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Sandra Laughlin
This session was recorded live at the
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Moderator (possibly Sandra Laughlin or another session host)
2026 ASU GSV summit in San Diego. I'm very excited to have you guys here. We are going to be spicy. I'm warning you now. And I want you to lean in on that spice. Because what we're going to talk about is not going to be a lot of soft, nice words. It's going to be very real on what it is going to take for us to succeed individually, collectively, as organizations, as governments and nations in a world of AI. So we're going to get real big and I want you to lean in. So this session, for those of you who are maybe in the wrong room, this is it. Just in case you need to leave. And what I want, I used to be a fourth grade teacher. You will see this repeatedly throughout this session. I'm going to ask you to turn and talk to the person next to you. And what I'd like you to do is to answer the question of what has the CEO needed from learning thus far? And you can take one of two hats. You can be the rainbows and kittens of what is L and D, or you can be the Debbie Downer and say, what is L and D? But please turn, talk, say hi, introduce yourself and answer this question. What has the CEO needed from L and D so far? Go. All right, I'm going to bring you back. Instead of sharing out, what I'd like you to do is just who picked the rainbows and kittens version? Just curious. All of 3 of people. Okay. Who picked the Debbie Downer version? A bunch of other people. Okay. Fascinating data point right there. Let's just not lean in on that too much. We're going to talk today about the future of learning and we're going to talk about why, at least. I think the conversation often misses the mark. And it's probably a little bit helpful to know who I am for having these thoughts. My name is Sandra Laughlin. I am the chief learning scientist at a company called EPAM Systems. Please raise your hand if you've ever heard of EPAM Systems. Stop. I'm so excited. It used to be the case that I would buy beers for people if they'd heard of us before. So I'm glad that the word's getting out a little bit and I'm going to talk a little bit about this later. But I, before joining epam was a professor at the University of Maryland, and my background was in learning science, which is not teaching. It's what happens in the mind and the brain when people Develop new knowledge or skills or mindsets, how they think differently. And so when I think about this challenge of learning, I'm going to be really focused on that definition of learning as opposed to learning as a thing that we make people endure. And so what I'm going to do is share a little bit about making a case for why I think the discussion misses the mark. And then we're going to talk with the three executives from Pearson who are going to come in and actually stress test some of these ideas and talk about what it will really take, really take, for organizations to meet the moment. And I'm going to ask them to talk about what they're doing inside Pearson and what they are doing for their clients. Because that is what collectively we are trying to solve for. Slido is new to me. So magically, maybe it will work. Please check to see if that QR code does, in fact work. If it does, what I would love for you to do is to, as this is going, react. Right. I would love. Is it working, by the way? Yes.
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Sandra Laughlin
Score.
- [04:07]
Moderator (possibly Sandra Laughlin or another session host)
I would love for you, as we're thinking through this, to say, oh, I resonated with this. This connected with my understanding. Or ooh, that's a new idea. This extended my thinking. Or oh, I'm gonna challenge you. Or this is a challenge for me. That's kind of some of the cognitive moves. Another option is to say what this is making me think about, right? Like is triggering something for me. What puzzles you about these ideas or what you would love to explore? These are just some ideas of what you can do during the session. But like, you know, think about this and respond and put your ideas in Slido. Cause I'd love to be able to talk through them with you. Okay, so let's get into the meat. The business paradigm is shifting very, very, very rapidly. And I'm going to talk a little bit about what I think this means. So first and foremost, everyone's talking about AI. Like it's like the next thing since sliced bread, which is kind of. Or the devil one of the two. But what I think a lot of people are missing in the conversation is the fact that AI is commoditizing as businesses. We are not going to be able to derive competitive advantage simply by having AI because everybody else has AI. So what does that mean? What does that mean? If we can't derive competitive advantage from AI and we also know that AI is eroding a lot of our existing competitive moats, what does that mean? I think it means in part that we are going to be facing a new world of business value created by human potential. And this is a problem for us because in the past, our human capital strategies have not really been about developing people. They've been about hiring and outsourcing or just like, treading water because our competitors couldn't solve the problem either. This concept of needing to actually really develop people, really get people to learn things, that's not common for us. And this means that the motion around learning for organizations needs to shift from compliance, check the box, activities, things that we say to competitive advantage. Can we get people to learn things how fast, how durably? And it's not just learning and learning's really hard already, but one of the biggest things that we actually need to be able to get people to learn to do and do is think. We all know that AI is a bifurcating technology. It amplifies what's underneath. And if you are a thinker, if you are an expert, if you are metacognitive, you can use AI to be dramatically better at what you do. But if you are a novice, if you are not good at thinking, if you don't know how you think, what AI is actually able to do is devalue and devolve your cognitive advantage. So we have to figure out, as organizations, how to solve for that. And so we also need to be moving from an understanding of what people know and can do, from guesses based on I don't know what, to evidence. We are going to need to understand what we actually have from a human capital perspective in our organizations. We need evidence so that we can innovate and intervene against it. So what this means to me, obviously I said this like, probably 15 times already, is that learning is about to become a competitive advantage for the first time ever. And when I say learning, as I previously mentioned, it's not about how well I train people, how many courses I have, what my open rates are, what my NPS score for my courses. It's demonstrably, do people actually know something new? Has their mindset changed? Has their knowledge changed? And very importantly, it's not just that it changed in the short term, but is it changing quickly, is it persisting, and is it continuous? This is a new paradigm, I think, for organizations. And what I want to do is kind of make the case a little bit. And again, I'm putting my learning scientist hat on to talk about what I think is the nature of an organization that is designed at its core to get people to learn and persist and think and behave in New ways. And then I'm gonna again bring the team up and we're gonna talk through this. But let's start with the one job of