Driving change with AI skills
What if your company’s greatest AI breakthrough isn’t a new tool, but your people? In this episode of AI at Scale, we sit down with Jean-Côme Renaudin, Director of the Data & AI School at Schneider Electric, to uncover how one of the world’s largest industrial companies is turning 150,000 employees into AI-literate innovators. From gamified promptathons to executive-backed learning strategies, Jean-Côme shares a bold, scalable blueprint for AI upskilling that’s already delivering measurable business impact. Whether you’re a CEO, CIO, or CHRO, this conversation offers a rare behind-the-scenes look at how to embed AI fluency into the DNA of your organization—and why the time to act is now.
Jean-Côme also walks us through Schneider Electric’s three-phase approach: Learn, Act, Advocate. You’ll hear how internal champions, monthly Data & AI Talks, and hands-on experiences like promptathons are driving real adoption across geographies and functions. We also explore the critical role of leadership sponsorship, the importance of responsible AI, and how Schneider is preparing for the next wave of innovation—including agentic AI and deeper sustainability integration. If you’re looking for a proven roadmap to scale AI learning across your enterprise, this episode delivers both inspiration and actionable insights.
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Transcript
Gosia Gorska: Hi everyone, welcome. This is Gosia Gorska and we are today at the very special place. It’s Viva Tech in Paris and I have a pleasure to have Jean-Côme Renaudin with me. Hello Jean-Côme.
Jean-Côme Renaudin: Welcome, thank you for having me today.
Gosia: Yeah, it’s really an amazing place to be. It’s really a great large event dedicated to technology, to startups. So it’s really like a buzzing background. You cannot hear the noise. And it’s because we are in a very professional studio at Viva Tech. So thank you to the organizers for allowing us to record from here. And let’s introduce our guest today properly. So Jean-Côme is the Director of AI & Data School at Schneider Electric. And he has a very diverse expertise both in data and AI, but also in marketing, sales, customer service across various industries. And he has been also in in the consulting area for industries like energy, consumer retail, aeronautics and banking. So over 22 years of international experience, you have led different organizations in building digital strategies, leveraging technology, driving business transformation. And what’s interesting, the fun fact about Jean-Côme is that he lived in many countries. So you have been in Thailand, Netherlands, France, UK, Germany, and also you spent three years in Asia and sometime in US. And at Schneider, your role is to guide large transformations on data. So welcome today to our show.
Jean: Thank you, Gosia. (1:38)
Data & AI school
Gosia: My first question is about, what is Data & AI school and what’s the AI upscaling initiative that you are driving at Schneider and what was the driving force behind this initiative?
Jean: So actually, you know AI is not new at Electric. So we have been starting the journey long time ago and in 2021 the group name Chief AI Officer and as to drive AI at scale in the company. And as part of this transformation, we cannot do technology without the human part. So it was decided to create this data in the AI school to try to democratize AI knowledge within directory employees. Remember, we have 150,000 employees, so very large audience. And the idea is also as we are a skills first company to accompany our employees so that they can build up their skills and ultimately have a better use of these AI tools because they know how to use them. And 3rd, I think the very important conviction we have at Schneider Electric is that what will make or break this transformation is actually the human element, so without adoption, we won’t get value. And so for this, we need human skills.
Program for large audience
Gosia: Exactly. So actually our audience today has a unique opportunity because what we can hear today is a real sneak peek behind the scenes of how Schneider is up skipping their employees. And the next question is exactly how did you structure the program to ensure that you reach such a large audience? You mentioned 150,000 employees in more than 100 countries. How do you do that?
Jean: So you know, we started with defining a strategy which comes into threefold. The first one is what we could learn. Basically, it’s a program where people come to learn new things. The second piece is called ACT. We are convinced that with technology and in particular with AI, you need to experience the technology to be to be able to understand it in in depth. And the third part is called advocate. So we have the ambition to turn part of our employees into AI adoption champions so that they can help with the company transformation. So free fold, learn, act, advocate and maybe if I describe a little bit those 3 pillars in learn, we actually created curriculum for different type of audiences. So we have defined 4 target audiences. The first one are the experts. So people that are hands on doing technology, people that are sitting in an organization, in the AI hub driving the AI at scale transformation, those people need to be top notch. They need to be certified, they need to be always at the last latest technology,
.
Gosia: Especially that it’s changing all the time
Jean: Exactly. We can see this and we can feel this in Viva Tech. You know, I was there also last year and it’s amazing how much progress has been done in just one year. The second audience for us is, you know, business people that are contributing to our transformation. They are sitting in finance, in HR, in the line of business or in a geography. They are project sponsors or business analyst or product owner and they hand in hand build the use case with our teams. They need to understand the concept of the technology, the case for change and what the technology can do so that they can solve their own business problems. The third audience is actually all employees and the 150,000. We have the ambition to bring them to a first level of understanding and not only understanding, but usage of the tool. And the last audience and you will discover that I’m quoting them as last for a reason, is actually managers and leaders. We want to equip them with the sufficient knowledge so that they can drive their own teams into becoming an AI and data-driven company.
