Inside WPP’s AI Work Transformation with Josh Newman & Josh Bersin

Siobhan Savage: Hello! Hello! Welcome, everyone!

We're gonna do the typical and give it a minute for folks to arrive and have that little moment of awkwardness at the start.

Josh Newman: You have any background music, Siobhan.

Siobhan Savage: I know I was literally thinking I should probably have prepared a little bit better.

Josh Newman: Elevator, music.

Siobhan Savage: Yeah, exactly. I was irresistible. Josh, did you guys have a good event?

I heard it was amazing.

Josh Bersin: Yes, it was fun and games again. That was the 4th year for us. So figure it out now.

Siobhan Savage: Incredible congratulations.

Josh Bersin: Thank you. It's just fun to go to a university campus and hang around with people in a different environment.

Josh Newman: Yeah.

Siobhan Savage: Sure.

Josh Newman: Good energy. There, I'm sure.

Josh Bersin: Yeah, it was a beautiful weekend, beautiful day. We went to the Grammy Museum. Did a lot of really cool stuff.

Siobhan Savage: Wow. Mostly, it's mostly senior executive Chro attendance right.

Josh Bersin: Yeah, HR, usually directors. And above, and then there's a special chro track, and we introduced our learning system there, our new version of our Academy. So that was great.

Siobhan Savage: Never been a more important time for folks in Hr. To be learning right and upskilling. So whatever everyone can do to help everyone, upskill and reskill and figure out how to navigate.

Josh Bersin: Every day. There's something to learn every single day. Have you noticed that.

Siobhan Savage: It's so crazy it is crazy.

Josh Bersin: Look at the.

Josh Newman: It's hard to feel you're you're staying on track. Right with that. I'm always behind.

Siobhan Savage: I know they should give a national day for Hr. To have a day off to . Go and learn stuff a bit more regular learning, because we're always.

Josh Bersin: Broadcast. Stop, X! Stop, Donald!

Trump! Stop the stock market!

Siobhan Savage: Welcome everyone. Just gonna give it another minute just to allow folks to enter in, get themselves a cup of tea, get nice and relaxed. We're gonna have a great conversation with our awesome guests, and hopefully, everyone won't get too confused with the 2 names.

I'm not too relaxed hopefully. There's a bit of.

Josh Bersin: it's a treat, Josh. It's a treat for me to be with another Josh, because in my age group there were never anybody. There was never anybody with my name.

Siobhan Savage: Really.

Josh Bersin: So.

Siobhan Savage: Are they random.

Josh Bersin: It was, it was naughty at all.

Siobhan Savage: Why were you called Josh, then what was the reason.

Josh Bersin: I don't know my parents. My brother's name is Adam. They just those kinds of names.

Oh.

Siobhan Savage: I love it.

Josh Newman: We did a good icebreaker with our people leadership team. A few months ago everyone had to go around and talk about the history of their name, or the back of why they were named, what they were named. And there were some.

I have a boring story, too, as far as I'm aware, but there was something tear jerking stories out there.

Siobhan Savage: Wow!

Josh Newman: Yeah, it's a it's a great icebreaker. I've used it since then.

Siobhan Savage: I don't even know , if my name I mean, most people can't even look at . Read my name they have no idea what my name even means. My name actually means Joan.

By the way, in English, Siobhan is Joan.

Josh Bersin: Oh!

Siobhan Savage: Which is, which is very not fancy and feisty savage Siobhan is Joan. It's not. It's a random one.

So speaking of names, let's get started, folks thanks everyone. Firstly, for joining for those who are listening live, and for those who are dialing. In after the event it's happened.

Welcome. I am Siobhan Savage. I'm 1 of the founders and the CEO of Reejig, and we're super excited today to welcome.

Not just one Josh, but 2. Firstly, we have Josh Newman. Josh is an incredible leader, and if folks are not following him right now, look at what he's up to.

It's 1 of my favorite stories in the market. Right now he is the global head of people strategy at WPP. They are the behemoth of all advertising.

One of the biggest companies in that space, he, as being leading one of the most ambitious workforce, redesigns that we've seen in probably this era of work. and also welcoming Josh Bersin for those who don't know and have been maybe living under a rock. Josh is the leader in all things, workforce strategy. Hr.

And the future of work and the leading analyst in this space. So welcome to you both.

Josh Newman: Thank you.

Josh Bersin: Thank you. Siobhan.

Siobhan Savage: So we are at possibly the biggest shift in work that we have ever seen, and before we get into talking to both Josh's about what this means, what they've experienced, what they're seeing, how they've solved it, how they're helping. I wanted to set a little bit of a scene first, st because I think it's important for us to grind where we're at today, what this means and why this is happening so that we all go into that conversation with an open mind, curiosity, and really some good questions for both Josh and Josh around some of the challenges that you might be facing in your workforce today. So this is a once in a generation change to work.

You are once in a generation leaders. This is not going to be something that's ever going to happen again in anyone's careers at this scale, as you heard Josh, in the beginning of the call, talking about just the constant change every day. This is happening at a pace that is a once in a generation.

Now, the reality today is that you are operating in a world where AI is disrupting all things in how we work and how we work with systems, how , we build our organizations, what that means for our workforces. And the reality is that the job architectures and the way that we have built our companies is really limited. , they are not designed for this AI powered workforce. They are not designed in a way that's going to help you evolve, reinvent your organization, but also make sure that you don't leave your folks behind during this big massive change. and the opportunity that exists right now for you all and for us as leaders in this industry is to redesign work in a way that brings together our employees.

So our human workers, but also the digital capability that now exists in the market today. And where we're going. We want to be able to build, , future ready roles.

