Keynote-Olivier Blum

19 Feb 2026 14:45h - 15:00h

Session at a glanceSummary, keypoints, and speakers overview

Summary

Speaker 1 opened the session by thanking Mr. Schneider and introducing Mr. Olivier Blum, the Global CEO of Schneider Electric, noting that the company sits at the intersection of energy efficiency and digital infrastructure challenges amplified by AI and data-center power use [1-5].


Blum began by congratulating the Indian government and describing his personal journey from arriving in India in 2008 to now leading a global firm, highlighting that access to reliable, clean power remains the planet’s biggest problem, not only for India but worldwide [13-17]. He explained that AI drives higher compute demand, which in turn raises energy consumption and will place unprecedented pressure on existing energy systems, a priority for governments and a geopolitical issue [21-27].


According to Blum, Schneider Electric is uniquely positioned after 190 years in the power sector to finally link the physical and digital worlds, a shift enabled by the post-Paris-Agreement focus on demand-side efficiency rather than just supply [31-34][38-40]. He argued that making every asset “connectable” and applying foundational AI models will create “energy intelligence,” allowing the company to overcome past inefficiencies and contribute to the climate transition [81-86].


Blum illustrated the rapid growth of data-center power density, noting racks in India now reach about 80 kW and in the US 150 kW, with future designs targeting 500 kW to 1 MW, which will force a complete redesign of energy infrastructure [55-60]. He mentioned the emerging 800-volt DC architecture as a necessary technology for the AI-driven data-center of tomorrow [60]. Highlighting India’s strategic importance, Blum pointed out that the country hosts Schneider’s third-largest workforce (40 000 employees) and its biggest R&D centre with 8 000 staff, providing a fertile ground for innovation [101-105]. He gave a concrete example of home-energy savings, stating that connecting residential electrical panels and applying AI agents could reduce consumption by 10-30 % and that he is already testing this in his own house [87-92].


Blum emphasized that such energy-intelligence solutions can be scaled globally, turning the world more electric while improving efficiency, which he sees as essential for meeting the massive additional electricity demand projected through 2050 [67-72]. He concluded that India’s cost-competitiveness, engineering talent, and creativity make it the ideal place to develop the next wave of AI-enabled energy technologies, and success there will unlock solutions worldwide [94-99][106-108]. Finally, he expressed confidence that AI-driven energy intelligence will help solve the climate transition and that cracking the code in India will enable Schneider Electric to do the same everywhere [86][112].


Keypoints


Major discussion points


AI is dramatically increasing energy demand.


Olivier Blum explains that AI “means more compute, more compute means more energy” and that this will put unprecedented pressure on the global energy system, a challenge that governments are already treating as a geopolitical priority. [21-24][28-30]


Schneider Electric is shifting from supply-side to demand-side solutions and building “energy intelligence.”


After the Paris Agreement the company began emphasizing demand-side efficiency, and now, for the first time in its 190-year history, it can “connect the physical and the digital world” to make energy systems smarter and save 10-30 % of consumption across applications. [31-33][38-40][82-84][86-87]


Rapid growth of data-center power use requires new infrastructure.


The speaker cites forecasts of >200 GW of new data-center capacity by 2030, with AI-driven loads pushing rack power from a few kilowatts to 80 kW in India and up to 150 kW (and potentially 500 kW-1 MW) in the US, driving the need for architectures such as 800-V DC systems. [51-60][61-65]


India is positioned as a critical hub for Schneider’s innovation and scaling of AI-enabled energy solutions.


India hosts Schneider’s third-largest market, its biggest R&D centre (8,000 staff), the largest pool of software engineers, and offers a cost-competitive, highly innovative environment that can “crack the code” for the rest of the world. [94-103][104-106][108-111]


Overall purpose / goal


The discussion aims to underscore the urgent intersection of AI-driven compute growth and global energy challenges, present Schneider Electric’s strategic pivot toward demand-side efficiency and “energy intelligence,” and rally stakeholders-especially in India-to collaborate on innovative, scalable solutions that will make the world’s power system more sustainable and resilient.


Overall tone


The tone begins with a formal, congratulatory opening, moves into a serious, urgent warning about rising energy pressures from AI, then shifts to an optimistic, solution-focused narrative about Schneider’s capabilities and the transformative potential of AI-enabled energy intelligence. By the end, the tone becomes inspirational and forward-looking, highlighting India’s unique role as a catalyst for global change. The progression moves from celebratory → urgent → hopeful → inspirational.


Speakers

Olivier Blum – Global CEO, Schneider Electric; expertise in energy efficiency, digital infrastructure, and AI’s impact on energy systems. (role stated in transcript)[S1]


Speaker 1 – Event moderator/host (role inferred from context). No specific area of expertise mentioned. [S2]


Additional speakers:


(none)


Full session reportComprehensive analysis and detailed insights

Speaker 1 opened the session by thanking Mr Schneider and formally introducing Mr Olivier Blum, Global CEO of Schneider Electric, noting that the company sits at the intersection of energy-efficiency and digital-infrastructure challenges amplified by AI-driven data-centre power use [1-5].


Blum congratulated the Indian government and summit participants, recounted his appointment as Managing Director of Schneider Electric India in 2007 and his arrival in 2008, and described the acute shortage of reliable power he witnessed then. He framed “access to reliable, clean electricity” as the planet’s biggest problem, a challenge that extends far beyond India to the whole world [6-13][15-18].


He explained that AI means more compute, and more compute means more energy, creating unprecedented pressure on power systems; governments are already treating energy as a geopolitical priority and AI will intensify that pressure [20-27].


Since the 2015 Paris Agreement, Schneider Electric has shifted from a historic supply-side focus to a demand-side strategy that leverages “energy-intelligence” to improve efficiency and support the climate transition [34-40][31-33].


Blum distinguished two phases of AI: (a) the massive new infrastructure-high-density data-centres and racks-that must be built for AI workloads, and (b) the subsequent, more exciting phase in which AI makes the energy system itself intelligent, enabling “energy-intelligence” solutions [70-73].