Training courses
Gosia: OK. So you have different audiences and also different levels of expertise and you are proposing different initiatives for each of them. So can you maybe mention some of them like what exactly are this kinds of training courses, this experiences that you are preparing for them?
Jean: So if I take the all employee, we have a curriculum that start with the 30 minutes foundational knowledge where people understand not only what is AI, but we are an engineering company. So we want our employees to understand how it works as well, the limits and the power. Because this technology comes with limits as well. And we want them to understand what are the use cases that we have in Schneider Electric. And not only for white colours, but also for blue colours, because we use AI in factories to help with the production. So this is the first 30 minutes mandatory for everyone that was launched in in 2025. We currently have 40% of Schindler employees that already completed the training. And we have to go up to 100%, which is our objective. So that’s the first step, the second step, there is 90 minutes of training, which is composed of few different ones to understand the AI strategy of Schneider Electric, to understand the link between AI and sustainability. At Schneider Electric, our mission is to help, you know, contribute to the climate change issues. So we want our customers to be more efficient with the energy they have. So we want to be sure that employee understand that AI can be used for that mission, because what you read out there on the newspaper is sometime AI is bad for the planet, right? So we want to make sure they understand we use it for a good reason. And the third thing is maybe that they start to practice because as we said before, we deployed many use cases at scale in the company and we want them to have the right skills so that they can do the right thing with those with those tools. So this is just an example of what we do for an all employee audience.
Data & AI talk
Gosia: And you also try to keep it very entertaining, I must say, because I also follow some of the initiatives. So the one that I like the most actually is the Data & AI talk. And maybe you can share something about this one. And another one that my colleague was actually advertising to me is a Promptathon for marketing people.
Jean: Yeah, great. So you know, we said, I said before we want people to actually touch the technology and to do this we have different ways. First way, the Data & AI talk are actually webinars that we organize every month where we bring customers, partners, internal experts or academies that come to explain value generated with AI. So we don’t talk too much about the how we do, we do it a little bit, but it’s much more about what business problem we can solve. And we have around about 1500 to 2500 participants every month, which is maybe one of the biggest webinar in the company. It’s like a Ted talk of Schneider Electric. And so the name of the game is that the content needs to be of super high quality because I really consider I steal time from people because, you know, it’s not in the flow of their work, but it’s very important for them. So that works quite well. And the second thing that you mentioned is a Promptathon. So a Promptathon, what is it? It’s actually a game that we organize where we invite people. It can be a physical event, it can be a digital event, and people come and play with the technology. And here we’re talking about generative AI, so they would use it in the context of their work. So if you, if we take the example of marketing, marketing people will come in an event where they will have a demo of few prompts how they can do their work as marketers. And then we will put them in a situation where they have to use it themselves and they have to show the benefits and the limits to their colleagues. They, challenge themselves. And ultimately, you know, we give a price for the best prompt and the outcome of those Promptathons is not only the experience in the learning, but also a kind of a prompt library. So first version of the best prompt for marketing. And that works very well. We have been organizing a lot of them and we are continuing to do this.
Gosia: And this is like real learning in action.
Jean: Exactly.
Measurement
Gosia: This is really nice. And OK, let’s talk about the results then what’s the adoption? How do you measure basically how successful you are with all these initiatives?
Jean: So we have different type of KPIs you know they are KPIs that are form forming measures that we have in the learning space which are the number of unique employee trained, the number of course completed, the number of learning hours. So in 2024 we had 48,000 employees, unique employees that took training and it was more than 140,000 completion for something that is not mandatory, that was not mandatory in 2024. So that was very interesting. We were impressed by the numbers. And I have to say that there is an appetite for AI learning. So the advice, if I can give an advice to the audience here is build those curriculum, make them available to your employees because for sure they will come. They know it’s important for themselves. So that’s for the learning KPI then you know we are looking at the KPI of adoption of each of the use case that we are deploying. And if I can give you an example for a general purpose AI. So we are using in Schneider Microsoft Copilot chat. And so we are doing all those Promptathons of training. And so now we have seen a huge peak in time of adoption because people went through the Promptathons. So the e-learning only is actually not enough. People need to see this in context. And maybe, if I rebound on something because you know, we said we talked about learn, we talked about ACT which are the webinars and the Promptathon. But ultimately we have the last phase, which I call advocate. And the objective for us is to build a network of champions that will help the organization to transform itself. And I have a decent team, but we are still a centralized team. And you all know that change management happens on the ground. So with this, you know, we have people in finance, in China, in, a line of business or in another one that are passionate about, they are natural leaders and they learn for themselves. But then we offer them training, they go to train the trainer, we give them toolkits so that they can do more or less our job, but in their organization, which works very well because you know when you try to make a change and you send someone from global or from a consulting firm, it works a little bit. But when it’s your colleague that is teaching you how to change, you have a much better chance to success.
Challenges
Gosia: Yes, but you know, all these initiatives and even the fact that you have this champions, I guess it wouldn’t be possible if you didn’t have a support from the leadership. So there must be, you must have a good buy in, in the company that you said already that there is an appetite and also people I guess understand what’s the stake that if they don’t learn about it, they will kind of there will be this fear of missing out on something. But do you face any challenges or what is helping you to have this high adoption? And is the leadership supporting you somehow in this as well?