We want to look at real tasks and understand deeply what is the work that's happening within our organizations. Now, the gap that we have all of us as companies is that unfortunately, most organizations lack the understanding of what is the actual work that is happening within our company. The way that we've structured our jobs is being jobs and job holders that, , if you look up Josh Bersin's research on this.

And we can share this after Josh, if it's okay with you, there's an incredible couple of slides that really talk to this new way that you're building, and the architect of work itself, and how agents will play into what you're calling Josh. the super worker organization and the frameworks and the gaps that we have today is not enabling us to get there. So we really need to start thinking about, how do we understand work? How do we build the critical infrastructure for this new world of work, and make sure that our organizations are ready.

And finally, the urgency right now to make sure the AI is here right? This is not something that's happening in a couple of years the train has already left the station people. So it becomes.

How do we redesign our work now and make sure that we don't leave people behind. And I think a lot of what you'll be really excited to hear from Josh Bersin when he's talking in a little bit, is about the concept of the super worker and talking about. how the individuals also can amplify themselves at the same time as making sure that we build the right workforces. So that's a little bit of where we're at and what really matters.

And today's conversation is going to be an awesome one, because, , there are not many companies that have actually really fully went on this journey, and the folks that are brave enough to go on this journey 1st to try to make mistakes, to innovate, to pioneer, and then to be able to come together this to share that knowledge and their learnings with the community. , Josh, we're super grateful for you to come and share the good, the bad, the ugly. What you've learned, what you believe is going to happen and really help folks think about that in the context of their workforce. So, Josh, I would love it.

If you can take us back to the beginning. Tell us what's happening inside of WPP. , what was the problems. And then my emojis are now because I'm very handsy.

We're going to start going off. But , tell us a little bit about the reason, , what was the critical event that happened in WPP. what made you realize that this was time to rethink how you were doing things, and what was the opportunity that you saw? And , if you're if you're cool, Josh person and I will probably drop in and ask you more and pull it little things, and if anyone has any questions. live also, please throw them into the chat.

We're really good on chat, and I can also make sure that they get their way to either of the Josh's. So, Josh, over to you.

Josh Newman: Yeah. Well, let's go with Newman. That might clear things up, though, context is just fine.

I think Josh person is Josh number one in this in this scenario, and honored to be here, Josh with yourself, and excited to chat again, and thanks Siobhan for pulling us together for this, , you said this started with a business challenge, and it started actually from the top and and the very top of WPP. Where, at a board meeting, the Board provoked our Chro at the time, who were very fortunate, sits in on every board meeting, so has that senior horizontal visibility. What is the future shape of the workforce going to be?

And are we going to have more or fewer individuals as we develop and deploy a state of the art marketing AI enabled marketing platform that we call WPP. Open. It was a advertising campaign launched yesterday actually to promote WPP AI.

So go check that out. . And I I think if I if I then step back and think about that question through the lens of what is the purpose of a people team and a modern Hr function. It's a few things.

One. I think it is mandatory that successful Hr organizations understand work architecture, how work gets done. That is the only way, AI or not to add strategic value to an organization.

And then, I think, a bit more with a future centric lens. And I see this triangulation, and I'm going to steal this from a mentor of mine who actually mentioned this yesterday in A, in a conversation the highest order value of an Hr. Function is triangulating 3 things, one.

Understanding how the organization makes money, understanding the dollars and cents, commercials, 2. Having the finger on the pulse of what is going on culturally. politically, socially, in the world. And then 3 have that future orientation.

So you can point business leaders in the direction that we should be going with all of that in mind, because ultimately we, as every organization that isn't just an organization of one plus a bunch of AI agents is a talent centric organization. Whether they realize that or not. We are very obviously a talent centric organization being in very much the professional services world through that lens of advertising.

So back to the original prompt of the question, what is going to be the the new shape and size of our organization as we are implementing tools that completely reinvent workflows. So to answer that we realized that the only way to do it justice was to pull out the microscope and dig in to who we have what they're doing in service of what they're delivering. and we did that. We partnered before we met Siobhan and Reejig we partnered with an internal Oh, my sorry!

My mom is calling. We partnered with a.

Siobhan Savage: Probably answer that. Okay.

Josh Newman: Couldn't figure out the zoom. We partnered with a machine learning engineer internally, who very generously was one excited about the project, but really donated his time aside from his his day job, and he built us a large language model that ingested our job architecture. It ingested little bits of information about workflow that we were able to capture And then what it did was paired.

AI related technologies that were fairly broad but still directionally right. Things natural language processing and recruitment process, outsourcing automation technologies that. And it gave us at the at the micro task level tied to each role. potential capacity unlock or time savings based on certain technologies in the back end.

That was the output in the back end. What this model really did was highlight to us. The complexity of our data, which we already knew.

Our data was a bit of a a bit of a shit show. And I see some some colleagues on the call who will very much know where I'm coming from. There we within our job architecture.

We had about 55,000 unique job titles. So there's no way to manually go through and say, , let's estimate, , 50 to 80% of what we think these people are doing on a day to day basis. What the large language model helped us do.

One of the things that helped us do do was crunch that by cleaning things up. Some were very much, , language based right? So Hr.

Business partner in Spanish is something different than it is in Italian. So it crunched those things, and it cleaned up commonalities where there might have been capitalizations that were different, or commas or periods that were in the wrong places, and we got down to about 5,000 clean job titles. So that was step one.

We were able to get this broad sense of the capacity, unlock that certain generic AI tools were going to give us if we applied them in very prescriptive ways. That's a whole different problem or challenge that we can get to later on. So when we when we took this data, these outputs to the business, they were , Okay, , the tasks.

They feel right. So the Llm. Did a really good job of that, .

