WAIC 2024｜AI at Scale, Peter Weckesser: Executive Vice President of Schneider Electric

Hello everybody, ladies and gentlemen. I feel very honored to be here on behalf of Schneider Electric. I want to introduce Schneider Electric real quick. We are a world market leading company in industry automation and also in energy management. We are actually very much present in China. China is our third largest country globally, and we have a fully localized value chain here in China with procurement, with R&D, with a good number of factories, with full service and support for our Chinese customers. At Schneider Electric, we are also very passionate about addressing some of the biggest challenges of today, which come with some of the mega trends, right? Climate change, the decarbonization of our energy systems is certainly one of the biggest challenges, and Schneider Electric feels very committed to really provide our contribution to solve and address some of these biggest challenges that we have globally. Now, we are also very passionate about technology, and here on the next slide, I want to share some technology data: how quickly certain technologies got adopted and how all that also relates to AI. So if we think of IoT devices, we are seeing a growth which is expected to be six times growth of IoT devices from 2020 to 2030. Why am I talking about IoT devices? IoT devices are important because IoT devices deliver all the data that we need in the OT space to really use AI in a very meaningful way. Then a couple of other data points: the worldwide web took 7 years to reach 100 million users. One of the very latest technology innovations, generative AI, took only two months to reach 100 million users. So we clearly see an acceleration in the innovation speed, how we introduce technologies to the market and also how technologies are being adopted. Now, I will in a minute really make the link between this energy transformation and also AI. Before that, let me talk about AI in general. At Schneider Electric, we really started to embrace AI a good number of years ago already, way before generative AI, and we look at AI really in two main dimensions. One dimension is to think of analytical AI, which is more the classical machine learning, which really generates insights into mostly structured data. And then we have generative AI, which is a relatively new technology, only like 2 years old really being introduced to the mass market, and generative AI really creates new content from mostly unstructured data. I believe we need both of them, the analytical AI and the generative AI, and in many use cases we need them to work hand in hand together. Then we have another belief at Schneider Electric. This belief is that AI, not only generative AI, that AI will be as transformative as the internet 30 years ago. If you think about the internet when it was introduced first about 30 years ago, it has really transformed every industry, every company. Today, basically nothing works anymore without the internet. We believe at Schneider Electric that AI has a very similar transformative potential. That not all the ideas and use cases that we can solve with AI have already been addressed. Technology is advancing very, very quickly, so we really believe every company in the future, every business, every industry will significantly be impacted by AI. We also look at AI in two dimensions that we use it internally in Schneider Electric to really improve our internal business processes, and we are also integrating AI very much into our portfolio, into our offerings. Now, I want on the next slide to show you one example and really make the bridge between AI and our energy transformation. Now, one of our beliefs is everything will become electrical, and I think we are very advanced on this. Over the last couple of days here in China, I have been very much impressed how advanced China is on the e-mobility transformation. So the number of e-cars is high, much higher than in Europe, very impressive. At the same time, buildings will become fully electric, which generates a lot of new challenges. If you look at this chart here, you can see that the future will be millions of microgrids. Every building, every industrial site, every home will become a microgrid, have its own power generation, this is solar panels to a high degree and other renewables. You have lots of consumers of electrical energy. You have the whole e-mobility transformation that you want to charge the electric cars, but at times the fleet of electric cars can also be the battery storage when we have an excess of energy. So what we will see in the future in this energy transformation is millions of microgrids which have their own energy production but also consumption, of course. That these microgrids will be integrated into a utility grid, and of course in order to manage this complexity of millions of microgrids, millions of decentralized energy generation capabilities, then AI seems to be the only technology that will allow us to really manage these energy flows, to stabilize our grids, and really decarbonize the demand side of the energy equation. At Schneider, we are very committed about this to make that a reality and contribute to this in the future. Now, on the next slide, I will really rush through a couple of examples because this is not only the future, this is already happening today. So here I'm showing an example on the left side of a food and beverage customer where we are using AI already today to significantly improve certain business processes, help this customer both on material savings and also on efficiency. When we go to the right side of that slide, it's about an automotive company here in China where in the paint shop of an automotive company you have the highest energy consumption, and with our process know-how plus our platform EcoStruxure that is able to collect data from the manufacturing processes, we are able to collect all these energy data and turn this into efficiency improvements as you can see them here on the slide. The next two examples very similar in data center customers. Data centers being one of the fastest industries that we are serving, we have the deep domain know-how and we can really drive together with our data center customers direct energy savings of north of 30%. And last example that I want to talk about is buildings. Buildings today stand for about 40% of the global energy consumption and also 40% of the global carbon footprint generation. Here we have solutions with our microgrid advisor where we can help all of our building customers really to manage their microgrids in an efficient way, balance the energy generation with the energy demand, and drive significant efficiencies, carbon reductions, and energy savings improvements. Now, at Schneider, we believe in a very simple equation. This equation is: the transformation of our energy systems only works when we go more electrical, so electrification of our energy systems is key. At the same time, electrification will lead to much more decentralized energy generation. We can only balance this and manage these more complex energy networks with the right digital technologies. This is the metering capabilities, it's IoT, and it's very much AI as a technology on top of that. And when I talk about AI, I really mean generative AI as well as analytical AI. And this is the path forward really to decarbonize and drive sustainability for the world. And the good news is these technologies exist today. We do not need to wait. These technologies really exist today. I want to close with my last slide that at Schneider we are really committed to drive that. We made the decision more than three years ago to create an AI organization. We were one of the first large companies nominating a chief AI officer. We have more than 350 AI specialists in the company today, a good number of them here in China, and these AI specialists work with our customers to really drive AI and the energy transformation hand in hand. Thank you very much. It was a pleasure to be here. Thank you very much.