L and D. Anybody know what it is? There's one job. To me. It is to close a delta. There is a Delta. Everyone has it. And the delta is between the skills that the business needs. And by skills, sometimes we get really bogged down in the word skills. I mean all the things that are important that people bring to work. So that can be skills, capabilities, interests, all kinds of different activities. Just suspend belief on the word skills for a hot second. And also think very explicitly, expansively about what are the kinds of things that people bring to work. We talk a lot about technical skills, which are great, very important. But there's also professional skills. Managing up, managing a calendar. Like all the different things that very new hires do badly, and even some very senior people do very badly. Professional skills. But there's also self skills like grit, resilience, learning how to learn, being metacognitive, having empathy, showing up, knowing nicely in the office, not being a jerk. Right? These are all very valuable skills that we need to develop in people. But very, very importantly is a fourth category of skills, which I think of as org specific skills. This is just like, what is your business? What is your ip? How does work really happen when something goes wrong? Who do you actually go to? These are the kinds of actually very, very important skills, skills that are required that we have to develop in our people over time, particularly the Org skills. Because how work is changing in your organization is something that people need to know and get better at. And the Delta is the numerator is what are those skills that every individual employee has? And collectively, what do employees have? So the one job, in my point of view for the L and D organization is getting people to continuously close that gap between the skills that they have and the skills the business needs them to have. So problem with this is that organizations know more about the chairs in their buildings than the skills and activities of the people who sit in them. So if our one job is to close the Delta and we have no idea what that is, we're not in a great position. And I want to actually ask Omar about this later. Why is it that we know very little about the biggest line item in any budget? It's a fascinating question to ask. The second question then is. Or the second issue or the second? Making a case point is that this Delta is actually very difficult to identify. There's a reason that we struggled with it the first is that the denominator is always changing. What the business needs for any individual to know and be able to do is constantly evolving, and it's evolving even faster now with AI. And that will not change. That goal post will keep moving. The second is that measuring skills of an individual is actually really freaking hard to do. Skills are a latent construct, and what that means is there literally is no way to measure them directly. The best way or the only way to measure skills is to get a ton of bad data, because every data point's imperfect, and from all of that bad data, derive a good signal. And that requires a data architecture that most organizations do not have. And that is a big issue. But I submit to you that it is going to solve for this. Not because of you, not because of skills, not because of human capital, but because that data architecture is the exact same data architecture that is required to leverage AI to operate the business. We're going to ask GP to tell us a little bit about that data architecture and how it gets solved. Now, we know that our job is to close that delta. We know that getting the data from that delta is hard, but it will happen, thanks to GP over here. So the next question is, what are the three conditions for learning? And there are three, and they are. This is universally understood. This is like the most simplistic way of defining the highly complex learning sciences. But there's three of them, and the first one is transparency. And again, thanks to gp, we have solved that problem. We now know we can tell our employees what are the skills that they have relative to the skills that they need. Okay, let's just assume we're going to suspend belief. That has been solved. The third element of conditions for learning is one that L and D loves. It's the support stuff. It's the stuff that we do to help people close that gap. Courses. And we'll talk about informal learning opportunities as well. But there is a piece in the middle that is missing. Does anyone know what the third condition for learning is? Out of curiosity. Or guess. Struggle. I like that we're gonna hang out more. Practice. Motivation. Who said that? Can I give you a gold star? All of these things are true. Motivation is the. If I could pick one thing that I could solve for in all three of these things that we build. Motivation. Because people cannot be learned at. Learning is an internal, constructive process that happens in your mind. If you don't want to learn, you won't. Mostly. And what's fascinating about motivation is that this is the thing that we are least equipped to solve for. And if you are an L and D, you know that there is a. It's called a push economy. We push content at people and like, hope for the best. And most people don't take it up. Not because it's not good. It can be amazing content. It can be amazing, perfectly designed learning experiences. But if the individual is not motivated to learn, it doesn't matter. Even if you force them to sit through the experience, it doesn't matter. Solving the motivation problem is the number one challenge, I think, of this future that we're all about to face. But luckily we're going to have. Our CEOs are going to solve for this. Don't worry, okay? Don't worry. We're going to assume that the CEO will want to solve the motivation problem. We're going to talk about and Omar is going to lean in, explain exactly how that's going to happen in a second. But let's assume. And again, I dead serious. I think this is really going to happen. I believe that this is going to be one of the most critical things that companies are going to want to solve for. And I will explain that later. But let's just assume that we have solved for this. Now we have transparency, motivation and support. All right, we're doing pretty well for ourselves. What's next? How do you get people to learn things in formal settings? There's four elements that I see. The first one is content. It's what everyone talks about. We talk about learning. It's always, always about content. But there are three other elements that are essential for learning and someone said one of them earlier. Reflective, practice, feedback, Timely expert feedback with those two things plus prior knowledge are the number one predictor of learning. It has nothing to do with content. In fact, most learning does not happen in the context of real content. It happens from doing stuff. So if you have enough refractive practice and, and enough feedback, you will learn. And then the fourth element is transparent results. Remember, the transparency part is really people need to know where they are relative to where they need to be. And so these four elements together make up what effective training really looks like. Yet in L and D organizations, we have pretty much exclusively focused on one of these elements, arguably the least important one. So we're going to ask Ali, why the heck is that? Why, as professionals who, by the way, know that this is true, we know that practice and feedback makes a difference. Why is it that we have focused almost exclusively on the content side of learning? We'll discuss.
