The Global Power Shift India’s Rise in AI & Semiconductors

20 Feb 2026 18:00h - 19:00h

The Global Power Shift India’s Rise in AI & Semiconductors

Session at a glanceSummary, keypoints, and speakers overview

Summary

The panel examined how AI has shifted from a niche technology to a catalyst for economic transformation, emphasizing that genuine AI leadership demands the integration of silicon, software, systems and policy [21-34]. Jaya highlighted India’s strong engineering talent, silicon-design capabilities and rapidly growing ecosystem of system and infrastructure partners, while stressing that collaboration across nations and organisations is essential [37-42]. She framed the discussion around three strategic questions: building the intellectual foundation, deepening manufacturing and supply-chain resilience, and establishing a credible sovereign AI capability [45-48].


Vivek noted that India’s AI Mission, backed by over ₹10,000 crore, tax holidays for data-centers and platforms like AI Coach, is creating credibility through large-scale deployments and the gradual development of domestic IP in AI and semiconductors [50-57]. He added that the country’s robust VLSI design ecosystem must evolve from relying on foreign IP to owning its own, a key step toward a trustworthy deep-tech sector [56-57]. Rahul observed that domestic demand for AI-enabled products is surging and that both government programmes (e.g., a ₹1 lakh crore AI fund) and private capital exceeding $100 billion are beginning to flow into data-center and manufacturing projects, though the breadth of investment remains uneven [66-79].


Thomas argued that India should move from merely seeking compute capacity to building sovereign capability, leveraging its unique data-residency needs and a large pool of startups to develop home-grown IP and niche supply-chain components such as co-packaged optics [89-104]. He suggested that India does not need to produce leading-edge 2 nm chips but can add value in adjacent technologies and AI-infrastructure deployment, positioning itself as a resilient partner in global supply chains [101-108]. On policy, Thomas advocated public-private partnerships like the U.S. “Genesis” model, where government de-risks large-scale research while avoiding direct subsidies, to align funding with grand-challenge problems and accelerate innovation [116-128][216-226].


Vivek stressed the need for strategic autonomy-clearly defining which technologies to indigenize and which to keep open-to balance national security with global collaboration [142-148]. He also pointed to expanding skilling programmes such as NASCOM’s Future Skill Prime and a shift from rote learning to creative problem-solving, arguing that massive reskilling is required to prepare the next generation for AI-driven jobs [178-188]. Rahul described India’s manufacturing path as a “vertical-stack” model where firms integrate design, fabrication and system integration, encouraging experimentation across many domains despite limited resources [153-164]. Thomas concluded that sustainability must be embedded in product design, noting AMD’s commitment to flattening the energy curve while acknowledging the need for humility and continuous correction [278-285].


The moderator wrapped up by stating that momentum alone is insufficient; coordinated sequencing, disciplined capital, institutional alignment and infrastructure depth are essential for India to realise its AI and semiconductor ambitions [198-202][255-262]. Overall, the discussion underscored that India’s AI and semiconductor future hinges on collaborative public-private effort, strategic focus on sovereign capabilities, robust talent development and sustainable execution [21-34].


Keypoints

Major discussion points


AI leadership requires a holistic, cross-disciplinary approach – true AI dominance can only be achieved when silicon, software, systems and policy are aligned; no single element is sufficient and broad collaboration is essential. [21-34]


Credibility in deep-tech hinges on large-scale, systematic investment and a balanced policy framework – India’s AI mission, data-center tax holidays, and semiconductor design strengths must be scaled up, while policy must protect strategic autonomy yet remain open to global collaboration. [50-59][131-148]


Building manufacturing depth and supply-chain resilience calls for sustained capital and focused niche capabilities – rather than trying to match the most advanced fabs, India should target areas such as optics, co-package interconnects and packaging, leveraging public-private risk-sharing to grow a robust ecosystem. [66-80][92-110][216-236]


Talent development and skilling are critical for the next-generation AI/semiconductor workforce – education must move from rote memorisation to AI-augmented, creative problem-solving, supported by programmes like Future Skill Prime and extensive startup incubators. [178-188][255-259]


Public-private partnership models (e.g., the U.S. “Genesis” project) offer a template for India – government can de-risk strategic initiatives, fund grand-challenge research, and align academia, national labs and industry without directly subsidising private ventures. [116-128][225-230]


Overall purpose / goal of the discussion


The panel was convened to assess India’s current position and future roadmap in artificial intelligence and semiconductor technologies, identify the strategic gaps (intellectual foundation, manufacturing depth, sovereign capability), and propose coordinated actions across policy, industry, academia and capital markets that will enable India to become a credible, self-reliant AI power by the 2030 horizon.


Tone of the discussion


The conversation began with an enthusiastic, forward-looking tone, emphasizing the transformative potential of AI and India’s “poised” status ([21-34]). As the dialogue progressed, speakers adopted a more analytical and realistic tone, acknowledging existing shortcomings (limited IP, capital constraints, supply-chain fragility) and the need for disciplined execution ([50-59], [66-80], [92-110]). Toward the end, the tone shifted to a constructive, solution-oriented stance, highlighting concrete programmes, public-private partnership models, and a call to action for talent and policy makers, ending on an optimistic, motivational note about the nation’s collective journey ([178-188], [255-259]).


Speakers

Rahul Garg


Role/Title: Founder and CEO of Moglix (Mr.)


Areas of Expertise: Industrial supply-chain platforms, manufacturing, industrial finance, AI infrastructure scaling


Jaya Jagadish


Role/Title: Session Moderator; veteran semiconductor industry executive with three decades of design-engineering experience (Jaya Jagadish)


Areas of Expertise: Semiconductors, AI leadership, technology strategy


Thomas Zacharia


Role/Title: Senior Vice President for Strategic Technical Partnerships and Public Policy, AMD, Inc.; former director at Oak Ridge National Laboratory (Dr. Thomas Zakaria)


Areas of Expertise: Exascale supercomputing, AI systems, semiconductor policy, public-private partnerships


Vivek Kumar Singh


Role/Title: Professor and Senior Advisor on Science and Technology, NITI Aayog (Professor Vivek Kumar Singh)


Areas of Expertise: National science & technology policy, AI strategy, semiconductor ecosystem, biomanufacturing, innovation governance


Moderator


Role/Title: Session Moderator (Moderator)


Areas of Expertise: Session facilitation


Additional speakers:


Pooja – mentioned briefly as someone who could also join the closing remarks; no specific role or expertise identified.


Subhash Suresh – referenced as former president of the U.S. National Academy of Engineering; expertise in engineering leadership and grand challenges.


Ray Kurzweil – quoted regarding longevity and AI; known as futurist and inventor, expertise in AI, futurism, and health technologies.


Medi CEO – referenced in discussion about Indian startups; name not provided, role is Chief Executive Officer of “Medi”.


Vivek Murthy – appears as a transcription error; likely refers to Vivek Kumar Singh already listed.


External source citations:


Rahul Garg – [S1]


Jaya Jagadish – [S3]


Thomas Zacharia – [S4][S5]


Vivek Kumar Singh – [S6][S7]


Moderator – [S8][S9][S10]


Full session reportComprehensive analysis and detailed insights

The moderator opened the session with a brief overview of today’s computing stack-CPUs, GPUs, SoCs and AI engines-that underpins modern systems, and introduced the three panelists: Dr Thomas Zakaria, AMD; Prof. Vivek Kumar Singh, Senior Advisor, NITI Aayog; and Mr Rahul Garg, founder-CEO of Moglix [1-15]. After welcoming the audience, the moderator announced the start of the discussion [16-17].


Jaya Jagadish set the thematic tone, observing that artificial intelligence has moved from a niche technology to a catalyst reshaping entire economies [21-25]. She argued that genuine AI leadership requires synchronising silicon, software, systems and policy-“no one aspect can really get us there” [32-34]. Emphasising India’s readiness, she highlighted the country’s engineering talent, strong silicon-design base and a rapidly expanding ecosystem of system-level partners and manufacturers [37-39]. She then framed the panel’s inquiry around three strategic pillars: building the intellectual foundation, deepening manufacturing and supply-chain resilience, and establishing a credible sovereign AI capability [45-48].


Talent development – Prof. Vivek Kumar Singh highlighted the shift from rote, memory-based learning to AI-augmented, creative problem-solving. He cited the availability of free generative-AI tools, the NASCOM Future Skill Prime platform and widespread university incubators that make this “the best time to be a student” [178-188].


When asked how the next generation should be prepared for the AI-driven future, Jaya directed the question to Prof. Singh [170-172].


Manufacturing and capital – Mr Garg shifted the focus to post-COVID supply-chain shocks that have heightened political will to localise production, noting the government’s ₹1 lakh crore AI fund and private-sector commitments exceeding $100 billion for data-centres and related infrastructure [66-73]. He acknowledged that capital remains unevenly distributed but affirmed that investment is already flowing and that demand for AI-enabled products is rising sharply across the country [70-78]. He cautioned that the ability to execute at the required speed and scale still needs to be proven [79-80].


Strategic focus for manufacturing – When asked where India should concentrate its manufacturing efforts, Dr Zakaria argued that the country should move from merely seeking compute capacity to building sovereign capability [89-92]. He distinguished “sovereignty” (keeping data and applications within India) from “resilience” (developing indigenous IP and participating in the global supply chain without necessarily mastering the most advanced 2 nm nodes) [93-103]. Zakaria identified niche, high-value segments such as co-packaged optics and AI-infrastructure interconnects as realistic entry points, noting that these components are not widely available globally and that India could “stab the jib” in these areas [104-108].


He advocated public-private partnerships (PPPs) modelled on the U.S. “Genesis” program, explaining that the public sector should provide policy direction and demand signals while de-risking large-scale research through collaborative frameworks that fund compute infrastructure, software stacks and “lighthouse” problems, without directly subsidising private ventures [116-124][216-226]. He cited U.S. programs such as Genesis and highlighted China’s 20-year HPC-to-AI trajectory as examples of how coordinated national compute initiatives can seed long-term AI leadership [119-124][123-125].


Zakaria also pointed to AMD’s Helios project, an open-standard platform that could enable Indian firms to become leading providers of specific components, illustrating how open-standard ecosystems can create a competitive edge [210-212].


Policy perspective – Prof. Singh added a complementary view, urging a “strategic autonomy” approach: clearly delineating which technologies must be indigenised for national security and which can remain open to global collaboration [141-148]. He stressed that such a framework would protect critical components while still benefiting from international knowledge exchange.


Private-sector model – Mr Garg described the Indian private-sector approach as a “vertical-stack” model, where firms integrate design, fabrication and system integration while simultaneously developing ancillary ecosystems such as clean-room facilities, chemical suppliers and packaging verification [153-164]. He argued that experimenting across many domains-“throwing darts at hundreds of problems”-will eventually reveal the few areas where India can achieve first-mover advantage, even if the nation is currently “late to the party” in semiconductor technology [153-154][165-166].