I don't know how you're getting to these capacity savings, and I don't. I don't really know what we're supposed to do with that. So we we noodled on that for a bit, and we were talking to organizations, Siobhan, yourself and a few others, and decided to work with you, to go that level deeper from a validation perspective, but also to create a sense of dynamism to how we were going to consistently re-engineer work, and the outputs of the work that we've partnered on together gives us very much role specific playbooks that we can implement that are beyond generic AI technologies.

You've been able to adjust your tool to incorporate specific workflows and technologies that we've built internally so that we can say within our platform, WPP. Open. a media planner should be using this module within open, and that because they spend this many hours on it today will unlock this amount of capacity. And we can, , calculate dollars and cents tied to tied to spend, and things that.

Now. what's really interesting for me personally about this work is that it has elevated the type of strategic value that we've been able to provide to the business because of AI and and the general narrative around AI. Externally as well as internally, business leaders are starting to ask Hre questions that they really were not asking before. So it's opened the door.

And and the work that we've done together has given us the insights to go and provide a certain level of credibility that we might not have had in the past to have, , work that work, architecture, business, model redesign conversation. So I'll pause there and , just underline, Siobhan. What you said at the beginning would love if people could pepper in questions.

And , maybe this isn't so much of a josh, you and I back and forth, but we can take some some questions.

Josh Bersin: Can I ask you a question, Josh, that that I think most people probably would have. So you take these 55,000 jobs. We're randomly titled, and so forth.

You go to 5,000 that are cleaned up. Then you end up going to something 6 100 or something. At the end of the whole process.

You told me the other day.

Josh Newman: Yeah, that was the that. Yeah, that was the next.

Josh Bersin: So so yeah, so what you're basically saying is, a bunch of the tactical work that this person is doing is exactly the same as the tactical work as this person is doing. So let's combine that into one job or or something that. There's there's you're reducing overlap.

I assume.

Josh Newman: Close. Yeah, close. Enough.

Josh Bersin: They're not as different as they sound . If you're an analyst in this, and you're an analyst in that. And you have a different job title in front of the word analyst.

You're still an analyst. So.

Josh Newman: Yes, and so I would say, , an account manager might do something very different in the media capability versus the creative capability versus the production capability. So we're keeping things separate where they deserve to be separate. But we're combining things on the back end.

Josh Bersin: Thing that amazes me about what you guys did. If I understand it is, you basically have to re-engineer the business itself. because you're not just squashing job titles together. Somebody's making a decision about what the new job title is that combines these other ones.

Is that correct?

Josh Newman: I would say that is, it's.

Josh Bersin: Or is that the next step.

Josh Newman: Well, the the this, the actual step, isn't to change people's job titles per se. Right , that's not an objective that we're we're pursuing by any means. What we're pursuing is more intelligence about the people we have via the work that is being accomplished.

And the reason again, that all started is because we started this whole thing by the business telling us we are re-engineering workflows through the technology we're building. So naturally, we we saw this through 4 layers. If workflows are being re-engineered, then teams need to be reshaped to deliver against those workflows.

If teams are being reshaped, who are they being reshaped.

Josh Bersin: Next step for you guys, in other words, is to take this new AI platform Wvp. Open. And now apply the new job architecture against it.

Josh Newman: That is down. That is down the line. Yeah.

Josh Bersin: Okay. Alright. Okay.

Josh Newman: And that will play that will play out in things resource management. Right? It will help way more intelligently as clients more and more reach out to WPP for integrated services rather than reaching out to one of our agencies.

They're looking our top clients which are growing the fastest reach out to WPP. They want the best of who we have.

Josh Bersin: What do you think the odds are that when WPP. Open starts to roll out more. that half the jobs you have won't even exist at all, or they may be.

Josh Newman: Everything half is over. Estimate

Josh Bersin: Or some percentage or.

Josh Newman: I think I think jobs will change. I mean, we're we're working on this this body of thought leadership, led by my colleague, Laura Weiss around the M-shaped worker that I believe you and I have talked about. It's an evolution from the T-shaped worker and what it is is taking relevant skill combinations and bringing them together so that we have individuals who have common horizontals or a common backbone that is the horizontal, whether that's commercial acumen or AI orchestration and brings together things media planning, which can be much more automated than it is today with media digital strategy, which is much more client centric thinking about the challenges.

But the future of digital strategy will need to have expertise in media planning. It cannot be separate.

Josh Bersin: The 2 t tips of the M.

Josh Newman: And I'm I'm dancing around your question a little bit, because, , I.

Josh Bersin: Let me. Can I? Can I explain why?

I asked. And I just want to bring up another example. Then we can go back into WPP.

So I've talked to a lot of companies about this AI stuff, I mean endlessly. And the one that was most interesting. The last couple of weeks was the story from Tanuj at Standard Charter.

So she's this she is. She is the chief strategy officer, and Hr. Reports to her.

So she owns the company strategy which most Hr. People do not. But she does.

And she said, Look, we looked at all this. AI, and then there's a hundred place. There's a thousand places to use it.

I can't possibly help people prioritize every single project. So , I'm looking across the whole company as a bank. Where do we have highly unproductive, important customer critical processes that we could re-engineer.

And she said, and they're global. They do. They're you guys in banking different kinds of business.

Of course, 130 countries. people come to standard charter because they're global. And they have this complex business that does business in all these different countries, she said. So the problem we have is that we have to open all these accounts for these different companies in all these different countries, and it's a mess.

We have manual people opening up accounts in each country for each client. So we're going to do. And she said.

If I look at the staff in the company, a high percentage of our staff behind the scenes does this thing called account opening? I don't really know what it is. But I could imagine it, she said.

So we're going to basically take our AI resources, or we're going to focus on account opening. And we're and we know that's going to affect a lot of people. But we're going to look at it a business standpoint and automate that 1st and and the second thing we're going to do is we're going to automate wealth management roles because the wealth management guys are making all these decisions by hand. that sounds to me , that's the next type of thing you guys are gonna want to do.

