00:00  The AI Journey: Excitement to Delivery

Das Rush: Last twelve months, where are we right now? Where are most organizations or the organizations you've been working with? 

Lindsay Pattison: I would say for the last twelve months, we've had three stages of our journey at WPP. So WPP has about 108,000 colleagues around the world working, and we provide marketing services. So the first stage was excitement, optimism, experimentation, all of which is good because, actually, I do know some other companies where, creative companies where some of the content producers are very nervous still about AI and worried about IP, whereas our industry is actually super optimistic. So I think having that optimism is good. So then become very focused on mass adoption. So "forced fun," but we would shut offices for a whole day and really push the training of AI. 

So I would say the first thing was excitement, experimentation, but kind of how people are assisted by AI. The second stage was to move it to more habitual use because it's fine to experiment and be excited, but we need to then be very specific about use cases by function and creating a workflow for our client work across WP that's enabled by AI was one. And then thinking from a business function perspective, so people, legal, finance, how do we think more specifically about functional roles, how they could be augmented by AI? 

So I would say we then moved into enabled by AI, so assisted then enabled, and now it's really about delivery by AI. So, actually, fundamentally, pieces of work, even org charts being delivered by AI and baking that into our absolute offering. And as some people talk about a wave of AI, but I think it's a tsunami of AI about to hit us all. And we are moving into the delivery phase. 

01:56  Mass AI Adoption & Change Management

Paula Landmann: So I would say at the start, we first understood which would be the tools we wanted to give in the hands of everyone. And, of course, we created then our own internal ChatGPT. We agreed that Copilot would be one of them. We also assessed which type of AI coach we also wanted to proceed with. And then, of course, there were more, the specialized tools that we agreed for specific groups for particular needs that they had to solve. 

So I think from GitHub to others that many of you probably use. And then I think our journey was understanding how would we get to real usage. And we started by very intentionally giving licenses to people who used heavily, for example, Word documents or prepare PowerPoint presentations. So we went by use. And that was very interesting because we could see that those people became very quickly our change agents as well. And that evolved into a network now of over a thousand change agents across the company. So starting with that. And then there intentionally, we also onboarded our executive committee members and top leaders of this company and started using in critical meetings. And when we had leaders together, we would use it. We would have sessions around it, persona based. 

So started with a very, very intentional change management, heavy investment in change management with support also of an external partner because we believe that that the start that was really needed for people to realize the benefits and really start using it. And what was interesting is we had a lot of gen AI immersion weeks and all those sorts of things. From the start, we could sense people were trying to understand and intrigued, and we slowly saw a huge change to real adoption in the day to day. And we track usage, right, of tools like Copilot. So we see how we became suddenly the number of hours people use per week and how slowly we became a company with a heavy usage, one of the companies with which, with more active users a week. 

So I think that was the journey. And then, of course, I think as people saw the benefits in business cases, is all, it also became part of how we work. So we see in development, for example, in research that this is part of how we solve day-to-day tasks and work. And that, I think, as more as more people saw the impact and the benefits, everybody wanted everybody wanted access to the tools. Everybody started using in meetings, and then it really became a bit more viral. 

So I would say we started by trying to understand the appetite, leveraging key cohort population to drive to now, like, I would say is really part of the way we work, and there's great use cases in every single area around the company. So it's a big shift. 

04:25  North Star: AI for Business Performance

Hein Knaapen: I think Paula and Lindsay are probably a little ahead of the curve. It's, and I cannot totally understand how that, yeah, how that is impacted by the sort of work you do. So that's really interesting to see. And what I'm seeing with solutions, whatever solutions that are available on whatever part of company's processes, we are often excited about new options, about new stuff. And that's great because once we lose our curiosity, we're going downward. But that, doesn't always make it easy to keep to keep company performance as a North Star. 

And so the interesting thing is and, of course, you don't think your way into new acting. You act your way into new thinking. So if you don't try out, you don't know. I totally get that. And I like everything that Lindsay and Paula gives as examples. And how are you sure or how are you evolving to a point where you are clear, here are parts of our processes where it works and it has value and here where it's only nice to have. I just, what I'm curious about. 

Das: Yeah. And it's so, it's like, a couple things up here in that, and I kinda wanna come to this question too for Lindsay and Paula, like, what you held as a North Star through your initiatives. 

Lindsay: I think the North Star, back to Hein's point, is performance and both, you know, Paula and I work in very competitive categories. So, actually, much more simplistically, it will come to managers with the majority of our workforce. We need a competitive advantage, and by getting ahead in adopting and using AI is gonna help us win and have the business succeed. Simple as that. 