Industry forecasts call for >200 GW of new data-centre capacity by 2030, with roughly 50 % attributable to AI. Rack power levels have already risen from a few kW to about 80 kW in India and 150 kW in the United States, and future designs target 500 kW-1 MW per rack, putting huge strain on the grid [51-58][59-60]. The emerging 800-V DC architecture is highlighted as the electrical framework required for these next-generation data-centres [60-62].


The IEA projects that an additional ≈ 10 000 TWh of electricity will need to be added between 2024-2035 and a further ≈ 12 000 TWh between 2035-2050; current scenarios do not yet incorporate AI-driven demand, meaning the true requirement could be far higher [67-72].


For the first time in its 190-year history, Schneider can connect physical assets to digital data and apply foundational AI models, creating “energy-intelligence” that could save 10-30 % of consumption across applications [31-33][81-84][86-87]. The company’s acceleration began when it built its partnership with NVIDIA and is now collaborating on next-generation AI chips [55-57].


A concrete example is connecting residential electrical panels to the cloud, extracting usage data, and managing them with AI agents; this could cut household electricity use-the single largest consumption of electricity in the world-by 10-30 %, and Blum is already testing the concept in his own home [84-86][87-92].


India is presented as a critical hub for developing and scaling these solutions. It is Schneider’s third-largest market, hosts the company’s biggest R&D centre with 8 000 engineers (the largest pool of software engineers globally), and employs 40 000 staff, giving it a unique cost-competitive and talent-rich environment for innovating under intense equipment-pressure conditions [94-105][106-111][112].


Speaker 1 thanked Mr Blum for foregrounding the technology and the power-consumption facts, underscoring that AI’s compute growth will dramatically increase electricity demand and that Schneider Electric’s demand-side, data-driven approach-particularly through India’s innovation ecosystem-offers a pathway to mitigate that pressure while advancing climate-transition goals [113-115].


In summary, Schneider Electric sees AI-driven compute growth as both a challenge and an opportunity, and it is leveraging its Indian R&D hub to develop “energy-intelligence” solutions that could cut global electricity use by up to 30 %.


Session transcriptComplete transcript of the session
Speaker 1

Thank you, Mr. Schneider, for your remarks. And ladies and gentlemen, I would like to welcome Mr. Olivier Blum, Global CEO, Schneider Electric. Schneider Electric sits at the intersection of two of the most pressing challenges of the AI era, energy efficiency and digital infrastructure. As data centers consume ever -growing share of global power, Olivier Blum is leading the company that is helping make that infrastructure sustainable. Please welcome the Global CEO of Schneider Electric, Mr. Olivier Blum.

Olivier Blum

Thank you very much. So, first of all, I’d like to congratulate the Prime Minister and the entire Indian government and all the associates for this beautiful event. This week has been tremendous. And that put together an ecosystem of stakeholders who are really moving technology to the next level. Now, I’d like to tell you a little bit about my own story. I landed in 2008. In 2007, in India, I was appointed at that point of time Managing Director of Schneider in India to develop Schneider Electric. And I discovered a country where the major issue was really access to power, access to reliable power. Now I am sitting in front of you, you know, I’m standing actually in front of you as a CEO of a global company, Schneider, almost 20 years later.

And guess what? What is the biggest problem of the planet? Access to reliable and clean power. So it’s not only the issue of India, it’s the issue of the worldwide planet. And we are just at the beginning of a new era because we are facing issues with access to power in many geographies. You heard many stories of problem of peak load in different geography, including the US where you have power cut. And we have not even started the era of AI. What AI changed to the world? AI means more compute, more compute means more energy. And we just don’t underestimate today. We don’t know exactly what is going to take, but that’s going to put the pressure on the energy system, which has nothing to do with what it is today.

So we know that energy is already a priority for government, for organizations everywhere in the world. It’s even a geopolitical topic. But we are entering a new era where AI could transform the planet. And since this morning, you have heard many, many speakers talking about how AI could impact our life, our businesses everywhere in the world. But the real question is, how we take the energy system to the next level and what AI can bring to make energy more efficient. So we do believe for a company like Schneider, it changed everything. Because we are the first time in the history of Schneider, after 190 years in the power sector, where we are at a point where we can connect the physical and the digital world.

And it was not possible before. Now, let me look back since 2015, what happened. In 2015, something very important happened in the world, which was the climate agreement, you know, the Paris Agreement, where… Well, I don’t know. The world has put a huge focus on energy. And if you remember at that point of time, a lot of people spent time on the supply, bringing clean energy everywhere in the world, which was great. But Schneider Electric was a very, very strong advocate to say, look, working on the supply is very important, but we have to spend even more time to work on the demand side, on how we make energy efficient. And guess what? In the past 10 years, companies like us, but not only, we’ve been really, really strong advocates that if we build a world which is more electric, if we build a world which is more electric and more digital, we might have a path really not only to decarbonize the planet, but to give access to energy everywhere in the world.

I think we’ve made good progress. We’ve made good progress, but it has been complicated because we faced a lot of resistance in the system. We faced resistance with poor grid actors. We faced resistance by companies implementing those new technologies. We know large companies don’t like necessarily to put all their data on the cloud. You know, they want to do it on purpose. Premise and so on. and so forth. But let’s make it clear, I don’t think all the technology we are ready everywhere in the world to make energy system much more efficient. So I think it has been a good journey in the sense that we’ve started really to electrify more and more in the world.

But I think we have just started to scratch the surface. Now, let me come to the topic of AI and the conference, and I will come back on energy. I’m sure you are aware that in any kind of report, we are talking about more than 200 gigawatts of capacity that needs to be built in data center in the next coming years, by 2030. We say usually that 50 % will be AI -driven, and we see the acceleration. For a company like Schneider, we see the acceleration since two years, and we started to see the acceleration when we built our partnership with NVIDIA, when we started really to understand the next generation of chips that will be used to NVIDIA.