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GP (Technology Representative from Pearson)
Okay,
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Moderator (possibly Sandra Laughlin or another session host)
I said it a Minute ago. I'll say it again. Most learning does not happen in formal contexts. The vast majority of what people learn all day long happens in a bunch of other places. This is my way of trying to articulate this. It happens in social engagement. Humans are very social creatures. We learn from talking to each other. We learn from observing each other. We just learn from being together. We learn a ton from teaching other people. Teaching other people forces you to actually process information differently and then you have to communicate it. And that in and of itself is a deeply reinforcing learning experience for the person who is teaching. Of course, there's reflection. We learn, hopefully from thinking about what just happened and what went well and what did not go well. We learn from investigation and research. We learn from, like, looking stuff up, right? From asking questions to ChatGPT or whoever. We learn from vocational activities like this, being in this room, following certain people on LinkedIn. We learn from engaging in vocational activities with people who do work similar to us. And we learn very critically from experiences, especially stretch assignments, when it has a reflective element. Right? These are. And everyone's like, nodding like, obviously, yes, we do these things. The question is, if these happen all the time, why aren't we supporting them or making them visible or documenting them in any way? Right? And what's crazy is that these informal learning things happen all the time. They happen. I mean, I'm in an IT company. They happen a ton in the technology organization very naturally. And so I was going to ask GP to tell us a little bit about some of the informal learning activities that happen within Pearson in his area of the organization that have nothing to do with L and D. There's a ton, and everyone has them. So we have laid out the five things that I think are really very, very critical to success for building learning into the fabric of organizations. And I think that there are direct implications for the CLO role and the L and D organization, including to support formal training beyond content, to really, really, really double down on practice and feedback and documentation. The second is to teach employees how they think and how they learn, because I'll tell you that most of them have no idea. And if they don't have any idea of how they think and how they learn, it's going to be really hard to partner with them, to think and learn, particularly as AI makes it a lot easier for them to not do either of those things. The third is to surface, not drive necessarily, but at least to surface informal learning opportunities. That should be something that we do as a matter of course. If we know that that's how learning happens. Part of our job is to help it happen more. The fourth one is to measure skills. And again, very broadly defined, not just after training. First of all, let's start by measuring skills after training. That would be number one. That would be great. But if we just did that, we would be very, very much limiting the understanding of what skills people have. Because again, so much learning happens outside of training contexts. And if we are only capturing skills after training, we are not capturing the full picture that we need for both individuals and organizations to understand that. Delta so we can close it better. We want to reveal barriers to actually working in new ways. What I mean by this is, or a business will come to L and D and say, hey, we have this problem. Build us some training. And L and D is like, sure, we're going to build you some training. And we build the training. First of all, we have no idea if it worked, but that's okay. Let's assume that it does, and we send people off on their way. But you know what? The problem could have been not knowledge. It could have been misaligned incentives, bad processes, stupid tools. There's so many different things that actually drive behavior or lack thereof in organizations. And if we treat all of those behavioral change problems as a knowledge problem, first of all, we're probably not going to solve them. But if we can actually measure what people knew before, what people know afterward, and they have actually learned and the problem still exists now, we can point to these other areas as issues to solve. So instead of just solving for learning and thinking that that's enough. We can understand learning as a singular variable that explains behavior. We can control for it, and then point to the business, other areas for them to focus their attention on to actually get people to work in new ways. Does that make sense? And the last thing is, this is a big one. It's to cultivate the talent pipeline outside of the organization. Again, if we can't hire the people that we need, we also can't not hire them, because that's a big problem. We need junior talent. And if universities are not going to be prepared as rapidly as we want them to be to develop the kind of talent that we need, the implication is that it is on us as learning leaders in enterprises to go outside of our boundaries and actually develop that pipeline of talent with or without universities. Cause otherwise we can't continue to drive our business forward. And that's a big, big problem. Okay, so that was making my case. Anyone feeling a little overwhelmed about their job at the moment. Here's the real paradigm shift that I think we need to talk about. The session was called what does the CEO need from Learning? Now, I would say that is the wrong question. The question is, what does the learning leader need from the CEO now? Because no CLO in the world can solve all of those problems, because those are not problems