Powering AI _ Global Leaders Session _ AI Impact Summit India Part 2

20 Feb 2026 17:00h - 18:00h

Powering AI _ Global Leaders Session _ AI Impact Summit India Part 2

Session at a glanceSummary, keypoints, and speakers overview

Summary

The panel examined how the rapid growth of artificial intelligence is creating unprecedented power and cooling demands for data centers worldwide, noting that a single large AI training run can consume as much electricity as thousands of homes in a year and that data centers and cooling are the two biggest sources of rising electricity consumption [5][56]. Ashish Khanna outlined the International Solar Alliance’s dual focus on “AI for Energy” – using AI to integrate decentralized solar, storage and peer-to-peer trading – and “energy for AI,” which addresses the surge in electricity use by data centers and cooling systems [27-33][54-57], emphasizing that about 40 % of recent solar growth is decentralized but often resisted by distribution companies, a gap AI-enabled digitisation could help bridge [21-25].


Professor Raghav Chandra argued that the single greatest constraint on AI’s future is the energy required by data centers, not algorithms or chips [73-74]. He cited high-profile outages at Meta, Google Cloud, AWS and Azure as evidence that power reliability is a critical vulnerability for AI services [75-85][86-94]. Current global data-center electricity consumption is about 415 TWh (1.5 % of total) and is projected to rise to roughly 945 TWh (3 %) by 2030, effectively adding the power demand of whole countries [113-119]. Chandra warned that reliance on fossil-fuel generation would increase emissions, raise electricity prices for nearby communities, and create social and environmental costs such as water scarcity, noise and land-use conflicts [121-128][133-136].


Nathan Blom highlighted that cooling innovation is moving from traditional air-cooled racks to liquid-cooling and emerging two-phase technologies, which can improve power-usage-effectiveness from around 1.5 to 0.5, dramatically reducing the electricity needed for heat removal [244-265].


Vineet Mittal described how AI can make intermittent solar and wind generation dispatchable at 15-minute intervals by processing climatic, satellite and grid data, enabling an “always-on” clean-power grid [148-156]. He emphasized India’s rapid expansion to 50 GW of new solar-wind capacity this year, its abundant sun, wind and pumped-storage resources, and a single, heavily invested national grid that can deliver power across the country in real time [160-168][188-194]. Mittal also pointed to policy measures such as tax exemptions for foreign-collaborative data centers and the need for data-sovereignty legislation, while acknowledging uneven ease of doing business and coordination between central and state authorities as major hurdles [227-233][224-231].


The discussion concluded with consensus that India and other developing regions have significant renewable potential and cooling-technology opportunities, but that coordinated regulation, infrastructure investment and sustained innovation are essential to meet AI’s energy needs sustainably [242][312-313].


Keypoints


Major discussion points


The massive and growing energy demand of AI-driven data centers, and the reliability and environmental risks this creates.


The opening remarks note that a single AI training run can use as much electricity as “thousands of homes” [5-6] and that data-center power consumption is already comparable to a small country’s grid [55-57]. Raghav Chandra underscores recent high-profile outages at Meta, Google, AWS and Microsoft as evidence that “energy reliability … is a big-time issue” [73-80][84-92]. He quantifies the scale – global data-center electricity use is 415 TWh today and could reach 945 TWh by 2030, equivalent to the power demand of entire nations such as Australia or Spain [112-119]. He also warns of the downstream social, economic and climate costs of relying on fossil-fuel generation [124-129][133-137].


AI as an enabler for renewable-energy integration and decentralized power markets.


Ashish Khanna explains that the International Solar Alliance (ISA) has launched an “AI for Energy” mission, emphasizing that AI can digitise millions of prosumers to enable peer-to-peer (P2P) trading of rooftop solar and storage [20-27][31-36]. He highlights the current skill gap – “AI engineers do not understand energy, energy engineers do not understand AI” – and announces the creation of an ISI Academy to train hybrid talent [33-36]. He also points to a burgeoning innovation ecosystem of startups tackling generation, transmission and financing challenges [38-44][46-48].


India’s unique renewable-energy endowment and its strategic vision to become a global data-center hub.


Vineet Mittal describes India’s rapid expansion to 50 GW of solar and wind this year, its “abundance of sun, wind and water,” and the ability to pair these with pumped-storage and battery systems to deliver round-the-clock green power [148-166][170-188]. He stresses the country’s single, highly-interconnected grid that can move power from Rajasthan to Mumbai in real time, and the policy environment that offers tax exemptions for foreign-collaborative data-center projects [226-228][282-285]. Raghav adds that India’s data-center load could rise from ~1 GW today to 8-9 GW by 2030, but that “ease of doing business” and state-center coordination remain the biggest bottlenecks [214-222][224-233].


Innovation in cooling technologies as a critical lever for energy efficiency.


Nathan Blom argues that the next breakthrough will come from “small companies” developing advanced cooling, moving from traditional air-cooling to liquid-cooling and, more importantly, two-phase (boiling) cooling that can improve PUE from ~1.5 to ~1.05 [244-265]. Vineet echoes this, noting that cross-industry expertise (clean-room design, battery cooling, PUE optimisation) must be cultivated locally, and that India’s open-access grid enables flexible, real-time power for such high-efficiency cooling solutions [267-280][281-284].


Policy, regulatory and coordination challenges that must be addressed to scale AI-powered data centres.


Ashish asks the panel to consider how “policy and regulatory landscape” and “innovation landscape” can accelerate data-center deployment [198-212]. Raghav points to fragmented state-center governance, the need for synchronized permitting, and recent budget measures such as tax exemptions for data centres with foreign components [224-230][226-228]. Vineet adds that while some states (e.g., Maharashtra) are streamlining land and permitting, a “stack-ranking” of states is being introduced to ensure uniformity, and that data-localisation policies must be communicated to both industry and government [282-285][286-287].


Overall purpose / goal of the discussion


The session was convened to examine the twin challenges of “energy for AI” (the soaring power and cooling needs of AI-driven data centres) and “AI for energy” (how artificial intelligence can enable more efficient, decentralized renewable-energy systems). Panelists aimed to identify technical, regulatory and market solutions-particularly for developing economies like India-so that the rapid expansion of AI can be sustained without compromising reliability, affordability or the environment.


Tone of the discussion


– The conversation opens with a formal, urgent tone, emphasizing the scale of the problem (Announcer, Ashish) and citing recent outages.


– It then shifts to a constructive, optimistic tone, highlighting opportunities where AI can unlock renewable integration and where India’s resource base offers a strategic advantage.


– When addressing policy and implementation, the tone becomes candid and critical, acknowledging “ease of doing business” bottlenecks and coordination gaps.


– Finally, the panel ends on a hopeful, forward-looking tone, stressing innovation, ecosystem building and the potential for India to become a leading AI-data-center hub.


Overall, the tone moves from alarm to optimism, tempered by realistic acknowledgment of the work still required.


Speakers

Announcer


– Role/Title: Event announcer/moderator


– Area of Expertise:


Vineet Mittal


– Role/Title: Chairman of Avada Group, renewable energy developer


– Area of Expertise: Renewable energy, AI for energy, power grid integration [S4]


Nathan Blom


– Role/Title: Vice President, Cooling Chambers


– Area of Expertise: Data center cooling technologies, liquid and two-phase cooling solutions [S6]


Ashish Khanna


– Role/Title: Director General, International Solar Alliance (moderator)


– Area of Expertise: Solar energy, AI for Energy, international energy policy [S7]


Raghav Chandra


– Role/Title: Professor, IIM Calcutta; Founder & CEO, Consult; former Chairman, NHAI; former Secretary to Government of India


– Area of Expertise: Infrastructure policy, energy systems, AI impact on power demand [S9]


Audience


– Role/Title: Associate Member, Indian Institute of Public Administration (Umesh Prasad Singh)


– Area of Expertise: Public administration, policy analysis [S12]


Additional speakers:


(None identified beyond the listed speakers)


Full session reportComprehensive analysis and detailed insights

The session opened with the moderator framing the debate. He warned that AI is expanding at “speed”, driving “unprecedented power and cooling requirements” for data-centres, which today consume electricity equivalent to Spain’s grid [13-15] and represent roughly 70 % of global data-centre demand in the United States and China [10-12]. This demand is projected to double every three years [16-18] and is further amplified by the electrification of cars/EVs [19-20]. The moderator highlighted the recent surge in solar capacity – 1 000 GW added in the last two years, a pace that previously took 25 years, with about 40 % of that growth being decentralised (rooftop, pumps, etc.) [20-22]. He noted that distribution companies often resist decentralised solar because it threatens revenue streams [23-25], but AI-enabled digitisation could help integrate these resources and lower system costs [25-26]. The International Solar Alliance (ISA) announced the launch of a global “AI for Energy” mission as part of the AI Impact Summit [21-23], and called for interoperable standards and new financing and de-risking models to enable large-scale projects [38-45][46-53][54-57].


Raghav Chandra then argued that the single greatest constraint on AI’s future is the energy required by AI-driven data-centres [73-74][75-94]. He cited high-profile power failures – Meta’s aborted nuclear-powered data-centre after a bee-colony incident, Google Cloud’s 2025 outage in Columbus, AWS’s 2019 failure in Northern Virginia, and similar setbacks at Microsoft Azure and TikTok’s US-DS joint venture [75-94]. He quantified current global data-centre electricity consumption at 415 TWh (≈1.5 % of world electricity) and warned it could rise to 945 TWh (≈3 %) by 2030, comparable to the demand of entire nations [112-119]. He outlined the broader environmental, social and equity ramifications – higher emissions, rising electricity prices for households, noise, heat, land-use conflicts and water scarcity [121-128][133-136], and answered an audience question on the global impacts, emphasizing water-use, social equity and climate-justice concerns [198-212].


Nathan Blom shifted the focus to cooling innovation. He traced the evolution from traditional air-cooled racks to liquid-cooling and, most importantly, emerging two-phase cooling where the coolant boils, delivering ten-to-twenty times higher heat-removal efficiency [259-264][260-262]. This technology can improve Power Usage Effectiveness from around 1.5 to as low as 1.05, dramatically cutting the electricity needed for heat removal and the overall power draw of data-centres [260-265]. Blom stressed that such breakthroughs are typically driven by small, agile startups that are later acquired by larger firms [247-248][267-270].


Vineet Mittal presented both “AI for Energy” and “energy for AI”. He explained that AI can schedule solar and wind output in 15-minute intervals, making intermittent renewables effectively dispatchable [151-156]. India is adding 50 GW of solar and wind capacity this year, positioning it as the world’s second-largest green-energy player after China [160-162]; the complementarity of solar and wind, together with pumped-storage and batteries providing 14-18 hours of power, enables round-the-clock green electricity [165-170][173-176]. India’s single, heavily-invested national grid can transmit power in real time from Rajasthan to Mumbai, supporting low-latency data-centre operation [188-194]. Policy levers such as recent budget tax exemptions for data-centres with foreign components [226-228] and open-access, real-time power trading were highlighted, though Mittal noted uneven “ease of doing business” across states [282-285]. Some states (e.g., Maharashtra) already offer streamlined land allocation, permitting and incentives, and the government’s “stack-ranking” of states aims to level the playing field [242-245][242-244]. A forthcoming national data-sovereignty act is also expected to shape investment [250-252].


In the policy and regulatory discussion, Raghav Chandra identified systemic bottlenecks: fragmented centre-state coordination, inconsistent permitting, and a lack of synergy among government departments [214-224]. He praised recent budget provisions offering tax exemptions for data-centres with foreign components [226-228] but warned that without synchronized policies and streamlined approvals projects can stall after multiple presentations [237-241]. Vineet Mittal offered a more optimistic view, citing states that already provide streamlined processes and the “stack-ranking” mechanism [242-245][267-274]. Both panelists agreed that new financing and de-risking mechanisms are needed, especially for regions lacking venture-capital ecosystems [41-44][45-48].