06:06  Game-Changing AI Coaching at Novartis

Das: Paula, you've embedded Nadia within your align initiative, which is explicitly an initiative for managers. And so I'd like to hear a little bit about, like, why that initiative and why an AI coach within that, before we kind of talk about change management. 

Paula: Yeah. So we actually have, they're separate, right? Nadia and Align, but we have both. So Align is a tool that we use for team effectiveness, and it's a super simple diagnostic tool. And what I love about it is it really allows team to rate themselves on habits shared by high performing teams, and then it triggers the right conversations, right, in the in the areas that the team needs. So we are using this now across the enterprise for all sorts of team conversations together sometimes with the perspectives tool, which is also an additional tool. Both are Valence tools, and I would say very, very helpful for us. 

Now coach Nadia, which is the AI tool that we have originally piloted with a few hundred people and now we're expanding to 5,000 people at Novartis, is really a game changer for us. And we've had experience now for a few months, I think almost a year with it across Novartis. And where we see is, and that's part of our North Star. This is really focused on individual development. And in essence, it helps any person who needs support in the moment they need it. So they don't need to wait for a next coaching conversation if they have a coach. They have it. It's really at their fingertips. It's pretty democratized. It creates a safe space for people. They don't have to worry about what they're asking, if somebody on the other end is judging or will do a face of any sort. 

So it's really, the feedback is really excellent. And we've surveyed with measure impact of those managers over time and also people using it. We now even embedded it, for example, in some of our leadership development interventions. We recently had a mentoring retreat for ECN executive leadership minus one, and we had an executive coach, we had Nadia, and the business leader. The three would coach individuals. And the feedback from participants was that many times Nadia was the most effective coach. 

So I think it, and then, of course, people who go through it see the benefit, they want their teams to have it, they really talk about it, and then you see the effect it really creates. And it can be as much as an opportunity for people to stop, reflect, learn, get advice as just truly a tool that hit nudges you to say, have you thought about that today, sending you an email. So that has been one of the most impactful tools, I would say, that we're currently using. 

Lindsay: And I just thought to pick up on that, Paula, because you mentioned it, I think, before. But it's as we think about adoption at scale, it's really FOMO. Right? It's fear of missing out once. And I think it's so clever that you started with your EXCO using the tools because everyone else need to understand that AI isn't cheating. AI is enabling. It's assisting. It's helping you. And then everybody wants to well, hopefully, in a high-performing organization, be better at their job. So whether that's coach Nadia really helping you think about how you have challenging conversations or you develop your career skills or whether that's Copilot, how can you functionally, you know, simplistically curate documents. It's really a way of being better at your job, and who doesn't wanna be better at their job? 

Paula: Exactly. And Lindsay, just to this point, what I found fascinating was we very intentionally also put out some videos of our EXCO members talking about where they use it. So one of our EXCO members said he used to create his own objectives. He actually used Copilot for that and got some hints from Nadia. The usage of the tools after the video went out just went up drastically. It was quite a big deal. 

Hein: Oh, beautiful. 

Paula: So that just shows how role modeling really plays a role in the day to day. Right? 

09:40  Supporting Overwhelmed Frontline Managers

Hein: And how to nudge people. Really how to nudge people. That's very, very nice. Yeah. But here's a perspective. I totally get how you guys, for your primary business, can make use of AI a lot. I was a bit or even a bit obsessed with the role of the middle manager. And so eighty-five percent of our people, they report to our full-time managers. And there's this beautiful book that I can really advise you to read. It's from last year, Bob Sutton. He's a professor at Stanford. It's called the Friction Project. And he says we are here, the leadership of the company, to be the guardians of the time of our people, for them to spend their time to being relevant for the customer. And then he says, in actual fact, we're the robbers of that time because we burden them with all kinds of pet projects. 

And then look at your, at your frontline managers. I mean, dignified, respectable people, often hardly more advanced in anything than the people they lead, and we just, we leave them alone. We often leave them alone with all kinds of practical stuff they need to drive performance today and tomorrow and day after tomorrow. And what I've also experienced over the past forty years is the most overlooked single one, most important driver of company performance is the skills of the manager. And it's from that perspective that I look at Nadia and at AI, and I'm an apprentice and a starter. I'm amazed with the functionality of Nadia, but I can also see how powerful it is because it creates a sort of safe space, if I may, a psychological safety for the manager to ask any questions they may be afraid are too stupid to ask other people. And that builds their skills, and, as a result, that builds their confidence to steer performance. 