For those who are not very familiar with what is a data center, we are talking, about a couple of years, about a couple of kilowatts per racks in the data center. Then we moved to 10, 20, 30. What we are building right now in India, it’s something which is already around 80 kilowatts per racks, even more. And what we are doing in the US right now with the GPU, which are available for NVIDIA, is already at 150. We are forcing a world with NVIDIA, where it can go to 500, to 1 megawatt. And that puts a tremendous pressure on the energy system that forces every single company to reinvent the energy system. I’m sure some of you have heard about the concept of 800 volt DCs, which are the new type of electrical architecture you will need to have for the data center of tomorrow that will be able to power the AI industry.

But again, I’m coming back. There is two phases of AI. There is one which is, there will be many, many new infrastructure that has to be built. But we have really to invent this next level of infrastructure to make sure that they can support what the AI would need. But the second part of the equation, which is even more exciting for me, is that probably we are entering in a new era where for the first time we can make energy more intelligent. But let’s be very realistic. There are a certain number of data from IEA which are telling that to support the global economy, the world will need another 10 ,000 terawatts of energy to be produced, of electricity to be produced between 2024 and 2035, and another 12 on top of that between 2035 and 2050.

When we are looking with our research team at Schneider Electric, we are building energy scenario. We believe that those scenarios don’t include what AI will bring to the planet. So the scenario in terms of electrification that you need for the planet is not about making usage more electrical and supporting the electrification of the planet for cars, for heat pumps, for electrification of process. What brings AI on top of that is another level of pressure on the energy system. And if you look at this conference, which has been great. We have learned a lot. We have spent a lot of time with great people. I’ve not heard enough about energy. And I’ve not heard enough about the need to make energy much more intelligent if you want to support the next AI journey.

Now, for a company like Schneider Electric, it’s really, really fascinating. We created the company 190 years ago. We have been a great company in the physical world. Ten years ago, and I mentioned the Paris Agreement, this is when we decided to make sure that every single asset that will connect, that will sell in the market, will have to be connectable. So we are entering a new era where all energy systems are connectable. And if we are able to apply all the great models, all the great foundational models, which have been built by a lot of partners with whom we are working, we can, for the first time in our history, connect the physical and the digital world.

And that’s what we call energy intelligence. And by doing so, we believe we can overcome many of the difficulties that we faced in the past 10 years to make energy systems more efficient. And by doing so, we believe we can overcome many of the difficulties that we faced in the past 10 years to make energy systems more efficient. That can eventually also solve one of the biggest problems of the planet, which is the climate transition. And by doing so, we believe we can overcome many of the difficulties that we faced in the past 10 years to make energy systems more efficient. because again it’s not only about clean energy it’s about more efficient and we believe we are entering in this new era where if we are able to connect system to collect data to apply foundational model that will connect the physical and the digital world we can save between 10 20 30 percent of energy consumption in every single application in the world and i’m just going to tell you and finish with one example think about your home you’re all sitting today in this conference or some of you are connected and while we are speaking there is a lot of energy consumption in your home tonight you will be back to your home you have an electrical panel somewhere in your home very likely your electrical panel is not connected today imagine a world tomorrow where every single connected if every single panel in the world electrical panel in a home will be connected imagine a world where you are able to extract data imagine a world where you can apply ai agent and where we can manage energy for you while you are not even in your home you can save again between 10, 20, 30 % of your energy consumption.

Actually, I can prove it. I’m testing it in my own home. So I’m telling you it works. Maybe you don’t know, but consumption of energy in home is the largest consumption of electricity in the world. So the good news, we are entering in a new era where we know that the world will be more electrical. And for the first time in our history, we can say that the world can become more electrical if we are able really to leverage the power of the new technology. And I will just finish by telling you that why I’m extremely pleased to be here in India, you know, almost 20 years after I started really my journey in this country, is because India has a lot of different factors which are very, very different than the rest of the world.

And what I’ve learned a lot by spending, you know, six years of my personal life in India, India is one of the countries where equipment is under tremendous pressure, more than in any other country. In the world. Point number two, India is an extremely cost -competitive country, where you need to bring the best innovation at the best price. Number three, the level of innovation. I know in India, some people say also Juga in India, but the level of creativity that you can have in India to create new systems that will solve the most complex problems of the planet can be done in this country. And when you look at the number of engineers you have in power, automation, digital, you have all the ingredients which are together at a point of time where we need to make AI a big transformation for the planet.

For a company like Schneider, I can tell you it’s not only words. India is the third largest country of Schneider Ethics in the world. This is the largest one in number of employees, 40 ,000 employees. You don’t know it, but this is the largest R &D center we have in the world with 8 ,000 employees. Largest number of software engineers. So I’m super excited because we are starting a new phase for the planet, a new technology revolution, which is called AI. where India can be the place where a lot of innovation starts with. I came to India, you know, 20 years ago where we are bringing a lot of product from outside. I think we are at a point of time where India can innovate the next technology that will make the world more efficient.

So we call that Schneider Electric Energy Intelligence. I’ve been very, very excited to be part of the summit. We’ve met a lot of people from government, from construction company, from technology company who have really this strong appetite to make sure that AI will bring progress for all and making sure that India can be at the center of that transformation. And I always say to my team, you know, because now I’m leading Schneider Electric globally, if you can crack the code in India, we’ll crack the code everywhere. Thank you very much.

Speaker 1

Thank you so much, Mr. Bloom, for highlighting the technology. Thank you for highlighting all those facts which concern the power consumption. So far as AI is concerned,

Related ResourcesKnowledge base sources related to the discussion topics (13)
Factual NotesClaims verified against the Diplo knowledge base (5)
Confirmedhigh

“Access to reliable, clean electricity is the planet’s biggest problem, extending beyond India to the whole world.”