with the L and D organization. Those are problems with the operating model of the business. And if we actually believe that learning is going to be a competitive advantage in an era of AI, we cannot just send learning to the L and D Org and just expect magic to happen. That's not what is going to work. Instead, we need to think about learning as a systems problem and address it as a systems problem. And the reason that, for what it's worth, I came to my company out of academia was because it was the only company and I still the only company in the world that I have ever, ever seen that has solved all those problems. It's a long story. I will not tell it. I'm not selling you anything, so don't worry. I left academia because I found a company who had designed the entire operating model of the business to get people to learn and think and work in new ways and persist all the time. And what I am doing passionate about is sharing what that looks like, because I think that it is the operating model of the future. It was built 30 years ago, like when I was in middle school, so I didn't build any of this. But what I can say is that there's this great quote which is, the future is already here. It's just not evenly distributed. Have you ever heard that quote? That, to me, is my company. And I share this. Again, not selling you anything. I share this just to help paint a vision of the future that I think we can all agree is optimal for humans. I think it's also optimal for business. And the question then becomes, well, how the heck do we get there? So with that, I think I said all of that stuff. I would love to bring up my friends from Pearson to help actually solve this problem within like the next 30 minutes. Great. And have you kind of. Again, we're going to think through this as a systems problem, as an operating model challenge. And what I would like again for you to do is go back to that slido thing, drop some questions in there. We're going to talk about them, your questions. But first I want to get a reaction from the team. And here's what we're going to do. So again, we have Three different perspectives here on purpose. We have Omar, who is the CEO who is thinking about competitive advantage both in terms of his own organization and for his clients. When he hears this whole thing, what is he thinking? We have Ali, who is the chief HR officer who is thinking about people in her organization but also thinking about the people in her clients organizations. And we have GP who is here to represent the technology organization. This is a data and technology problem. What is he thinking? You're solving all of our problems, right? Like I said you were. Okay, there we go. Perfect. So we're going to just have a very free flowing conversation. I would love to start by just asking. Yeah, how was that guys? How did that go?
- [27:31]
Omar (CEO from Pearson)
You're a tough act to follow. So I have to go back to one of the points around blended learning and this idea that you can learn a lot from LinkedIn and I have been a fan girl of Sandra and for, for a while. But, but I think you set up, you set it up quite nicely that you want this to be a very provocative and, and kind of like instigate some really good discussions. And I think you set that up quite well. And, and we're going to jump right in.
- [28:01]
Ali (Chief HR Officer from Pearson)
I mean I'm going to just say I've been on a couple of panels this week and you know, you all know the moderator makes a difference and I'm sure that the audience quickly realizes, okay, this is going to be a great moderator, even if she is a cheeky rascal. So you know, pick some of that up.
- [28:17]
Moderator (possibly Sandra Laughlin or another session host)
Okay, but let's push back because really we're talking like this sounded cute. Their slides were adorable. Right? Thank you. I made those myself. This is a big freaking challenge. Is it even possible, Is it possible for incumbent organizations who are incentivized to optimize for the next quarter not solve any of those problems? What does it mean? Is it possible? And if so, what's the thing that really kind of makes you hopeful that it could work? So two questions.
- [28:50]
Ali (Chief HR Officer from Pearson)
I mean, so I really love what you painted out there. I think it is way harder than many people perhaps may feel or realize. I'm not sure what the audience thinks, but because at the core of it, I mean you said that the operating model, the business model is not right, not set up correctly. Changing that is non trivial. I would wager that culture is a huge, huge topic. I mean when you talk about motivation. Yeah. I mean I hear all sorts of things from the workforce on a spectrum from. I'm super eager. Help me learn to just leave me Alone. And there are some fundamental cultural things that you have to grapple with in that now. The reason I think we're going to have to deal with it. You know, at the World Economic Forum earlier this year, I was running around all my CEO colleagues and saying, listen, in the olden days, you'd have said, I'm going to fire a load of people with this new technology and then hire the new ones who can do AI. That is not going to work. And it will not work because A, there are not the people, you know, with the demographic changes happening, particularly in the Western world, is we're running out of workers. That's actually, that's a real thing. And secondly is even if we had the people, they don't have the skills that we're looking for for the future. It doesn't exist because this thing is so new and it's growing at like a vertical rate, like Xbox exponential. So companies have to deal. And so the argument I was making is that that means that the CEO now is the Chief Learning Officer. That's the change. So to make the changes that you're talking about, the CEO has to profoundly change how they think about shaping the workforce in partnership with technology and HR and other leaders.
