look like, the Superworker and putting together a different way to approach the conversation?

Kathi Enderes 05:18
Yeah, the Superworker concept is something that we introduced last year, and it’s certainly something that every organization wants to hear about, because we talk about the AI transformation in HR, but then also outside of HR, with every conversation that we have. And so what we mean by Superworker is actually a very powerful and very positive concept. There’s two ways to think about AI transformation. One way to think about it is, it’s all about AI replacing humans. So like, basically, AI can do the work that humans do, and then you need less people, which is kind of that splashing and burning, kind of whittling away some of the value that the organization might provide to the customers into the market and just doing less, basically with doing doing maybe more with less, so just doing needing less resources, that’s kind of the non Superworker concept of thinking about AI, right? You can say, well, I have 10 marketing people, and now I use AI for marketing automation and all of that. Now I not only need seven marketing people, and you just kind of let go of three people, or there’s the Superworker concept, way of saying, well, AI and humans are actually not good at the same things. AI is much better than people at certain things, and people are much better than AI at certain other things. And so how about powering every employee in the organization, from the front line to mid level managers all the way to executives to do 10 times more and to get 10 times more value for the organization. So rather than saying we now lead only seven marketing people, how about you use these 10 marketing people. You provide them with AI now you can broaden your reach and you can grow much faster. So that kind of growth mindset, rather than the productivity and slashing and burning mindset, is what we mean by Superworker? And every organization actually really has Superworkers. There’s many people that experiment with AI, that try to use AI to get rid of the work that they don’t love to do, and do more of the work that they love to do. As a matter of fact, for example, in our organization, as soon as AI came, came on board, we have somebody who is a graphic designer, and he lays out research reports and all of that, and immediately, and he’s, he’s a fairly early career young person, very creative and all of that. But as soon as AI came on board, he used an AI agent to basically help him with doing layouts and PDFs and all of that, the stuff that is not all that exciting. And now he can focus much more on creative graphics and all of that. Or our editorial team now uses AI video tools, for example, to create new videos, rather than just doing kind of laid out reports. All of those are examples of Superworkers already existing in the organization, and we in HR can actually power those Superworkers. And what we found is the highest performing organizations, these pace that organization actually tap and release the energy of all of these Superworkers in the organization and power them to take the organization forward in new ways, to grow more to have more talent and to have more customers and more business outcomes, because I think when you put those things together, right?

Rebecca Warren 08:44
Like, when I think about using AI in a lot of the things that I do, it actually forces me to be more creative, right? It enhances that maximizer, right? Like, it starts to make it better. It makes your life so much easier when you can put those pieces together, and then you’re focusing on that human potential. And I love that, right? That’s exactly what we’re talking about as we think about what’s happening in HR. So let’s talk about HR, and let’s talk about talent. So you talk about Pacesetters. So first, can you define what you think a pay or what you define a Pacesetter as. And then let’s talk about investing in efficiency and the Superworker. How does that translate to productivity, but also enhancement of human potential?

Kathi Enderes 09:34
Yeah, that’s perfect. As part of the Global Workforce Intelligence Project, where we looked at all these different industries, we also identified that in each of these industries, there’s five to 10% of companies that are the industry leaders. They are not just leading in all categories. So they’re leading in customer satisfaction, they’re leading in financial performance, they’re also leading in innovating in their industry. But they’re also leading in people factors. So basically, they have a better workplace, they have more engaged employees, they have kind of a supportive culture, all of those kinds of things. They are more systemic HR organizations, what we call them, so much more integrated HR organizations. So we identified who these paces are in each of these industries. So we know basically each of the industries. We know in healthcare, who are some of these paces. We know it in insurance, and on and on and on, we know who these places are and what we did. And as part of this pace, the GWI and Pacesetter research is really looking at the data, in all of this skills data and all of these talent data sets, to say, what are they doing differently in terms of the AI transformation? So not based, again, it’s all data based. It’s all data informed. We couldn’t do any of this, by the way, without AI too, because it’s very hard to digest all of these themes without AI, because there’s so many data points, like billions of data points basically coming in. So we identified, what are they doing differently in the AI transformation? And one of the things that we saw there, or really the overarching theme that we saw with these pace data organizations are doing differently. They’re not just focusing on skills depth or skills availability, but what we call skills velocity. The skills velocity is a really important concept, because skills are changing so quickly now, because of the AI transformation, because every industry is changing and transforming, and so these pace set our organization in an overarching theme. Basically what they’re doing differently is they’re focusing on how quickly they enable people to move to different skills and to learn new skills, and to move people around in kind of human, centered, people centered way, as you said, to to put them on the most important initiatives and projects in the organization based on these new skills. So basically, that skills philosophy was overarching to solving the nursing shortage in healthcare, for example, to solving the R&D kind of speed of R&D and pharmaceutical or whatever we identified as the business problems, the overarching business problems in each of these industries. So that was kind of a common theme that they had all around them, and it really relates to the AI transformation, because AI, of course, changes the skills that we need and that we have in the organization in a significant way.