The knowledge base explicitly states that the biggest problem of the planet is access to reliable and clean power and that it is a global issue, not limited to India [S1] and [S6].

Additional Contexthigh

“AI increases compute demand, which in turn raises energy consumption and puts unprecedented pressure on power systems; governments are treating energy as a geopolitical priority and AI will intensify that pressure.”

Sources note that the AI boom is triggering alarms in the energy sector, with data centres projected to consume a larger share of global electricity (about 3% by 2030) and creating mounting pressure on power infrastructure, supporting the claim of rising energy demand due to AI [S32] and [S19].

Additional Contextmedium

“Since the 2015 Paris Agreement, Schneider Electric has shifted from a historic supply‑side focus to a demand‑side strategy that leverages “energy‑intelligence” to improve efficiency and support the climate transition.”

The knowledge base highlights a broader industry consensus that a paradigm shift from supply-side infrastructure focus to demand-side, holistic approaches is needed, providing context for Schneider’s stated strategic shift [S46].

Additional Contextmedium

“Blum distinguished two phases of AI: (a) building massive new high‑density data‑centre infrastructure, and (b) using AI to make the energy system itself intelligent, enabling “energy‑intelligence” solutions.”

Other speakers describe the rapid evolution of data-centre rack power density-from traditional 10-20 kW racks to higher-density designs of 30-50 kW and the need for purpose-built facilities-supporting the first phase, while the concept of AI-enabled energy management aligns with the second phase [S7] and [S17].

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Correctionmedium

“Rack power levels have already risen from a few kW to about 80 kW in India and 150 kW in the United States, with future designs targeting 500 kW‑1 MW per rack.”

The knowledge base reports that traditional racks handled 10-20 kW and are evolving to 30-50 kW, which is lower than the 80 kW and 150 kW figures cited; thus the reported current rack power levels appear overstated relative to the cited sources [S7].

