Good morning everybody. I'm quite happy to be here today and to have the opportunity to share with you the views of my company TotalEnergies on this fundamental topic which is data and AI. As you know, our ambition at TotalEnergies is to provide an accessible, reliable, affordable and sustainable energy to our customers. And to achieve this, we have implemented an ambition, a strategy which is more energy and less emissions. An integrated multi-energy strategy that supports our energy transitions built around two pillars. On one side, we want to produce low-cost, low-emission gas for our customers, which is the energy of today. But at the same time, we are developing aggressively an integrated power electricity business on the other side.
To achieve this ambition, we also need to master key technologies of the energy transitions, including and that's why I'm here today, data and AI. Artificial intelligence is a strategic lever for TotalEnergies which on one side will support our operational performance, but on the other side as well the energy transition of the company. It's a tool on both: we are using and we will use data and AI to have better performance and to deliver more affordable energy to our customers. But it's also for us a huge opportunity as an energy producer to provide more energy and to develop our business.
So first, I would like to remind that data and high-power computing have been integrated into TotalEnergies' activity for several decades, particularly in all our geoscience and seismic data businesses. In fact, we are a data company for several decades. And now data and AI are gradually integrated into our real operations: safety, electricity, renewable energies, trading, R&D, all over the business.
We started our journey I would say in AI and data in a more scalable size five years ago when we decided to create a digital factory within Paris, because there is a lot of talents here in France, and we have today 300 data scientists and AI engineers with the objective to scale our capacity to deliver use cases and to industrialize AI delivery within the company. In five years, more than 100 apps have been developed and more than 10,000 AI models went into production, from simple models with few parameters on a single equipment to complex industrial environment mobilizations.
Data and AI are now entering a new era, supporting our strategic programs around assets performance, safety and the full value chain. And our company has the strategic objective to manage this new technology, because I think that it's really a new industrial revolution which we are entering into.
Of course, first and foremost, accessing more reliable data is key to develop AI solutions. And this is why in 2024 and 2025, we have decided to launch some major data platform development programs within the company. In 2024, it was about the power value chain with Amazon. And for industrial assets, it's in 2025 that we recently decided to develop and deploy worldwide two major platforms: one with AspenTech, the other one with Cognite.
AI will be indeed an enabler to improve operational performance and safety. I would say increasing our revenues more than lowering our cost. This is the main objective. AI will help optimizing industrial operations, anticipating failures for example, improving plant availability and again enhancing revenue, but also will help us to reduce emissions. I will give you two examples of that. We have, for example, thanks to AI, used a huge amount of data coming from all our equipment to anticipate equipment failures. We have already connected 3,000 equipment through, followed by AI, and we will increase it to dozens of thousands, adding generative AI assistance to help analyze the root cause, propose corrective actions, and help to prepare maintenance work. But we are also today monitoring our methane emissions, which were at the core of the COP conference, in all our operated assets. We are deploying 13,000 sensors combining multiple sources: cameras, satellites, drones to be able to analyze very precisely the locations and the cause of any methane leaks, to intervene quickly and correct the root causes. These are two examples of implementing the strategy: more energy on one side, less emissions on the other side.
In the field, as I mentioned, diversification to electricity and what we call integrated power, which is combining renewable assets with flexible assets like gas-fired power plants and batteries. We are also deploying and we have framed in 2025 what we call the strategic research and technology program with four platforms where in fact data and AI are the core. The program is developing some integrated power modeling, optimizing the design and integration of assets into power grids, for example, with more accurate assessments of renewable energy resources and yields, better forecasting the weather and energy trends, price trends over short, medium, long terms, ensuring predictive maintenance again of flexible and renewable assets, accelerating renewable project development, and achieving our operational excellence through AI agents. These are the four platforms that we intend to develop in France and with the support of a competence center in India.
AI is also, and it's important for a company like TotalEnergies, about developing an ecosystem. I would underline the partnership that we have launched in 2025 with Mistral AI, where we have set up together an innovation lab where our joint teams are exploring the potential of generative and agentic AI to develop agentic systems for the performance of our operations, customer support, but also assistance for R&D teams, which is quite interesting. We are also today jointly examining opportunities for TotalEnergies to use Mistral AI infrastructure in Europe in view of the issue of digital sovereignty.
AI, as I said, is also for us a big business opportunity as we are diversifying our scope of energy to electricity, to integrated power. Our objective within TotalEnergies is to be able to provide to tech companies a clean and firm power. AI creates indeed a huge new demand for energy; data centers represent today around 4% of electricity demand and this number should grow to 8, 10, 12% according to different prospective works. We are today TotalEnergies, an energy supplier, an electricity supplier with an offer available to large companies in the field of AI. And this is our objective again: to provide clean and firm power. We have announced 10 days ago a very... an acceleration of our strategy in Europe with the creation of a joint venture with EP in order to have access to several gigawatts of gas-to-power assets, which will allow us to develop this same offer of clean firm power to our customers here in Europe. And we really want to be at the forefront of this offering.
We have already engaged with many, many major digital players to provide them clean energy: Amazon in the US and in Europe, Microsoft with also some battery energy storage systems in Europe, recently with Data4, the European champion of data center industry, to which we will supply renewable electricity with a stable consumption profile in Spain. And also we have announced recently our first partnership and PPA with Google data centers in the US in Ohio. And there is more to come because this is really a booming segment on which we can apply all our know-how and knowledge as an energy supplier.
So to conclude this speech, I just would like to share that the key assets from our point of view to maximize the value of AI will be, on our side, data. So we need to have this data, and it's a real differentiator for us. But also people: we need people, we need to train and to develop people, knowledgeable people who, of course, will understand our company, our business model, but we will train them. We can offer them a lot of interesting topics to develop use cases. We have been able to attract people within the digital factory; we wanted to have more. This is for me a second strategic asset: data and people. And thanks to both assets, if we can continue to take care of them and develop them, I'm sure that TotalEnergies will be at the forefront of this AI and data opportunity in France, in Europe, and across the world. Thank you for your attention.