Rebecca Warren 12:44
Yeah, skill velocity is so interesting when you think about it that way, right? Like, how do we get folks empowered, enabled, moving more quickly, and not just by the skills that they have in a list or something that they’ve already done, but what is their potential? What are the things that they could do right? Those rising skills, those waning skills. How are we continuing to empower folks to continue on that velocity track, to move up, up the efficiency ladder, as opposed to feeling like, Oh, I’m not really engaged. I don’t really love this, so nobody’s really paying attention to the things that I want to do as well as the things that I’ve already done. I love it. I love it. Exactly. Okay, so let’s talk about workflows. Let’s talk about roles. Let’s talk about how that changes when we think about redesigning work. So you talk about, let me see productivity based work redesign. I want to make sure I say it right, yeah. So talk about what that looks like. That is, rethinking workflows, roles, outlining the stages of AI adoption and what that does. So let’s talk about that. And then I want to talk about what may get in the way for that moving as quickly as we might like, yeah, when we think about the AI transformation overall, not just in HR, but in organizations.

Kathi Enderes 13:58
And HR, of course, plays a significant role in all that we see organizations be at one of four stages of this AI transformation. And the first one basically is just, you’re using AI assistance just to make yourself your job a little bit better and easier. So you might use a copilot or something like that, or chatbot or whatever you’re going to use to maybe write a little bit better emails or draft better communication, or maybe improve your slide content, whatever you do, basically, but it’s still your job. It’s still your job, and you just do things a little bit faster, and I think many organizations are still at that stage. Every time we talk about that, people say, Well, usually we’re in that stage. We give the copilot or some other tool to all of our employees, and they can use it, but there’s not a lot of direction on how to use it. So you might have maybe three or 2% of employees who act. Like Superworkers, and they have really taken the AI tools and significantly changed how they do their work. But most others have maybe started experimenting a little bit or just using it in some of these daily workflows, without a lot of change to the jobs and the work. So that’s kind of stage one of this AI transformation. Use AI assistance. No work. Will design your job, still your job. And then you go to the place where you significantly use AI to automate some parts of your job. So for example, you might use AI to, if you are a recruiter, to automate scheduling of interviews, right? That’s right, it’s a really time consuming thing, and AI could take this task from you, and you don’t have to schedule the interviews anymore. So there’s a whole task that you don’t need to do anymore, but your job is still your job. And if you are a recruiter, for example, then you have more time maybe to have conversations with candidates or with hiring managers. But your job is still your same job, so it’s still, like not a huge impact, and still bottom up kind of frame Molly, so you give the tools to employees, and the employees, then maybe reduce, like, for example, use AI agents, so it’s not just assistants, but baby agents that do kind of can transact things in in the process as well. So that’s stage two, many organizations are maybe between stage one stage one and a half. A lot of organizations say that, but we see that there’s stage three and stage four, where there’s not a lot of organizations there yet, but we see this coming. So stage stage three would be these multi functional, cross functional agents that pull different parts of the organization together. So here, for example, you could have an agent that doesn’t just do interview scheduling in the recruiting side, but then also connects with the learning agent to say, maybe we need to not just hire from the outside, but we also need to train people from the inside in order to fill a certain skills need in the organization. And that happens, of course, in marketing and sales and operations too. I’m just bringing the examples of HR. So that requires people to think outside of their job. And usually people can’t really do that right, because you don’t really know what other teams and what other groups are doing. So we need to do a little bit more top down productivity based work redesign, to think about what is the job of a recruiter, for example, in this new world, what is the job of the instructional designer in the new kind of learning design paradigm where we have content being created really quickly and kind of tested really quickly. So this gets to the kind of productivity based job and work redesign, where we in HR, can play a big role, but the productivity gain is also going to be much higher because then we have different jobs, higher order jobs. So very quickly, you could think about a recruiter becoming much more a talent advisor, a career advisor, because they could talk much more with internal candidates, with hiring managers who work with on strategic workforce planning, all these higher order things that basically you don’t want the AI to do, but you can have a recruiter, for example, do on stage four is where you have fully autonomous agents that over that they basically The person only overseas, and they do kind of the orchestration of all of this. They do the kind of business that needs analysis and all of that. And the roles change significantly, and the productivity increase is much higher there as well.