The audience asked about the global ramifications of AI-driven data-centre growth. Raghav Chandra answered that beyond emissions, the expansion will intensify water-use pressures, exacerbate social inequities and create cross-border environmental externalities, underscoring the need for coordinated international policy and standards [198-212][121-128][133-136].


Key take-aways


1. AI’s rapid expansion will push data-centre electricity use from ~1.5 % to ~3 % of global consumption by 2030, with attendant environmental and social costs.


2. Energy reliability is the greatest constraint on AI, as illustrated by recent high-profile outages.


3. AI-driven forecasting can schedule solar and wind output in 15-minute intervals, making renewables effectively dispatchable.


4. India’s strategic advantages – abundant renewables, a single national grid, low per-capita consumption [165-166], and a large AI talent pool – position it to become a global hub for gigawatt-scale green data-centres.


5. Advanced cooling, especially two-phase systems, can cut PUE from ~1.5 to ~1.05, dramatically reducing overall power demand.


6. Coordinated policy, tax incentives, streamlined permitting, and a national data-sovereignty act are essential to attract investment.


7. ISA’s AI-for-Energy mission and the planned ISI Academy aim to build the hybrid skill set needed for this transition.


8. New financing and de-risking models, as well as interoperable standards for AI-energy integration, remain critical open challenges.


The moderator concluded with a series of follow-up questions to guide future work, covering policy landscapes in developing countries, the composition of the cooling-innovation ecosystem, global standards, financing models, data-sovereignty legislation, centre-state coordination in India, water-scarcity-aware cooling, commercialization pathways for two-phase cooling, social and environmental impact assessments, AI-optimised renewable dispatch for AI workloads, peer-to-peer power-trading platforms, energy-efficient AI models and hardware, backup-power reliability, projected global electricity and carbon impacts by 2030, integration of pumped storage with AI, and transfer of gaming-industry cooling advances to data-centres [198-212][214-224][226-233][242-245][267-274][280-283][297-304][312-313].


Session transcriptComplete transcript of the session
Announcer

Good evening, distinguished guests. Welcome to the session on powering AI. As AI scales at speed, so does its infrastructure demands. Data centers are facing unprecedented power and cooling requirements. A single large AI training run can consume as much electricity as thousands of homes use in a year. This raises critical questions like how do we plan for rapidly rising and uncertainty energy demand? Can edge computing reduce the load, or is centralization inevitable? To address these critical issues, we are joined by our exceptional panelists. Mr. Vineet Mittal, Chairman of Avada Group. Sir, I request you to please come on stage. Mr. Natham Blom, Vice President, Cooling Chambers. Professor Raghav Chandra, Professor at IIM Calcutta, Founder and CEO of Consult and former Chairman of NHAI and Secretary to Government of India.

Moderating this important conversation is Mr. Ashish Khanna, Director General of the International Solar Alliance. Mr. Ashish Khanna, Director General of the International Solar Alliance. Thank you panelists for being here with that I now request Mr. Khanna to please take the discussion forward

Ashish Khanna

Good evening everyone not easy being the last panel especially when we are probably starting at the time that we are supposed to end but we hope and we will try and make it more interesting for all of you we are here to talk about Powering AI the format will be that I will begin in terms of framing some of the issues at heart and also tell you a little bit about what International Solar Alliance is going to do then I will hand over to each of the esteemed panelists to make an opening kind of a statement of what’s their vision on this question of Powering AI for about 5 minutes each and then I will ask them one question each and then I will ask the question and then I will ask the question on some of the specific issues for which they are probably an expert on.

And finally, if there is any time left, we will see if any audience member wants to ask a question. Let me start off by saying, why is International Solar Alliance in this session and in this AI Impact Summit? We are here primarily for two reasons. The first reason is, the world has done 1000 gigawatt of solar doubled in just last two years, what was done in last 25 years. Almost 40 % of that is decentralized, which means it’s either solar rooftop or pump or others. That figure is only 15 or 20 % in India and obviously very low in a lot of developing countries. And a distribution company often does not like decentralized solar because it impacts the distribution. It impacts the distribution system and finances.

But the right amount of digitization and AI can actually help them absorb it and reduce the cost of the system as a whole. And therefore, India’s ability to more than double decentralize renewable energy, but in general, world over, will require AI. That’s issue number one, for which actually I will say that we launched a global AI mission for energy in the AI Impact Summit. We call it AI for Energy. The session is going to talk about energy for meeting AI demands. But let’s first talk about AI for Energy. Why? Because there are some elements that the world has not seen, which is, if some of you were part of some sessions earlier, can consumers trade power based on what rooftop and batteries do you have, P2P trading, that requires certain digital enablement of the trade of millions of consumers, producers and consumers, that right now needs a lot of regulatory evolvement.

An IT architecture, so that each distribution company in India, but for that, that matter anywhere in the world will know what will it make ready to actually trade that power. all. It’s about jobs. Today, a lot of AI engineers do not understand energy. Energy engineers do not understand AI. We at International Solar Alliance, which is now 125 country member body, headquartered in India, is creating an ISI Academy to train people to bring together AI and energy skills engineers together. This intersection of energy and AI will be the fundamental shift over next five years, the way Amazon changed retail. This is what is going to happen, we believe, in renewable energy. Third, is about innovation ecosystem. We are in the AI Summit.

A lot of startups are having fundamentally disruptive ideas on both decentralized renewable energy, as well as the way you manage generation, transmission, and others. The fourth is about financing. How will all this financing and de -risking be done? Because not all places have a lot of venture capital or commercial loans and equity possible. We are in the process of creating a new industry. We are in the process of creating a new industry. We are in the process of creating a new industry. We are in the process of creating a new industry. We are in the process of creating a new industry. We are in the process of creating a new industry. And finally, there’s a global dimension where International Solar Alliance is involved.

What are going to be the interoperable standards? Because the world is not united on how all of this will be done. So that’s a lot about AI for energy. But there’s also an equally important element of energy for AI. The world’s largest sources of increase in electricity consumption right now are only two. Data centers and cooling. Some of it is going to happen through electrification of cars, EVs as well. Now, 70 % of all data center demand today is US and China. But in times to come, it’s increasing by almost more than 50%. A lot of it is going to happen in developing countries. And we’ll hear some of that in addition to global elements. A lot of that is also having a lot of innovation that will renewable energy provide that energy.

Can 24 by 7 solar and storage provide cost -competitive energy to some of these data centers, whether they’re small or hyperscale, hyperscale being above 100 megawatt? What’s happening on innovation on cooling? We will hear some of the experts on the private sector who are trying to come out with a lot of innovation on that and what happens on the ecosystem. Obviously, today’s data centers are consuming a grid equal to Spain right now, and it’s going to double every three years. So this is a very important segment. Without further ado, I’m actually going to go probably to the esteemed panel. I’m going to request Mr. Raghav Chandra. Sir, you have been part of the government and now teaching. When you look at this big…

element of powering AI, how do you see it?

Raghav Chandra

Thank you, Ashish. You’ve done a fantastic job in a short time period covering the larger macro issues connected with this sector. Friends, as we gather here in a nation racing towards digital sovereignty and sustainable growth, I want to emphasize and putting on my academic professorial hat, the single greatest constraint on AI’s future, which is not algorithms, not chips, but it is energy for AI -based data centers. And, you know, I’m going to mention a few such instances. In late 2024, Mark Zuckerberg made a confession that stunned his employees. A nesting colony of bees had torpedoed. Meta’s plans to open the world’s first nuclear -powered AI data center. That single environmental snag exposed their deeper vulnerability that Meta’s AI strategy depended on a single resource that it did not control and command, which is electricity.

Power outages and energy shortages have increasingly disrupted major tech companies’ operations, particularly as AI -driven data center demands strains global grids. There has been another very famous incident of March 29, 2025. A sudden loss of utility power in Google Cloud’s Columbus, Ohio unit triggered a critical failure in the uninterruptible power supply UPS batteries that created a major havoc for society. Several hours. This caused a cascading outage of six hours, in fact. Over 20 services were hit. Various customers experienced degraded performance or total unavailability, affecting cloud -dependent apps and websites globally. No direct apology was, of course, issued, but the event underscored energy reliability in a big way in an era of AI growth. In September 2019, utility power failed at one data center in Amazon Web Services, AWS’s North Virginia zone.

Backup generators activated but ran out of fuel after about an hour due to faulty automated refueling systems exacerbating the blackout. And it affected about 7 .5 % of the volume of… Apps and databases and some customers lost data permanently. Backups weren’t in place. Services like Slack and Netflix saw major ripples. And this has happened not only with Google Cloud or with Amazon AWS, but it has happened with companies such as Microsoft’s Azure, which suffered a major setback in 2018. It has affected TikTok, that’s ByteDance’s new USDS joint venture, causing widespread system failures. And what it underscores is the need for ensuring that there is suitable energy availability for data centers and that there is suitable backup for data centers.

Otherwise, you will not be able to have high powered. So energy guzzling, AI based data centers, which are the basic, basic. unit for AI to be implemented across the board for simplifying and for making and achieving our goals of ensuring that we have AI which is responsible, ethical, efficient, and which can do our job effectively. There is one county in the U .S. which my friends here on the dais would be aware of, of Ludon County, Virginia, just outside Washington, D .C., where data centers now outnumber people in density. And this 40 -square -kilometer area of computer server farms is Christend, the data center capital of the world. It hosts about 200 operational facilities, and another 100 or so are coming up.

Their peak draw is nearly 3 gigawatts. That’s enough to power a small country. Over 70 percent of the global Internet traffic passes. This is the clear area. What brought Ludon and its implications to the world’s notice was the massive outage at Amazon, causing tripping of crucial banking services and various social media companies. In Ireland, their data centers consume already one -fifth of the nation’s electricity, more than all the urban homes combined. Data centers traditionally began as largely in -house centers for proprietary computing data storage. They have since evolved, and today they are largely remote facilities or networks of facilities owned by cloud service providers, housing virtualized infrastructure for the shared use of multiple companies and customers. They need tons of electricity.

With all the power -hungry hardware and cooling systems, a data center today uses, higher -density racks, and whereas earlier… the data center typically used something like 150 to 300 watts of electricity per square foot. Today these higher density racks can consume as much as 100 kilowatts per cabinet which equates to 10 ,000 watts per square foot. And therefore a data center power problem can have global ramifications for the company. AI is supercharging data center boom that will recharge global energy systems. Global data center electricity consumption today is 415 terawatt hours. That’s about 1 .5 % of the world’s total consumption of electricity. And by 2030 it’s predicted to be nearly 945 terawatts or 3 % of the total consumption. So AI is not a side story. It’s the main driver with accelerated servers growing 30 % annually.

in the United States, which is the current epicenter. Data centers use 176 terawatts in 2023, or 4 .4 % of the national electricity. Projections are staggering. That’s like adding, in fact, the entire power demand of countries like Australia or Spain. So, you know, when we look at powering AI, we have to look not just at the upstream issues of creating the requisite demand, of creating the requisite power supply, but the other factors which come into play are the downstream effects and the hidden costs of progress. Environmental, if we rely only on fossil fuels to bridge the gap, emissions soar, so you have the debate between thermal and between renewable. which my colleague here will talk about. Big tech’s scope to emissions are already up 30 to 50 % since 2020.

Globally, data centers could claim 40 % of new fossil generation if clean supply lags. And so, while on the one hand, AI can help to accelerate decarbonization through optimal strategies and with intelligent working, but at the same time, the very fact that they are power guzzlers, they have an environmental issues which is inherent, and therefore there is a need for choosing a virtuous path. They have economic and social costs, while power prices are spiking. For instance, in the US, in and around areas which have data centers, the power cost has gone up significantly. In fact, wholesale electricity has jumped 200 to 250%. . in five years in certain areas, and the households are feeling that pinch. There is an issue of reliability.

Grids weren’t built for this. Voltage swings in Virginia have already tripped dozens of centers. In a warming world with rising AC loads, blackouts aren’t theoretical. They’re a governance failure waiting to happen. You have the equity issue. Who bears the burden? Communities near data centers face noise, heat, and land -use conflicts. In developing nations such as India, the digital divide widens if energy access for AI crowds out basic needs. So there’s a need for ingenuity when we’re dealing with this issue, and efficiency has to be the best weapon for dealing with the larger social, environmental, and other issues connected with this. And, of course, you know, in India, a lot is happening about which we’ll talk about.