External Sources (49)
S1
Keynote-Olivier Blum — -Moderator: Role/Title: Conference Moderator; Area of Expertise: Not mentioned -Mr. Schneider: Role/Title: Not mentione…
S2
Keynote-Martin Schroeter — -Speaker 1: Role/Title: Not specified, Area of expertise: Not specified (appears to be an event moderator or host introd…
S3
Responsible AI for Children Safe Playful and Empowering Learning — -Speaker 1: Role/title not specified – appears to be a student or child participant in educational videos/demonstrations…
S4
Building Trusted AI at Scale Cities Startups & Digital Sovereignty – Keynote Vijay Shekar Sharma Paytm — -Speaker 1: Role/Title: Not mentioned, Area of expertise: Not mentioned (appears to be an event host or moderator introd…
S5
Is AI the key to nuclear renaissance? — The global acceptance and widespread use of artificial intelligence are greatly affecting worldwide energy demands and t…
S6
https://dig.watch/event/india-ai-impact-summit-2026/keynote-olivier-blum — And guess what? What is the biggest problem of the planet? Access to reliable and clean power. So it’s not only the issu…
S7
Building Trusted AI at Scale Cities Startups & Digital Sovereignty – Keynote Giordano Albertazzi — A central theme of Albertazzi’s presentation focused on the dramatic transformation occurring in data centre design due …
S8
Open Forum #9 Digital Technology Empowers Green and Low-carbon Development — Eduardo Araral: Thank you, Professor Fang and to colleagues at Tsinghua University for this invitation. I am honored…
S9
Navigating the Double-Edged Sword: ICT’s and AI’s Impact on Energy Consumption, GHG Emissions, and Environmental Sustainability — This supports wider energy transition goals while fostering ‘Energetic Communities’ where solar energy can meet local en…
S10
The Global Power Shift India’s Rise in AI & Semiconductors — Great insights. Thank you, Thomas. Now, continuing, today AI leadership is ultimately limited not by ambition, but by ac…
S11
A Conversation with Satya Nadella and Klaus Schwab — Another issue raised by Schwab is the high energy consumption of artificial intelligence. He warns that this could lead …
S12
Open Forum #53 AI for Sustainable Development Country Insights and Strategies — A crucial dimension addressed energy consumption concerns. Abhishek noted that “when we build compute systems for AI app…
S13
Rapid AI growth raises global energy demands — The global demand for AI technologyis set to consumenearly as much energy by 2030 as Japan does today, with much of that…
S14
Panel Discussion AI in Digital Public Infrastructure (DPI) India AI Impact Summit — Contrary to common assumptions that infrastructure coverage is the primary barrier in developing regions, Sangbu reveals…
S15
Climate change and Technology implementation | IGF 2023 WS #570 — Speaker:Thank you, Millennium. I’m Sakura Takahashi from Japan. I’m speaking here today on behalf of Climate Youth Japan…
S16
AI and Data Driving India’s Energy Transformation for Climate Solutions — “that analysis -based decision -making has to be adopted.”[13]. “And so for that we need for the right public policy, we…
S17
From KW to GW Scaling the Infrastructure of the Global AI Economy — The infrastructure demands represent a fundamental shift from traditional data centre design. The speakers noted that wh…
S18
Prosperity Through Data Infrastructure — Another key argument put forth in the analysis is the need for legislation that is predictable, understandable, and adap…
S19
AI energy demand accelerates while clean power lags — Data centres are driving asharp rise in electricity consumption, putting mounting pressure on power infrastructure that …
S20
Powering AI _ Global Leaders Session _ AI Impact Summit India Part 2 — This comment shifted the discussion from problem identification to solution positioning, introducing geopolitical and ec…
S21
Indias Roadmap to an AGI-Enabled Future — The discussion outlined a pathway for India to build genuine AGI-enabling capabilities rather than simply importing fore…
S22
Building Trusted AI at Scale Cities Startups & Digital Sovereignty – Keynote Amb Thomas Schneider — The tone is consistently diplomatic, optimistic, and collaborative throughout. Schneider maintains a respectful, inclusi…
S23
Powering AI _ Global Leaders Session _ AI Impact Summit India Part 2 — This comment reframes the entire AI development narrative by identifying energy as the primary bottleneck rather than th…
S24
Strengthen Digital Governance and International Cooperation to Build an Inclusive Digital Future — This comment provides a crucial counterpoint to concerns about AI’s energy consumption by highlighting AI’s potential to…
S25
Navigating the Double-Edged Sword: ICT’s and AI’s Impact on Energy Consumption, GHG Emissions, and Environmental Sustainability — In summary, Colombia’s comprehensive approach to energy transition is manifested through shifts in hydrocarbon explorati…
S26
Is AI the key to nuclear renaissance? — The global acceptance and widespread use of artificial intelligence are greatly affecting worldwide energy demands and t…
S27
Keynote-Olivier Blum — This comment reveals that current energy planning may be fundamentally inadequate because it doesn’t account for AI’s ex…
S28
Is AI the key to nuclear renaissance? — The global acceptance and widespread use of artificial intelligence are greatly affecting worldwide energy demands and t…
S29
Powering AI _ Global Leaders Session _ AI Impact Summit India Part 2 — The scale of the challenge is substantial. Current global data centre electricity consumption stands at 415 terawatt hou…
S30
Rapid AI growth raises global energy demands — The global demand for AI technologyis set to consumenearly as much energy by 2030 as Japan does today, with much of that…
S31
AI boom drives massive surge in data centre power demand — According to Goldman Sachs, the surge in AI is set totransformglobal energy markets, with data centres expected to consu…
S32
Tech giants work to avert an AI‑driven energy crisis — The AI boom istriggering alarms in the energy sector, with data centres expected to consume 3% of the world’s electricit…
S33
Keynote-Olivier Blum — “But Schneider Electric was a very, very strong advocate to say, look, working on the supply is very important, but we h…
S34
Climate change and Technology implementation | IGF 2023 WS #570 — Speaker:Thank you, Millennium. I’m Sakura Takahashi from Japan. I’m speaking here today on behalf of Climate Youth Japan…
S35
Panel Discussion AI in Digital Public Infrastructure (DPI) India AI Impact Summit — Contrary to common assumptions that infrastructure coverage is the primary barrier in developing regions, Sangbu reveals…
S36
Schneider joins SK Telecom on new AI data centre project in Ulsan — SK Telecomhas expandedits partnership with Schneider Electric to develop an AI Data Centre (AIDC) in Ulsan. Under the de…
S37
Panel 4 – Resilient Subsea Infrastructure for Underserved Regions  — So I would like to now turn my question to the government of India. Mr. Farley, India is experiencing a new wave of data…