- [30:16]
Omar (CEO from Pearson)
I think to Omar's point, but also what is a really important starting point and it is a difficult one. And I like to think of myself with Omar and certainly with GP as we're sort of capability architects. And what that means is I think before you actually hand off the focus around where you want the learning to go and to really invest in, you really got to understand deeply what are the roles that you need in your organization, what are the skills that are required for those individuals to be. Be successful in those roles. And then you can be much more intentional and you can aim the learning at the upskilling of the roles that, you know you need. And it is, it is something that Pearson had to tackle and it was very difficult. We had in our organization, we had 1600 roles, we had 5500 titles. And so of course, like learning was dispersed and ineffective and we weren't able to let it capture the value. What we did is we took the 1600 roles and we got super connected around what are the roles that we need that really align around the capabilities that Pearson needs to be successful and then got incredibly precise around the skills that are required for those roles. We know too that those skills have half lives and they're changing all the time. And I love what you said is we have to be more systematic with the career architecture to not have something that's static, but much more of a system that works in conjunction with learning and with the business so that you can actually close that skills gap.
- [31:56]
Sandra Laughlin
And I think what you said at some point was very important. So in a world where we really believe that our workforce and the skills that they develop is going to be the real differentiator in the world of AI can do everything, the biggest problem is how do we measure the readiness. And in the past, all my colleagues, including me, were really focused on let's develop a tool or provide a tool for hr. And then the celebration happened when we went live for the new tool and then we forgot about it. And it's a paradigm shift. Now we have to partner with HR to understand how do we measure the skills that are required for the organization of the future. How do we measure how our workforce get to that level so that we can know where to invest and which people to reward for their upscaling and learning. Because today, let's be very frankly, people are struggling at work with I need to get my job done and this will be the measure at the end of the quarter if I achieve the OKR and then my career path and so on, or should I invest in learning? And this is always losing against getting the stuff done. So we are constantly fighting and the motivation and the friction of starting learning something new, it's super high. So as technologists, we have to start cooperating with the chros of the world, making these tools, first of all, much more usable from the users that want to learn more and connect all the data points, like you said before, all the signals that will come from different places, they have to converge into a single place. And we can call it skill wallet or whatever we want to call it that accompanies the journey of the learner of the talent across the company growth so that we can invest in them and reward those that actually want to learn more and actually achieve to learn more.
- [33:46]
Omar (CEO from Pearson)
Doesn't he sound like a clo? Like this is the brilliant part of it. I mean, it really is where the partnership's going. I mean, to have a partner like GP thinking about what is needed for the organization and the way that like you're designing for the customers, but it's also really having this.
- [34:01]
Ali (Chief HR Officer from Pearson)
What Ali hasn't told you is that her team, you know, down in the bowels of hr, started building agents for our people to help them navigate the career architecture that Ali described. So now in the teams window of every person at Pearson, there's a little agent called Kara, a career architecture agent. And you can go and interrogate it in terms of what do I need to learn to progress in my career? What courses should I take? What does it take for me to be successful in this role? How do I progress to the next role? What does it take to get a promotion? All those questions that people care about deeply. Normally at work we're trying to expose it to the organization and it wasn't actually an IT driven thing and it wasn't a top down driven thing. It was folks in Ali's org who just went and built it.
- [34:43]
Omar (CEO from Pearson)
Which I think makes me sound like a technologist.
- [34:46]
Sandra Laughlin
We should swap seats.
- [34:47]
Omar (CEO from Pearson)
But I do think that is, I mean you hear this sort of power couple conversation going on and I think that is really an important, I think paradigm shift. Especially when Sandra, you talk about the data and really how we can think about the data and the domains that we need to kind of map that data to, to get the real signals. And it's really cool.
- [35:09]
Moderator (possibly Sandra Laughlin or another session host)
I'm going to actually just push on my own thought. But with you guys, okay, I'm making the case that human capability in an AI world matters. And not just that it matters. It matters enough that we would blow up our systems the way that our operating model works in order to achieve it. Now I'll tell you my rationale, but I'd love to hear you to say that doesn't make any sense, Sandra, or for you to give your own rationale. But here's for what it's worth, here's mine. If AI is commoditizing, that means everybody has the exact same thing. Competitive advantage disappears. Aside from your existing moats. I'm going to just be very clear about that. Every company has existing moats and they are eroding, but they're not disappearing. My argument is that humans provide insights on top of AI that feeds that AI. And very critically that the human capability in combination with the data of your proprietary data on how you work, how your customers think, what skills your people have, those two things together are the next, I think competitive moat for organizations. But that's a pretty high bar and I mean I'm making that up right now. I'm super curious to hear your feedback. And then what going to open this conversation up for everyone to share, not just about your thoughts on AI and human capability, but on the whole concept. Let's just start like you guys are in a people business, a learning business. Do you think that this is real or is that more like pie in the sky, like people thinking.