But there is, indeed, a moment of great… happiness that AI is powering us, but there is also need to be concerned about whether we will be able to power AI effectively and whether we will be able to effectively and efficiently manage the downstream effects of powering that AI effectively. Thank you.

Ashish Khanna

Thank you so much, Raghavji, for the different elements of sustainability risks for the society. Nathan, your opening statement especially from the cooling perspective.

Nathan Blom

that keeps these northern Virginia, as an example, data centers from adapting to more efficient and effective technologies. But when you’re starting with new builds, with white space technologies, you have the opportunity to actually build for the future instead of build for the past. And so that, to me, is the most important element as to how we’re going to solve powering AI in the future.

Ashish Khanna

Thank you, Nathan. I’m sure you educated a lot of us in terms of what’s really happening on the cooling side on the innovation. Vineet, over to you, that from one of the leading renewable energy developers, how do you see?

Vineet Mittal

Good evening, everyone. So I see AI as one of the biggest opportunity. For the renewable sector, historically, people believe that renewable is intermittent, which it is. It is difficult to predict when the sun shines and wind blows. So we needed the technology which can help us intermittent power dispatchable at 15 minutes interval so that the grid can operate in a stable environment. So what AI has helped that with the help of a lot of climatic data, which your weather department collects, company like renewable companies are collecting, defense department collects. And then you can get real time data from low earth orbit satellites. If you use all of them in the right way, you are able to predict using AI that what would be my generation like.

And then you go a step further and you can schedule and dispatch that power like a conventional thermal power would do. So that makes AI for energy and energy for AI. And that empowers the grid to have always on. Clean power. which is the uniqueness India offers. So let me tell you, friends, when India started adding solar and wind some 15 -16 years ago, we didn’t even have 5 megawatt of operational asset. And this year alone, India is going to add 50 ,000 megawatt of solar and wind capacity, making us the second largest green energy player besides China. And what it gives power to India is that, like the previous panelists were saying, in the U .S., in Malaysia, even in Ireland, which used to be the data center capital, every country started charging some surcharge on powering the data center.

But the reality of life is that there are not going to be 50 megawatt or 100 megawatt data center. Now we are talking about 500. 500 megawatt, gigawatt data center because the… compute requires so much of eating as Nathan has explained. Without impacting the society and affordably if you have to do, India is the place. And the reason I say that we are blessed with abundance of sun, wind and water. So using the pumped storage because of our geography, we are actually getting a natural ability to do storage. And largely in most of the states, sun and wind are complementary in nature. So what happens is using sun and wind alone, you can generate 14 to 18 hours of power and then you complement it with pumped storage and battery.

And if you combine with the AI and you build your AI stack properly, you are looking for round the clock green power. So India is the perfect location India is adding 50 gigawatt It’s not competing with the normal consumer. India has a lot of very good policy where using green power, they are able to move even farming activity from the night shift to the day shift. So and our per capita power consumption is one of the lowest in the world. We are less than 1500 kilowatt hour per year per capita. So if India has to become a Vixit Bharat, you can’t become Vixit without data. And data is the new oil. And unfortunately, what is happening today is that we are we have 1 .4 billion people and out of which a billion people are connected.

And we are one of the cheapest data connectivity package in the world. So we are. The largest user of YouTube in the world, almost 700 million. user on the YouTube is from India and we are the largest content creating economy whether you take Insta, whether you take YouTube, you take any social media. It’s a repeat story even on WhatsApp we are more than half billion user. And all of this data as previous speaker was saying resides in some other countries. So why should we generate so much of data and the data should reside in any other country because probably earlier we didn’t focus to use all this abundance of energy and power that data center and now today the scenario is it makes economic sense in US.

Now you cannot get any power before 2030. All even the gas machines are sold out. So if you look at the grid waiting time in the US is typically 7 to 8 years. Permitting you can get during that time but if the world has to adopt TI at a massive scale India offers that opportunity where we can set up multiple gigawatt data center. We can provide them green power using solar, wind and storage. And we actually have a very unique situation. Unlike US or Europe, India has a single grid. You can insert the power in Rajasthan and can pick up in Mumbai in real time basis. And India has invested heavily into the grid. And we continue to grow that national grid where the whole country is connected.

So the best location for solar, best location for wind, best location for pumped storage and battery can bring power to the data centers in Mumbai, Chennai, which are already connected. So the latency does not become the bottom line and it becomes the ideal choice. What is needed is probably more data sovereignty type of act. Indian user content has to be located in India by certain time frame and so that developers can plan for the grid they can plan for the large data center capacity and can bring that to light so it’s one of the greatest opportunity for India Indian ecosystem is purely geared up for that and on top of that we have if you look at even in the AI probably more than 25 % of talent resides in India and that talent currently is working for other countries so they will be based in India, work for India and provide services and intelligence to the rest of the world and that’s the way moving forward

Ashish Khanna

Great so let’s have a little bit of a discussion and I do hope we get time for one or two questions so there was a little bit of questions that, Raghavji, you talked about, but a lot of optimism on both sides. I will ask a question combining two elements, which are important. One of it relates to the whole policy and regulatory landscape. Is India, or for that matter, developing world’s policy and regulatory landscape conducive for promoting data centers? I think, Vineet, you talked about the importance of data, the policy and regulatory landscape related to data sovereignty. Even Africa, I remember, was thinking of having a legislation like Europe, where the data for that particular continent or that particular country should be within that region.

But then there is also a policy and regulatory landscape for discovering price of power for data centers. India believes it’s very competitive. U .S. is struggling with the cost of providing power. Power probably is a limiting factor rather than the Nvidia chips. So that’s where the U .S. is. The second element is on innovation. I think you spoke about it, Nathan, but we’d like to hear what would an innovation landscape for cooling look like? Is it a lot of startups? Is it a lot of some of the larger companies doing some process efficiency? What would this innovation landscape look like? I want to request each of you to think about and say what would a policy and regulatory landscape change and an innovation landscape change accelerate both the speed and the cost of what meeting the demands of data centers look like?

Raghav.

Raghav Chandra

So in the Indian context, you know, the stakes for us, as Vineet mentioned, with all the opportunity and the resources that are available to us in terms of land, in terms of water, in terms of the skilled manpower, the opportunities are enormous. And the data center capacity is all set to explode. Today, it consumes about one gigawatt of power today. We are expecting it to reach about eight or nine gigawatts by 2030. And it’s continuously growing. We have ambitious states like Andhra Pradesh, which can effectively be called the data cities or data states for the country. We have a coal -dominated grid, which India has fortunately allowed to continue in a very pragmatic way. We have rising cooling needs from extreme heat.

And as Nathan mentioned, that some of our states can have a power usage efficiency or effectiveness, which can be extraordinary. Because of all the heat, whereas ideally it should be. one which is the perfect index and we also have a net zero ambition of ensuring that we have complete renewable focus non -fossil fuel based energy dependency to reach by the year 2070 which is our global commitment which is I think again a very bold and generous commitment of India but the biggest issue that I find in this entire landscape if you ask me is about the ease of doing business in India and I am not being skeptical but having been an administrator who has been a managing director of the state industrial development corporation the state investment corporation the managing director of the road corporation the urban development principal secretary chairman of the national highway authority and various other such positions Now when I sit back and I’m on six company boards, I realize that the biggest bottleneck in India today is the lack of synergy between the states and the center, between the departments of the government and essentially between the states and the center.

And if India has to move forward to achieve this huge target that it has set for itself for ensuring that we become the data center country for the world, that we exploit our entire human resources, that we exploit our land resources, the solar energy that we have, we must have, you know, apart from the regulatory schemes, et cetera, and for the regulatory. On the regulatory side, much is being done. For instance, in the latest budget, we are all aware that how the finance. Minister announced the scheme for ensuring tax exemption for data centers that are set up in India with foreign collaboration for the foreign component part of the investment and for their revenues. Lots happening on the renewable energy front.

Lots happening on the various data centers that are being set up. However, lots needs to be done in terms of getting synchronized coordination, ensuring that the best technologies are brought in. One of the points which Nathan made was about leapfrogging and ensuring that India should capture technologies which other nations have faultily or by mistake adopted. We can certainly skip that and go on to the best technology. Water in the days to come is going to be a very, very big and critical issue. Thank you for India. And therefore, using liquid coolants and solutions such as that for cooling are going to be extremely important. And this has to be realized not only by the central government, by the states, and by everybody who is working in the field that they must facilitate ensuring that these things are adopted in a positive manner.

I had an example of a foreign company which the other day was talking to me. And they had signed an MOU with a particular state government for a huge amount of data centers to be established there. And they said that, you know, we are struggling. We’ve made eight presentations and we haven’t been able to move forward on that. That’s the kind of thing which with the best intentions and with our prime minister being so proactive that we should really have proactive chief ministers, everyone getting down to business, and using the large number of experts who are available all around to explain to them the best technology and moving beyond perhaps even L1 to be able to get the best configurations on the ground to ensure that we are not only efficient but we are effective.

Ashish Khanna

Great. So a lot of potential but work to be done on ease of doing business, center state coordination and also from innovation a big potential for Indian companies to innovate on cooling, liquid cooling especially given water constraints. Nathan, over to you.

Nathan Blom

Yeah, I’ll comment on that innovation because that is innovation is the foundation that the IT industry is built upon and it’s built upon the idea that any one individual or small group of individuals can create an idea that changes the entire multi billion dollar industry itself and those who don’t innovate end up falling off the map. You know, you don’t talk anymore about AOL or Ask Jeeves or companies like that, and maybe we’ll say the same thing about Meta or Microsoft or, you know, Google or Amazon someday. Who knows? Because that’s the nature of the industry. And so as we look into the future, I think the innovation is going to require these smaller companies who are able to take risks and think bigger, especially around these cooling technologies.

And that’s what’s already happening today is we’re seeing people who are thinking outside the box of what we’ve normally considered to be advanced cooling technologies. Today, when we talk about advanced cooling that’s being deployed, what we’re really talking about is moving from that air -cooled ecosystem to just a simple liquid cooling ecosystem, which was developed in the 1960s for the Apollo space mission in the United States by IBM. And it’s been used for all of those years, including in the 1960s. If you’re a gamer at home, it’s been used in those large desktop gaming systems. And so this is an old and proven technology. You basically use… ethylene or propylene glycol mixed with water and you pump it through a pipe and it touches a cold plate on top of the hot chip and it captures it in liquid and moves away.

And that is a very simple and easy way of capturing heat, but it has limits. And what we’re facing is the limit that that liquid, as it leaves the chip, is getting so hot that you then have to have some coolant, some way to cool it back down. And that uses an incredible amount of electricity to cool that water back down, to use chillers on the roof of your data center to chill that water back down. And so the delta between the heated water, glycol, and the chilled water has to continue to get bigger and bigger and bigger, which means you have to cool that water lower and lower and lower using more electricity, so you eliminate the efficiency.

There’s now technologies emerging, and this is what my company is focused on, that is very similar to the way we cool. You can cool air in an air conditioner or in your car or in your refrigerator, and it’s called a two -phase technology, and basically what that means, instead of pumping liquid around… and it’s staying liquid, it actually, the liquid boils and vaporizes and that change of phase that is from a liquid to a gas is 10 to 20 times more effective and efficient at capturing heat. And that technology, though, is being spearheaded by small companies and those small companies will get bought up by large companies and they’ll be adopted into the ecosystem. And so expect to see that.

Expect to see the same basic use of refrigeration or refrigerants that we have today and we’ve been using for a long time, but using them specifically within the IT load of a data center ecosystem. That allows us to get those PUEs, that utilization efficiency ratio, not 1 .5 but 1 .05. You see that, I mean, that’s a massive step function increase in efficiency, which means the power generation doesn’t, doesn’t have to be strained nearly as much. And so I think that’s where the innovation is really going to come in the next three to five years.