S38
AI energy demand accelerates while clean power lags — Data centres are driving asharp rise in electricity consumption, putting mounting pressure on power infrastructure that …
S39
Growing data centre demand sparks renewable energy investments — US Energy Secretary Jennifer Granholm has assured that the country will be able to meet the growingelectricity demandsdr…
S40
Building Trusted AI at Scale Cities Startups & Digital Sovereignty – Keynote Amb Thomas Schneider — The tone is consistently diplomatic, optimistic, and collaborative throughout. Schneider maintains a respectful, inclusi…
S41
Social Innovation in Action / DAVOS 2025 — – Barbara Frei: Executive Vice President at Schneider Electric, CEO of Industrial Automation Barbara Frei from Schneide…
S42
Powering the Technology Revolution / Davos 2025 — Dan Murphy: ♫ ♫ Welcome to Red Bee Media’s Live Remote Broadcasting Service. I’m from CNBC, I’m CNBC’s Middle E…
S43
Taking Stock — Specifically mentioned affordability, rural connectivity, and reliability as key challenges in global south The same sp…
S44
The Glasgow environment summit: A new paradigm? — As India’s incomes rise, this per capita share will inevitably rise; that becomes a global problem because of the countr…
S45
National Strategy for Artificial Intelligence — The action plan for smart energy will examine how smart solutions can couple energy consumption closer to energy product…
S46
WS #484 Innovative Regulatory Strategies to Digital Inclusion — High level of consensus with significant implications for policy direction. The agreement suggests a paradigm shift is n…
S47
How AI Drives Innovation and Economic Growth — Akcigit distinguishes between two layers of AI development in advanced economies. The application layer has low entry ba…
S48
Building the AI-Ready Future From Infrastructure to Skills — And Manhattan Project, about 65 % of the entire funding of Manhattan Project was at Oak Ridge National Laboratory. And i…
S49
Media Briefing: Unlocking the North Star for AI Adoption, Scaling and Global Impact / DAVOS 2025 — Cathy Li: Thanks for having me. So first of all, just a very quick overview. The work is done not by one organisation…
Speakers Analysis
Detailed breakdown of each speaker’s arguments and positions
O
Olivier Blum
9 arguments192 words per minute2222 words691 seconds
Argument 1
AI increases compute needs, which dramatically raises energy consumption and pressures existing power systems
EXPLANATION
Blum argues that the rise of artificial intelligence drives a surge in computational demand, which in turn requires substantially more electricity. This added load will strain current power grids and accelerate the need for new energy capacity.
EVIDENCE
He explains that “AI means more compute, more compute means more energy” and warns that this will put pressure on the energy system that is not prepared for it [22-24]. He also cites reports forecasting over 200 GW of data-center capacity to be built by 2030, with about 50 % driven by AI workloads [51-52].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Blum’s claim is echoed in external observations that AI’s growing compute demand drives higher electricity use and strains power systems [S1][S5][S10][S11][S12].
MAJOR DISCUSSION POINT
Global energy challenge & AI‑driven demand
AGREED WITH
Speaker 1
Argument 2
Schneider shifts emphasis from energy supply to demand‑side efficiency, advocating smarter use of power
EXPLANATION
Blum states that Schneider Electric has moved from focusing solely on supplying clean energy to improving how that energy is used. The company promotes demand‑side management as a key lever for reducing overall consumption.
EVIDENCE
He notes that after the Paris Agreement, Schneider became a strong advocate for working on the demand side, arguing that “working on the supply is very important, but we have to spend even more time to work on the demand side, on how we make energy efficient” [38-39].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Schneider’s shift to demand-side efficiency is documented in Blum’s keynote where he emphasizes focusing on energy efficiency over supply [S1].
MAJOR DISCUSSION POINT
Schneider Electric’s strategy: demand‑side focus & energy intelligence
Argument 3
By linking physical assets with digital data and AI models, Schneider can create “energy intelligence” that improves system efficiency
EXPLANATION
Blum describes a new capability where Schneider can combine sensor data from physical equipment with AI‑driven models to optimise energy use. This “energy intelligence” is presented as a way to achieve significant efficiency gains across applications.
EVIDENCE
He highlights that for the first time in its 190-year history Schneider can “connect the physical and the digital world” and apply foundational AI models, which he says can save “between 10, 20, 30 percent of energy consumption in every single application in the world” [31-33][82-84][87].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The concept of “energy intelligence” linking assets with AI models is described in Blum’s remarks about Schneider’s new capability [S1].
MAJOR DISCUSSION POINT
Schneider Electric’s strategy: demand‑side focus & energy intelligence
Argument 4
AI‑driven data centres will require far higher power per rack (80 kW‑150 kW now, moving toward 500 kW‑1 MW), necessitating new designs
EXPLANATION
Blum points out that the power density of AI‑focused data centres is rapidly increasing, demanding new architectural approaches to handle the load. Current racks already consume tens of kilowatts, and future designs aim for half‑megawatt to megawatt levels.
EVIDENCE
He provides concrete figures: Indian racks are around 80 kW, U.S. GPU racks are about 150 kW, and Schneider is working with NVIDIA to push designs toward 500 kW-1 MW per rack [56-58].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Data-center power density trends, from tens of kilowatts to hundreds, are supported by Blum’s figures and by independent reports on rack densification [S1][S7].
MAJOR DISCUSSION POINT
Evolution of data‑center infrastructure for AI workloads
Argument 5
Adoption of 800 V DC electrical architecture is essential to support the next‑generation AI data‑center
EXPLANATION
Blum mentions that traditional power architectures are insufficient for the upcoming AI data‑center loads, and that a high‑voltage DC system (800 V) is required to deliver the needed efficiency and reliability.
EVIDENCE
He refers to “the concept of 800 volt DCs, which are the new type of electrical architecture you will need for the data center of tomorrow” [60].
MAJOR DISCUSSION POINT
Evolution of data‑center infrastructure for AI workloads
Argument 6
AI can cut energy use by 10‑30 % across applications, illustrated by smart‑home panel example that autonomously optimises consumption
EXPLANATION
Blum claims that AI‑enabled control of energy assets can reduce consumption by a double‑digit percentage. He illustrates this with a connected home electrical panel that uses AI agents to manage loads even when the homeowner is away.