Lindsay: And to build on that point about why and how managers are so, they're overwhelmed. Right? And they're on, I think you've talked about them being on the front line. And, actually, what we found, we looked at our use of Nadia, which thousands of people use Nadia across WPP. It's piloted first by VML, who are also speaking at the summit, the brilliant Maree. But, we looked at more senior-level users, mid-level managers, and junior colleagues. fifty-five percent of the use was by managers. Thirty two percent was, senior managers, and then the small minority were junior colleagues because they're overwhelmed with asks of them. And what was also interesting is the amount of things they use Nadia for was the most diverse because they're we're throwing stuff. They're grappling. They're trying to get up the corporate ladder. They've got lots of super tech, tech-savvy, ambitious, Gen Z below them. And these are the millennials, really, struggling with Gen X's on top who've earned their place, super literate tech-savvy people below them who can superficially become very good at everything. 

So I think there's a lot, there's a big burden on managers, and it's our job to really support them and help them move through the organization. 

Paula: If I can build on that, I, yeah. It's interesting because when we also look at topics, things that managers bring to Nadia, we also get a lot of insights of what we can do to support managers much better. So, of course, we don't see any individualized data, but on the aggregate, we see, wow, managers are really trying to understand how to influence that scale. How are we supporting them build this capability? So I think it gives also insights in in those directions as well. 

13:10  Pragmatic AI Tools for Managers in the Flow of Work

And what I also heard a lot from our managers is we're doing this gen AI weeks to support people understand what to do. And the sessions that are really persona-based focus on tools and tips for managers. They have the highest uptakes. Thousands of managers are joining. I think in in total, we had 15,000 across the company. And really, because they are overwhelmed and they want to understand how to best leverage the tools available to them. So if things are pragmatic, practical, they really appreciate. It becomes hard if it takes a lot for them to learn because it takes the time they don't have to learn. And I think that's one of the things we're really taking into account as we build the capabilities and skills of managers, how to really leverage the time they have to ensure they get what they need and can be more effective in their roles. And, of course, they end up being then the role model for their people. Right? So they're absolutely critical for us. 

Hein: Yeah. I get that. And there's the point, I guess, Paula, those are, relatively speaking, micro interventions. So you don't need to go to a three-day course. So you can take ten minutes, and that is, and that is wonderful. 

Paula: Yeah. Correct. In the flow of work and the power of nudges. In addition to the role itself, the way they have to lead their people and what we expect them to do in leading their people has drastically evolved. And this is where we hear from managers that having tools at their fingertips that increase their productivity, help them unlock hours for them to be more innovative is really helpful. And I think tools that help them, again, on the self-reflection, help them prepare, for example, for development conversations. And at times, it's the simple things. 

But I was talking to another manager this, you know, yesterday, and she told me, listen. I had to sometimes think, where do I find again the tool to help me have a difficult conversation or host development conversation? You guys now have not only Nadia who supports me, but also in Copilot, all these prompts that I use. And I'm so ready for it because it's all automated. And then I have it in front of me when I'm having set conversations. 

Lindsay: The key factors and the reasons why we're using Nadia very specifically as a tool to help managers is a democratization of coaching, and everyone talks about the value of the safe space, the testing. There's no better, you know, the reason why senior people often get to the top is simply due to experience, that they've had experiences, and Nadia allows you to shortcut and role play experiences. And so it's really the democratization of what's, of something that's really been a tool that's only been available for very senior people, which is why we love it. Speed and democratization. 

15:37  Measuring AI Impact on Workforce & Performance

Das: What does it take to go from, you know, AI is going to transform your workforce, these general vague terms, to this is how we did it, this is how performance management changed with x impact? 

Lindsay: We paid a lot of attention in thinking about strategic workforce, planning the shape of the organization, the number of colleagues we'll have in the organization, and trying to be very specific about what exactly AI will do to unlock. And I think the more specific you can be, the better. So we've created our own LLM. We put in 6,000 different roles. I mean, way too many. I know. And then we broke down and looked at every single role to say what would be based on our AI tools available now, what would be the capacity unlock? Because otherwise, people talk in very, very vague terms. Someone will say ninety-five percent of marketing can be done by OpenAI. Obviously, I would say that's nonsense. But we did a lot of very detailed work, and we understand there's a capacity unlock. So not necessarily time saving, but capacity unlock from AI of twenty-three percent. But that varies wildly from, say, sixty percent for somebody in payroll to below one percent for a clapboard operator at the start of a shoot because we still need a human to do that. 