Closing remarks – The moderator stressed that momentum alone will not secure India’s AI and semiconductor ambitions; disciplined sequencing, capital allocation, institutional alignment and deep infrastructure are essential [198-202]. He also raised the question of embedding sustainability as a core design choice rather than a trade-off [274-277].


Dr Zakaria responded that AMD designs its products with an explicit goal of flattening the energy curve, acknowledging that sustainability requires humility and continuous course-correction [278-285].


When asked what single move India must execute flawlessly, Rahul Garg emphasized that success will not hinge on a single action but on a fast-follower capability combined with a global-scale ambition. He argued that India must rapidly scale capital (≈ $10-20 bn) through coordinated public-private effort to compete with larger global pools [240-247].


Key agreements (each supported by transcript citations):


– AI leadership demands a holistic ecosystem linking silicon, software, systems and policy [32-34][116-119].


– Substantial public and private financing, preferably through PPP de-risking mechanisms, is critical [56][70-78][216-221][255-262].


– India’s large talent pool provides a fast-follower advantage that must be leveraged via coordinated action [38-39][214-215][239-240].


– Developing indigenous IP and nurturing local startups are essential for sovereign capability [84-86][98-100][56-57].


Points of divergence (with supporting citations):


Scope of manufacturing: Zakaria advocates focusing on niche supply-chain components such as co-packaged optics [104-108]; Garg argues for building mid-range fabs and a vertically integrated ecosystem that includes clean-room and packaging capabilities [153-164].


Capital mobilisation: Zakaria suggests government de-risk projects without direct subsidies [216-221]; Garg highlights the need for massive pooled capital (potentially $10-20 bn) that may require more direct state involvement [70-78][214-218].


Openness vs. strategic autonomy: Singh calls for clear rules on strategic autonomy, delineating indigenisation priorities [141-148]; Zakaria’s Genesis model favours an open, collaborative research environment [225-229].


Strategic posture: Garg’s fast-follower narrative contrasts with Zakaria’s forward-looking supercomputing mission that seeds long-term capability rather than merely chasing existing technologies [119-124][214-218].


The panel concluded with consensus that India’s AI and semiconductor future hinges on coordinated public-private effort, strategic focus on high-value niche technologies, aggressive talent skilling, and embedding sustainability into design. Unresolved issues include defining the exact roadmap for private-capital mobilisation, specifying timelines for moving from niche participation to more advanced fab capabilities, establishing mechanisms for IP transfer from academia to industry, and creating metrics to monitor sustainability outcomes. Together, these insights outline a roadmap that combines ambitious policy, targeted investment and a skilled workforce to realise India’s AI sovereignty by the 2030 horizon.


Session transcriptComplete transcript of the session
Moderator

Thank you. Thank you. across CPUs, GPUs, SoCs, and AI engines that power cutting -edge compute systems worldwide. She brings a rare combination of deep silicon expertise, global product leadership, and national ecosystem engagement. She is deeply committed to talent development in the ecosystem as well. Please join me in welcoming Jaya, who will be moderating our session. Our first panelist is Dr. Thomas Zakaria, Senior Vice President for Strategic Technical Partnerships and Public Policy at AMD, Inc. Dr. Zakaria previously led Oak Ridge National Laboratory, where he oversaw the deployment of multiple world -leading supercomputing systems, including Frontier, the first exascale supercomputer. His career spans scientific discovery, national compute infrastructure, public policy, and global partnerships. Please welcome Dr. Thomas Zakaria.

Joining us is Professor Vivek Kumar Singh, Senior… advisor on science and technology at NITI IO. Professor Singh plays a central role in shaping India’s science, technology and innovation architecture. From R &D governance to university industry collaboration and state level innovation ecosystems. With a background in computer science, data analytics and experience in academic leadership at leading institutions, he bridges research depth with national policy execution. Please welcome Professor Vivek Kumar Singh. My apologies. And finally, we have Mr. Rahul Garg, founder and CEO of Moglix. Rahul has built one of India’s leading industrial supply chain platforms and has expanded into manufacturing and industrial finance, navigating the realities of scale, capital and execution in India’s industrial ecosystem. Please welcome Mr.

Rahul Garg. We will now be beginning the discussion. Thank you so much for joining us.

Jaya Jagadish

All right. Good afternoon, everyone. And I would like to extend a very warm welcome to each one of you for this session. And thank you for taking time to be here with us. So we are meeting at a moment when AI is no longer a niche technology. And these conversations have become foundational. And there is a shift in shaping the entire economies. And that’s the global impact that this technology can have. And having spent about three decades in semiconductor industry doing design engineering, I have seen compute evolve. From a single threaded processor to massively parallel AI systems. And that’s. stupendous growth that we have seen and a transformation of technology. And honestly, AI is a technology that is probably the most transformational that we will be able to see in our lifetimes.

And true AI leadership is something globally there’s a contest. Every country wants to achieve self -reliance and, you know, leadership in AI. And that’s the importance of this technology that we are talking. But true AI leadership itself happens when silicon, software, systems, and policy, all of these aspects have to come together to achieve that leadership. No one aspect can really get us there. And that’s what truly excites me for today’s session. We have experts who have the knowledge. In each of these, many of these aspects, and we will be, you know, asking questions and they’ll be sharing their perspectives on this, which I’m sure all of us will enjoy listening to. So coming to India, from what I see, India is truly well poised for this technology shift.

And we bring together engineering talent, silicon design strength, and a growing ecosystem of system and infrastructure partners, including manufacturing. But what truly defines and makes this moment different is the scale and the speed at which we are moving. So we do see a strong commitment, but what is also important is collaboration. No one country or one organization can truly achieve the results or be successful at this, but we all need to collaborate. We all need to become very aware because this is not a simple thing. It has the potential to touch human lives and humanity. At a time when we are in a situation where we are in a situation where we are in a situation where we are in a situation where we are in a situation where we are in a situation where we are in a situation where we are in a situation where we are in a situation where we are in a situation where we are in a situation where we are in a situation where we are in a situation where we are in a situation where we are in a situation where we are in a situation where we are in a situation where we are in a situation through this panel, today I want to look at three perspectives.

First, how do we continue to build the intellectual foundation? Second, how do we build manufacturing depth and supply chain resilience through a sustained investment model? And third, how do we build a credible, sovereign AI capability? I will get to Vivek. I’ll

Vivek Kumar Singh

Thank you, Jaya. This is a very important thing, very important question. I think India has already taken a call to go in a big way in the whole deep tech domain. And a lot of changes that we see happening in terms of AI compute, then AI data centers and so on. Recently, we all heard about the tax holidays for data centers that are going to be created in India. Also, platforms like AI Coach, because that’s very, very important. If you want to create AI applications for India, you need AI data, which is centered in India, which is for the context of India. So what I believe, when you talk about credibility and how credible we are into this deep tech domain, comprising AI, semiconductor, biomanufacturing, even other, areas what is very very important is that credibility doesn’t come only from announcements so what we what we really need to know and what we really need to do is to go at a scale and fortunately a lot of positive changes are already happening we have india ai mission we all know about that 10 000 plus crores for five years and it’s a very systematic effort where we have almost all so all seven pillars address you know all kind of needs that we need for ai and similarly if you look at semiconductors we we all know about what is happening in fabs also you know we know that india has a very strong ecosystem of uh you know vlsi design semiconductor design and so on unfortunately most of that ip is not with india but you know there’s a time when is also going to happen that india would also be owning a lot of ip so credibility i think uh for india would be very very important and this is coming not only as part of announcement but it’s it’s coming you know it’s coming it’s coming it’s coming it’s coming it’s coming it’s coming it’s coming you know as part of commitment for scaled deployments, for scaled growth, accelerated growth.

And what we see now is something, you know, which nobody could have thought of 10 years back or 5 years back. So we, I believe we are on the track and we are very much into, you know, into the whole realm of AI and semiconductors. And a lot of push is there and the whole ecosystem is evolving and we all, as we move further, we all are going to work towards, you know, creating a very, very credible ecosystem for overall growth of the sector.

Jaya Jagadish

Now, great insights. Thank you, Vivek. Now, moving to Rahul. There’s clearly a growing momentum to strengthen manufacturing in India. Given your journey, you have expanded Moglex from digital marketplaces into manufacturing and industrial financing. Do you believe the Indian private sector is truly ready financially and have the mind? set to take on long term investments that are needed?

Rahul Garg

So firstly, thank you for having me. I think the question is very pertinent because again, pre -COVID there was a very different environment, both from a geopolitics perspective, supply chain perspective. And I think the supply chain as a word started to become popular in COVID times. So and I think I take some pride in the fact that at least as Moglex, we have been part of seeing the supply chain journey in the country as well as continuing to now see the manufacturing journey. On the specific point that you raised on both from a will perspective, capital perspective, demand perspective, if you look at these three aspects of it. So I think the demand in the country clearly is growing rapidly.

And one of the changes that has happened, obviously India becoming the larger in terms of GDP size, consumer demand, people expecting faster and faster products, people want variety. products so on so forth so i think demand discretionary spend is increasing the one significant change that has happened post covid we see is that while the demand is growing there is also an increasing uh appetite for people to start building more and more manufacturing to also start to look at many of those being localized rather than just depend on global supply chains because obviously we have gone through moments where like we may not have enough mask capacity in the country we may not have enough oxygen concentrated capacity in the country and we some of those shocks kind of uh got both the private and the public sector realizing that there is a bare minimum manufacturing that needs to happen in the country for it to be truly self reliant at the population scale that we are in so i think that will has gotten generated the capital is starting to flow in i think the question on whether the capital is large enough and long term enough i think we are seeing increase increasing trend that there are clearly government will whether it is in terms of the fund that we have seen of 1 lakh crore, now 1 .2 billion dollar for specific AI deep tech, things like that.

But also private capital, which within this week, the numbers that I’m hearing is more than 100 billion dollar plus commitment from the private capital companies saying that they are going to invest into data centers, localizing, so on, so forth. So I think the capital is happening today. Is it happening broad -based? The answer may be no. No. But has it started to happen? And has it started to go from like maybe few hundred crores to few billions of dollars? So that is happening. Can we execute at the same speed and scale? Only time will tell.

Jaya Jagadish

Sure. No, there’s definitely an increased momentum. But along with manufacturing, I mean, I’m also biased more towards the design front based on my experience. I do definitely want to see lot more local startups. And Vivek just mentioned, we don’t have the IPOs. I mean, having our own IPs is one of the key steps. we need to take. So moving on, question for Thomas. If advanced fabs remain limited globally, where should India focus on in the near future? Where can we realistically create value in the next three to seven years?