EVIDENCE
He describes a scenario where every home electrical panel is connected, data is collected, and an AI agent manages usage, achieving “10, 20, 30 % of your energy consumption” savings, and says he is testing it in his own home [87-90]. He also notes that residential consumption is the largest electricity use globally [91].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Blum’s example of AI-driven home energy management achieving 10-30 % savings aligns with external discussions of AI enabling residential energy optimisation [S1][S8].
MAJOR DISCUSSION POINT
AI as a catalyst for energy efficiency
Argument 7
Deploying AI‑based energy intelligence supports climate‑transition goals by making electricity use more efficient
EXPLANATION
Blum links the concept of energy intelligence to broader climate objectives, arguing that improved efficiency can significantly lower emissions and aid decarbonisation. He positions AI‑driven optimisation as a key tool for the climate transition.
EVIDENCE
He states that energy intelligence “can eventually also solve one of the biggest problems of the planet, which is the climate transition” and that saving 10-30 % of energy across applications contributes to this goal [86-87].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
AI-based energy intelligence contributing to climate transition is highlighted by Blum and reinforced by literature on AI supporting clean-energy modelling [S1][S8].
MAJOR DISCUSSION POINT
AI as a catalyst for energy efficiency
Argument 8
India provides cost‑competitive innovation, a large pool of engineers, and the world’s biggest Schneider R&D centre (8,000 staff), making it a hub for new solutions
EXPLANATION
Blum highlights India’s unique advantages: high pressure on equipment, cost competitiveness, strong creativity, and a massive talent base. He notes that India hosts Schneider’s third‑largest employee base and its largest R&D centre, positioning it as a strategic innovation hub.
EVIDENCE
He mentions India’s equipment pressure, cost-competitiveness, and creativity [95-98], then cites that India is the third largest Schneider market with 40,000 employees, the largest R&D centre of 8,000 staff, and the largest number of software engineers [101-105].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
India’s cost-competitiveness, talent pool, and large Schneider R&D centre are noted in Blum’s statements and corroborated by external commentary on India’s AI and semiconductor strengths [S1][S10].
MAJOR DISCUSSION POINT
India’s strategic importance for Schneider Electric and AI innovation
Argument 9
Success in India is viewed as a template (“crack the code”) for global rollout of Schneider’s AI‑enabled energy solutions
EXPLANATION
Blum asserts that mastering AI‑driven energy solutions in India will provide a blueprint for worldwide deployment. He suggests that breakthroughs achieved in the Indian market can be replicated globally.
EVIDENCE
He tells his team that “if you can crack the code in India, we’ll crack the code everywhere” [111].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The idea of using India as a template for global rollout is reflected in Blum’s “crack the code in India” comment [S1].
MAJOR DISCUSSION POINT
India’s strategic importance for Schneider Electric and AI innovation
S
Speaker 1
1 argument154 words per minute107 words41 seconds
Argument 1
Power consumption concerns are central to the discussion of AI’s impact
EXPLANATION
Speaker 1 emphasizes that the conversation about AI must foreground the issue of electricity demand, noting that AI’s growth cannot be separated from its energy implications.
EVIDENCE
After Blum’s remarks, Speaker 1 thanks him for “highlighting all those facts which concern the power consumption” and stresses that power consumption is a key point in the AI discussion [113-115].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Speaker 1’s emphasis on power consumption mirrors broader concerns about AI’s electricity demand documented in multiple sources [S1][S11][S12].
MAJOR DISCUSSION POINT
Global energy challenge & AI‑driven demand
AGREED WITH
Olivier Blum
Agreements
Agreement Points
AI-driven increase in compute raises power consumption and pressures energy systems, making energy demand a central concern in the AI discussion
Speakers: Olivier Blum, Speaker 1
AI increases compute needs, which dramatically raises energy consumption and pressures existing power systems Power consumption concerns are central to the discussion of AI’s impact
Both speakers highlight that AI’s growth translates into higher electricity demand and that power consumption must be foregrounded when discussing AI. Blum notes that “AI means more compute, more compute means more energy” and warns of pressure on the energy system [22-24], while Speaker 1 thanks him for “highlighting all those facts which concern the power consumption” [113-115].
POLICY CONTEXT (KNOWLEDGE BASE)
This concern mirrors statements from the AI Impact Summit that reposition energy as the primary bottleneck for AI development rather than computational capability [S23], and aligns with expert warnings that existing energy planning does not account for AI’s exponential demand, indicating a looming policy gap [S27]. It also reflects broader observations about rising operational energy costs as AI systems become more sophisticated [S26].
Similar Viewpoints
Both see the surge in AI compute as a major driver of electricity demand and consider power consumption a key issue that must be addressed in any AI‑related dialogue. Blum stresses the systemic pressure caused by AI workloads [22-24], and Speaker 1 explicitly acknowledges the importance of power‑consumption facts [113-115].
Speakers: Olivier Blum, Speaker 1
AI increases compute needs, which dramatically raises energy consumption and pressures existing power systems Power consumption concerns are central to the discussion of AI’s impact
Unexpected Consensus
Recognition that AI’s energy impact is a primary focus rather than solely a technological opportunity
Speakers: Olivier Blum, Speaker 1
AI increases compute needs, which dramatically raises energy consumption and pressures existing power systems Power consumption concerns are central to the discussion of AI’s impact
While Blum’s remarks cover both challenges and opportunities of AI for energy, Speaker 1’s brief comment unexpectedly aligns by emphasizing the same concern about power consumption, confirming that even a brief acknowledgment from the moderator mirrors the CEO’s central message.
POLICY CONTEXT (KNOWLEDGE BASE)
The shift toward prioritizing AI’s energy footprint over pure technological optimism was highlighted at the Global Leaders Session of the AI Impact Summit, framing energy as the central constraint [S23], and is echoed in calls for holistic impact assessments that balance AI’s potential benefits with its environmental costs [S24].
Overall Assessment