Ashish Khanna

great I think on the lighter note I’m always it’s baffled but amusing that the gaming industry was the start of GPU and now the cooling as well it’s fascinating how gaming industry is responsible for the AI revolution but lot of space for small companies if you have on the innovation side Vineet what do you think?

Vineet Mittal

Gaming and best actually because the large batteries requires the same amount of cooling so the way I see innovation happening across the board is when the knowledge and cross industry expertise starts fertilizing and for that to happen you have to start creating local ecosystem see we can’t be sitting on the fence and be solving and innovating consistently that you are doing in theory but when you are building large data center of gigawatt scale you can find solution and use those skill because the similar challenge comes when you design the clean room. So how do you combine the expertise of building a clean room of millions of square foot with the expertise which is required for cooling the batteries and the expertise which is required for power usage efficiency in the data center.

How do you combine those skills and build the solution which is good for India where the humidity in some of the cities where optical fibers are terminating through the sea is large and how do you balance it out. So you have to use the external environmental data also to customize your PUE efficiency. So we see that efficiency is possible at all levels whether the ceiling height should be 6 meters or 8 meters. How close to India. So India is in that sense is fortunate that we are building those expertise locally without being building those expertise locally. building those 100 gigawatt off data center. In Morgan Stanley did a study. There is a $4 million opportunity cost for the power.

So they are saying the battle for the AI is no more compute. And it’s no more intelligence. It’s the power. Power is the biggest challenge. And there is a lot of innovation which is happening on power sector in India. You gave a good example of P2P trading using AI. And the policy in India is quite open on open access. So when I give power to the grid and I’m taking it out, I’m getting the power in the real -time basis, which is very few countries are able to do globally. And we have to account for on the monthly basis. So that gives a flexibility to the data center, which you always want. clean power and they want 24 by 7 365 days reliable power that is what is available in India and I agree with Raghavji ease of doing business is not similar across the states in the country but that’s why government of India is doing stack ranking of the state so today you can’t be just dependent on one state like look at Maharashtra the kind of support they are providing today if you want to build data center is amazing like permitting land everything is fairly streamlined and on top of that they incentivize so I think government has got it not every state is on the same page that if you have to become a developed nation your data is the biggest enabler if you have to win any kind of manufacturing battle data is the biggest enabler like if you look at today even our financial data most of the software companies whether it is Oracle or SAP or Microsoft they want the data to be on the cloud and those data even your financial data now even SAP you can’t do ECC everything goes on HANA on rise which is on the cloud so you buy the space either from AWS or Microsoft because they have only partnership with those two so even the 40 ,000 odd companies which are on these ERP softwares in India where are their data going and so the opportunity wise I think India because of its own need will innovate consistently ease of doing business is a challenge and that’s where there is an opportunity to continuously work with the government on transparently on your challenges and suggesting a solution which is not benefiting one voice is a And then third is understanding the nuances of how the application layer is working across the industry and educating government also that why should they have the data localization initiative.

And I see all of this getting combined and India becoming probably the third largest country where the AI adoption and data center would be one of the enabling block for the future growth. Thank you.

Ashish Khanna

So a lot of optimism. I did promise one question. I have one question space only. So please go ahead. If you can identify yourself and have a brief question.

Audience

My name is Umesh Prasad Singh and I’m an associate member of Indian Institute of Public Administration. Sir, my question is directly to you. In your paper you have mentioned about global ramification. that particular aspect of global ramifications are of both types that is positive and negative. With respect to that, will you just have the clarification on that note? I wanted to know on that.

Raghav Chandra

When I said global ramifications, I’m talking of both essentially the downstream effects of focusing on data centers and the implications it has on the fact that it will have an implication for the environment because they are power guzzling, as Nathan mentioned, that today earlier we had data centers which were full of CPUs, today they are full of GPUs and you’re going into all kinds of even more complex computing units so because of the storage, the networking, they are becoming far more complex. So it’s going to have an impact on the environment because of the heat. That is generated intrinsically because of the data center, because of the environment that will be affected, because when you’re consuming coal to produce that power, you’re using water, that same water which could feed millions of people and pay the, you know, today we are not able to feed enough people for, provide adequate drinking water 24 by 7 to all our cities, yet you would have water effectively being used for the cooling of the data centers.

You will have social issues, because people today already for thermal power plants, they are creating issues where they find that their land, especially in the scheduled areas, et cetera, is being consumed for coal mining, so there are issues connected with that. Likewise, there are all kinds of social and environmental issues that are likely to happen. There are issues on the side of… You know, whether we, you know, what other implications it can have… So all these are things which are not essentially just localized, though they are local problems, but they will affect global companies which can have the benefit of India is that we can leapfrog in terms of technology. And hopefully, as one of the speakers earlier in the previous session mentioned, chips are also becoming more and more efficient.

So, you know, as they become, computing becomes more efficient, the chips become more efficient. So you will require a lesser amount of energy. If we can leapfrog, adopt the best technologies in terms of design and infrastructure, that again will be a great saving. So today, no nation is an island. Everyone is connected. And anything which impacts one nation affects the entire thing because data centers, if they are located here, as I mentioned, the case of the Ludon County outage, it affected billions of people all across. So it has a global ramification. while you have to think of your own benefit you have to keep an eye also on the impact whatever you are doing has on all across the nations and which is why when the Prime Minister talks of Manav, it is the human being who is at the center of it and the human being is not just you it is the larger mankind and the larger human community

Ashish Khanna

Thank you, unfortunately we do not have time for any more questions but it’s pretty late I’m ending without summarizing but it’s pretty apparent huge optimism on the power of India and developing countries to meet the demand for AI both through solar storage, innovation on liquid cooling and of course the ecosystem with ease of doing business please join me in giving a big round of applause to all of them and thank you for staying very late thank you everyone for joining Thank you. Thank you.

Related ResourcesKnowledge base sources related to the discussion topics (28)
Factual NotesClaims verified against the Diplo knowledge base (7)
Confirmedhigh

“Data‑centres today consume electricity equivalent to Spain’s grid.”

The knowledge base notes that current data centres consume electricity equivalent to Spain’s entire electricity consumption [S4].

Confirmedhigh

“Around 1 000 GW of solar capacity was added worldwide in the last two years.”

A source states that the world has added roughly 1 000 GW of solar capacity, matching the figure cited in the report [S5].

!
Correctionmedium

“Meta’s aborted nuclear‑powered data‑centre was shut down after a bee‑colony incident.”

The knowledge base reports that Meta is planning to harness nuclear energy for its data centres, but provides no evidence of an aborted project or a bee-colony incident; the claim appears inaccurate [S95].

Additional Contextmedium

“Electrification of cars/EVs is amplifying data‑centre energy demand.”

Policy discussions highlight the rising energy needs of EVs and the need for integrated charging infrastructure, adding nuance to the claim about EVs driving higher electricity demand [S17].

Confirmedmedium

“Power‑consumption concerns are pushing data‑centres toward edge deployment.”

A source explains that power consumption and site-requirements are the main factors encouraging edge-location of data centres [S94].

Additional Contextlow

“Cooling accounts for roughly 40 % of data‑centre power use.”

An expert notes that about 40 % of a data-centre’s power budget goes to cooling, providing additional detail to the discussion of cooling challenges [S19].

Confirmedlow

“The AI Impact Summit 2026 includes global ministerial discussions on inclusive AI development.”

The knowledge base mentions that the AI Impact Summit 2026 hosts global ministerial discussions on AI, confirming the summit’s role [S92].