Thomas Zacharia

Thank you, Jaya, and I just want to echo the sentiments that my colleagues here on the panel have mentioned, so I’ll build on that. So I think the opportunity for India is to move from compute to capability, right? I mean, that’s really where we need to be. And I’ll pick a couple of areas. So sovereignty and resilience gets intermingled. So I’m going to sort of keep those two things separate. Sovereignty is one where you are really trying to make sure that your data and your application or use cases are resident in country and it’s relevant to country. And that’s an area that is uniquely India to lead because no one else is going to do that.

It has to be done and you already mentioned the opportunity, we were with the CEO of Medi today talking about 50 ,000 startups. I don’t know how to get my head wrapped around 50 ,000 startups so I asked him, can you tell me who the top 50 are so that perhaps a company like AMD can partner with them and try to help them to mature. So that is on the sovereignty side. On the resiliency side the reality is that clearly India needs any sovereign country expects to have resiliency create their own IP and India should have the same aspiration given the scale of ambition and scale of population and here I think while we certainly should have an ambition to go up the development cycle to the leading edge of chip design.

I think there is an opportunity to also look at being part of the supply chain for leading edge deployment. So you don’t necessarily have to be at the two nanometer scale for GPUs or CPUs. There are critical technology in the deployment at scale of AI infrastructure where India can play a role. For instance, we know that the entire ecosystem is going to be driven to optics as interconnect technology, co -package optics. And there are clear supply chain that is not available globally. That is something that is being considered today. And leading candidates obviously today I would say are U .S., Japan, Malaysia. But those are the kind of niche areas where India can stab the jib.

And that is the journey where you are. really contributing to the first -of -a -kind or the nth -of -a -kind leading -edge technology. So that’s the way I would approach it.

Jaya Jagadish

Great insights. Thank you, Thomas. Now, continuing, today AI leadership is ultimately limited not by ambition, but by access to secure scalable computing resources. So, Thomas, continuing with you, you have led exascale class systems and now you’re working on sovereign AI partnerships globally. In the U .S., programs such as Genesys and broader national compute initiatives have attempted to systematically align infrastructure, research, and industrial capacity. So what lessons from these models are actually applicable to India?

Thomas Zacharia

So I think this is a great area for public -private partnership, in my view. The public part of it is a uniquely government function. Government brings both policy as well as the demand signal, particularly in the area of science and innovation, critical infrastructure, whether it is energy sector or national security, as well as uniquely government missions. And the opportunity here is to, I mean, India has supercomputing mission. I think there is an opportunity, and I think India is already thinking about deploying this national supercomputing mission and national scientific infrastructure that is on a trajectory to be at global leading scale. So today, countries like U .S. China. China is a particularly interesting example. China developed the intellectual ecosystem around HPC, which then translated to AI, over a period of 20 to 25 years.

It was intentional. And if you look at where the AI penetration, AI adoption, AI infrastructure resides globally, you can directly trace that to investments in sort of supercomputing mission that built the underlying infrastructure. So I think that is a great opportunity. Already plans are there. But it’s not a static view. So one of the things that I would encourage as we plan for the future is not plan based on where things are, but plan on where things will be by the time we deploy this kind of infrastructure.

Jaya Jagadish

That’s great. A future -looking planning is what we… Thank you, Thomas. Vivek, moving to you, from a policy standpoint, how do we balance national security concerns with openness and global collaboration?

Vivek Kumar Singh

Vivek Murthy Well, it’s a very tricky question, I would say. You know, for a country like India, we all know, you know, I mean, the kind of culture that we have in India is we have always believed in the fact that knowledge is a common good. And that is how, you know, our whole innovation ecosystem has been operating. Our universities have been creating a lot of knowledge and we all, you know, researchers, R &D persons, they have been trained with the fact that whatever you create should be for a, you know, for a common good. There were never efforts to productize them, to convert them into socioeconomic goods, to, you know, protect them with, you know, excess rights and so on.

So that was the common thing that we have been doing earlier. But what is happening now is that we are not doing it in a way that is, you know, we are not doing it in a way that is, you know, we are not doing it in a way that is, you know, we are not doing it in a way that is, you know, we are not doing it in a way that is, you know, we are not doing it in a way that is, you know, we are not doing it in a way that is, you know, we are not doing it in a way that is, you know, we are not doing it in a way that is, you know, we are not doing it in a way that is, you know, we are not doing it in a way that is, you know, we are not doing it in a way that is, you know, we are not doing it in a way that is, you know, we are not doing it in a way that is, you know, we are not doing it in a way that is, you know, we are not doing it in is a completely different word.

And that is where our academia, our R &D institutions are also being asked to, you know, change the complete quotes. So it’s not only that researchers, you know, faculty members in universities, they should end up with research publication, that’s all. So it’s very, very important that you productize also. Now what is happening, see, if you talk about the culture of innovation and how you see in terms of the global world that we are in, particularly for sectors like AI and semiconductor, I think what we need to do is we need to go for a, you know, a strategic decision -making in the sense that what is it that we want to do? So, for example, there are certain sectors where, you know, the setup that we are using has certain components which may be used in some critical deployment.

So in those cases, what we need is a set of clarity of rules. What is it that we would like to indigenize? What is it? that we would like to have built on our own? And what is it that we can keep open for rest of the world, for collaboration and so on? So I think what we need is, I would say two words would be important is strategic autonomy. Autonomy in the sense that autonomy where it is needed, but at all other places where we can collaborate with the world, where we can contribute in terms of collective knowledge creation, India can always play a role and India is playing a role

Jaya Jagadish

Great. Rahul, question to you. As AI infrastructure scales, demand patterns for chips and hardware will shift. How should Indian manufacturers position themselves early? And secondly, where are the first mover advantages?

Rahul Garg

I think. we are kind of late to the party in some sense in the semiconductor and chips some say it’s two decades three decades late to the party right so and then there are couple of countries which have a disproportionate advantage not just in terms of what is more popularly known as the 2nm and two three companies dominating that but also in terms of the entire ecosystem that is required around all of those factories and chipsets and systems so on so forth so I think for us I think the India journey will be its own unique path so that’s one thing that I’ve always at least over the last 20 years I’ve seen that if you were to wait for landline to become 10 % of the population we would have not had the mobile revolution if you had to wait for credit cards then I mean like it would not have happened right so I think the in this new era that we are living I think the manufacturers will have to find few spots which may not be as obvious which given the conventional way the countries and ecosystems are built and I think one of the good advantages of events like this is you start to have a very large population and smart and talented people throw darts at hundreds of problems simultaneously and maybe five years later we will say like okay we knew that these are the three things which will work or all of that kind of thing right but I don’t think there is like a today unique path I mean definitely does seem that we need to start building capabilities and capabilities need to be built design we have capabilities we don’t have the productize capability so that is one capability which needs to be built the manufacturing capability while we are starting with some of the fabs which are in the mid zone but the entire ecosystem of chemical suppliers like clean room suppliers utility suppliers.

How do you make sure that. there is enough packaging verification and many of that ecosystem getting developed. So all of those are going to happen simultaneously. So I think the opportunity remains in all of the areas. And I think therefore, at least my encouragement to even my management and the way we are looking at Moglex and so on and so forth is, I mean, you try 10 things. Do not be scared to try one thing or two things and then you fail. And conventionally also while in the Western and so world, there have been horizontal capabilities companies have built and scaled. In India, historically over the last 15 years, every startup, every large company has built vertical stacks of companies.

So they are doing an integrated. They may be chip designed to manufacture, to systems, to product. I mean, like that’s how just the model has evolved so far. So. I think that’s what vertical stack manufacturing all. parts of the ecosystem will have to give a shot and maybe over time will become horizontal.

Jaya Jagadish

That’s great. Thank you. So, you know, I do see quite a few students in the audience. So one thing that we are now facing is kind of with this technology. What is knowledge? How do we acquire knowledge? I mean, traditionally, we go to schools, universities for that. But today it’s at your fingertips. And with that advancement of AI, it’s just going to get better. You want to learn about something, you always have it on your fingertips. So what really do we need? How do we prepare the next generations to solve the problems of the future is the question. I mean, we cannot just stick around with our traditional ways of learning. And we have to scale and adapt to the newer ways.

So question for you, Vivek, how can we prepare ourselves and equip ourselves for this next phase that’s coming?

Vivek Kumar Singh

well I would say efforts have already started so that’s the best thing and as you rightly said this is the best time to be a student you know if you take yourselves 20 years back you will always be constrained with resources the best that you have is lot of books you will have to go to a library there are books that you can’t afford and so on and books are also not on time so you have later editions and so on so what is happening now is you know with lot and lot of information information which is which is you know can be customized for you specifically then you have lot of recommended systems you have retrieval augmented generation systems you know all of this with generative and what is happening so the best part is that you have plenty of information you want to learn anything you want to acquire a skill you always have resources and most of the time these resources you really don’t have to pay for that because this lot of material that you can access for for free.

The programs, particularly for India, we have something called NASCOM’s Future Skill Prime, where you can, you know, which is an aggregator for a lot of online courses. Similarly, there are platforms across the world that you can use. Now, what is happening is that essentially what we have been doing in our universities and generic colleges and, you know, other institutions earlier is that it was largely a kind of memory -based learning where we were acquiring knowledge, we were memorizing things. But now, over a period of time, it’s a more synthetic perspective which is being, you know, percolated across institutions. So, students now are going more into that creative aspect where they’re able to create solutions for certain problems.

And with the whole ecosystem around startups, we all know India is the third largest startup ecosystem of the world. With a lot of support system that we have, most of our universities have incubators. You know, other support systems. So, this is… best time and that is why I said this is the best time to be a student if you want to do anything if you have a creative idea you always find support and there are lot of skilling programs from government of India from many other organizations many you know philanthropic supports are there so even lot of organizations which have their own products they are you know offering free of cost training to students so this is very good but what is important is largely also due to the fact that you know we keep on hearing that AI is going to cause a number of you know disruption in terms of jobs that are there because lot of jobs which were there in areas like software testing and customer support and all of that is gone but at the same time these technologies are also creating new jobs and for that you need to prepare yourself and fortunately the best part is that we have enough material enough resources enough support system that we can use to create a new job and for that you need to prepare yourself for the new kind of jobs that are going to come so this The whole revolution that we see in front of us will require massive skilling, a bit of reskilling also.

So many of my batchmates, 25 years into the careers, and they now feel that they have to reskill themselves with many, many new things. Life was very good somewhere in Silicon Valley, 25 years, a lot of money, but now they feel threatened. And that is the beauty of startups and all these new ideas that are there. So I would simply end by saying that this is the best time to be

Jaya Jagadish

Absolutely, totally agree. You know, I have to share this thing. I was actually conducting a panel discussion within AMD with the senior execs. And one of the fun questions was, if there is a machine or an equipment that you want to invent, what would it be? And the unanimous answer is, I would love to have a machine that can make me 20 years old. 20 years younger, right? So, you know, you guys are extremely lucky, make use of this opportunity to the maximum. All right. So as we come to the final leg of this discussion, India’s opportunity in AI and semiconductors is very real. But it’s also time bound. Momentum alone will not be enough. Sequencing, capital discipline, institutional alignment and infrastructure depth truly matters.