- [36:48]
Ali (Chief HR Officer from Pearson)
I like to try and focus on what we know and distinguish that from what we don't know. I mean, I like your thoughts. I think it's very nuanced. So if you say, does having an AI model differentiate you? The answer is no, because the folks building the models are trying to make them available to everyone and the price is sort of, sort of going down. And so in theory that won't differentiate you. So I like to look at and say, well, what happens in different industries and you know, there are different margin structures in different industries which normally reflect the level of competitiveness and the level of, let me call it moatness. So very high margin industries have a higher moat. The super competitive industries have razor thin margins. And what distinguishes a winner versus a loser in those razor thin margins, like think retail for example, logistics, those sorts of places actually is execution. And so you can still distinguish yourself by taking the common model that everyone else has by executing better with it, faster, quicker. So that's leaning into the innovation and moving quickly is always going to be a winning play. It always was with, you know, other technologies it will still be. So I think that that is the case. And so in that industry you, you, you can be a winner. But yes, you're right, if you have domain knowledge, if you have domain IP and that's already commanding higher margins, which is a clue that there's some moatness in that industry and then you apply AI to it, you could probably turbocharge that. So I think that is something that will happen.
- [38:15]
Omar (CEO from Pearson)
It, it might sort of add onto what Omar's saying, but I'm almost thinking about, because you brought it into the context of human capability and what Omar was describing at the role level, it might just be your role in understanding how to use AI and build agents is to really be super sharp on execution and move fast and better. And it might be for other roles in engineering and in GP's role, it's like move us forward and develop the products that we know we need for our customers. And that's a whole different place. So I think you have to start to think through back to like the expectations of our people and the roles that they have in terms of what is the sort of minimum expectation of use of AI and identify the executors or the creators, et cetera, and be super intentional around that development in those skills.
- [39:06]
Sandra Laughlin
And I think from a technology point of view, I agree that at some point, let's say the AI will become commoditized, will become an Infrastructure like the Internet is or the mobile phones are or the cloud computing. These have been really revolutionary technology that have brought the tools for companies to build their business on. Now people have built the business on top of these tools, and the same will happen with AI. So my philosophy and what I tell my teams is that AI is not taking your job, is giving you superpower to do something better, faster or different or innovative that you couldn't have done before. I wish I was a student now at this time would be like, you know, a kid at Disneyland. Like you can do anything in one hour. When I was younger, I mean, you had to spend one day to install everything you needed on your computer before you could start coding. So it's really amazing what you can do with technology, but it's about people, how we use this to actually go faster and do stuff. Stuff more innovative that others couldn't do.
- [40:06]
Moderator (possibly Sandra Laughlin or another session host)
There's a lot. We can talk about this for days. There's a lot in here. But I want to make sure that we give you guys time to join the conversation. I think I have. I never used Slido. I should have probably practiced before that happened. Yeah. Or which we can just. You just talk to each other. So we have a roving mic, we have a couple of them. Love to. Again, get your feedback, get your pushback. Right. This is supposed to be a provocative conversation. It's probably a little bit overwhelming, but again, what it connected. What did extend. What questions do you have? Let's chat.
- [40:48]
Audience Member / Panel Questioner
Well, I'm tempted to be really provocative now, so I'll put my former employer a little bit on the spot here. I started my career at McKinsey and my former employer back in the day, you know, I'm the Gmail generation. We used to use Lotus okay. To check our emails. Our head of IT, for whatever reason, thought it's more secure. So when you would send a client an email, you have to press synchronize. And one or two times my partner didn't get the deck because I didn't press synchronize anyhow. So, you know, jump forward. Many years I've worked at Google Meta, all of these fun places, and one of the things that I've noticed is that the leaders of the organization and the culture always gets in the way. Now I'm the founder of a startup, and my rule with my team is if I don't have a fire to put out every week, you're not moving fast enough. Like, your job is to give me fires to put out. My job is to Give you fires to start, so to say. And you know, this just, there's a diametric difference almost in the culture and the speed. So when we go and sell to organizations, they're just, they're either moving at the speed of light or they're moving slower than a tortoise. How do you see Pearson shaping the organizations that they're looking to support in such a world where you're now interacting with companies moving at extremely different speeds, needing to interact at extremely different speeds? And how does Pearson itself do this? Now I'm really going to put you on the spot. I've met people at Pearson and explained to them our technology, how it's 10 times better. And they're like, oh, it's fine, I'm just going to use Zoom. And I'm like, dude, you're a learning company. Like, shame on you. At least learn about my solution. And they don't, which is embarrassing.
- [42:46]
Ali (Chief HR Officer from Pearson)
I mean, so thank you for the question. Actually, in one of my very first notes to the Pearson people, because I write periodically to the folks, when I arrived early on, as I said, I didn't feel that we had enough of learning culture. That was like back at the beginning of 24 when I joined Pearson. And how can you not have a learning culture if you're meant to be helping people learn? So we're pushing very hard on that. Like one of our core values now that we're beginning to explain to our people, help people, is around curiosity. But you're right. Like, I think with any company there's a bell curve of performance. We've got some amazing, incredible forward leaning, innovation leaning people. And then we've got some others who probably feeling, as Sandra said, like a little bit overwhelmed and like we need to deal with that. Actually, what's happening in Pearson right now is the tech companies are coming to us and saying, help us help our sellers learn AI, help us help our partner organizations learn our new products and help us help our customers use our new products. And they're coming to us because they think we're actually the best at doing that. And so, and we're working on it. It's hard because at the heart of your question is culture. And that even applies in the world's best companies. You know, even if you go into an anthropic or an OpenAI today, the new paradigm for how product and engineering and UI and all these things work is unknown. And we're figuring it out together. And so I'm actually very excited about this. But your push is good. So thanks.