External Sources (96)
S1
Building Trusted AI at Scale Cities Startups & Digital Sovereignty – Keynote Giordano Albertazzi — -Announcer: Role/Title: Event announcer/moderator; Area of expertise: Not mentioned
S2
Building Trusted AI at Scale Cities Startups & Digital Sovereignty – Keynote Takahito Tokita Fujitsu — -Announcer: Role as event announcer/host, expertise/title not mentioned
S3
Building Trusted AI at Scale Cities Startups & Digital Sovereignty – Keynote Cristiano Amon — -Announcer: Role/Title: Event announcer/moderator; Areas of expertise: Not mentioned
S4
Powering AI _ Global Leaders Session _ AI Impact Summit India Part 2 — -Vineet Mittal: Chairman of Avada Group, renewable energy developer and expert
S5
https://dig.watch/event/india-ai-impact-summit-2026/powering-ai-_-global-leaders-session-_-ai-impact-summit-india-part-2 — Good evening, distinguished guests. Welcome to the session on powering AI. As AI scales at speed, so does its infrastruc…
S6
Powering AI _ Global Leaders Session _ AI Impact Summit India Part 2 — – Nathan Blom- Ashish Khanna – Vineet Mittal- Nathan Blom- Ashish Khanna
S7
https://dig.watch/event/india-ai-impact-summit-2026/powering-ai-_-global-leaders-session-_-ai-impact-summit-india-part-2 — Moderating this important conversation is Mr. Ashish Khanna, Director General of the International Solar Alliance. Mr. A…
S9
Powering AI _ Global Leaders Session _ AI Impact Summit India Part 2 — Good evening, distinguished guests. Welcome to the session on powering AI. As AI scales at speed, so does its infrastruc…
S10
https://dig.watch/event/india-ai-impact-summit-2026/powering-ai-_-global-leaders-session-_-ai-impact-summit-india-part-2 — Good evening, distinguished guests. Welcome to the session on powering AI. As AI scales at speed, so does its infrastruc…
S11
WS #280 the DNS Trust Horizon Safeguarding Digital Identity — – **Audience** – Individual from Senegal named Yuv (role/title not specified)
S12
Building the Workforce_ AI for Viksit Bharat 2047 — -Audience- Role/Title: Professor Charu from Indian Institute of Public Administration (one identified audience member), …
S13
Nri Collaborative Session Navigating Global Cyber Threats Via Local Practices — – **Audience** – Dr. Nazar (specific role/title not clearly mentioned)
S14
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…
S15
AI energy demand accelerates while clean power lags — Data centres are driving asharp rise in electricity consumption, putting mounting pressure on power infrastructure that …
S16
https://dig.watch/event/india-ai-impact-summit-2026/heterogeneous-compute-for-democratizing-access-to-ai — That’s the edge cloud. And as you go deeper from there onwards, then you have the data centers. It then mitigates the ov…
S17
Climate change and Technology implementation | IGF 2023 WS #570 — One argument suggests that the internet and technology can enable innovative solutions by using artificial intelligence …
S18
Building Climate-Resilient Systems with AI — But here’s what we came up with. The first one, I mean, this is a kind of bottom line, but it’s important. AI does have …
S19
HETEROGENEOUS COMPUTE FOR DEMOCRATIZING ACCESS TO AI — “as we go from one gig to nine to ten gig … we have to realize that india is challenged by three physical things that …
S20
Efforts to improve energy efficiency in high-performance computing for a Sustainable Future — The demand for high-performance computing (HPC) has surged due to technological advancements like machine learning, geno…
S21
Greening digital companies: — 5G is enabling energy reductions per unit of data that are not possible with older generations of mobile technology. As …
S22
Creating Eco-friendly Policy System for Emerging Technology — Data centers, which use emerging technologies, consume a lot of energy. Nevertheless, despite their numerous benefits, …
S23
Open Forum #64 Local AI Policy Pathways for Sustainable Digital Economies — Anita Gurumurthy emphasised that despite improvements in chip efficiency, energy demand from data centres continues crea…
S24
Internet Governance Forum 2024 — AI emerged as a key technology with the potential toaccelerate progress on SDGs by up to 70%. From real-time policymakin…
S25
The Innovation Beneath AI: The US-India Partnership powering the AI Era — -Energy Grid Transformation and Clean Power: Detailed exploration of how AI’s massive energy demands require “programmab…
S26
Revisiting 10 AI and digital forecasts for 2025: Predictions and Reality — To address this, companies are exploring innovative solutions such aspower capping(limiting processor power to 60-80% of…
S27
Keynote-Jeet Adani — As we all know, under peak load, advanced processors generate extraordinary heat. Systems throttle when power falters an…
S28
Indias Roadmap to an AGI-Enabled Future — Data centers of India. I mean, that’s the kind of thought that government needs to think. then we can become so that’s w…
S29
Shaping the Future AI Strategies for Jobs and Economic Development — This comment reframes the AI competition from a purely technological race to an economic sustainability challenge, intro…
S30
Business Engagement Session — Dr. Al-Surf highlights the importance of innovative energy efficiency technologies in addressing sustainability challeng…
S31
Powering the Technology Revolution / Davos 2025 — HPE’s liquid cooling technology reduces energy consumption by 90% compared to air cooling in data centers. Neri discuss…
S32
From principles to practice: Governing advanced AI in action — – **Implementation Challenges Across Jurisdictions**: Participants highlighted the tension between rapid technological a…
S33
Revisiting 10 AI and digital forecasts for 2025: Predictions and Reality — To mitigate this,innovative cooling technologiessuch asimmersion coolingandliquid-to-liquid heat exchangersare gaining t…
S34
Powering AI _ Global Leaders Session _ AI Impact Summit India Part 2 — -Innovation in Cooling Technologies: The discussion explored critical innovations in data center cooling, moving from tr…
S35
Global AI Policy Framework: International Cooperation and Historical Perspectives — And these are principles that were established with VCs 20 years ago. And for us, these are non-negotiable foundations f…
S36
Main Session | Policy Network on Artificial Intelligence — Benifei argues for the importance of developing common standards and definitions for AI at a global level. He suggests t…
S37
WS #288 An AI Policy Research Roadmap for Evidence-Based AI Policy — The discussion highlighted the importance of policy interoperability rather than uniform global governance, recognizing …
S38
AI could optimise power grids and reduce energy waste — AI could helpmake power grids cleaner and more efficientwhile reducing energy waste, even as data centres powering gener…
S39
Agentic AI and the new industrial diplomacy — Energy systemsare perhaps the most politically sensitive arena for agentic AI. As renewables grow, grids become harder t…
S40
AI power demand pushes nuclear energy back into focus — Rising AI-driven electricity demand isstraining power gridsand renewing focus on nuclear energy as a stable, low-carbon …
S41
Building Trusted AI at Scale Cities Startups & Digital Sovereignty – Keynote Ebba Busch Deputy Prime Minister Sweden — “local job anchors if implemented and used correctly.”[73]. “They can be infrastructure for hospitals, for research, def…
S42
Data centre boom drives surge in legal services in India — India’s data centreexpansion, fuelled by investment inAI-ready infrastructure and cloud capacity, is creating strong dem…
S43
AN INTRODUCTION TO — Given the multi-disciplinary nature of Internet governance and the high diversity of actors and policy fora, it is parti…
S44
Government notices · GoewermentskennisGewinGs — –  Existing processes, procedures and fees are not streamlined: There is ‘ no central co-ordination, no consistency in …
S45
Bangladesh Rapid eTrade Readiness Assessment — The private sector has been intimately involved, with encouragement from the Government, in strategic planning rela…
S46
WS #484 Innovative Regulatory Strategies to Digital Inclusion — The disagreements are substantial enough to potentially impact policy coordination and resource allocation, particularly…
S47
TABLE OF CONTENTS — Ensuring sufficient investment and funding in for the policies and strategies outlined in the Policy will be critical to…
S48
Contents — It should be noted that liberalization in the GATS sense the granting of market access and national treatment – is not s…
S49
POLICY BRIEF — – Innovations that speed up cross-border commerce while ensuring trade compliance and lowering trade risks are i…
S50
WS #257 Emerging Norms for Digital Public Infrastructure — These key comments shaped the discussion by highlighting the complex, multifaceted nature of DPI. They moved the convers…
S51
WS #98 Universal Principles Local Realities Multistakeholder Pathways for DPI — Balancing national sovereignty with international interoperability Discussion of need for universal definition, common …
S52
WS #290 Sovereignty and Interoperable Digital Identity in Dldcs — Policy mapping of different regulations across countries is crucial for establishing trust frameworks Regional agreemen…
S53
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…
S54
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 …
S55
Open Forum #64 Local AI Policy Pathways for Sustainable Digital Economies — Anita Gurumurthy emphasised that despite improvements in chip efficiency, energy demand from data centres continues crea…
S56
Creating Eco-friendly Policy System for Emerging Technology — Nevertheless, despite their numerous benefits, emerging technologies present substantial challenges and risks. Foremost …
S57
Powering AI _ Global Leaders Session _ AI Impact Summit India Part 2 — “Friends, as we gather here in a nation racing towards digital sovereignty and sustainable growth, I want to emphasize a…
S58
Greener economies through digitalisation — Furthermore, greater stakeholder participation, particularly of Micro, Small, and Medium Enterprises (MSMEs), should be …
S59
The Innovation Beneath AI: The US-India Partnership powering the AI Era — -Energy Grid Transformation and Clean Power: Detailed exploration of how AI’s massive energy demands require “programmab…
S60
Revisiting 10 AI and digital forecasts for 2025: Predictions and Reality — To address this, companies are exploring innovative solutions such aspower capping(limiting processor power to 60-80% of…
S61
Climate change and Technology implementation | IGF 2023 WS #570 — João Vitor Andrade:Hi, everyone. I’d like to thank you all to be present here today. My name is João Vitor, I’m from Bra…
S62
Indias Roadmap to an AGI-Enabled Future — Data centers of India. I mean, that’s the kind of thought that government needs to think. then we can become so that’s w…
S63
Keynote-Jeet Adani — As we all know, under peak load, advanced processors generate extraordinary heat. Systems throttle when power falters an…
S64
The Battle for Chips — In conclusion, India’s strategic approach to developing a comprehensive semiconductor ecosystem demonstrates a commitmen…
S65
Powering the Technology Revolution / Davos 2025 — – Andrés Gluski- Greg Jackson- Uljan Sharka HPE’s liquid cooling technology reduces energy consumption by 90% compared …
S66
Business Engagement Session — Dr. Al-Surf highlights the importance of innovative energy efficiency technologies in addressing sustainability challeng…
S67
Safe and Responsible AI at Scale Practical Pathways — The panel revealed that making data AI-ready is fundamentally a governance challenge rather than merely technical. The a…
S68
From principles to practice: Governing advanced AI in action — – **Implementation Challenges Across Jurisdictions**: Participants highlighted the tension between rapid technological a…
S69
Green AI and the battle between progress and sustainability — AI is increasingly recognised for its transformative potential and growing environmental footprint across industries. Th…
S70
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S71
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S72
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S73
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S74
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S75
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S78
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S79
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S80
Chief Economists’ Briefing: What to Expect in 2025? / DAVOS 2025 — The tone was generally serious and analytical, with economists offering measured but somewhat pessimistic views on globa…
S81
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S82
Panel Discussion AI in Digital Public Infrastructure (DPI) India AI Impact Summit — The tone was consistently optimistic and forward-looking throughout the conversation. Speakers expressed excitement abou…
S83
Keynote-Rishad Premji — Opening framing by the moderator
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S85
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S86
WS #202 The UN Cybercrime Treaty and Transnational Repression — A panel of experts convened at the Internet Governance Forum to discuss the UN Cybercrime Treaty and its potential impli…
S88
Seismic Shift — More than 270 million people will be added to India’s urban population over the next two decades, and Oxford Economics p…
S89
https://dig.watch/event/india-ai-impact-summit-2026/the-global-power-shift-indias-rise-in-ai-semiconductors — And one of the changes that has happened, obviously India becoming the larger in terms of GDP size, consumer demand, peo…
S90
https://dig.watch/event/india-ai-impact-summit-2026/ai-and-data-driving-indias-energy-transformation-for-climate-solutions — A very important question indeed. When in the public policy, the equity is extremely important. And equity means the ent…
S91
Artificial intelligence (AI) – UN Security Council — During the9821st meetingof the Artificial Intelligence Security Council, a key discussion centered around whether existi…
S92
AI Impact Summit 2026: Global Ministerial Discussions on Inclusive AI Development — He’s building an AI to police, AI. And it’s an international effort, and he welcomes partnerships. We will be announcing…
S93
Cooperation for a Green Digital Future | IGF 2023 — Alexia Gonzalez Fanfalone:Thank you very much. Patrick. Everybody hears me okay? Yes? Yes. Okay. So thank you very much….
S94
Designing Indias Digital Future AI at the Core 6G at the Edge — Power consumption concerns are driving data centers toward edge deployment Roy emphasizes that infrastructure challenge…
S95
Meta eyes nuclear energy to power AI and data centres — Metahas announcedplans to harness nuclear energy to meet rising power demands and environmental goals. The company is so…
S96
Day 0 Event #260 Securing Basic Internet Infrastructure — Erica Moret: Well, thank you very much, first of all, for the kind invitation to join you today. You can hear me okay? Y…
Speakers Analysis
Detailed breakdown of each speaker’s arguments and positions
A
Announcer
2 arguments88 words per minute177 words119 seconds
Argument 1
AI scaling is driving unprecedented power and cooling demands for data centers.
EXPLANATION
The announcer highlights that as AI models become larger and more numerous, the infrastructure required to run them consumes massive amounts of electricity, creating new challenges for data centre operators.
EVIDENCE
The speaker notes that a single large AI training run can consume as much electricity as thousands of homes in a year and that data centres are facing unprecedented power and cooling requirements as AI scales at speed [5][4][3].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The unprecedented power and cooling needs are documented in [S5] and [S4], which note that a single large AI training run can consume electricity comparable to thousands of homes and that data centres face record-high power and cooling requirements. Higher rack power densities are also highlighted in [S1] and [S14].
MAJOR DISCUSSION POINT
AI growth creates massive energy demand for data centres
Argument 2
Planning for rapidly rising and uncertain energy demand requires evaluating edge computing versus centralisation.
EXPLANATION
The announcer raises the strategic question of how to meet the accelerating energy needs of AI, asking whether decentralised edge solutions can alleviate the load or whether centralised data centres remain inevitable.
EVIDENCE
The speaker explicitly asks how to plan for rising and uncertain energy demand and whether edge computing can reduce the load or centralisation is inevitable [6][7][8].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The strategic trade-off between edge and centralised data-centre capacity is discussed in [S16], which describes how edge cloud can mitigate overall data-centre demand, and in [S5] which calls for planning around rising energy needs.
MAJOR DISCUSSION POINT
Strategic planning for AI energy demand
V
Vineet Mittal
5 arguments141 words per minute1722 words732 seconds
Argument 1
AI makes renewable energy dispatchable and grid‑stable by predicting generation with climatic and satellite data.
EXPLANATION
Mittal explains that AI can process large volumes of weather and satellite information to forecast solar and wind output, allowing renewable plants to be scheduled and dispatched like conventional thermal generators.
EVIDENCE
He describes using AI together with climatic data, weather department data, low-earth-orbit satellite data to predict generation and then schedule and dispatch power in 15-minute intervals, making renewables behave like conventional thermal power [151][152][153][154][155][156].
MAJOR DISCUSSION POINT
AI enables renewable predictability and dispatch
AGREED WITH
Ashish Khanna
Argument 2
India’s abundant solar, wind, water and pumped‑storage resources uniquely position it to provide 24/7 green power for data centres.
EXPLANATION
Mittal points out that the complementary nature of India’s renewable resources, combined with pumped‑storage and battery capacity, can deliver continuous power, making the country an ideal location for large‑scale data centre deployment.
EVIDENCE
He notes that sun and wind are complementary, can generate 14-18 hours of power, which is then supplemented by pumped storage and batteries to achieve round-the-clock green power, and cites India’s massive solar-wind addition of 50 GW this year [165][166][167][168][169][170].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Mittal’s points are corroborated by [S4], which details India’s complementary solar-wind generation, pumped-storage and the addition of 50 GW of renewable capacity annually, enabling round-the-clock green power for data centres.
MAJOR DISCUSSION POINT
India’s renewable mix can power data centres continuously
Argument 3
Recent policy measures such as tax exemptions for foreign‑collaboration data centres and open‑access power trading create a favourable environment for data‑centre growth in India.
EXPLANATION
Mittal highlights that the Indian budget introduced tax incentives for data centres with foreign components and that the power market allows real‑time, open‑access trading, both of which lower costs and improve flexibility for operators.
EVIDENCE
He references the budget scheme granting tax exemption for data centres with foreign collaboration [226][227] and describes how open-access, real-time power trading gives flexibility to data centres [280][281][282][283].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
[S4] reports the budget-driven tax exemption scheme for data centres with foreign components and the open-access, real-time power-trading framework that lowers costs and adds flexibility for operators.
MAJOR DISCUSSION POINT
Policy incentives boost data‑centre investment
AGREED WITH
Ashish Khanna, Raghav Chandra
DISAGREED WITH
Raghav Chandra
Argument 4
While ease of doing business varies across Indian states, the government is ranking states and streamlining permits to accelerate data‑centre deployment.
EXPLANATION
Mittal acknowledges uneven business environments but notes that the central government is creating a state‑ranking system and simplifying land‑allocation, permitting and incentives, especially in states like Maharashtra.
EVIDENCE
He mentions the stack-ranking of states, streamlined permitting, and strong support from Maharashtra for data-centre projects [242][243][244][245].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
State-level reforms, including a ranking system and streamlined land-allocation and permitting-especially in Maharashtra-are described in [S4].
MAJOR DISCUSSION POINT
State‑level reforms improve data‑centre rollout
AGREED WITH
Ashish Khanna, Raghav Chandra
DISAGREED WITH
Raghav Chandra
Argument 5
Data sovereignty and localisation are essential; India should ensure Indian user‑generated content resides domestically to drive infrastructure planning.
EXPLANATION