And all these areas have to work in complete alignment with each other. So, you know, let me close the session by asking each of you one more question. First one is for Rahul.

Moderator

was if there is a machine or an equipment that you want to invent, what would it be? And the unanimous answer is I would love to have a machine that can make me 20 years younger, right? So, you know, you guys are extremely lucky, make use of this opportunity to the maximum. All right. So as we come to the final leg of this discussion, India’s opportunity in AI and semiconductors is very real, but it’s also time bound. Momentum alone will not be enough. Sequencing, capital discipline, institutional alignment and infrastructure depth truly matters. And all these areas have to work in complete alignment with each other. So, you know, let me close the session by asking each of you one more question.

First. First one is for Rahul. In the global race where others are moving fast, what is the one move India must execute flawlessly to stay competitive?

Rahul Garg

I think like many other things I think it’s not one move so maybe we do everything as a Bollywood dance move right so they’re like 10 moves to everything but I think the one of the things which has happened at least from my vantage in the startup ecosystem is over the last 15 years we have become extremely good at being fast followers like maybe 15 years back if there was a product or a service in US or in Europe it would take three to five year lag to come to India and now maybe that lag is like one month 15 days I mean like so probably chat GPT within the first one month the maximum number of users are coming from India right so we have become extreme fast thanks to technology that we are fast followers the number of apps that might be built in India might be higher than most countries combined together maybe US China might be the only ones but otherwise I think India would be in the top three in terms of building all the apps in the world I think the move that needs to happen is the scale of ambition beyond India into the global platform because most of this effort that has happened in last 15 years are around kind of dominating the Indian consumer businesses applications so on so forth I think we need to up the game on global and we would require a significant amount of public private upping the game because most of the countries capital pools that we are fighting cannot be only attracted by the private players so I mean if someone is raising 100 billion dollar 200 billion dollar we need to at least start the race with 10 billion 15 billion 20 billion right which is not possible today completely in the private so I think how do we bring this and push the you capital bar, global bar together as a government and as private players I think that’s one thing I would love to see

Moderator

That’s a very valid statement Right Next question to Thomas Thomas, if we had to place one strategic bet that defines India’s position in AI and semiconductors by 2030 what should it be?

Thomas Zacharia

So I’m going to repeat what Rahul said there is, you know, the one I don’t know much about Bollywood dance moves but I would say one move is certainly ambitious I’m going to sort of regress back to a few previous questions since we have a few minutes, I thought I will sort of start with public -private alignment. Rahul mentioned that it is very, very hard for private sector to to to raise the kind of capital that’s being raised elsewhere in India. And that’s part of it is, you know, so one of the important things that government can do is to de -risk that enterprise. Now, I don’t believe that government should de -risk a private sector’s business venture by investing in that effort.

But there are unique places where government can de -risk through public -private partnerships that would enable this ecosystem to develop so that additional ventures can be taken up by private sector on their own. Because I don’t think that my taxpayer money should be used to subsidize. I mean, look, there is a role. So you mentioned Genesis. I did not describe Genesis. I don’t know whether… of you in the audience know what genesis is so I’ll take a couple of minutes to just discuss that as an opportunity to think about how to frame public private partnership so today United States spends a trillion dollars a year in R &D expenditure and roughly about 20 to 25 percent of that is government the rest is private sector now if you look at the R &D spend in the United States it’s been steadily growing at about keeping up with inflation maybe slightly above inflation 2 to 3 percent year over year but if you look at innovation output it’s been flat lined part of it is because the problems are getting more and more complicated discovering new materials cure for cancer all All those things are increasingly, significantly impactful for society, but also significantly challenging.

So the goal of Genesis Project is to really, one, align public and private partnership, two, invest government resources to bring academia, national laboratories, and private sector to identify what they call lighthouse problems, so you can call it grand challenge problems, that are relevant, that is likely to move the needle across these areas. And the government is then investing substantial resources for compute infrastructure, software stack, partnering with private sector in these important problems. Because it is being done in a… open, collaborative framework, private… This work is, in my view, appropriate for government to invest because the government is not investing directly in any particular business, but the business is able to take the fruits of this collaboration to drive innovation in their own sector.

So I think that is a really good model. I think it was already alluded to. If you are a fast follower or if you follow anybody, the danger is that it may be appropriate for a business, but as a nation, anytime you follow somebody, and if that is your ambition, you are destined at best to be number two, at best, because there is always somebody ahead of you. So I think for a country with the history of India, the ambition of India, the talent of India, and now the will of India, there is nothing wrong with aspiring to be, strategically deciding where India can go. can be world leading in part of this, I mean, no country is going to dominate every aspect of this ecosystem, identifying strategically where one can be that leader globally.

And I would say there are, at least if I can speak to AMD, just as an example, we were discussing about Helios and how it is based on open standards. There are many components. It may not be GPU that you start, but there are many components there where a private sector in India can aspire to be a leading provider based on open standards so that a business like AMD or a public private sector would say, well, I can get a better product, better total cost of ownership if I can plug into that. And one last thing, I cannot let you get away with, you know, just this time. I’m being great for the youngsters. Ray Kurzweil said that today, for each of us in this room, we age only eight months for every chronological year because of advances in medical care.

And that is true because longevity, people are living longer because of better drugs, better health, living, etc. So AI has the added advantage of providing greater solutions. So it’s not just the youngsters, there is hope for us if

Moderator

Absolutely. So we are all lucky to be here at this age of AI. We are truly lucky to be in this. No, that was very insightful. Thank you, Thomas. So Vivek, a question for you. I’m going to say what is the one bold decision, but I’m going to change that to what are some of the bold decisions. We must take to ensure we don’t look back and regret five years from today.

Vivek Kumar Singh

well i think uh what the the biggest advantage that india has is of course you know a huge pool of talent so that is something that we all need to rely on that’s that’s uh that’s the most important thing for a country like india and this essentially see india has an inherent culture of innovation so it’s not that you know we’re always following or we’re looking at technologies and so on the fact is the ecosystems where we have been living in they were not you know uh geared up they were not situated in the context that we were creating products so the culture of transforming that innovation to products has not been there unfortunately for a long period of time things are changing now and probably what we need to do is to invest more in our youth to invest more in skilling to invest uh more in how do we convert the knowledge that we generate generate in our universities, in our R &D labs into actual usable products which have, you know, socio -economic impact.

So that’s the most important thing that I believe we should be looking at. Of course, given the fact that we also have an advantage that we have the advantage of scale also. So, you know, a lot of things that we have done and we have proved it in terms of the digital public infra that we have created at a population scale of size India, it matters a lot. If you go to any part of the world, particularly anywhere in Europe, if you identify yourselves from India, you know, and you are in some discussion related to IT and so on, so you will always be regarded with, you know, a lot of depth in the sense that everybody believes that India is an IT superpower largely because of the talent that we have.

So this is something that we should leverage on and we should do it. And something that we really need to invest in heavily to see what is going to come for the next generation and to provide an environment and our prime minister keeps on saying ease of doing business so that is something that we really need to look into to to enable and to create an environment where we are able to transform the knowledge that we create into usable products

Moderator

no absolutely right i mean talent skilling and ease of doing business i mean all of these are coming together for india and in fact i led the committee for future skills and i worked i got the opportunity to work with 13 other eminent leaders from industry academia across the board and one thing that stood out was if we can actually get our skilling right we can actually supply talent not just for india but globally you know that’s something that’s going to be very effective you if we can get our skilling actions right so thank you again Today’s conversation was truly insightful and inspiring. We touched upon many aspects of semiconductors and AI and the ecosystem and India’s potential as such.

And again, AI leadership will not really happen by accident. It will require a deliberate alignment across policy, industry, research, and infrastructure. And we have many strengths that we need to work on. We need to work on strengthening and leveraging for the growth that we are ambitious about. And truly what matters now is decisive execution, moving with clarity and with urgency. So it’s going to be a great journey. And I once again want to iterate that we are truly lucky to be here in this phase. And what a fantastic journey we have ahead of us. And let’s be committed to that journey of learning and advancement. Thank you also. much for attending this session. I appreciate your time.

Thank you. Do we have time for audience questions? We can take one question, one or two. Out of 500 out of 500 sessions here, this is one on semiconductor. I’m very glad that you guys organized it. Very, very insightful. A few amazing questions and a good response. Quickly to my question. I teach AI and sustainability at IIM and I cover the entire supply chain starting from the rear, going through the chip design, manufacturing, the semiconductor supply chain, essentially, and all the way to data centers and electronic use. So, sustainability is at the core of all design decisions in my class. And that’s what we are trying to teach the new management human resources in India. Your thoughts on having sustainability not as a trade -off but as a core design choice for every decision that is made either in India or some country.

Thomas Zacharia

So it’s a great question and I think every one of us, certainly I can speak for the company that I represent here and I must say I’m in India so I am going to give a shout out to the 10 ,000 AMDers in this country. AMD would not exist without you. We would not be able to do what we are doing without the contributions that they make every day. So India is already very much part of a global supply chain. Sustainability is very key. We design our products with a goal, explicit goal of flattening the energy curve because it’s easy to say we’re going to build megawatts and gigawatts, which we may because it is going to be a fundamental infrastructure in which society is going to progress.

But it’s incumbent on us to ensure that we are very, very thoughtful and committed to sustainability. I also would like to say that we have to be humble enough to know that we are not going to get everything right. I was at a U .S. National Academy meeting where Subhash Suresh, he was the president at the time, we had just rolled out the grand challenges for the 21st century. And he said, you know, if you look at it, the grand challenges of the 21st century. are attempting to solve the problems created by the solutions to the grand challenges of the 20th century. So the reality is that we don’t know what we don’t know. But yet, as long as we use sustainability as a core goal and be humble enough to know that we are not going to get it all right, then I think we cannot stop progress.

We need to continue to move forward. But know that we are not going to get everything right and course correct as we go along.

Moderator

Okay, I’m told we are out of time. Yes, actually we are running out of time. And I really appreciate for joining us for this session. And I’m very much heartfelt thankful to our distinguished guests. So as a token from Mighty’s side, I would like to give a short, I mean cute memento. Pooja, you can also join. Thank you. Thank you. Thank you. Thank you.

Related ResourcesKnowledge base sources related to the discussion topics (14)
Factual NotesClaims verified against the Diplo knowledge base (2)
Confirmedhigh

“Dr Thomas Zakaria is Senior Vice President for Strategic Technical Partnerships and Public Policy at AMD.”