The discussion shows clear alignment between the CEO and the moderator on the importance of energy demand and power‑consumption issues linked to AI. Beyond this, there is limited overlap on other themes such as demand‑side efficiency, energy intelligence, or India’s strategic role, which remain specific to Blum’s presentation.

Moderate consensus limited to the shared recognition of AI’s energy impact; this consensus underscores the urgency of integrating energy‑efficiency considerations into AI policy and industry strategies.

Differences
Different Viewpoints
Unexpected Differences
Overall Assessment

The exchange shows strong alignment on the importance of energy consumption in the AI era. Blum provides detailed technical and strategic arguments about AI‑driven compute growth, data‑center power density, and the need for energy‑intelligent solutions, while Speaker 1 simply acknowledges these points without contest. No substantive disagreement emerges from the transcript.

Minimal – the speakers are largely in consensus, with only a brief acknowledgment from Speaker 1 that does not challenge Blum’s positions. This suggests that, for the topics covered (energy impact of AI and the need for smarter energy management), the discussion is collaborative rather than contentious, facilitating a unified narrative on the challenges and opportunities.

Partial Agreements
Both speakers emphasize that electricity demand is a key issue when talking about AI. Speaker 1 thanks Blum for “highlighting all those facts which concern the power consumption” [113-115], while Blum repeatedly stresses that AI drives higher compute and therefore higher energy use, warning that this will put pressure on the energy system [22-24][51-52]. The two share the goal of drawing attention to power consumption, but Speaker 1 does not elaborate on the specific mechanisms (e.g., data‑center rack power density) that Blum describes.
Speakers: Olivier Blum, Speaker 1
Power consumption concerns are central to the discussion of AI’s impact AI increases compute needs, which dramatically raises energy consumption and pressures existing power systems
Takeaways
Key takeaways
AI-driven compute growth will dramatically increase global electricity demand, putting unprecedented pressure on power systems. Schneider Electric is shifting its focus from solely supplying clean energy to improving demand‑side efficiency through “energy intelligence” that links physical assets with digital data and AI models. Next‑generation AI data centres will require far higher power per rack (80 kW–150 kW today, moving toward 500 kW–1 MW), driving the need for new electrical architectures such as 800 V DC systems. AI can enable 10‑30 % energy savings across a wide range of applications, exemplified by smart‑home panel use cases that autonomously optimise consumption. India is strategically critical for Schneider Electric: it offers cost‑competitive innovation, a large engineering talent pool, and hosts the company’s largest R&D centre (8,000 staff), making it a testbed for global AI‑enabled energy solutions. Successful deployment of energy‑intelligence solutions in India is viewed as a template for worldwide rollout.
Resolutions and action items
None identified
Unresolved issues
How to scale AI‑enabled energy‑intelligence solutions across diverse grid operators and overcome resistance from legacy infrastructure owners. Development of standards and widespread adoption of 800 V DC architecture for future AI‑heavy data centres. Quantifying the exact additional electricity required for AI workloads beyond existing IEA forecasts and integrating AI impact into global energy scenario planning. Ensuring data security and addressing concerns of large enterprises reluctant to move all data to the cloud.
Suggested compromises
None identified
Thought Provoking Comments
The biggest problem of the planet? Access to reliable and clean power.
Frames the entire discussion around a universal, concrete challenge rather than abstract AI hype, setting a purpose‑driven lens for the rest of the talk.
Establishes the central problem that all subsequent points (AI’s energy demand, Schneider’s role, India’s potential) are measured against, steering the conversation toward solutions for power access.
Speaker: Olivier Blum
AI means more compute, more compute means more energy… we don’t know exactly what is going to take, but that’s going to put pressure on the energy system.
Links two megatrends—AI and energy—highlighting a feedback loop that many audiences overlook; it raises a new risk dimension for AI adoption.
Creates a turning point where the dialogue shifts from celebrating AI to confronting its hidden cost, prompting listeners to consider sustainability as a prerequisite for AI growth.
Speaker: Olivier Blum
We have been strong advocates that if we build a world which is more electric and more digital, we might have a path not only to decarbonize the planet, but to give access to energy everywhere.
Introduces the demand‑side focus—electrification coupled with digitalization—as a dual lever for climate action and universal energy access, challenging the traditional supply‑centric narrative.
Broadens the conversation to include policy and business strategies on the demand side, influencing later remarks about grid resistance and data‑center needs.
Speaker: Olivier Blum
For the first time in our history we can connect the physical and the digital world… we call that Energy Intelligence.
Coins a new concept—Energy Intelligence—that encapsulates Schneider’s strategic shift and suggests a transformative technology platform.
Serves as a thematic anchor; subsequent examples (data‑center power, 800 V DC architecture, home‑panel connectivity) are framed as applications of this Energy Intelligence vision.
Speaker: Olivier Blum
We are moving from a few kilowatts per rack in data centres to 80 kW, 150 kW and aiming for 500 kW to 1 MW per rack – that puts tremendous pressure on the energy system.
Provides a concrete, quantifiable illustration of how AI workloads are scaling energy demand, turning an abstract concern into a vivid technical reality.
Triggers a shift toward discussing infrastructure upgrades (e.g., 800 V DC) and underscores the urgency for new energy‑management solutions.
Speaker: Olivier Blum
If every electrical panel in every home were connected and managed by AI agents, we could save 10‑30 % of energy consumption.
Offers a tangible, everyday‑level use case of Energy Intelligence, showing how AI can directly reduce consumption rather than just increase demand.
Deepens the analysis by moving from macro‑scale data‑center concerns to consumer‑level impact, making the argument relatable and expanding the scope of the discussion.
Speaker: Olivier Blum
India is the third largest Schneider location, with the biggest R&D centre (8,000 engineers) and the most cost‑competitive environment – if we crack the code here, we can crack it everywhere.
Positions India not just as a market but as a global innovation engine, linking regional strengths to the worldwide AI‑energy challenge.
Shifts the tone toward optimism and strategic partnership, setting up potential follow‑up dialogues about collaboration, policy, and scaling solutions globally.
Speaker: Olivier Blum
Overall Assessment

The discussion pivots around a series of high‑impact statements that move from framing the core problem (global access to clean power) to exposing AI’s hidden energy cost, then to unveiling Schneider’s strategic response—Energy Intelligence. Each comment either introduces a new dimension (supply vs. demand, data‑center scaling, home‑level AI control) or reframes the geographic focus (India as an innovation hub). These turning points guide the audience from abstract concerns to concrete metrics and actionable visions, deepening the conversation and setting the stage for collaborative solutions.

Follow-up Questions
What will be the actual energy consumption increase due to AI and how can we accurately predict it?
Understanding AI‑driven load is essential for planning new generation capacity and avoiding under‑estimation of future energy needs.
Speaker: Olivier Blum
How can we make the energy system more intelligent using AI and digital connectivity?
Creating ‘energy intelligence’ is presented as a way to handle the added pressure of AI workloads while improving overall efficiency.
Speaker: Olivier Blum
What are the technical and regulatory challenges to connecting every electrical panel in homes to the cloud for energy management?
Connecting residential panels could enable 10‑30% savings, but requires solutions for standards, data privacy, and deployment at scale.
Speaker: Olivier Blum
How can we overcome resistance from grid actors and companies reluctant to put data on the cloud?
Adoption of connected, data‑driven energy solutions depends on addressing stakeholder concerns about security, control, and legacy systems.
Speaker: Olivier Blum
What role will 800‑volt DC architecture play in future data centers, and what are the implementation pathways?
High‑voltage DC is cited as a needed architecture for AI‑intensive data centers; understanding its rollout is critical for infrastructure planning.
Speaker: Olivier Blum
How will AI affect the IEA energy scenarios, and what revised models are needed?
Current IEA forecasts do not incorporate AI impact, so new scenario modelling is required to capture true future demand.
Speaker: Olivier Blum
What specific innovations can be developed in India to address high equipment pressure, cost competitiveness, and AI‑driven energy efficiency?
India’s unique market conditions and talent pool are highlighted as a potential engine for breakthrough solutions that could be replicated globally.
Speaker: Olivier Blum
How can foundational AI models be applied to physical energy assets to achieve 10‑30% energy savings across applications?
Demonstrating concrete use‑cases of AI on physical assets would validate the promised efficiency gains and guide product development.
Speaker: Olivier Blum
What metrics and data are needed to validate the claimed 10‑30% energy savings in homes and other settings?
Empirical evidence is required to substantiate the savings claim and to build confidence among consumers, regulators, and investors.
Speaker: Olivier Blum

Disclaimer: This is not an official session record. DiploAI generates these resources from audiovisual recordings, and they are presented as-is, including potential errors. Due to logistical challenges, such as discrepancies in audio/video or transcripts, names may be misspelled. We strive for accuracy to the best of our ability.