Mittal argues that keeping data within national borders will encourage investment in local power and data‑centre capacity, aligning with broader data‑sovereignty initiatives.
EVIDENCE
He calls for a data-sovereignty act that mandates Indian user content be stored in India, linking it to grid planning and large-scale data-centre capacity [194][195][196].
MAJOR DISCUSSION POINT
Data localisation supports domestic infrastructure
N
Nathan Blom
3 arguments173 words per minute697 words240 seconds
Argument 1
Transitioning from air‑cooled to liquid‑cooled data‑centre architectures is crucial for improving energy efficiency.
EXPLANATION
Blom explains that liquid cooling, originally developed for the Apollo program, directly removes heat from chips via a cold plate, offering a more efficient alternative to traditional air‑cooling systems.
EVIDENCE
He describes the liquid-cooling technology that pumps ethylene or propylene glycol mixed with water through a pipe to a cold plate, capturing heat directly from the chip, and notes its long history since the 1960s [249][250][251][252][253][254].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The shift to liquid cooling and its efficiency benefits are highlighted in [S4] (innovation in cooling technologies) and supported by broader HPC efficiency discussions in [S20].
MAJOR DISCUSSION POINT
Liquid cooling enhances data‑centre efficiency
AGREED WITH
Vineet Mittal
Argument 2
Emerging two‑phase cooling technology can deliver 10‑20 times higher heat‑removal efficiency, dramatically lowering PUE values.
EXPLANATION
Blom highlights that two‑phase cooling, where the liquid boils and vaporises, provides a far more effective heat‑transfer mechanism, potentially reducing PUE from around 1.5 to 1.05.
EVIDENCE
He explains the principle of two-phase cooling, its superior heat-capture efficiency, and quantifies the expected PUE improvement from 1.5 to 1.05, representing a massive step-function increase in efficiency [259][260][261][262][263][264].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
[S4] explains two-phase cooling’s superior heat-transfer, projecting PUE reductions from ~1.5 to ~1.05, i.e., a 10-20× efficiency gain, and [S20] references similar advances in high-performance computing cooling.
MAJOR DISCUSSION POINT
Two‑phase cooling promises major PUE gains
AGREED WITH
Vineet Mittal
Argument 3
Small, innovative companies will drive breakthrough cooling solutions and will later be integrated into larger firms, shaping the industry’s future.
EXPLANATION
Blom argues that the cooling ecosystem thrives on agile startups that pioneer new technologies; as these solutions mature, larger corporations will acquire them, accelerating widespread adoption.
EVIDENCE
He notes that small companies are spearheading the two-phase technology and that they are expected to be bought up by larger firms, leading to industry-wide deployment [260][261][262].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The role of agile startups in pioneering cooling breakthroughs, later to be acquired by larger corporations, is noted in [S4].
MAJOR DISCUSSION POINT
Start‑ups are the engine of cooling innovation
A
Ashish Khanna
5 arguments153 words per minute1530 words598 seconds
Argument 1
AI can enable decentralized renewable integration and peer‑to‑peer power trading, reducing system costs and supporting the rapid growth of AI workloads.
EXPLANATION
Khanna outlines that AI‑driven digitisation can help distribution companies manage large numbers of rooftop and battery assets, facilitating P2P power markets and lowering overall energy costs for AI‑intensive applications.
EVIDENCE
He cites that 40 % of recent solar growth is decentralized, that AI can help distribution companies absorb this and reduce costs, and that the International Solar Alliance has launched a global AI-for-Energy mission to address these challenges [20][21][22][25][26][27][28].
MAJOR DISCUSSION POINT
AI as a tool for decentralized renewable integration
AGREED WITH
Vineet Mittal
Argument 2
Data centres and cooling are the largest drivers of the current surge in global electricity consumption, and must be addressed to sustain AI development.
EXPLANATION
Khanna points out that data‑centre and cooling loads now dominate electricity growth, especially in the US and China, and that without innovative solutions the energy demand for AI will become unsustainable.
EVIDENCE
He states that data centres and cooling are the world’s biggest sources of electricity consumption increase, that 70 % of current data-centre demand is in the US and China, and that demand is projected to double every three years, especially in developing countries [54][55][56][58][59][60][66][67].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
[S15] warns that AI-driven data-centre growth is accelerating electricity demand faster than clean-power supply, making data-centre and cooling loads the dominant source of recent electricity consumption increases; [S5] also emphasizes the scale of AI-related power use.
MAJOR DISCUSSION POINT
Energy for AI is dominated by data‑centre and cooling loads
AGREED WITH
Announcer, Raghav Chandra
Argument 3
Global interoperable standards and coordinated policy are essential for scaling AI‑energy solutions worldwide.
EXPLANATION
Khanna stresses that without common standards and regulatory alignment, the deployment of AI‑driven energy systems will be fragmented, hindering global adoption.
EVIDENCE
He mentions the need for interoperable standards, noting that the world is not united on how AI-energy integration will be done, and that the International Solar Alliance is involved in shaping this global dimension [50][51][52][53].
MAJOR DISCUSSION POINT
Need for global standards in AI‑energy integration
AGREED WITH
Raghav Chandra, Audience
Argument 4
Financing and de‑risking AI‑energy projects are critical, especially for developing countries that lack venture capital and commercial loan access.
EXPLANATION
Khanna highlights that without appropriate financial mechanisms, many promising AI‑energy innovations will not scale, underscoring the importance of new industry‑wide financing models.
EVIDENCE
He raises questions about how financing and de-risking will be done, noting the scarcity of venture capital and commercial loans in many regions [41][42][43][44][45][46][47][48][49].
MAJOR DISCUSSION POINT
Financial mechanisms are needed for AI‑energy scaling
AGREED WITH
Vineet Mittal, Raghav Chandra
Argument 5
Regulatory evolution is required to enable P2P power trading and the digital enablement of millions of consumers and producers.
EXPLANATION
Khanna argues that current regulations limit the ability of consumers to trade power generated from rooftop solar and batteries, and that AI‑driven digital platforms need supportive policy frameworks to function at scale.
EVIDENCE
He describes the need for regulatory evolution to allow P2P trading of power from rooftop and battery assets, requiring IT architecture and digital enablement for millions of participants [31][32][33].
MAJOR DISCUSSION POINT
Regulation must adapt for AI‑enabled P2P energy markets
AGREED WITH
Vineet Mittal, Raghav Chandra
DISAGREED WITH
Vineet Mittal
R
Raghav Chandra
5 arguments129 words per minute2453 words1140 seconds
Argument 1
Energy availability is the single greatest constraint on AI’s future, as data‑centre power shortages cause major service disruptions.
EXPLANATION
Chandra emphasizes that without reliable electricity, AI workloads cannot be sustained, citing multiple high‑profile outages that illustrate the fragility of current power supplies for data centres.
EVIDENCE
He references incidents at Meta’s nuclear-powered data centre plan, a March 2025 Google Cloud outage in Ohio, an AWS Virginia blackout in 2019, and similar failures at Microsoft Azure and TikTok, all caused by power loss and inadequate backup systems [75][77][78][80][81][82][83][84][86][87][88][89][90][91][92][93][94][95][96].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Reliability challenges such as voltage swings in Virginia that tripped dozens of data centres are documented in [S4], underscoring power-availability as a critical constraint.
MAJOR DISCUSSION POINT
Power reliability is critical for AI infrastructure
AGREED WITH
Ashish Khanna, Audience
Argument 2
Data‑centre electricity consumption will grow to levels comparable with entire national grids, creating significant environmental and social costs.
EXPLANATION
Chandra projects that global data‑centre electricity use will rise from 415 TWh (1.5 % of world consumption) to nearly 945 TWh (3 %) by 2030, equating to the power demand of whole countries and raising concerns about emissions and resource use.
EVIDENCE
He provides figures on current consumption (415 TWh, 1.5 % of global electricity) and future projections (945 TWh, 3 %), noting that this is comparable to the power demand of nations like Australia or Spain [112][113][114][115][116][117][118][119][120].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
[S15] projects global data-centre electricity use rising to ~945 TWh (≈3 % of world consumption) by 2030, a level comparable to the demand of whole countries.
MAJOR DISCUSSION POINT
Data‑centre growth threatens national‑scale energy balances
Argument 3
Continued reliance on fossil‑fuel power for data‑centres will sharply increase emissions; a shift to renewable energy is essential for a virtuous path.
EXPLANATION
He argues that if clean supply does not keep pace, data‑centres could account for up to 40 % of new fossil generation, urging a transition to renewable sources to mitigate climate impact.
EVIDENCE
He notes that big-tech emissions have risen 30-50 % since 2020, that data-centres could claim 40 % of new fossil generation if clean supply lags, and calls for choosing a virtuous path [121][122][123][124].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
[S15] warns that without clean-power supply, data-centres could account for up to 40 % of new fossil generation, urging a transition to renewables; [S4] also highlights India’s renewable potential as an alternative.
MAJOR DISCUSSION POINT
Renewables needed to curb data‑centre emissions
Argument 4
Rising power costs, grid reliability issues, and equity concerns create social challenges for communities near data‑centres.
EXPLANATION
Chandra points out that electricity prices have surged 200‑250 % in some US regions, that voltage swings cause outages, and that nearby communities face noise, heat, and land‑use conflicts, highlighting the need for equitable burden sharing.
EVIDENCE
He cites wholesale electricity price jumps of 200-250 % over five years, voltage swings tripping dozens of centres, and mentions equity issues such as noise, heat, land-use conflicts, and the digital divide in developing nations [125][126][127][128][129][130][131][132][133][134][135][136][137].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
[S4] cites wholesale electricity price spikes of 200-250 % and voltage-swing-induced outages, and mentions equity impacts such as noise, heat, land-use conflicts and the digital divide affecting nearby communities.
MAJOR DISCUSSION POINT
Energy costs and equity affect data‑centre siting
Argument 5
Lack of coordination between central and state governments in India is a major bottleneck for data‑centre expansion and energy planning.
EXPLANATION
Chandra, drawing on his extensive administrative experience, argues that fragmented governance hampers the implementation of large‑scale data‑centre projects, and calls for better synergy and streamlined processes.
EVIDENCE
He describes the absence of synergy between states and the centre, cites an example of a foreign company unable to progress after eight presentations, and stresses the need for coordinated policy and technology adoption [214][215][216][217][218][219][220][221][222][223][224][225][226][227][228][229][230][231][232][233][234][235][236][237][238][239][240][241].
MAJOR DISCUSSION POINT
Governance coordination needed for data‑centre growth
AGREED WITH
Ashish Khanna, Vineet Mittal
DISAGREED WITH
Vineet Mittal
A
Audience
1 argument175 words per minute67 words22 seconds
Argument 1
A clear understanding of the global ramifications—both positive and negative—of powering AI is essential for responsible policy making.
EXPLANATION
The audience member requests clarification on how AI’s energy demands affect the world, indicating concern that the impacts extend beyond national borders and encompass environmental, social, and economic dimensions.
EVIDENCE
Umesh Prasad Singh, an associate member of the Indian Institute of Public Administration, asks the panel to clarify the positive and negative global ramifications of powering AI [292][293][294][295][296].
MAJOR DISCUSSION POINT
Need for insight into global impacts of AI energy use
AGREED WITH
Ashish Khanna, Raghav Chandra
Agreements
Agreement Points
AI scaling creates unprecedented power and cooling demand for data centres.
Speakers: Announcer, Ashish Khanna, Raghav Chandra
AI scaling is driving unprecedented power and cooling demands for data centres. Data centres and cooling are the largest drivers of the current surge in global electricity consumption, and must be addressed to sustain AI development. Energy availability is the single greatest constraint on AI’s future, as data‑centre power shortages cause major service disruptions.
All three speakers stress that the rapid growth of AI is leading to massive electricity and cooling needs for data centres, making energy availability a critical bottleneck for AI progress [3-5][54-57][66-67][112-119][120].
POLICY CONTEXT (KNOWLEDGE BASE)
The surge in AI workloads has driven data-centre power densities from 10-20 kW per rack to 30-50 kW and beyond, prompting concerns about electricity consumption comparable to small cities and prompting calls for policy attention [S53][S54]. The EU’s Energy Efficiency Directive is also pressuring operators to adopt more efficient cooling solutions to curb rising demand [S33].
AI can enable renewable energy dispatchability and grid stability.
Speakers: Ashish Khanna, Vineet Mittal
AI can enable decentralized renewable integration and peer‑to‑peer power trading, reducing system costs and supporting the rapid growth of AI workloads. AI makes renewable energy dispatchable and grid‑stable by predicting generation with climatic and satellite data.
Both speakers highlight that AI-driven forecasting and digital platforms can turn intermittent solar and wind into dispatchable, grid-stable power, facilitating large-scale AI workloads [20-26][31-33][151-155][156].
POLICY CONTEXT (KNOWLEDGE BASE)
AI-driven forecasting and optimisation are recognised as tools to improve grid dispatchability, reduce renewable curtailment and enhance stability, as highlighted in research on AI-enabled grid management [S38] and discussions on industrial diplomacy around cross-border energy balancing [S39]. Policy briefs also note AI’s role in supporting renewable investments [S41].
Innovation in cooling (liquid and two‑phase) is essential for improving data‑centre energy efficiency.
Speakers: Nathan Blom, Vineet Mittal
Transitioning from air‑cooled to liquid‑cooled data‑centre architectures is crucial for improving energy efficiency. Emerging two‑phase cooling technology can deliver 10‑20 times higher heat‑removal efficiency, dramatically lowering PUE values.
Both speakers argue that moving away from traditional air-cooling to liquid-based solutions-especially emerging two-phase systems-can cut PUE dramatically and reduce the overall power burden of AI data centres [249-254][259-264][267-270][271-274].
POLICY CONTEXT (KNOWLEDGE BASE)
Emerging liquid-immersion and two-phase cooling technologies are cited as ways to cut water use by up to 55 % and lift PUE from ~1.5 to 1.05, with regulatory pressure from the EU’s Energy Efficiency Directive encouraging adoption [S33][S34].
Supportive policy, regulatory and financing frameworks are needed to scale AI‑energy solutions.
Speakers: Ashish Khanna, Vineet Mittal, Raghav Chandra
Financing and de‑risking AI‑energy projects are critical, especially for developing countries that lack venture capital and commercial loan access. Regulatory evolution is required to enable P2P power trading and the digital enablement of millions of consumers and producers. Recent policy measures such as tax exemptions for foreign‑collaboration data centres and open‑access power trading create a favourable environment for data‑centre growth in India. While ease of doing business varies across Indian states, the government is ranking states and streamlining permits to accelerate data‑centre deployment. Lack of coordination between central and state governments in India is a major bottleneck for data‑centre expansion and energy planning.
All three speakers stress that coordinated policy, clear regulations (including P2P trading), targeted financial incentives and streamlined business processes are essential to unlock AI-driven energy projects and data-centre growth, particularly in developing economies [31-33][41-49][50-53][226-227][242-245][214-224][225-236][237-241].
POLICY CONTEXT (KNOWLEDGE BASE)
International AI policy frameworks stress the need for coordinated standards, financing mechanisms and regulatory support to scale energy-efficient AI, as outlined in the Global AI Policy Framework and calls for enabling investment environments [S35][S47].
Powering AI has global ramifications and requires interoperable standards.
Speakers: Ashish Khanna, Raghav Chandra, Audience
Global interoperable standards and coordinated policy are essential for scaling AI‑energy solutions worldwide. Energy availability is the single greatest constraint on AI’s future, as data‑centre power shortages cause major service disruptions. A clear understanding of the global ramifications—both positive and negative—of powering AI is essential for responsible policy making.
The panel agrees that AI-driven data-centre power use has worldwide environmental, economic and social impacts, making common standards and a shared understanding of these ramifications crucial [50-53][297-304][292-296].
POLICY CONTEXT (KNOWLEDGE BASE)
Multiple forums have advocated for common AI standards and interoperable digital infrastructure to manage cross-border impacts, including proposals for global norms by Benifei [S36] and emphasis on policy interoperability rather than uniform governance [S37][S49][S51][S52].
Similar Viewpoints
Both see AI as the key technology to turn intermittent renewable sources into reliable, dispatchable power for AI workloads, leveraging digital platforms and forecasting to lower system costs [20-26][31-33][151-155][156].
Speakers: Ashish Khanna, Vineet Mittal
AI can enable decentralized renewable integration and peer‑to‑peer power trading, reducing system costs and supporting the rapid growth of AI workloads. AI makes renewable energy dispatchable and grid‑stable by predicting generation with climatic and satellite data.
Both emphasize that next‑generation cooling—liquid and two‑phase—will be decisive for reducing data‑centre power consumption and enabling large‑scale AI deployments [249-254][259-264][267-270][271-274].
Speakers: Nathan Blom, Vineet Mittal
Transitioning from air‑cooled to liquid‑cooled data‑centre architectures is crucial for improving energy efficiency. Emerging two‑phase cooling technology can deliver 10‑20 times higher heat‑removal efficiency, dramatically lowering PUE values.
All three agree that coordinated policy, financing and regulatory reforms are essential to scale AI‑energy solutions and data‑centre capacity, especially in emerging markets [31-33][41-49][50-53][226-227][242-245][214-224][225-236].
Speakers: Ashish Khanna, Raghav Chandra, Vineet Mittal
Financing and de‑risking AI‑energy projects are critical, especially for developing countries that lack venture capital and commercial loan access. Regulatory evolution is required to enable P2P power trading and the digital enablement of millions of consumers and producers. Recent policy measures such as tax exemptions for foreign‑collaboration data centres and open‑access power trading create a favourable environment for data‑centre growth in India. While ease of doing business varies across Indian states, the government is ranking states and streamlining permits to accelerate data‑centre deployment.
Unexpected Consensus
Gaming industry as a driver for cooling innovation in AI data centres.
Speakers: Nathan Blom, Vineet Mittal
Transitioning from air‑cooled to liquid‑cooled data‑centre architectures is crucial for improving energy efficiency. Emerging two‑phase cooling technology can deliver 10‑20 times higher heat‑removal efficiency, dramatically lowering PUE values. Gaming and best actually because the large batteries requires the same amount of cooling…
Both speakers, coming from different backgrounds, unexpectedly converge on the observation that the gaming sector’s demand for high-performance GPUs and large battery packs is spurring the development of advanced cooling technologies that will also benefit AI data-centre efficiency [249-254][259-264][267-270].
Overall Assessment