The knowledge base lists Dr Thomas Zakaria as Senior Vice President for Strategic Technical Partnerships and Public Policy at AMD, confirming his role [S1].

Confirmedmedium

“Prof. Vivek Kumar Singh said AI‑augmented learning shifts education from rote memorisation to creative problem‑solving.”

Future-Ready Education material describes a shift from regurgitation-based learning to critical thinking and creativity, supporting Singh’s description of the transition to AI-augmented, creative problem-solving [S79].

External Sources (80)
S1
The Global Power Shift India’s Rise in AI & Semiconductors — First. First one is for Rahul. In the global race where others are moving fast, what is the one move India must execute …
S2
https://dig.watch/event/india-ai-impact-summit-2026/the-global-power-shift-indias-rise-in-ai-semiconductors — First. First one is for Rahul. In the global race where others are moving fast, what is the one move India must execute …
S3
The Global Power Shift India’s Rise in AI & Semiconductors — The discussion was framed around India’s opportunity in AI and semiconductors, with the moderator establishing that AI r…
S4
Building the AI-Ready Future From Infrastructure to Skills — – Timothy Robson- Thomas Zacharia
S5
The Global Power Shift India’s Rise in AI & Semiconductors — – Thomas Zacharia- Rahul Garg – Vivek Kumar Singh- Thomas Zacharia
S6
The Global Power Shift India’s Rise in AI & Semiconductors — -Vivek Kumar Singh(Professor): Senior advisor on science and technology at NITI Aayog; plays central role in shaping Ind…
S7
https://dig.watch/event/india-ai-impact-summit-2026/the-global-power-shift-indias-rise-in-ai-semiconductors — Joining us is Professor Vivek Kumar Singh, Senior… advisor on science and technology at NITI IO. Professor Singh plays…
S8
Keynote-Olivier Blum — -Moderator: Role/Title: Conference Moderator; Area of Expertise: Not mentioned -Mr. Schneider: Role/Title: Not mentione…
S9
Keynote-Vinod Khosla — -Moderator: Role/Title: Moderator of the event; Area of Expertise: Not mentioned -Mr. Jeet Adani: Role/Title: Not menti…
S10
Day 0 Event #250 Building Trust and Combatting Fraud in the Internet Ecosystem — – **Frode Sørensen** – Role/Title: Online moderator, colleague of Johannes Vallesverd, Area of Expertise: Online session…
S11
Interdisciplinary approaches — AI-related issues are being discussed in various international spaces. In addition to the EU, OECD, and UNESCO, organisa…
S12
Building Trusted AI at Scale Cities Startups & Digital Sovereignty – Keynote Kiran Mazumdar-Shaw — “I believe that nations that command the convergence of biology and AI, or what I like to call the convergence of biolog…
S13
Panel Discussion Data Sovereignty India AI Impact Summit — Okay, I’m quickly coming to the third question. I think you had so many things. Supply chain trust, absolutely. Today, i…
S14
Building Trusted AI at Scale Cities Startups & Digital Sovereignty – Keynote Vivek Raghavan Sarvam AI — And it’s a core technology that a country like India must understand. from the foundational level. Otherwise, we will be…
S15
Scaling Trusted AI_ How France and India Are Building Industrial & Innovation Bridges — And thank you. And maybe I will introduce a few of them. Agri -Co is transforming agriculture through digital tools that…
S16
Scaling AI for Billions_ Building Digital Public Infrastructure — “Because trust is starting to become measurable, right, through provenance, through authenticity, as well as verificatio…
S17
https://dig.watch/event/india-ai-impact-summit-2026/indias-roadmap-to-an-agi-enabled-future — So my point was that, for example, geo tagging of all the assets of your, you know, right from the power generation to t…
S18
Diplomatic policy analysis — Policy analysis serves as the backbone of diplomacy’s decision-making. It equips leaders and negotiators with the eviden…
S19
Judiciary engagement — AI implementation in judicial systems has wide-ranging effects on various stakeholders including lawyers, litigants, and…
S20
Effective Governance for Open Digital Ecosystems | IGF 2023 Open Forum #65 — Lastly, the analysis emphasises the importance of a cross-disciplinary approach. It highlights the necessity for collabo…
S21
Global AI Policy Framework: International Cooperation and Historical Perspectives — Mirlesse outlines practical steps for implementing open sovereignty, emphasizing domestic AI deployment in key sectors w…
S22
High-Level sessions: Setting the Scene – Global Supply Chain Challenges and Solutions — Emphasis is placed on boosting supply chain resilience and embedding sustainability as fundamental to the private sector…
S23
The Battle for Chips — In conclusion, India’s strategic approach to developing a comprehensive semiconductor ecosystem demonstrates a commitmen…
S24
AI Transformation in Practice_ Insights from India’s Consulting Leaders — Talent development, education and future skills
S25
AI-Powered Chips and Skills Shaping Indias Next-Gen Workforce — -Massive Workforce Development Challenge: The industry faces a critical shortage of approximately 1 million skilled work…
S26
Sovereign AI for India – Building Indigenous Capabilities for National and Global Impact — The government’s response through the India AI Mission has established a shared compute framework providing access to 38…
S27
Open Forum #53 AI for Sustainable Development Country Insights and Strategies — The participant explains that India is following the same successful approach used for DPI development, where basic buil…
S28
The Global Power Shift India’s Rise in AI & Semiconductors — And again, AI leadership will not really happen by accident. It will require a deliberate alignment across policy, indus…
S29
Developing capacities for bottom-up AI in the Global South: What role for the international community? — Jovan Kurbalija: Thank you. She’s quiet. Okay, okay. Good. Great. We heard from our excellent speakers at the very begin…
S30
Global Digital Compact: AI solutions for a digital economy inclusive and beneficial for all — A strategic ecosystem approach requires early use cases in areas where private sector can lead, areas where public secto…
S31
AI/Gen AI for the Global Goals — Boa-Gue mentions the African Startup Policy Framework as an example of an initiative to enable member states to develop …
S32
Open Forum #33 Building an International AI Cooperation Ecosystem — Participant: ≫ Distinguished guests, dear friends, it is a great honor to speak to you today on a topic that is reshapin…
S33
WS #462 Bridging the Compute Divide a Global Alliance for AI — However, other panelists emphasized the importance of local infrastructure for enabling indigenous innovation and ensuri…
S34
Building Trusted AI at Scale Cities Startups & Digital Sovereignty – Keynote Kiran Mazumdar-Shaw — “When it comes to discovery, we need to develop foundation models for proteins, RNA, cellular circuits and systems biolo…
S35
Trade Deals or Disputes? / DAVOS 2025 — 4. Investment De-risking: Ensuring stable fiscal arrangements and rule of law to encourage long-term investments. Vandi…
S36
Panel 4 – Resilient Subsea Infrastructure for Underserved Regions  — -Policy and Regulatory Frameworks: Multiple panelists emphasized the critical role of government policy in reducing inve…
S37
Biology as Consumer Technology — Notably, the analysis highlights the importance of investors taking more risks, as venture funds often shy away from ris…
S38
European Tech Sovereignty: Feasibility, Challenges, and Strategic Pathways Forward — Moderate disagreement with significant implications. The disagreements are not fundamental conflicts but represent diffe…
S39
Day 0 Event #270 Everything in the Cloud How to Remain Digital Autonomous — This balanced approach influenced how other speakers framed their arguments, moving away from binary thinking toward mor…
S40
High-Level sessions: Setting the Scene – Global Supply Chain Challenges and Solutions — Crucially, the address underscored the importance of incorporating developing countries into the global supply chain, ad…
S41
Parallel Session D3: Supply Chain Disruptions – The Role and Response of NTFCs — In summary, the analysis accentuated TFAs as catalysts for managing and enhancing supply chain efficiency. It also under…
S42
How Investment Promotion Agencies (IPAs) and trade institutions could leverage digital tools to create sustainable supply chain partnerships’ — Cambodia has implemented the Pentagon Strategy, a new social and economic policy agenda, to combat climate change and pr…
S43
Keynote-Alexandr Wang — “That’s transformative, perhaps most especially in countries like India, where so many languages are spoken.”[11]. “That…
S44
Public-Private Partnerships in Online Content Moderation | IGF 2023 Open Forum #95 — Partnerships can help address the toughest challenges within a country by utilizing data-centric or artificial intellige…
S45
Assessing the Promise and Efficacy of Digital Health Tool | IGF 2023 WS #83 — The value of cross-sector partnerships, especially during the pandemic, is emphasised. Collaborations between the public…
S46
WS #460 Building Digital Policy for Sustainable E Waste Management — Sustainability must be designed into products from the beginning rather than treated as an afterthought
S47
Empowering the Ethical Supply Chain: steps to responsible sourcing and circular economy (Lenovo) — However, there are challenges that hinder progress towards sustainability. The analysis identifies knowledge gaps in sus…
S48
Creating Eco-friendly Policy System for Emerging Technology — Decision making should be based on evidence. Her argument conveyed a positive stance towards the central role of higher…
S49
Multistakeholder Partnerships for Thriving AI Ecosystems — Not only the big players. So all those things need framework and need governance. And we have to make sure that the outc…
S50
Indias Roadmap to an AGI-Enabled Future — Researchers, founders and policy makers. At Chariot, we are proud to be one of the companies mandated to build frontier …
S51
The Global Power Shift India’s Rise in AI & Semiconductors — The panelists emphasized that true AI leadership requires alignment across four key pillars: silicon, software, systems,…
S52
Democratizing AI Building Trustworthy Systems for Everyone — “of course see there would be a number of challenges but i think as i mentioned that one doesn’t need to really control …
S53
WS #270 Understanding digital exclusion in AI era — The speaker stresses the need for collaboration among multiple stakeholders to address AI challenges. No single stakehol…
S54
WS #462 Bridging the Compute Divide a Global Alliance for AI — Successful collaboration requires openness, compromise, and recognition of diverse community needs rather than imposing …
S55
From KW to GW Scaling the Infrastructure of the Global AI Economy — Specific timeline and investment details for India’s semiconductor manufacturing capabilities (Semicon mission) remain u…
S56
The Battle for Chips — Additionally, India advocates for providing more opportunities, investments, and technology to countries with greater po…
S57
Scaling Trusted AI_ How France and India Are Building Industrial & Innovation Bridges — Irakli Beridze (UNICRI) This comment introduced the governance perspective into the scientific discussion, emphasizing …
S58
High-Level session: Building and Financing Resilient and Sustainable Global Supply chains and the Role of the Private Sector — Businesses are encouraged to look outside the finite Caribbean market Effective collaboration, as demonstrated by the C…
S59
AI Transformation in Practice_ Insights from India’s Consulting Leaders — Talent development, education and future skills
S60
AI-Powered Chips and Skills Shaping Indias Next-Gen Workforce — -Massive Workforce Development Challenge: The industry faces a critical shortage of approximately 1 million skilled work…
S61
AI for Safer Workplaces & Smarter Industries Transforming Risk into Real-Time Intelligence — The panel reached consensus on the need for fundamental educational reform to prepare students for an AI-integrated futu…
S62