Is that correct? Josh, the business level engineering.

Josh Newman: It is level engineering. Yeah, it is happening both in parallel. But it's also happening with our people team involved in a way that it wouldn't have in the past, because we're able to come to the table with this task workflow role level.

Siobhan Savage: Yep.

Josh Newman: Detail, and the only thing I the only thing I'd add that I I I'd be remiss not to say we're not. We're not looking at technology implementation as an efficiency play. And I think anyone who is looking to simply drive the bottom line and drive margin is going to miss out on the reality of human nature, which is that people will fill their time.

So if we can help people fill their time in order to be more effective in order to drive, work up the value chain and remove the work that people just don't to do. push paper in the case of, I'd imagine, account openers at Standard Chartered that that is the ultimate goal. And you may have heard me say the the company that wins the talent. War will be the one that is able to actualize the statement.

Come, work for us, and do more of what you were hired to do more of what it says in your job, description, description, and less of all the other bullshit, because people spend so much of their time on things that are not what they signed up for. Just because that's how the that's the nature of . That's the nature of how workflows exist and how systems are disconnected.

We're working towards connecting systems on the back end so that we can leverage our human talent to its maximum capacity.

Siobhan Savage: So listening to both of you has been really interesting. And I think the conversation point that you're saying just even taking us through the high level of where you're at. Can we just dial back a minute, though, because I think with the folks in the community that are on on this session.

I think we're gonna have folks that are my CEO is not talking about this. What is this? I've been told to do this.

I have no idea what to do next, or I've started doing something. I think what would be really interesting is to to come back to the principles of what is actually required for someone to to take action in their company today, because what we want to do is make sure that folks can leave this today and take some value out of lessons learned so that they, if they're in that moment, and and I can tell you. most companies right now. I know you're saying from a WPP perspective, it's not about efficiency, a lot of companies.

It's about efficiency and reallocation of budget, not essentially just taking costs out, but actually reallocating budget so that they can par other new business lines or their own AI software or whatever it is, there is an element that cost and efficiency will be important. And the primer for probably priming you is, . Josh version, it would be really good.

If you can give a little bit of context. that slide you have that has the 3 different components of , the 3 different stages of company. That would be a really awesome. I'll see if I can find it.

I'll ping my marketing team while I'm on. I'll see if I can find it and share it while you have. But that would be really good context, because then I think, Josh Newman, if you can then say, here are the key fundamentals in order to start moving and taking action because you are privileged to be upfront on this. and I've learned would be really good to give some practical views on that.

Does that sound.

Josh Bersin: You want to go first.st

Josh Newman: Yeah, I mean, look, I think my answer is straightforward, and it's more underlining what I've said in the past, and I see Whitney posted a question that I think might be somewhat relevant. I think it is utterly essential, AI or not to understand work architecture, to understand how work is delivered in your organization. What are the outcomes that your people drive to?

How does that happen on a very tactical, practical basis? And then, , tied to. That is, how does that translate to dollars?

Because if you understand that whole system, you can influence where you apply technology in the most impactful way, right. If you think about an effort versus impact matrix, you could fairly easily. If you have that chart of of a workflow, you can pinpoint exactly where you you want to start.

Josh Bersin: Okay, thank you. How about if I walk through this real quick? And I'm gonna give you guys example.

So let's take an example that most of you probably understand, and that is corporate learning and development. If any of you work in learning and development. so going to the left, workers are abundant. We get an inquiry for some new training.

We get on a plane, we go visit with the people, we interview all the clients we get to know what their problems are. We develop a bunch of content. We develop a bunch of storyboards.

We prototype a bunch of courses. We build a bunch of videos. We throw it into some tool, we prototype it, we test it, we roll it out, we publish it, we stick it in the Lms, we update the Lms, we send a bunch of emails to a bunch of people.

We try to make sure they take it. They don't take it. So we have a bunch of change management activities to get them to take it.

Then we try to measure whether they took it. Then we try to see if it improved the performance. and then we go back and say, Well, let's hire Jack Per, Jack Phillips to do an Roi analysis. And then and we say, well, okay, that was fun.

We didn't. We forgot to translate it into Chinese. Go back and find a contractor that can translate it into Chinese.

A lot of people involved. Okay, that is the way learning and development takes place in most companies. Or maybe we just buy the content because it's not worth building ourselves, and we go through the same exercise. those are now, and we have a job title called Performance Consultant, a job title called Instructional Designer, a job title called publisher, Tester Lms.

Administrator, analyst, survey, developer, survey, launcher. Whatever we have all these job titles of people that do these things and they end up with an L. And D.

Department that has 600 people in it. If you're a big company, or at least it has a couple of 100 people in it. Now, in the middle of this, in the second model, you say, well, , maybe everybody in this group of people should have cross functional skills, because rather than doing these training programs.

And and in the case of the WPP their advertising engagements as independent tasks in a chain, maybe we could work together. And one person could do more than one thing. And so we build cross functional skills.

And that's what the skills based organizations have been all about is, , maybe I don't need an Lms administrator. If the person developing the course knows more about what the Lms. Does so they can build it in a way that can be loaded automatically, etc.

And that's what we've been working on for the last 4 or 5 years. But let's suppose there was an agent that developed the content for you, and tagged it, and actually put it into some platform that you might or might not call an Lms. And then automatically sent messages to the people that were in that topic area and told them about it and actually measured whether they were consuming it.

Now, what would the these 200 people in L and D do? That to me, is an example of exactly what's going on in every single part of business sales, marketing. content, development, customer service, etc. And the problem that we have that is generally because we set everything up on the task or the job centric model on the left, left, Shaban said. you look at the model on the right, and a lot of the people on the left are hesitant or resistant to implementing it because it threatens their job.