The panel shows strong consensus that AI’s rapid growth is driving massive energy and cooling needs, that AI can be leveraged to make renewable energy dispatchable, that innovative cooling technologies are essential, and that coordinated policy, regulatory and financing mechanisms are required. There is also agreement on the global nature of the challenge and the need for interoperable standards.

High consensus across technical, policy and environmental dimensions, indicating a unified view that addressing power for AI will require integrated solutions spanning AI, renewable integration, cooling innovation and supportive governance. This alignment suggests that future initiatives can build on shared priorities without major ideological friction.

Differences
Different Viewpoints
Effectiveness of Indian policy and regulatory environment for data‑centre expansion
Speakers: Raghav Chandra, Vineet Mittal
Lack of coordination between central and state governments in India is a major bottleneck for data‑centre expansion and energy planning. Recent policy measures such as tax exemptions for foreign‑collaboration data centres and open‑access power trading create a favourable environment for data‑centre growth in India. While ease of doing business varies across Indian states, the government is ranking states and streamlining permits to accelerate data‑centre deployment.
Raghav argues that fragmented governance and poor centre-state synergy hinder data-centre projects, citing a foreign company stalled after eight presentations [214-241]. Vineet counters that the Indian budget now offers tax exemptions for foreign-partner data centres and that a state-ranking system and streamlined permits, especially in Maharashtra, are already improving the business climate [226-227][242-245].
POLICY CONTEXT (KNOWLEDGE BASE)
India’s rapid data-centre expansion has generated demand for legal and regulatory guidance, highlighting both opportunities and challenges in land acquisition, approvals and compliance under current policies [S42].
Readiness of regulatory framework for peer‑to‑peer power trading
Speakers: Ashish Khanna, Vineet Mittal
Regulatory evolution is required to enable P2P power trading and the digital enablement of millions of consumers and producers. Policy measures such as open‑access, real‑time power trading gives flexibility to data centres.
Ashish stresses that new regulations are needed for consumers to trade power from rooftop solar and batteries, requiring IT architecture for millions of participants [31-33]. Vineet says India already provides open-access, real-time power trading that allows data centres to obtain flexible clean power, implying the regulatory gap is already addressed [280-283].
Unexpected Differences
Government coordination vs optimism about reforms
Speakers: Raghav Chandra, Vineet Mittal
Lack of coordination between central and state governments in India is a major bottleneck for data‑centre expansion and energy planning. While ease of doing business varies across Indian states, the government is ranking states and streamlining permits to accelerate data‑centre deployment.
Both speakers are senior Indian officials, yet Raghav highlights systemic governance failures while Vineet portrays a rapidly improving policy landscape, an unexpected contrast given their shared national perspective. [214-241][242-245]
POLICY CONTEXT (KNOWLEDGE BASE)
Observations of fragmented procedures, lack of central coordination and inconsistent pricing underscore coordination gaps that may hinder reform optimism, as documented in government notices and analyses of policy coherence challenges [S44][S46][S43].
Global interoperable standards vs national data‑sovereignty
Speakers: Ashish Khanna, Vineet Mittal
Global interoperable standards and coordinated policy are essential for scaling AI‑energy solutions worldwide. Data sovereignty and localisation are essential; India should ensure Indian user‑generated content resides domestically to drive infrastructure planning.
Ashish calls for worldwide standards to avoid fragmentation, whereas Vineet pushes for a national data-localisation act, revealing a tension between global harmonisation and national control that was not anticipated. [50-53][194-196]
POLICY CONTEXT (KNOWLEDGE BASE)
The tension between universal digital infrastructure standards and national sovereignty is a recurring theme in DPI discussions, with calls for regional trust frameworks that balance interoperability with data-sovereignty concerns [S37][S51][S52].
Overall Assessment

The panel largely concurs on the urgency of addressing AI’s energy demand, but diverges on policy effectiveness, regulatory readiness, and the balance between global standards and national data‑sovereignty. Disagreements centre on Indian governance (coordination vs reforms) and on whether new regulations are needed for P2P trading. These gaps could slow coordinated action unless reconciled.