So actually being really specific has helped us. And we did another study just very recently which showed it was about twenty, twenty-one percent. And that's great knowledge to have, but actually what we need to move to is then directing and guiding targets against that capacity unlock, one, and then thinking about what do we do with this time saved, the capacity unlock. What are these mysterious high-level activities that we're gonna enable our amazing colleagues to do because we've taken away some of the drudgery of time. So versus having we got the specifics. We have very directional data. We now actually need to be actually slightly more prescriptive on exactly gaining that unlock back, turning that into a commercial model, driving performance, and then thinking about what else we can do. Because if nothing else, we're always super entrepreneurial. So what can we now do versus what can we do more efficiently? What do we do now? What's unique to the human? What's creative? 

Paula: I think for us, what we're also trying to understand is the impact in different parts of the business. In our space, for example, the way operations or technical operations uses AI is quite different than the way somebody in sales uses or somebody in research and development. So being quite specific to measure the impact in the different areas. And I can say, so far, what we've seen is it diverts. It's not the same. On average, what we get reported is that people say, and again, it's self-reported, that they save at least four hours a week with the tools they're provided. And, of course, we see it started by two hours. Sorry. I said four hours a week. Did I say four hours? I hope so. So it's four hours a week. They are, they save with the tools we provide. And we start by two hours a week, now it's four hours a week. So we want to see a trend and see how this increases. 

And to Lindsay's point, I think what we're also focusing a lot is helping our people understand that it helps with productivity, but it also should help them really save this time to do other work, to innovate. And when we did some surveys, so we have now almost 40,000 users of Copilot, for example. And we survey people and we ask a few questions that eighty-nine percent say they feel more productive, seventy-six percent feel more creative, which is something that is also very important for us. And it's part of our culture aspiration. We want people to feel inspired at work. So that is also something that we believe is really important. 

And the last thing I would call out is we're really tracking some of the use cases in the business and very intentionally investing in use cases where there's a clear business need. So for example, in our development space, what we're doing with Copilot is you're really using it to summarize complex clinical trial data. Or we're also using research, so taking raw research inputs and making a very nice, polished presentation out of it. So being very intentional in those use cases and seeing them actually blooming in so many parts of the company is the other piece that I would say we're heavy on. 

So happy to say that moving from AI saved me time to start hearing in the surveys that the AI helped me lead my team more effectively as well. That's the journey we're in. 

19:50  How Will the Best Companies Be Using AI in 12 Months?

Das: What are some of the things we we're observing now that kind of hinted where we're gonna be twelve months from now? And then I'm gonna fold into that, you, where do you hope to be twelve months from now? 

Paula: So if I would describe, the future twelve months from now, I would say that people will stop calling it AI and just call it the work, the work we do. So I think the best companies won't treat AI as a separate stream, as a work stream. They'll really embed into everything that the company does from onboarding, performance, coaching, leadership, but on the day to day of the business areas as well, no matter which part of the business it is. And I think the companies that get it right will really be the ones where we hear from managers that they just don't use the tools, but they really felt and it helped them have everyone around them believe that they could also use and actually use it as part of their day to day in the flow of work. 

Lindsay: I think what companies, including ours, and I think anybody in the audience needs to really consider, not to bring a downer, is not what can be done by AI because almost everything can be done or enhanced by AI or augmented in some way, but what should be done by AI? So I think the other the larger macro piece is the ethics, actually, of AI and thinking about the values of the company, the values of the company that you work for and thinking responsibly about how you use AI in terms of the goods and the products and the services that you offer out. 

So not worried about tools like Nadia are just amazing and super effective, and I—we really hope are gonna help people be better managers, better leaders, and create a happier, productive, efficient, and effective workforce. But there are other aspects of AI that I think we should just be a little attendant to and think about the values we've always held as a business and how that's, how we use AI going forward, not what can it do, but what should it do for our business. 

Hein: Yeah. Yeah. And I'm not sure whether twelve months is possibly a bit too short. In the slightly longer run, I think the companies who will have done better are those that have tightly linked it to value, business value metrics. And, of course, we are now in discovery, and it's great that people get to know it and feel familiar, and that is a necessary and very useful step. In the longer run, if it's not linked to well-defined company performance metrics, it will have been another fad. That's what I'm a bit afraid of. 

Lindsay: It'll be another Metaverse, if we remember that. Do you remember that? I don't think so. I think this one's here to stay. 

Das: Yeah. I think so. And I think we've traced a nice arc here a little bit maybe along the Gartner Hype Cycle for where we are, and we'll see you where we are twelve months from now. Wonderful. Lindsay, Paula, Hein, thank you so much for joining.