They don't know what is my new job going to be so, they resist it, or they don't really understand it, or they don't really want to understand it, because, , maybe this thing is threatening to me. And this is why so much data is coming out about how worried people are about their jobs. On the other hand, if you get them involved in the process.

Once you move to the right. Now you have super workers. Now you have people that see these AI platforms and use them in a way to add value above them, because in the case of L and D, once you have this new dynamically.

By the way, this is the product we just launched, called Galileo. Learn! That's the reason it's fresh in my mind.

Now, this person running this system can say, Aha! There's some guys over here in this part of the company that aren't getting this, because I can see from the kinds of questions they're answering. They don't understand what we're doing here.

I need to build a special version for them. Let me let me tweak it. Let me add something new, or let me talk to their manager.

So we're all going to have higher level jobs, all of us. By the way, everybody. not just some people. And we're going to be learning how to use these systems to make more intelligent decisions.

And what Josh is talking about in a very, very large company is trying to get ready for that in a more systemic way as opposed to letting the AI system suddenly appear, and then everybody scramble around and figure out who's going to do what? I just tell you. I mean the reason I think this is such an important topic right now, as Siobhan said in the beginning, from what I'm hearing from all the companies I'm talking to.

This is coming from the top down. This is Ceos saying. Hey, you guys, we're going to spend a bunch of money on AI.

Cut the head, count, figure out how to do it. Not let's try these new systems and see what happens. So I think we have to get involved in the reengineering and the redesign of work.

At the same time, we're experimenting and implementing the AI platforms. and the reason that I use the word super worker last fall is, I don't want people to be afraid of this. I, personally, and maybe a lot of people disagree with me. I don't believe these AI things are evil robots coming to kill us.

They're tools that are going to make our lives better. But we have to just be ready to use them and feel comfortable, that we are okay, changing our M's in our careers to take advantage of them. And if you get into that mindset, this is, as Siobhan said, this is the most exciting opportunity.

Every single one of us have to do more work in a more constructive way. It's just hard to do at a very large corporate level, where where there's many, many people involved.

Siobhan Savage: Once you go over a handful of jobs that this becomes at scale a company of over a thousand people. This becomes challenging to do. , in highest and just on on your own.

Josh Bersin: 

What you guys, what Reejig's doing is so important because you can do this at a systemic level and show the company what what the transformations are gonna look , and where to.

Siobhan Savage: Yeah.

Josh Bersin: Yes.

Siobhan Savage: Yeah. And what you were saying was really interesting as well, Josh, was that, as you move through these 3 pillars of evolution of work. And , that's why I'm so excited because that world is real, that's actually, , the train has left the building, so to speak.

I do think there is 2 elements that we, as leaders, need to think about one. We got to help the company boldly reinvent . If you don't, someone else will.

And it's your job. It's your responsibility to do that as a leader and be part of that evolution of company, because the company must survive that, . The second part is, how do you make sure that you are part of that journey, so that you don't leave people behind.

So yes, there will be elements of people getting super workered and amplified. But there is going to be elements of actually, if this rule is going to take out 80% of that person's job. Then we have a high impact moment.

Josh Bersin: Gonna be. There's gonna be people changing jobs. And that means probably losing jobs and getting.

Josh Newman: Always been the case.

Josh Bersin: But that's.

Josh Newman: Welcome to adulthood. I go.

Siobhan Savage: That's the point , that's.

Josh Newman: There's 2 crystal clear examples in our industry, in my industry. Right before the introduction of Google there were no SEO engineers. There was no one thinking about how to optimize certain.

And before. So before Facebook, there was no social media management right before. I guess you would say maybe Instagram, certainly, Tiktok.

There were very few firms, if not individuals, who focused on influencer strategy. And now we have hundreds, if not thousands, of those.

Siobhan Savage: Totally.

Josh Newman: 

Evolution of roles is not a a new thing to your point, I I will say, and I just I see a few questions. Coming in, and we'll we'll get to the rewards and the skilling one. Ryan, I saw your question on. the combination of Hr.

And it departments. I think it's really interesting what Moderna has done, I think, and I was having a conversation with in a form of Chros yesterday. I think it's really interesting to see capability combinations and ownership over functions combined through the lens of people even more so than it.

And Hr, I think that's a fairly novel example, because the expertise levels are at this moment very drastically different. I think the com. I've seen a few examples of Hr organizations also owning corporate comms, corporate affairs. all sorts of external and internal communications, and why?

I think that is more interesting and also more relevant. Not for every organization, but certainly more than the Combo of Hr. And it at this moment is because a huge part of the change management effort which let's be real.

Everyone sucks at change. Management is communications, is transparency is understanding what we started with, which is understanding the cultural, political, social situations that your people are dealing with on a day to day basis. So we saw.

I think it was last week or the week before Duolingo. CEO sent out this note, and basically said, Look, we're going to provide you with some training around AI. But if you're waiting for us, you're screwed , I'm sorry to say it.

But that's just the way it is. You need to figure out how to use these tools. And yeah, we'll help you along the way.

But again, you're gonna learn by using. That's the only way. And our our head of our head of our our platform talks a lot about people only remembering one thing when it comes to change management.

And so the the thing that we have anchored on, or or he has anchored on when it comes to our internal platforms is that adoption is our IP right? Adoption, adoption, adoption. It might not be the best Kpi or the best metric to drive change, but it's 1 that's super crystal clear.

And we know the more people use the tools the smarter the tools get. And it's just this flywheel effect. So figuring out that one. that one metric Kpi message.

You can drumbeat at all levels of the organization from the CEO all the way to line managers is absolutely critical. And , back to the combination of of functions. Hr.

And it I I mean, I love the idea in theory, because we're talking about managing work right through human resources and agentic resources. I think we're a little further away from that happening at scale. Happy to be proven wrong, though.