Moderate – while there is shared recognition of the problem, the differing views on policy and regulatory pathways create noticeable friction that may affect implementation speed and coherence.

Partial Agreements
All speakers agree that reducing the energy burden of AI‑driven data centres is essential, but they propose different pathways: Raghav focuses on reliability and renewable transition, Ashish on AI‑driven market mechanisms and standards, Nathan on advanced cooling technologies, and Vineet on AI‑based renewable forecasting and abundant Indian resources. [73-80][112-119][27-30][50-53][249-254][259-264][151-155]
Speakers: Raghav Chandra, Ashish Khanna, Nathan Blom, Vineet Mittal
Energy availability is the single greatest constraint on AI’s future, as data‑centre power shortages cause major service disruptions. AI can enable decentralized renewable integration and peer‑to‑peer power trading, reducing system costs and supporting the rapid growth of AI workloads. Transitioning from air‑cooled to liquid‑cooled data‑centre architectures is crucial for improving energy efficiency. AI makes renewable energy dispatchable and grid‑stable by predicting generation with climatic and satellite data.
Takeaways
Key takeaways
AI’s rapid growth is driving unprecedented electricity and cooling demand in data centers, now ~1.5% of global electricity and projected to reach ~3% by 2030. Energy reliability is the greatest constraint for AI; recent outages at major cloud providers highlight the risk of power shortages. Advanced cooling technologies (liquid and two‑phase) can dramatically improve Power Usage Effectiveness (PUE) and reduce overall power consumption. AI can enable renewable integration by providing high‑resolution forecasting and dispatchability, turning intermittent solar/wind into reliable 24/7 power. India possesses strategic advantages: abundant solar, wind, pumped‑storage, a unified national grid, low per‑capita electricity use, cheap broadband, and a large AI talent pool. Policy and regulatory alignment (central‑state coordination, data‑sovereignty rules, tax incentives, interoperable standards) are critical to attract data‑center investment. Financing, de‑risking mechanisms, and skill‑development (ISA’s AI‑for‑Energy mission and ISI Academy) are needed to build a sustainable AI‑energy ecosystem.
Resolutions and action items
ISA will launch the AI‑for‑Energy mission and establish the ISI Academy to train professionals at the intersection of AI and energy. Indian government to continue tax‑exemption scheme for foreign‑collaborative data centers and to streamline permitting (e.g., Maharashtra model). Call for improved coordination between central and state authorities to synchronize policies, land allocation, water use, and cooling technology adoption. Encourage development of interoperable standards for renewable‑powered data centers and P2P power‑trading platforms. Promote R&D and support for liquid and two‑phase cooling startups, leveraging cross‑industry expertise (clean‑room, battery cooling).
Unresolved issues
How to create a unified, nation‑wide regulatory framework that balances data‑sovereignty, pricing, and environmental safeguards. Financing and de‑risking models for large‑scale green data‑center projects, especially in regions lacking venture capital. Water scarcity management for liquid cooling solutions and the environmental impact of large‑scale cooling operations. Specific mechanisms for real‑time grid integration of renewable generation with AI‑driven dispatch at 15‑minute intervals. Global governance of standards and cross‑border data‑center impacts; no consensus on interoperable standards yet.
Suggested compromises
Leverage India’s existing coal‑dominant grid pragmatically while aggressively expanding renewable capacity to meet reliability needs. Adopt a hybrid cooling approach: combine proven liquid cooling with emerging two‑phase technologies to balance efficiency and water use. Use AI to improve both energy efficiency of data centers and the efficiency of renewable generation, mitigating the paradox of AI’s own power demand. Encourage state‑level incentives (e.g., Maharashtra) while pursuing a central policy framework to ensure consistent ease of doing business across states.
Thought Provoking Comments
I will call it AI for Energy and Energy for AI – we need AI to enable decentralized solar, P2P power trading, and an ISI Academy to train engineers at the intersection of AI and energy.
Sets a dual‑frame that reframes the whole debate, highlighting that AI is both a driver of energy demand and a tool to solve energy challenges, and introduces concrete initiatives (global AI mission, P2P trading, training academy).
Establishes the two‑sided lens that structures the rest of the conversation; prompts panelists to address both supply‑side (renewables, grid) and demand‑side (data‑center power) issues, and leads directly to the first round of opening statements.
Speaker: Ashish Khanna
The single greatest constraint on AI’s future is not algorithms or chips, but energy for AI‑based data centres – illustrated by high‑profile outages at Meta, Google Cloud, AWS and Azure.
Uses concrete, high‑profile failure cases to argue that reliability of power is the bottleneck for AI scaling, shifting the focus from pure compute to systemic energy security.
Triggers a shift from abstract discussion of demand to concrete reliability concerns; other speakers reference the need for backup, grid stability, and regulatory support, deepening the analysis of risk.
Speaker: Raghav Chandra
Global data‑centre electricity consumption is already 1.5 % of world use and could rise to 3 % by 2030 – equivalent to the power demand of whole countries – with serious environmental, social and equity costs.
Provides striking quantitative context that frames data‑centres as a macro‑economic and environmental force, not a niche issue, and links energy use to emissions, price spikes, and equity.
Leads the panel to discuss mitigation strategies (renewables, efficiency, cooling) and brings policy and social justice dimensions into the conversation.
Speaker: Raghav Chandra
AI can make intermittent solar and wind dispatchable at 15‑minute intervals by fusing climatic data, satellite observations and real‑time forecasting, turning renewables into a stable grid resource.
Introduces a concrete technical breakthrough—AI‑driven ultra‑short‑term forecasting—that directly addresses the intermittency problem of renewables, turning a perceived limitation into an opportunity.
Shifts the dialogue toward how AI can solve the supply‑side challenge, prompting further discussion of India’s renewable capacity, storage options, and the role of AI in grid management.
Speaker: Vineet Mittal
Two‑phase cooling technology, where the liquid boils and vaporises, can improve PUE from ~1.5 to ~1.05, dramatically cutting the electricity needed for data‑centre cooling.
Highlights an emerging, high‑impact innovation that tackles the biggest energy consumer within data centres—cooling—by orders of magnitude, and frames it as a startup‑driven breakthrough.
Spurs a focused discussion on the innovation ecosystem, leading other panelists to talk about startup involvement, scaling of new cooling tech, and the need for policy to support rapid adoption.
Speaker: Nathan Blom
The biggest bottleneck in India is the lack of synergy between centre and states, and the uneven ease of doing business; without coordinated policy, even well‑funded projects stall.
Moves the conversation from technology to governance, pinpointing a systemic obstacle that could undermine all technical solutions, and calls for concrete institutional reform.
Redirects the panel to address regulatory reforms, prompting Vineet and Ashish to discuss state‑level incentives, data‑sovereignty laws, and the need for a unified national strategy.
Speaker: Raghav Chandra
India’s single, real‑time interconnected grid, abundant solar‑wind‑water resources, and pumped‑storage capability make it uniquely positioned to host gigawatt‑scale, 24/7 green data centres.
Combines geographic, infrastructural, and policy strengths into a compelling argument that India can become a global data‑centre hub, linking energy abundance to data‑sovereignty and economic growth.
Reinforces the optimism theme, influencing Ashish’s later question about policy and prompting other panelists to acknowledge India’s competitive advantage while also noting the regulatory challenges.
Speaker: Vineet Mittal
Overall Assessment

The discussion was shaped by a handful of pivotal remarks that moved the conversation from high‑level optimism to concrete challenges and solutions. Ashish’s framing of AI‑for‑Energy and Energy‑for‑AI set the dual‑lens agenda. Raghav’s vivid illustration of power reliability failures and his macro‑scale electricity statistics forced the panel to confront the gravity of energy constraints. Vineet’s AI‑enabled renewable dispatch concept and his articulation of India’s unique grid turned the debate toward actionable supply‑side innovations. Nathan’s breakthrough cooling technology introduced a tangible demand‑side efficiency lever. Finally, Raghav’s critique of regulatory fragmentation and Vineet’s emphasis on India’s systemic advantages highlighted the governance dimension that can either enable or block the technical advances. Together, these comments redirected the flow from abstract enthusiasm to a nuanced, multi‑layered dialogue about technology, policy, innovation ecosystems, and geopolitical opportunity.

Follow-up Questions
Is the policy and regulatory landscape in India and other developing countries conducive to promoting data centers?
Evaluating existing regulations, incentives, and barriers is essential to enable rapid data‑center expansion in emerging markets.
Speaker: Ashish Khanna
What will the innovation landscape for cooling look like – will it be driven by startups, large firms, or both?
Understanding the mix of innovators informs investment, research focus, and speed of adoption of efficient cooling technologies.
Speaker: Ashish Khanna
What interoperable global standards are needed for AI‑energy integration?
A lack of unified standards hampers cross‑border collaboration and deployment of AI‑driven energy solutions.
Speaker: Ashish Khanna
How can financing and de‑risking models be developed for renewable‑powered AI infrastructure in emerging markets?
Capital constraints limit deployment; innovative financing mechanisms are required to scale clean AI data centers.
Speaker: Ashish Khanna
How should data‑sovereignty legislation be implemented to ensure Indian user data remains locally stored?
Legal frameworks are needed to attract data‑center investment while protecting national data interests.
Speaker: Vineet Mittal
How can coordination between central and state governments be improved to streamline data‑center approvals and infrastructure deployment?
Current inter‑governmental bottlenecks slow down scaling; better alignment would accelerate projects.
Speaker: Raghav Chandra
What water‑scarcity‑aware cooling solutions (e.g., liquid, two‑phase) are viable for data centers in water‑limited regions?
Cooling consumes significant water; sustainable methods are critical where water resources are constrained.
Speaker: Raghav Chandra, Nathan Blom
How can two‑phase cooling technology be scaled and commercialized for data‑center use?
Emerging two‑phase cooling promises high efficiency but requires pathways to mass adoption and integration.
Speaker: Nathan Blom
What are the environmental and social impacts (noise, heat, land‑use) of large data‑center clusters on local communities?
Assessing equity and community effects is necessary to mitigate negative externalities of data‑center growth.
Speaker: Raghav Chandra
How can AI be used to optimize renewable generation dispatch at 15‑minute intervals to support grid stability for AI workloads?
Fine‑grained AI‑driven dispatch can make intermittent renewables reliably serve power‑hungry AI data centers.
Speaker: Vineet Mittal
What is needed to develop AI‑enabled peer‑to‑peer (P2P) power trading platforms for millions of prosumers?
P2P trading could democratize energy markets and support decentralized renewable integration, but requires regulatory and technical frameworks.
Speaker: Ashish Khanna
How can AI models and hardware be designed to be more energy‑efficient, reducing data‑center power consumption?
Lowering compute energy demand directly lessens the overall electricity and carbon footprint of AI services.
Speaker: Raghav Chandra
What strategies improve the reliability of backup power systems (UPS, generators) for AI data centers to prevent cascading outages?
Past grid failures highlight the need for robust backup solutions to ensure continuous AI service availability.
Speaker: Raghav Chandra
What will be the impact of AI‑driven data‑center growth on global electricity consumption and carbon emissions by 2030?
Quantifying macro‑level effects guides policy and investment decisions toward sustainable AI expansion.
Speaker: Raghav Chandra
How can pumped storage combined with AI provide 24/7 renewable power for data centers?
Integrating storage and AI scheduling could overcome intermittency and deliver continuous clean energy to compute facilities.
Speaker: Vineet Mittal
How can innovations from the gaming industry (e.g., GPU cooling) be transferred to improve data‑center cooling technologies?
Cross‑industry technology transfer may accelerate adoption of efficient cooling solutions for large‑scale AI workloads.
Speaker: Vineet Mittal

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