Jean: Yes, so actually that’s a very good point. We started with a very strong sponsorship from both of Chief AI Officer Philippe Rambach and of Chief Digital Officer Peter Weckesser. He’s an ex Comm member from Schneider Electric. That was very helpful for the initial phase to get the resources to, you know, set up the team to just launch the date on a school because, you know, they, they initiated it. And then, you know, we, we got a lot of adoption from, the learners. So I saw a lot of bottom up adoption, which help us to come to very good numbers. And then this allowed us to go back to the other executive board members, and ask them for sponsorship. And the interesting thing is that this gave us some air support to go even much further because now we have most of the executive committee members are pushing their teams to learn on AI and this is how.
Future
Gosia: Like a snowball effect once it started, it continues right now. OK, Yeah, that’s really, really impressive. And I’m glad that that we see this interest in Schneider. So what are your plans for the future? Do you plan to I guess one of area is for sure to follow on all the innovations that is happening in the AI space. But any other plans? What particularly to do, what do you do?
Jean: Yes, so actually we are, we are always looking for the next thing because as you said, the environment of AI is moving very, very fast and the skills as well. So we try to develop that culture of continuous learning. So I’m actually here at Viva-Tech also to see what others are doing. We are exchanging with my peers in Fortune 500 almost every two months to get to know what they do. We also share a lot. And so what’s next for the next 6 months. So we will continue to do the Promptathon, on generative AI. We’ll, launch a new training that will be mandatory for next year, which is the Data & AI training 30 minutes. This training will combine all the strategy that we have in Schneider on data plus boosting the adoption of AI. So this is a continuation Chapter 2, if you see. And then we launch new trainings on the new trends. So we have a lot of things around agentic AI. The teams have been trained in H1, but we’ll continue H in H2. And very important and dear to my heart is how do we do AI in a responsible manner, in Schneider, but also with our partners and customers. So this is also a big focus for us at the moment.
Achievement and advice
Gosia: The big topic for us. That’s really great. So maybe more from a personal perspective—can you share with us one moment or one situation that made you really proud of all the achievements you’ve accomplished?
Jean: Yeah, actually, that’s a very good question because I have something in mind. My dream was to get to know Andrew Ng. If you don’t know Andrew Ng, he’s a rock star. He trained more than 8 million people through his courses on Coursera and DeepLearning.AI. And we actually had the chance to have him come to Schneider Electric and share his knowledge, together with Peter Weckesser, our Chief Digital Officer. That was a great moment. We had more than 4,000 employees connected online. So that was a proud moment for me—to have the rock star of AI at Schneider with us.
Gosia: That’s amazing. Really. I’m so happy for that moment. I was also there—watching, listening, asking questions. It was really, really impressive and a great momentum, actually. I think you are really building on this momentum and on the growing interest in AI topics. So I think we have time for one last question. You mentioned that you are connecting with peers. So if you would like to share some advice—maybe to other companies who are thinking about how to structure their learning organization—what should they focus on? Where should they start when it comes to upskilling employees in the AI field?
Jean: OK. So I think what is very important is that I see some companies that don’t really have a very clear AI strategy. And because of that, they think they should not start to build the skills of their employees, which I think is not the right approach. Because independent from the technology choices your company is doing or where you are with your strategy, AI knowledge is very important to employees anyway—and they will go learn it anyway. So you better have this. Our approach was to build a curriculum, make it available, and do a lot of marketing and communication around it. So that’s the first thing. The second piece of advice I can give is that sometimes companies have a tendency to do things and not share them. They want to hide because they think it gives them a competitive advantage or something like that. And I think that in the AI world, things are moving so fast that you have better success if you actually share—if you give and receive from others—rather than trying to do something in your corner, on the side. And it’s true both with partners like Microsoft, AWS, Databricks, and others, but also with big companies in the same venue. Maybe not your direct competitors, but all the others.
Gosia: Yes, and I definitely heard this on stage at Vivatech—the words about collaboration between companies, collaboration between different industries—that is needed if we want to move forward with some challenges around AI. And also what you mentioned about peer-to-peer sharing and open source. This is also what we’ve heard here at Vivatech. So this is very timely advice, and I guess it pays off because you were awarded for the Data & AI School initiatives. Can you maybe, in one last sentence, tell us about the awards?
Jean: Yes. So actually, we were super proud of this because we spent—not three years in the hall—we spent two years building everything, working hard. It’s super hard. And we took some time to bid for something where we were competing against over 500 Fortune companies. We had a great panel of big tech vendors judging what was good or bad. And we actually won a prize at U Spring for digital transformation that recognized our change adoption program. So it’s not only about learning—it’s actually our approach to driving change and change adoption. That was a great moment for the team.
Gosia: Congratulations on this one. I’m keeping my fingers crossed for all the next episodes of your Data & AI Talks and all the initiatives that you’re driving. I think they are very, very useful and very needed. So thank you to our audience for listening. Jean-Côme Renaudin the Director of Data & AI School was our guest today.
Jean: Thank you so much, Gosia.
Gosia: Thank you.
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