Siobhan Savage: 

I mean the comments about the Duolingo thing that that gets me because I'm they're in education platform.

Josh Bersin: I'm not crazy about that.

Siobhan Savage: No, and I'll tell you why it's got me. Oh, , and I'm pretty visual as a person so we as Hr. People have no clue about what jobs are coming next.

So how the hell is everyday person supposed to know and have the responsibility. Imagine people working 2 jobs right now to stay alive and keep their family in a house, and then we're saying to them, It's not our responsibility. You go figure that out.

I think that's a complete lack of leadership. In my opinion.

Josh Newman: I think I'll push back and say, I think it's a shared responsibility. And people who are one of the one of the Chros that I was with yesterday mentioned that in her workforce the average usage of AI. Their AI tools was 10 min a day, and I think it was only 30% of the organization or something small.

So even the people who are using it are just dipping in and dipping out. And the reality is the in. It won't be this powerful, , C-suite executive group who is creating a new job.

It's going to be individuals who represent the archetype of the future who are doing their jobs currently, but doing it differently. And that will evolve into these new roles that yet exist. It's going to happen from the people doing the work today.

Siobhan Savage: Yeah, I think I mean more enough reason again, we got to boldly reinvent while making sure we don't leave people behind, whether people go up ahead and but we got to help other people. I think, as Hr. Leaders, our responsibility is to make sure that we're prepared for what that world looks .

And this is why this conversation is so important. Right? It's understanding the work and the opportunity to use AI.

But also, you didn't just use that opportunity for a you looked at it then. Okay, what does that mean? How our work changes so that your team can figure out that was the beautiful thing that you're looking at is that we're looking from both lenses of where is the maximum opportunity for for using this tool.

But also, how do we make sure that we're aware of how our rules are going to change over time? Which is why your story is incredible. Right?

Josh Newman: Speaker.

Siobhan Savage: Well.

Josh Newman: Sorry that just to jump in there, the narrative that we've hammered over and over again is that we're talking about efficiency and capacity unlock for the sake of improved effectiveness. We're not talking about unlocking capacity, and by unlock, we mean, , get rid of a bunch of employees. That is by no means the goal right?

The time saved can, and organically does, get applied to other things upskilling. Yes, sometimes well-being initiatives, but certainly doing more of the higher value work.

Siobhan Savage: 

Yeah. And the direct correlation to that is essentially more revenue, higher velocity, productivity, more. what I mean. . There there comes with that some business element or no one would be doing this right.

Let's be clear, there has to be something for that to happen. I mean, there's quite a few questions in the chat quite a bit on RAM, which I think that's a webinar in itself, just about how to pay in this world. So I think we'll come back on that one.

There was a point I seen early on to Josh Bersin about the super worker, which I think you . Give a little bit of context into that. So it's the super worker company.

And then the super worker, individual. A lot here.

Josh Bersin: For a section.

Siobhan Savage: Yeah, I think that would be really good if you can give that, and I'll look at the questions and see what else.

Josh Bersin: So, eventually these AI things will not be chat bots. They'll be applications, and there'll be much easier. You won't be just have a blank screen.

They'll just be doing things for you. But we're. We're beginning to get a whole bunch of questions from companies along the lines of what are the skills, not technical skills how to create a chat, a prompt but what are the human behavioral skills?

We need to become good users or exploiters of AI or trainers of AI. Whatever the word is. So we're actually working with another company to build a model for that.

But one of the Chros I was with last week at our conference, said. we have a lot of people, and this is a manufacturing company. We have a lot of people in our company that do what they are told. And so they're waiting for someone to tell them what to do.

Train them in the job so that they can do the job as defined. But then we have other people that are problem solving by nature. They ask more questions.

They are more inquisitive. They're just more curious, maybe, and I think these super worker jobs are more of this latter type than of the former type. There's still going to be routine work, and maybe some of the routine work that we do will result in more complex work done by the AI.

But we also need to start, , sifting through and helping people understand , if I think about SEO, Josh. I remember when SEO started. it was stupid. You just type some words into the web page and hoped Google would find them.

Now, it's really sophisticated. right? It's a really complex, sophisticated domain. So the person who just typed in the words maybe didn't understand. the intricacies of how it all works.

Now, if you're an SEO expert. You need to really understand the technology and the use cases and the tools and the implications and how Google's changing and all that. It is a much more complex way of thinking about your job than it was before.

So I think the super worker transformation is going to force all of us to be a little bit more expansive in our thinking and our skills in in every domain. And I know for most of us , if you're a salesperson. You don't want to play around and hack around in salesforce all day.

You just as soon not touch it. You want to talk to people and identify their problems and engage with them. And it's going to free you up to do that and less of the routine stuff.

So there's a human transformation that has to take place, too. It isn't just defining some new job and saying, , here's your new scope or responsibilities.

Siobhan Savage: I think, as well. And and that's super helpful. Josh, thank you.

I think to you as well. Josh Newman, the the summary of okay. If you were telling folks who who are about to go on this journey. and we're just the CEO just called them up and said, we need to solve this problem , what are the things that you would the must have that folks must do about understanding work, , upgrading job , talk us through a little bit about practically, how does someone leave this call and go and do what you're doing?

Josh Newman: Yeah, I mean, assuming you don't have a machine learning engineer just waiting for your call. I go back, I think 3rd time I I've said it. I I would make sure that you are.

You have a deep knowledge of how work gets done. What are the steps it takes to accomplish an outcome that drives ultimately revenue. That's step one.

Most companies don't have that. We certainly do not have that at scale through with any consistency, but we have it in a lot better place than we had it just a few months ago, and and certainly 2 years ago. Some of that is because of the work we're doing.