Rebecca Warren 18:35
Well, yeah, and we think about that right, work looks significantly different because we’re currently organized into, you know, spots on an org chart, and we have a job title and we have a description when you start leading with the work. And that was what the previous conversation was right? Nicole and Alessandra were talking about, when you lead with outcomes, what do we need to accomplish? Then the work changes, because you’re focused on what actually the outcome is, as opposed to what my job title says. So there’s a lot of shifting that has to happen, and I can see why there’s a lot of companies who aren’t there yet, because it’s significant to say we may start supervising AI agents or workflows, as opposed to supervising people. And I think in all of that, before we talk about what the barrier is to getting to that next level, I think in all of that, we have to be clear about what work belongs with AI and what work belongs with the human. There’s always going to be a space for humans. It’s just going to look significantly different at stage four than it does at stage one, right?

Speaker 1 19:40
Yeah, absolutely.

Rebecca Warren 19:44
What’s the challenge to get to that stage? Like, I think there’s a lot of things that I can probably come up with off the top of my head, but what causes folks to not get to that level for maybe as quickly as some other folks might like, yeah, it’s not really a technology thing because the technologies exist already, right?

Kathi Enderes 19:58
There’s all these multi functional, cross functional, autonomous agents already out there. So it’s not about the technology availability. It’s really a problem of people, culture and organization and changing adoption. So change agility. How quickly can we adopt these things, right? Mindset shift. How can we, I mean, people be intimidated? I was just doing a workshop yesterday with one of our clients, and there were senior HR leaders, basically, and they all said, Well, honestly, I haven’t gone to the AI yet. We have all these AI tools, but I don’t dare go there. And there were two of them in this team of 10 or something. They said, yes, absolutely, I know what. How to do this. And then we asked others, and who said, what gets in the way? And it’s, it’s your general, like, change the adoption process, right? People are intimidated. They don’t know how to use it. They think they’re going to break it. I’m like, You’re not going to break these AI tools. Just try it out. But it’s, it’s your change of adoption curve and your culture. That’s what’s in the middle of that, which is exciting, because it really amplifies the role that we have in HR to support all of this, because that’s what we do. Well, it’s not an IT thing. It’s really a change in culture, people prioritization, a kind of exercise that we need to help the organization through.

Rebecca Warren 21:19
Yeah, and moving from fear to curiosity, right? Like, how do we take maybe those little steps giving folks a guided tour, like, “Hey, let’s go in and play around with it.” And if you have a question, somebody’s here to help, right? And as you get more confident, you become less afraid of it, right? Because, right now, we’re asking people to do things they don’t understand, to use technology they don’t really understand, right? It is a little overwhelming, but if we do it in bite sized chunks, and learn as we go, and develop that curiosity, shifting that mindset in the organization to a learning culture, as opposed to a culture of fear or, you know, I don’t want to be an early adopter, that’s a little bit too much for me. That makes a big difference. So okay, we’re running out of time here, so I’ve got, I’ve got a question here that I want to maybe wrap with this one. So for folks who want to start doing this right, maybe they’re at level one, maybe they’re not even at level one. Maybe they’re two and having a hard time switching to three. For folks who want to start applying these principles, what is a step that you would recommend that they should take to start building the Superworker organization. What’s, what’s one or two things that folks should start thinking about and that they could actually do?

Kathi Enderes 22:31
Yeah, I think that one of the biggest shifts is the mindset shift. So thinking about AI, not as just a cost cutting, but a growth opportunity, right? So it’s not AI, it is not here. I think if you use it well, and that’s kind of the Superworker mindset, just don’t think about it as a cost cutting exercise, because cost cutting always slows down and you cut more and more and more and more until you have nothing left. But think about how it can amplify the growth of your organization. How can you do more new markets, new products, new opportunities, not less, do less and cut on that, but amplify what humans can do, and that applies organizationally, also individually. How can I use these tools that I already have to do more of the stuff that I like to do and less of the stuff that I don’t like to do, and just try it out and experiment and kind of collaborate around it. So I think that the biggest thing is to shift that mindset and also highlight and lead that mindset in your organization as well. Right?

Rebecca Warren 23:33
Find those early adopters, get them trying things, poke a little bit, and see what happens. Right? I love the idea that you can’t break it. It might not react the way you want it to, but it’s not going to break, it’s not going to buy it. People have those conversations and say, oh, okay, we don’t want to do that, because we go down a path that isn’t as productive or efficient, right? So getting people that try it, test it out, right? Maybe it’s a, you know, kind of like the idea of a food you don’t like, but hey, I haven’t tried this in a while, or let me try something new and see where you go. I love that. Okay, we are out of time. Kathi, thanks so much. Our conversations always go longer than we have time for. But I really appreciate you sharing a little bit more about the Superworker, and how that makes us more productive and efficient.

Kathi Enderes 24:21
Thanks so much, Rebecca.