- [44:13]
GP (Technology Representative from Pearson)
Hi. I think a lot about how to motivate and train my folks to get into learning AI. One of the challenges that I face and something that I've heard a lot over the last couple of days is, you know, there's some people who have environmental concerns or don't want to do it. And the, what I've been hearing is just acknowledge that. And so one of my questions is, how do you, what do you mean, just acknowledge that? Like, what do you, what do you actually say to that person to get them to maybe not change their mind, but, like, understand that this is something that's happening? And also how do you motivate people who have, like, deep skepticism in terms of like, job displacement? Right. And I've heard throughout this conference, oh, yeah, jobs aren't going to go away, but like, you know, you can, we can say that, sure. But like that, how do you navigate that conversation with like, the people who are, you are trying to motivate, to learn this thing that have these types of skepticisms?
- [45:06]
Ali (Chief HR Officer from Pearson)
Do you want to talk about the sustainability?
- [45:14]
Omar (CEO from Pearson)
I mean, you get the same question that we get. And the thing that I actually have to first acknowledge, which is Pearson is a learning company and there are a lot of learners. So I think we almost consider ourselves at an advantage. But, but your, your point around what I would call like the resistance. And there's a sustainability piece and we do get that question. But the resistance around, I, I just, if I, if I learn it and I don't do well with it, or if I don't learn it, then my job goes away. I think what we're trying to do, especially when we think about the visibility, the skills that you need, and not just the skills you need in AI, but the skills that you need to actually adopt new technology and what that will help you with, to be more like, how that will help you be more successful. But what I would call the psychological safety is really top of mind for us. And back to curiosity as one of our values, as well as being customer focused, we know that we're in the business of helping our customers adopt the technology as teachers, as students. So if you can do that connection around how it can help them with the customers, that will go a long way as well. So I don't know what industry you're
- [46:27]
Ali (Chief HR Officer from Pearson)
in, but yeah, I mean, let me pile on. I mean, you're asking a very tough question, and I'll tell you honestly how I think about it. Are there any media in the room? Any investors? I'm just Checking here. Okay. In the 1990s there was a wave called RE engineering and it basically said, look, corporations were constructed in the 1950s to have these big layers of middle management and bureaucracy because that's how you needed to manage global scaling, which was happening. And in the 1990s they came along and said, well, that's not efficient. Now you've got modern technology like ERP systems and you can re engineer the processes and engineer a lot of cost out of the company. We're about to go through another giant wave of RE engineering where people look at their processes and figure out where can I plop AI agents into the process to do things and how do the people and the agents work together. That is a profound change. And so yes, some jobs at the margin I think will just go away because they'll be fully automated, but all jobs will be redone, reconfigured with AI. And that's a lot of change on humans. And so how do you encourage the humans to change? And again, I'm not going to tell you anything you don't know. There's like the carrots and then there's the other kind. So we work hard to put the resources in the hands of our people, to encourage them strongly to learn the new resources and get with the program. We make heroes of the people who've leant forward and done stuff leading into the innovation. And then for the ones who are not, we're going to remind them and say, look, if you are doing a role and GP sitting next to you doing the same role and GP is good at AI and you haven't bothered to try and learn, probably you're putting yourself more at risk. And I believe that. And I'll say that in any forum that for each of us as individuals, if we stop learning, I think we start dying. I really believe that and I think so. We all have to lean into the innovation. We all have to grab these tools and figure out what they mean and how can we put them to good use. I think technology always can be double sided, but if the good people put it to good use, you can make amazing things happen. And that's the push that we're trying to make.
- [48:40]
Omar (CEO from Pearson)
How are you measuring value creation from an investor perspective or from a company? So how are you measuring value creation then with these new metrics and systems from an investor or company perspective?
- [48:56]
Ali (Chief HR Officer from Pearson)
I mean, as far as I could tell, the investment community haven't changed their logic on how you measure the value of companies. Like are you growing free cash flows which is basically a feature of revenue and cost and risk and tax. That's what it is. So those things are still there. What we're strongly believe in and what we're working on is that the companies that will get the best financial outcomes will do so because their people have been invested in. You cannot succeed in the future by not investing in people and human learning because the conversation we just had about the modern re engineering requires humans to do things differently and they need to learn a lot. So actually we're finding, and I said this to the gentleman over here, that AI is a huge tailwind for us in terms of the demand for reskilling. And I think that's going to just. And it's starting in a crescendo in the tech sector because that's the most impacted. It's going to go to all segments of the economy and we're seeing signs of that already.
- [49:55]
Audience Member / Panel Questioner
Next question. So the future is here, but it's not evenly distributed. And as a technology guy, I look at this issue through a lens of technology problems probably. Next question to GP How Pearson does help clients enable data layer to be prepared to support these dynamic architecture roles when you need to gather signals and you need to reflect in form of skills that need to be acquired.