A lot of that is through the implementation of our technology platform WPP open because it is creating a 2 state of a future state or current state in a lot of a lot of cases. So beyond that it it's fairly straightforward what the steps are. Because, again, if you understand the steps it takes to to deliver something, whether that's something physical or some piece of knowledge that ultimately turns into dollars for your customers or clients.

Then you have a way to pick out what the high low value slash high importance steps are that you can work on either automating or highly augmenting. And throughout that process you'll understand who is touching what parts of work I do. I know.

I know we could probably spend an hour on Comp. And rewards and performance management tied to all of this, but I think I mentioned it at some point earlier. We're we're getting questions from leaders through this part of the conversation, through the workflow redesign part of the conversation, which again, we're not entirely in charge of right.

It's coming from the technology side through workflow integration and things that. They're asking about how we get individual humans and people in roles ready to deliver in ways they haven't in the past or ways that are evolved from what they're doing. Currently, so again, it gives us an end to start talking about things Comp.

Strategy, talent, management, succession, planning, upskilling L and D, certainly in a way that , it might not have been top of the radar for certain leaders that hold the purse strings. So that would be the 2 sentence overview on on the Comp. And rewards, and I think that there was another question around skilling related to that.

Siobhan Savage: One of the things. I think there was a question there from Grace Story as well. Just on what are we doing on the on the reject side, the data itself.

I think one of the things that's really important to clarify when Josh was saying about knowing the work. That sounds pretty broad. But when we're talking about work, we're talking about tasks.

We're talking about subtasks. We're talking about outcomes. And the subtask is a really important set of data right now, because subtask is actually where automation is available today.

So we're not looking at agentic full taking full workflows out right now. So you're taking parts of the task. And you're either deploying out of the box pre-configured, or you're building your own a agents that's typically , really, simply so if if I was to to talk a little bit about what what we've been doing, it's understand the work right down to task subtask, and then the triangulation of the skill to the task.

So , when you take out this task, that these will be the skills that will be impacted because we know a lot of folks. I've had this debate with folks. A lot is people keep talking about the future of work.

And what will our jobs be in the future? And they talk about the future of skills. You will only know the future of skills if you actually impact the task.

And when you bring in AI, you're not only taking out a task, but you're bringing in new tasks that didn't exist before. So it's really important for everybody, regardless of whether you try to stitch this together yourself, whether you use it, whatever you need to understand, work at a deep, level task, subtask, outcome, skill triangulated. And then what you need to do is you need work intelligence to understand the effort level.

How long folks typically spend on those tasks the cost of that task, based on some idea of salary versus the breakdown. And then you need to know about what AI is available today, not a press release, actually the maturity of AI, so that you understand how to orchestrate the recommendation of agent to the task. And then that is what really the data play is that Josh is talking about from the reject side.

Anyway, it's it's really about understanding. Then where to take action. And that's step one is having the data to understand, make work visible, use work, intelligence to understand what's possible and where our opportunity exists, because, . we're not going to transform all of our business overnight, , it's gonna be a long journey.

And, by the way, once you finish one department AI will evolve again, and you're probably going to be able to evolve even more as a team. It's this constant , Josh Bersin was saying at the start of the call, this constant shift that's happening now. And technology is just getting so much better over time.

So this is why, when we talk about this critical infrastructure. you need to have a dynamic model that'll keep this whole thing live and up to date, because it's not you go in and do it once, and we're done and see you later, you're expected to understand where the opportunity exists, and then how to impact that. So that's a little bit about. the the elements of what's required to then take action on orchestrating agents looking at what skills will be impacted because of that. The other thing that we talk a lot to chief learning officers around.

And and Josh person, this is probably something that we've talked about quite a bit. Is that net new task? Who is scaling up all of the folks to enable them to complete this thing that no one's ever done before. , this is where that's gonna be really important to think about. that view as well.

So I can see Sarah has a question there for Josh. Do you want to jump in.

Josh Bersin: Well, I yeah, I mean, I think I've probably talked to dozens and dozens of blue collar or frontline organizations about this, from nurses to restaurants, to manufacturing, to automobiles, and so forth. In some ways those jobs have been going through this for much longer. because they've had automation tools thrown at them for decades, and they've re-engineered how they use them. So. , I think in a in a, in a, in a blue collar, whatever blue.

I'm not sure. Sit where Sarah works, but in a in a in a frontline operation. There's usually a lot of scale.

So there's a lot of throughput. And there's a lot of people involved in in the work. So it really needs to be engineered before you don't experiment as much, because, you have to build these systems, and then when you roll them out, they have to work because there's a whole bunch of customers or products that are going through them. but I've seen it, .

Over and over again we visited, for example, there was a I think it was stellantis plant. Yeah, it was a stellantis plant that was one of the most automated plants that Bill and I had ever seen. Bill's my business partner, and they'd been inter enter, , entered injecting or implement implementing multiple levels of AI based manufacturing for years to the point that now, when a manufacturing worker walks into that plant the equipment.

Not only do they badge themselves in, and then the equipment knows if they're trained, which is common, it's not common in retail and hospitality, but it is common in manufacturing. You're not even allowed to use the machine unless you're trained, and the system knows you're trained. But the system knows, figures out how tall you are, and the equipment moves up and down, based on your height, so that you're not reaching up or down or hurting your back, and that the machine realigns itself for you as a human being.

I don't think chatgpt yet, but it does in a way, , these AI agents. They they should remember who you are and adjust to you. So the things we're beginning to see in the, , white collar work.

A lot of that's happened in blue collar work for years. And then, of course, the , there's an interesting, I think what's interesting about this. If you look at a company Starbucks, for example, then there's a business decision of do you want there to be a lot of automation or not, .