AI: The Great Equaliser? — While the introduction of AI technology may result in job losses in certain sectors, it also creates new job opportuniti…
S63
Sovereign AI for India – Building Indigenous Capabilities for National and Global Impact — The government’s response through the India AI Mission has established a shared compute framework providing access to 38…
S64
Cyber Resilience Playbook for PublicPrivate Collaboration — – Governments can completely exit the zero-day market and avoid research dedicated to finding software vulnerabilities….
S65
AI-driven Cyber Defense: Empowering Developing Nations | IGF 2023 — He introduces a panel of experts from different fields
S66
Building Public Interest AI Catalytic Funding for Equitable Compute Access — Deepali Khanna from the Rockefeller Foundation opened by framing the central challenge: the digital divide is evolving i…
S67
Keynotes — At the European Dialogue on Internet Governance (EuroDIG) 2024, the imperative of multistakeholder collaboration in shap…
S68
Opening of the session — Support expressed for paragraphs 15 and 16
S69
IGF 2019 – Dynamic coalition on blockchain technologies — After Diedrich’s presentation, the moderator opened the discussion to questions from the audience. The first question wa…
S70
Comprehensive Report: China’s AI Plus Economy Initiative – A Strategic Discussion on Artificial Intelligence Development and Implementation — I heard from Jingdong JD. That’s the goose named with smart has doubled the last year and the the the fourth one is to i…
S71
Impact & the Role of AI How Artificial Intelligence Is Changing Everything — The discussion maintained a cautiously optimistic tone throughout, balancing enthusiasm for AI’s potential with realisti…
S72
Closing Ceremony — This argument positions artificial intelligence as a transformative force rather than merely a technological tool. It su…
S73
Closing remarks – Charting the path forward — Bouverot argues for comprehensive inclusion in AI governance discussions, extending beyond just governmental participati…
S74
Global Enterprises Show How to Scale Responsible AI — The implementation challenge extends beyond organisational commitment to practical tooling and automation. Gurnani empha…
S75
Keynote Adresses at India AI Impact Summit 2026 — Gore reinforced this assessment, noting that “India’s entry into Pax Silica isn’t just symbolic, it’s strategic, it’s es…
S76
We are the AI Generation — In her conclusion, Martin articulated that the fundamental question should not be “who can build the most powerful model…
S77
Open Forum #30 High Level Review of AI Governance Including the Discussion — Lucia Russo from the OECD emphasized three strategic pillars: moving from principles to practice, providing evidence-bas…
S78
Opening keynote — Bogdan-Martin framed the AI revolution as a pivotal moment for the current generation, calling it an opportunity to take…
S79
Future-Ready Education: Enhancing Accessibility & Building | IGF 2023 — In the analysis, the speakers highlight the importance of future education being skills-oriented to prepare students for…
S80
AI (and) education: Convergences between Chinese and European pedagogical practices — **Norman Sze** (former Chair of Deloitte China) provided industry perspective on AI’s impact on professional work, notin…
Speakers Analysis
Detailed breakdown of each speaker’s arguments and positions
J
Jaya Jagadish
2 arguments141 words per minute1141 words484 seconds
Argument 1
Integrated approach: AI leadership requires coordinated silicon, software, systems, and policy (Jaya Jagadish)
EXPLANATION
Jaya stresses that true AI leadership cannot be achieved by focusing on a single element; it demands the simultaneous development of silicon hardware, software ecosystems, system integration, and supportive policy frameworks. This holistic coordination is essential for a nation to become a leader in AI.
EVIDENCE
She explained that “true AI leadership itself happens when silicon, software, systems, and policy, all of these aspects have to come together to achieve that leadership. No one aspect can really get us there” [32-34].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The Global Power Shift report stresses that AI leadership demands deliberate alignment across policy, industry, research and infrastructure, confirming the need for a coordinated silicon-software-systems-policy ecosystem [S1].
MAJOR DISCUSSION POINT
Holistic AI ecosystem coordination
AGREED WITH
Thomas Zacharia, Moderator
Argument 2
Development of local startups and indigenous IP is essential for a sovereign AI ecosystem (Jaya Jagadish)
EXPLANATION
Jaya argues that building a sovereign AI capability depends on fostering homegrown startups and creating indigenous intellectual property rather than relying on external IP. Indigenous IP is a cornerstone for self‑reliance and credibility in the AI domain.
EVIDENCE
She noted, “I do definitely want to see lot more local startups. … having our own IPs is one of the key steps we need to take” [84-86].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Credibility in deep-tech is linked to owning semiconductor IP and fostering domestic capabilities, supporting the emphasis on indigenous IP and local startups [S1].
MAJOR DISCUSSION POINT
Local startup and IP development
AGREED WITH
Thomas Zacharia, Vivek Kumar Singh
V
Vivek Kumar Singh
4 arguments201 words per minute2089 words622 seconds
Argument 1
Massive government funding (₹10,000 crore) and a systematic AI mission create scale and credibility (Vivek Kumar Singh)
EXPLANATION
Vivek highlights that the Indian government’s AI mission, backed by more than ₹10,000 crore over five years, provides the financial muscle and systematic approach needed to build credibility at scale. This funding underpins large‑scale deployments rather than isolated announcements.
EVIDENCE
He referenced “the India AI mission … 10 000 plus crores for five years” as part of a systematic effort that addresses all AI needs [56].
MAJOR DISCUSSION POINT
Government funding for AI credibility
AGREED WITH
Thomas Zacharia, Rahul Garg, Moderator
Argument 2
Credibility stems from large‑scale deployments and genuine IP ownership, not merely announcements (Vivek Kumar Singh)
EXPLANATION
Vivek asserts that credibility in deep‑tech arises from actual large‑scale implementations and ownership of intellectual property, rather than from promotional announcements. Sustainable credibility requires tangible, scaled outcomes.
EVIDENCE
He stated that “credibility doesn’t come only from announcements… it comes as part of commitment for scaled deployments, for scaled growth” [56-57].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The analysis notes that credibility depends on scaling deployments and owning semiconductor IP rather than on promotional announcements [S1].
MAJOR DISCUSSION POINT
Substance over hype for credibility
AGREED WITH
Jaya Jagadish, Thomas Zacharia
Argument 3
Post‑COVID supply‑chain shocks have generated strong will and government incentives (tax holidays, ₹1.2 bn AI fund) to localise production (Vivek Kumar Singh)
EXPLANATION
Vivek points out that disruptions caused by COVID highlighted the need for domestic supply‑chain resilience, prompting policy measures such as tax holidays for data centres and a sizable AI fund to encourage localisation. This has created a political will to build manufacturing capacity within India.
EVIDENCE
He mentioned recent “tax holidays for data centers” and the broader push to localise production following pandemic-induced supply-chain shocks [53-55].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Post-COVID supply-chain trust issues and the push for domestic hardware and AI provenance are discussed in the Data Sovereignty panel, reflecting policy incentives such as tax holidays [S13].
MAJOR DISCUSSION POINT
Policy response to supply‑chain shocks
Argument 4
Balancing strategic autonomy for security‑sensitive sectors with open global collaboration is crucial (Vivek Kumar Singh)
EXPLANATION
Vivek emphasizes the need for India to define clear rules on which technologies should be indigenised for strategic autonomy while keeping other areas open for international collaboration. This strategic autonomy ensures security without isolating the ecosystem.
EVIDENCE
He outlined the need for “clarity of rules” on what to indigenise versus what to keep open, describing this as “strategic autonomy” [141-147].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The need for sophisticated frameworks to decide which components to indigenise versus keep open, i.e., strategic autonomy, is highlighted in the Global Power Shift briefing and the Data Sovereignty discussion [S1][S13].
MAJOR DISCUSSION POINT
Strategic autonomy vs openness
DISAGREED WITH
Thomas Zacharia
R
Rahul Garg
3 arguments172 words per minute1338 words466 seconds
Argument 1
Growing demand, political will, and rising private‑capital commitments (>$100 bn) are enabling manufacturing expansion (Rahul Garg)
EXPLANATION
Rahul observes that India’s expanding consumer demand, reinforced by political commitment and a surge in private‑sector capital—exceeding $100 billion—are driving rapid growth in manufacturing and AI infrastructure. This confluence of demand and financing is reshaping the industrial landscape.
EVIDENCE
He noted that “demand in the country clearly is growing rapidly” and cited “more than 100 billion dollar plus commitment from the private capital companies” for data-center localisation [70-73].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Private-sector appetite for localisation post-COVID, with commitments exceeding $100 bn, is documented in the Global Power Shift report [S1].
MAJOR DISCUSSION POINT
Demand and capital fueling manufacturing
DISAGREED WITH
Thomas Zacharia
Argument 2
Companies should adopt vertical‑stack models, develop mid‑zone fabs, and nurture ancillary ecosystems (clean‑room, packaging, chemicals) (Rahul Garg)
EXPLANATION
Rahul recommends that Indian firms pursue vertical integration—from chip design through manufacturing to system integration—while establishing mid‑range fabs and building supporting ecosystems such as clean‑room facilities, chemical suppliers, and packaging verification. This approach can accelerate capability building across the supply chain.
EVIDENCE
He described the need for “vertical-stack models” and highlighted the importance of “mid-zone fabs” and ancillary ecosystems like “clean-room suppliers, utility suppliers, packaging verification” [153-163].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Recommendations for vertical integration, mid-zone fabs and supporting ecosystems such as clean-rooms and packaging are outlined in the Global Power Shift analysis [S1].
MAJOR DISCUSSION POINT
Vertical integration and ecosystem development
DISAGREED WITH
Thomas Zacharia
Argument 3
India’s large talent pool gives it a fast‑follower advantage; scaling this to a global platform requires coordinated public‑private effort (Rahul Garg)
EXPLANATION
Rahul argues that India’s abundant talent enables it to adopt new technologies quickly, as seen with rapid adoption of tools like ChatGPT. To translate this speed into global leadership, coordinated action between government and private sector is essential.
EVIDENCE
He highlighted that “we have become extreme fast followers” with India leading in early ChatGPT adoption, and stressed the need for “significant public-private” collaboration to raise capital to global levels [214-218].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The report emphasizes that coordinated public-private action is needed to translate India’s talent and fast-follower capability into global-scale leadership [S1].
MAJOR DISCUSSION POINT
Fast‑follower talent leveraged with PPP
DISAGREED WITH
Thomas Zacharia
T
Thomas Zacharia
6 arguments136 words per minute1744 words765 seconds
Argument 1
India should target capability rather than leading‑edge fabs, focusing on niche supply‑chain areas such as co‑package optics and AI‑infrastructure components (Thomas Zacharia)
EXPLANATION