- [50:24]
Sandra Laughlin
And I think there's a couple of answers to this question. So first of all it's a data architect. So how do we model such a soft things like skills into a data that can be measured? And this is all about the data architecture. So we have to have a taxonomy of skills that map to the occupation so that we can measure across the board in the company but across the industry ideally standardized so that we can really start collecting signals and put it in each of these boxes. Right. So one thing that we do with fadm, one of our products is really to do this mapping between occupation and skills. But then how can we populate the skills the value within? Today most of the companies rely on self assessment and I mean we know how when we self assess ourselves, I mean it's probably optimistic or at least it's not generalizable across the board. So can we use techniques and AI? It's helping us there technology like ambient assessment assessment so that while you do your job, you actually collect evidence. While people do their job, the system collect evidence and signals of what they are good at and what are the things that they need to improve further. And we have an example of a product that we launched now recently, the Communication Coach. It's a plugin or it's an application installed on the Microsoft Teams ecosystem so that when users have normal calls like we all spend a lot of time in every day, at the end of the call, they get a feedback in the chat that tells them how well they were performing in terms of communication. So this is helping people with low proficiency in English, for example, to correct grammar mistakes or pronunciation or articulate things better so that they are more impactful in the communication as well as giving feedback on how well you are, for example, giving or receiving feedback or engaging with the crowd or with the audience and building up on ideas. These can be all signals that we can place into the screen skills ontology map that can give a great help to the L and D managers. When you see it from the other side, anonymized data of your organization, seeing what are the skills emerging, what are the skills needed in that specific department or country and then you double down again with learning in the flow of work, type of activities. So we bring learning where people already are. So we bring learning activities into the chat of the Microsoft Teams in this example, where we provide quizzes on grammar or practice pronunciation or for example, role play scenario with an avatar where you can practice in a safe space how you do better at communicating. So these are techniques that answering also the gentleman questions before we can motivate people to learn faster or to learn even if they are not motivated, just by removing the friction of them going to a learning platform to learn. But learning moments happen when you already are.
- [53:21]
Audience Member / Panel Questioner
Thank you again. I have a question that may be a little more specific, but with an educator on the panel, what role do you see with all the change happening, pressures on margin, trying to make human capital as a competitive advantage. A lot of this discussion was focused in the L and D space. What do you see the role in this ecosystem of institutions, particularly higher ed institutions, what role can we play in helping both facilitate and accelerating the change?
- [53:54]
Moderator (possibly Sandra Laughlin or another session host)
I think we probably all have thoughts on this particular topic. I'll just start by saying what I think AI is revealing is a significant both opportunity and challenge right now when it comes to human cognition. If we are offloading cognition to AI, that means that we are going to collectively get less competitive against it. This is a downward spiral of doom. But AI also, if it's used properly, it's amazing. It can help us. It can help us learn to think, it can help us understand different conditions under which to apply different types of knowledge. And so if I could ask higher education to do one thing and not just higher ed, K12 as well, I would Love for us to really double down on teaching, thinking, making it visible, giving feedback, lots of practice, because really the technology will keep changing. We don't know what the jobs of the future are, we don't know what the jobs of tomorrow are. But we know that if humans are going to be doing work in the knowledge industry, it's going to require us to think. And as a society, we need to get a lot better at doing that. And also making that skill signal clear through validation, through activities and credentials that allow us to see as employers and individuals, what are our skills as it relates to cognition, for example. Does that make sense?
- [55:24]
Ali (Chief HR Officer from Pearson)
I just want to pile on. So I agree 1000% with everything Sandra just said. So I've got two boys, a 17 year old and a 21 year old, and they're exactly in that moment where they're looking at like, you know, what is the future and like jobs. And so the push that I have on them is there's three things that I would love K12 and higher ed institutes to fill them, their brains with and everyone else that three things that you need for the future. One is agency, the ability to go and solve problems, first principles, hustle, don't take no for an answer. Get stuff done. Like that's all about grit and resilience. Two is learning velocity. So Sondra talked about learning to learn skills, all those behavioral, metacognitive things, things that you all know we can teach people, but we do not. That is probably like the most critical skill for the future is the ability to learn. Because what you need to learn is changing so fast. And then the third one is eq. Humans, like at work, you have to be with people and you know, people. The Silicon Valley guys love talking about billion dollar companies with one person. I mean like, great, good luck with that story. I mean, so it's like at the end of the day, you have to be empathetic, you have to be able to listen well. You have to be able to work in teams, you have to collaborate. And so agency, learning, velocity, eq. In England we call that ale because we like beer.
- [56:36]
Moderator (possibly Sandra Laughlin or another session host)
But anyway, we have, we have seven seconds. Oh no, we're over by nine seconds now. Do we actually have time? No, we're done. We are done. Sorry. I got the message. You guys, this has been awesome. Thank you so much. I have our LinkedIn profiles here if you're interested in, interested in following up and continuing the conversation. But thank you so much for engaging and have a wonderful rest of your conference.