Is it going to wreck the customer experience when it's so automated that the humans are irrelevant? Starbucks basically found it wasn't. The experience of the store had a lot to do with the relationship people had with their barista surprise, surprise.

Siobhan Savage: Yes.

Josh Bersin: Probably going to be true.

Siobhan Savage: Human connection. For, yeah. that whole human touch. One of the things that I've seen in quite a lot of conversations is the this talk about digital factories.

So for those who don't know what the terminology of digital factories is is , think of, Fmcg, Cpg, any manufacturing areas. these huge factories that'll be powered pretty much with AI and robotics. And that's a real thing that's happening in the Us. Right now, there is a lot of that happening under the radar that's not really being talked about right now.

And I think that's not just chat Gpt, that is essentially taking huge factories and turning them into something completely different. And that's where the the understanding of where the clos and anyone who's involved in reskilling is going to be critical mission critical, because that's not a pivot them into something else that is completely taking out a whole pile of work that will not turn into anything else, because robots are doing it that are powered by AI so without being dramatic, that is literally what's happening. And that's we have started to see that coming about now where we're not just talking about understanding.

AI, we're talking about a robotic system.

Josh Bersin: Well, I actually think most of us experience this when we go to the doctor, when you go to your general practitioner. And now he's typing everything into epic, and you're wondering if he's ever going to look you in the face. The poor doctor is wondering why I have to spend all this time typing.

Siobhan Savage: Yeah, exactly 100, but it. But it's true . And I think to to go back to the the point of this discussion. it's not just about bringing in AI.

It's the whole life cycle. Because somebody put in the question, I seen something about how does it and Hr. Play together it will not own this.

Hr. Will not own this everyone around the campfire. To solve this problem, you might have a key leader from one of those teams stepping in to lead.

But you're going to have to have the people team and the it and the AI teams together on this journey, because. , the reality will be that you make any of these changes. It drastically impacts the workforce, and you cannot be hiring people the way you hired them before. If your jobs keep changing, because then you're doing the whole thing wrong.

So I think it's , if you're not already connected into whoever is making those decisions internally, or at least exploring this, my advice to everyone on this call would be, go and find out who is in charge of that AI strategy, and thinking about that on behalf of the company. and then help them with data to figure out where is the best place to start Josh Newman was talking about. Is that whole using data as the GPS for your company to really understand where.

Josh Bersin: Can I make a plug for you guys, Siobhan, for reaching.

Siobhan Savage: I mean sure.

Josh Bersin: Just just I don't know who's on this call, but the as just as Josh said, if you don't know what people are doing in these jobs. You're of no value as an Hr person. because you're just operating at a surface level. So what Reejig does and what I've seen from it.

What we've used it is. It shows you the tasks that people are doing, that you'd never really actually thought about, because when you look at the task lists that come out of Rebig. You're , Oh, my God!

Now I understand what these people are doing all day. and I understand where we can add some value and some automation and some skills that alone is actually missing in most Hr departments. Unless you're a very embedded Hr person working right on the line of business.

Josh Newman: Permission. Josh, you're saying, it gives you permission to go to people doing those jobs and say, is this is this right? Is this a hundred percent, right?

Not. Let's get it a hundred percent right at least for today, even though that will that will evolve.

Siobhan Savage: Yeah. And it's just the the one thing that we noticed on the reason why we built the work ontology and the work ontology for folks who don't know is that common language of work which Hr. And the business share, and it's the task, the subtask and the skill triangulated to that, and it was because we had no idea what was happening in work no one did across all of our customers in our early days, Job.

Descriptions are not work. They're marketing, labeled type things that I don't even know. If anyone knows.

Does that resonate? what I mean it's and and in a structure of hierarchy, the way we built them into job architectures, it just doesn't enable any way for folks to be dynamic to create these super worker. , organizations, or at least have data to understand what's happening.

Josh Bersin: The people that actually in Hr, that know this stuff are Lnd people because they generally get their hands dirty with the jobs because they had in order to.

Josh Newman: They have to move people.

Josh Bersin: But a lot of them are embedded in the business now.

Siobhan Savage: And then the knowledge gets lost. I think that as as work evolves and , we're going to see a pace of change in work coming very fast now, it's not, it's not going to slow down. It's going to get even more aggressive.

And you're going to be asked questions that you need answers to, and you're going to have to help the organization evolve. And the one thing I'd say is to make sure that this critical infrastructure becomes really important. As Josh Newman was saying, really about understanding the work itself. giving you decision-making support.

So imagine someone's in your passenger side seat whispering in your ear what move to take? That's essentially what you need, because you got to make good decisions. And AI is not cheap to make these decisions on, and everybody's watching.

So it , how do we tell you? Where is that best place to take that action? And then what's the outcome to the workforce, because I think we're all agreed on the call no one wants to, .

Put folks at harm. We want to make sure that everyone has access to that meaningful work. We could talk about this with both Josh's for quite some time.

Josh Newman: I know we're out of time. Can I? Can I just end by saying one more thing?

Sorry to interrupt Siobhan. I don't think there is a cooler time to be in Hr. And that's coming from someone who doesn't want to be called an HR person.

Siobhan Savage: Yeah, I agree.

Josh Newman: I'm stoked about the opportunity to add significant strategic value in ways that we were not able to before. So I'll just end with that.

Siobhan Savage:  I agree. And if this whole thing doesn't work out, I'm getting that job where they bring IT and the HR together.

I want to run that team. So I think that would be the best opportunity to reinvent the company. But on that note, Josh Newman, thank you so much for coming here, sharing your learning, sharing everything that's happened.

Thank you. To everyone who has dialed in for those who are listening after the fact, thank you for listening as well. And to Josh Bersin.

Thank you as always, for sharing your knowledge with the crowd. Have an amazing rest of the day, folks and stay safe. see everybody.