Thomas suggests that India’s realistic path is to develop capabilities in specialized, high‑value supply‑chain segments—like co‑package optics and AI‑infrastructure interconnects—rather than attempting to build leading‑edge 2 nm fabs. This niche focus can still contribute significantly to global AI deployments.
EVIDENCE
He explained that “you don’t necessarily have to be at the two nanometer scale… there are critical technology in the deployment at scale of AI infrastructure where India can play a role” and cited “co-package optics” as a niche area where India can “stab the jib” [102-108].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The briefing argues that India’s realistic path is to focus on strategic supply-chain participation and niche capabilities rather than pursuing leading-edge 2 nm fabs [S1].
MAJOR DISCUSSION POINT
Niche capability focus over leading‑edge fabs
DISAGREED WITH
Rahul Garg
Argument 2
Private sector must build and protect its own IP while leveraging global collaborations (Thomas Zacharia)
EXPLANATION
Thomas emphasizes that Indian companies need to generate and safeguard indigenous IP, while also seeking partnerships with global players to mature startups. This dual approach balances self‑reliance with the benefits of international collaboration.
EVIDENCE
He recounted asking the CEO of Medi about the “top 50” startups so that AMD could partner to help them mature, underscoring the need for local IP development and strategic partnerships [98-100].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Ownership of semiconductor IP and strategic partnerships with global firms are identified as essential for Indian companies in the Global Power Shift document [S1].
MAJOR DISCUSSION POINT
IP creation and strategic partnerships
AGREED WITH
Jaya Jagadish, Vivek Kumar Singh
Argument 3
Capital is beginning to flow, though still uneven; public‑private de‑risking can broaden the base (Thomas Zacharia)
EXPLANATION
Thomas notes that while capital is entering the ecosystem, its distribution is uneven. He proposes public‑private de‑risking mechanisms to encourage broader private investment without direct subsidy, thereby expanding the funding base.
EVIDENCE
He discussed the role of public-private partnerships in de-risking ventures, stating that “government can de-risk through public-private partnerships that would enable this ecosystem to develop” [216-221].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Public-private de-risking mechanisms to broaden capital flow are discussed as a way to support the emerging ecosystem [S1].
MAJOR DISCUSSION POINT
PPP de‑risking to broaden capital base
AGREED WITH
Vivek Kumar Singh, Rahul Garg, Moderator
DISAGREED WITH
Rahul Garg
Argument 4
A national supercomputing mission can seed AI infrastructure and drive long‑term innovation (Thomas Zacharia)
EXPLANATION
Thomas argues that a dedicated national supercomputing mission can provide the foundational compute resources needed for AI research and industrial applications, thereby catalyzing sustained innovation across the country.
EVIDENCE
He referenced India’s “supercomputing mission” and compared it to China’s 20-25-year intentional build-up of HPC that later powered AI adoption [119-124].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
India’s supercomputing mission is cited as a catalyst for AI research and industrial applications, analogous to China’s HPC build-up, in the Global Power Shift analysis [S1].
MAJOR DISCUSSION POINT
Supercomputing mission as AI catalyst
AGREED WITH
Jaya Jagadish, Moderator
DISAGREED WITH
Rahul Garg
Argument 5
PPP frameworks like the “Genesis” project can de‑risk large‑scale R&D, focus on lighthouse problems, and align academia, labs, and industry (Thomas Zacharia)
EXPLANATION
Thomas describes the Genesis project as a model where government funds are used to bring together academia, national labs, and industry to tackle grand‑challenge problems, thereby de‑risking research while fostering open collaboration.
EVIDENCE
He explained that the Genesis Project “aligns public and private partnership, invests government resources to bring academia, national laboratories, and private sector to identify lighthouse problems” and supports compute infrastructure and software stacks [225-229].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
The Genesis project, a public-private partnership that aligns academia, national labs and industry around lighthouse problems, is described in the Global Power Shift report [S1].
MAJOR DISCUSSION POINT
Genesis PPP for R&D de‑risking
DISAGREED WITH
Vivek Kumar Singh
Argument 6
AMD embeds energy‑efficiency goals in product design and acknowledges the need for continual humility and course‑correction on sustainability (Thomas Zacharia)
EXPLANATION
Thomas states that AMD designs its products with explicit energy‑efficiency targets to flatten the energy curve, while recognizing that sustainability is an ongoing journey that requires humility and iterative improvement.
EVIDENCE
He said “we design our products with a goal, explicit goal of flattening the energy curve” and admitted “we are not going to get everything right” but must continue to move forward [282-289].
MAJOR DISCUSSION POINT
Sustainability embedded in product design
M
Moderator
1 argument97 words per minute981 words602 seconds
Argument 1
Aligning policy, industry, research, and infrastructure is essential to translate talent into global‑competitive products (Moderator)
EXPLANATION
The Moderator stresses that deliberate coordination among government policy, industrial capabilities, academic research, and infrastructure investment is required to turn India’s talent pool into globally competitive AI and semiconductor products.
EVIDENCE
He summarized that “AI leadership will not really happen by accident. It will require a deliberate alignment across policy, industry, research, and infrastructure” and called for “decisive execution, moving with clarity and with urgency” [255-262].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Deliberate alignment across policy, industry, research and infrastructure is identified as a prerequisite for AI leadership in the Global Power Shift briefing [S1].
MAJOR DISCUSSION POINT
Cross‑sector alignment for AI leadership
AGREED WITH
Vivek Kumar Singh, Thomas Zacharia, Rahul Garg
Agreements
Agreement Points
A coordinated, holistic ecosystem (silicon, software, systems, policy, research, infrastructure) is essential for AI leadership.
Speakers: Jaya Jagadish, Thomas Zacharia, Moderator
Integrated approach: AI leadership requires coordinated silicon, software, systems, and policy (Jaya Jagadish) A national supercomputing mission can seed AI infrastructure and drive long‑term innovation (Thomas Zacharia) Aligning policy, industry, research, and infrastructure is essential to translate talent into global‑competitive products (Moderator)
All three speakers stress that AI leadership cannot rely on a single pillar; it demands simultaneous development of hardware, software, system integration, supportive policy and research infrastructure [32-34][119-124][255-262].
POLICY CONTEXT (KNOWLEDGE BASE)
This view mirrors policy calls for a deliberate alignment across silicon, software, systems, policy, research and infrastructure to achieve AI leadership, as articulated in the Global Power Shift report on India’s AI ambitions [S28] and reinforced by broader strategic guidance on coordinated AI ecosystems [S43].
Public‑private partnership and substantial financing are critical to scale AI and semiconductor capabilities.
Speakers: Vivek Kumar Singh, Thomas Zacharia, Rahul Garg, Moderator
Massive government funding (₹10,000 crore) and a systematic AI mission create scale and credibility (Vivek Kumar Singh) Capital is beginning to flow, though still uneven; public‑private de‑risking can broaden the base (Thomas Zacharia) Growing demand, political will and >$100 bn private‑capital commitments are enabling manufacturing expansion (Rahul Garg) Aligning policy, industry, research, and infrastructure is essential to translate talent into global‑competitive products (Moderator)
The panel concurs that large-scale funding-both public (AI mission, tax incentives) and private (hundreds of billions of dollars)-combined with PPP de-risking mechanisms, is needed to build a credible AI/semiconductor ecosystem [56][216-221][214-218][255-262].
India’s abundant talent pool provides a fast‑follower advantage that must be leveraged through coordinated action.
Speakers: Jaya Jagadish, Rahul Garg, Thomas Zacharia
India is well‑poised with engineering talent, silicon design strength and ecosystem partners (Jaya Jagadish) India’s large talent pool gives it an extreme fast‑follower advantage; scaling this globally requires public‑private effort (Rahul Garg) India’s talent and ambition can be directed toward strategic capabilities (Thomas Zacharia)
All three highlight that India’s strong engineering and scientific talent enables rapid adoption of new technologies, but realizing global leadership will require coordinated public-private strategies [38-39][214-215][239-240].
POLICY CONTEXT (KNOWLEDGE BASE)
India’s talent advantage is highlighted as a key strength in the Global Power Shift analysis of India’s AI rise [S28] and in discussions about bold national AI strategies that leverage human capital across many languages and domains [S43].
Developing indigenous IP and nurturing local startups are essential for a sovereign AI ecosystem.
Speakers: Jaya Jagadish, Thomas Zacharia, Vivek Kumar Singh
Development of local startups and indigenous IP is essential for a sovereign AI ecosystem (Jaya Jagadish) Private sector must build and protect its own IP while leveraging global collaborations (Thomas Zacharia) Credibility stems from large‑scale deployments and genuine IP ownership, not merely announcements (Vivek Kumar Singh)
The speakers agree that owning IP and fostering home-grown startups are cornerstones of credibility and sovereignty in AI and semiconductors [84-86][98-100][56-57].
POLICY CONTEXT (KNOWLEDGE BASE)
Calls for indigenous IP and startup ecosystems echo the emphasis on technological sovereignty and local infrastructure for innovation found in the Global Alliance for AI report [S33] and in India’s NDIA mission to build sovereign frontier models [S50].
Similar Viewpoints
Both note that COVID‑related supply‑chain disruptions created a policy push (tax holidays, AI fund) and heightened private‑capital interest in building domestic manufacturing capacity [53-55][70-73].
Speakers: Vivek Kumar Singh, Rahul Garg
Post‑COVID supply‑chain shocks have generated strong political will and incentives (tax holidays, AI fund) to localise production (Vivek Kumar Singh) Pandemic‑induced supply‑chain disruptions have spurred demand for domestic manufacturing and capital inflows (Rahul Garg)
Both propose a realistic, incremental path that leverages niche capabilities and mid‑range manufacturing rather than chasing the most advanced process nodes [102-108][153-163].
Speakers: Thomas Zacharia, Rahul Garg
India should focus on niche, high‑value supply‑chain capabilities (co‑package optics, AI infrastructure) rather than leading‑edge fabs (Thomas Zacharia) Companies should adopt vertical‑stack models, develop mid‑zone fabs and ancillary ecosystems (Rahul Garg)
Unexpected Consensus
Recognition that sustainability must be embedded in product design despite limited discussion elsewhere.
Speakers: Thomas Zacharia, Moderator
AMD embeds energy‑efficiency goals in product design and acknowledges the need for humility and continual improvement (Thomas Zacharia) Moderator raises a question on making sustainability a core design choice for AI and semiconductor decisions (Moderator)
Although sustainability was not a primary focus for most panelists, both Thomas and the Moderator converge on the view that sustainability should be a foundational design principle, highlighting an unexpected alignment [282-289][274-277].
POLICY CONTEXT (KNOWLEDGE BASE)
The need to embed sustainability from the design stage is directly reflected in the guidance that sustainability should be designed into products rather than treated as an afterthought [S46].
Overall Assessment

The panel shows strong convergence on four major themes: (1) the need for a coordinated, holistic AI ecosystem; (2) the importance of sizable public and private financing through PPP mechanisms; (3) leveraging India’s deep talent pool as a fast‑follower advantage; and (4) building indigenous IP and startup ecosystems for sovereign capability. Additional nuanced agreements appear on niche supply‑chain focus and the emerging emphasis on sustainability.

High consensus across speakers on strategic direction and required enablers, suggesting a unified policy and industry roadmap is feasible. The alignment reinforces the urgency of implementing integrated funding, talent development, and IP strategies to achieve AI and semiconductor leadership.

Differences
Different Viewpoints
Strategic focus: niche supply‑chain specialization vs building vertical‑integrated mid‑zone fabs
Speakers: Thomas Zacharia, Rahul Garg
India should target capability rather than leading‑edge fabs, focusing on niche supply‑chain areas such as co‑package optics and AI‑infrastructure components (Thomas Zacharia) Companies should adopt vertical‑stack models, develop mid‑zone fabs, and nurture ancillary ecosystems (clean‑room, packaging, chemicals) (Rahul Garg)
Thomas argues that India can contribute to AI and semiconductor ecosystems by specializing in high-value niche components (e.g., co-package optics) without pursuing leading-edge 2 nm fabs, whereas Rahul contends that India needs to build its own mid-range fabs and vertically integrate the entire supply chain, including clean-room and packaging ecosystems, to achieve capability. [102-108] vs [153-163]
POLICY CONTEXT (KNOWLEDGE BASE)
The tension between niche supply-chain specialization and vertical integration mirrors discussions on moving developing countries up the global supply-chain ladder and promoting balanced development beyond lower-tier roles [S40][S41].
Capital mobilisation and the role of government in de‑risking versus direct large‑scale funding
Speakers: Thomas Zacharia, Rahul Garg
Capital is beginning to flow, though still uneven; public‑private de‑risking can broaden the base (Thomas Zacharia) Growing demand, political will, and rising private‑capital commitments (>$100 bn) are enabling manufacturing expansion (Rahul Garg)
Thomas says the government should de-risk ventures through public-private partnerships without direct subsidies, while Rahul points to massive private-capital commitments already flowing and calls for coordinated public-private pools to raise billions, indicating a more direct funding role for the state. [216-221] vs [70-78] and [214-218]
POLICY CONTEXT (KNOWLEDGE BASE)
Debates over de-risking capital versus direct funding reflect policy recommendations on investment de-risking, stable fiscal arrangements and rule-of-law mechanisms to encourage long-term investments [S35] and the broader role of government policy in reducing investment risk [S36].
Openness versus strategic autonomy in security‑sensitive technology domains
Speakers: Vivek Kumar Singh, Thomas Zacharia
Balancing strategic autonomy for security‑sensitive sectors with open global collaboration is crucial (Vivek Kumar Singh) PPP frameworks like the “Genesis” project can de‑risk large‑scale R&D, focus on lighthouse problems, and align academia, labs, and industry (Thomas Zacharia)
Vivek stresses the need for clear rules on what technologies must be indigenised for strategic autonomy, while Thomas promotes an open, collaborative public-private model (Genesis) that de-risks research without imposing strict indigenisation boundaries. [141-147] vs [225-229]
POLICY CONTEXT (KNOWLEDGE BASE)
The openness versus strategic autonomy dilemma parallels the European tech sovereignty discourse, where regulatory philosophy and the balance between openness and autonomy are contested [S38].
Speed‑driven fast‑follower model versus long‑term capability‑building via a supercomputing mission
Speakers: Rahul Garg, Thomas Zacharia
India’s large talent pool gives it a fast‑follower advantage; scaling this to a global platform requires coordinated public‑private effort (Rahul Garg) A national supercomputing mission can seed AI infrastructure and drive long‑term innovation (Thomas Zacharia)
Rahul emphasizes leveraging India’s talent to quickly adopt and build AI applications as a fast follower, whereas Thomas advocates building sovereign capability through a dedicated supercomputing mission that underpins long-term AI innovation, suggesting a more measured, capability-first approach. [214-218] vs [119-124]
POLICY CONTEXT (KNOWLEDGE BASE)
The contrast between a fast-follower approach and a long-term supercomputing capability aligns with India’s NDIA supercomputing and sovereign frontier-model mission, which emphasizes building deep, long-term compute capacity [S50].
Unexpected Differences
Perception of being ‘late to the party’ versus confidence in immediate niche contributions
Speakers: Rahul Garg, Thomas Zacharia
So I think we are kind of late to the party in some sense… (Rahul Garg) You don’t necessarily have to be at the two nanometer scale… there are critical technology in the deployment at scale of AI infrastructure where India can play a role (Thomas Zacharia)
Rahul frames India as significantly behind the global semiconductor race, implying a need to catch up, while Thomas downplays the need for leading-edge fabs and asserts that India can immediately add value through niche components, making the contrast between a ‘catch-up’ narrative and a ‘ready-to-contribute’ stance unexpected. [153-154] vs [102-108]
Degree of openness in public‑private research collaborations
Speakers: Vivek Kumar Singh, Thomas Zacharia
Balancing strategic autonomy for security‑sensitive sectors with open global collaboration is crucial (Vivek Kumar Singh) The Genesis Project aligns public and private partnership, invests government resources to bring academia, national laboratories, and private sector to identify lighthouse problems… (Thomas Zacharia)
Vivek calls for clear limits on what should be indigenised, suggesting a more guarded approach, whereas Thomas promotes an open, collaborative PPP model (Genesis) that encourages shared problem-solving without strict indigenisation rules-an unexpected tension between protectionist and open-innovation philosophies. [141-147] vs [225-229]
POLICY CONTEXT (KNOWLEDGE BASE)
Discussions on openness in public-private research echo multistakeholder partnership models that promote open-source development and shared datasets, as highlighted in the multistakeholder AI ecosystem framework [S49].
Overall Assessment

The panel displayed broad consensus on the importance of talent, coordinated ecosystems, and public‑private collaboration, but diverged sharply on strategic focus (niche vs vertical integration), the mechanism for capital mobilisation (de‑risking PPP versus large pooled funding), the balance between strategic autonomy and open collaboration, and whether India should pursue a fast‑follower catch‑up path or a longer‑term capability‑building route.

Moderate to high – while the participants share common goals (AI leadership, sustainability, talent development), their prescriptions differ substantially, indicating that policy design will need to reconcile competing priorities and reconcile fast‑follower ambitions with strategic, niche‑focused investments.

Partial Agreements
All three agree that AI leadership cannot be achieved in isolation and requires coordinated action across technology, policy, and public‑private mechanisms, even though they differ on the exact balance between openness, strategic autonomy, and partnership models. [32-34] vs [116-119] vs [141-147]
Speakers: Jaya Jagadish, Thomas Zacharia, Vivek Kumar Singh
Integrated approach: AI leadership requires coordinated silicon, software, systems, and policy (Jaya Jagadish) So I think this is a great area for public‑private partnership, in my view. (Thomas Zacharia) Balancing strategic autonomy for security‑sensitive sectors with open global collaboration is crucial (Vivek Kumar Singh)
The speakers concur that India’s abundant talent is a core asset that must be nurtured and leveraged through education, startup ecosystems, and coordinated policy‑industry‑research frameworks, even though they propose different mechanisms (startup IP, fast‑follower scaling, strategic autonomy, broad alignment). [38-40] vs [214-218] vs [141-147] vs [255-262]
Speakers: Jaya Jagadish, Rahul Garg, Vivek Kumar Singh, Moderator
Development of local startups and indigenous IP is essential for a sovereign AI ecosystem (Jaya Jagadish) India’s large talent pool gives it a fast‑follower advantage; scaling this to a global platform requires coordinated public‑private effort (Rahul Garg) Balancing strategic autonomy for security‑sensitive sectors with open global collaboration is crucial (Vivek Kumar Singh) Aligning policy, industry, research, and infrastructure is essential to translate talent into global‑competitive products (Moderator)
Takeaways
Key takeaways
AI leadership requires a coordinated ecosystem of silicon, software, systems and policy; no single element is sufficient. India’s AI mission and large government funding (≈₹10,000 crore) provide scale and credibility, but true credibility comes from large‑scale deployments and indigenous IP ownership. Manufacturing depth can be built by focusing on niche, high‑value supply‑chain segments (e.g., co‑package optics, AI‑infrastructure components) rather than trying to own the most advanced fabs immediately. Public‑private partnerships (e.g., the “Genesis” model) are essential to de‑risk large R&D programmes, align academia, national labs and industry, and address lighthouse problems. Balancing strategic autonomy for security‑sensitive domains with open global collaboration is critical for sustainable growth. India’s large talent pool and emerging fast‑follower capability can be leveraged through aggressive skilling, free AI‑driven learning platforms, and university incubators. Sustainability must be embedded as a core design principle in semiconductor and AI hardware, with humility and continuous course‑correction.
Resolutions and action items
Encourage public‑private de‑risking mechanisms for deep‑tech R&D (e.g., Genesis‑style projects) to broaden private capital participation. Prioritize development of mid‑zone fabs and ancillary ecosystem (clean‑room, packaging, chemicals) while targeting niche supply‑chain opportunities such as co‑package optics. Accelerate IP creation and protection by supporting local startups and facilitating pathways from research to productisation. Scale existing government skilling initiatives (e.g., NASCOM’s Future Skill Prime) and promote AI‑driven learning resources to up‑skill the workforce for emerging roles. Formulate a strategic autonomy framework that delineates sectors requiring sovereign capability versus those open to global collaboration. Integrate energy‑efficiency and sustainability targets into semiconductor product design and AI infrastructure planning.
Unresolved issues
How to ensure broad‑based, long‑term private capital flows that match the scale of global competitors. Specific timeline and roadmap for moving from niche supply‑chain participation to more advanced fab capabilities. Concrete mechanisms for IP transfer and commercialization from academia to industry. Detailed policies for balancing national security concerns with openness in collaborative research. Metrics and governance structures to monitor progress on sustainability goals within the semiconductor supply chain.
Suggested compromises
Adopt a strategic autonomy approach: retain sovereign control over security‑critical technologies while remaining open to collaboration on non‑sensitive domains. Use public‑private partnerships to de‑risk projects without direct government subsidies to private firms, sharing risk and reward. Encourage vertical‑stack business models initially, with a gradual transition toward horizontal ecosystem participation as capabilities mature.
Thought Provoking Comments
AI leadership is not achieved by a single pillar; silicon, software, systems, and policy must all come together. No one aspect can get us there alone.
Sets a holistic framework for the entire discussion, emphasizing interdisciplinary collaboration rather than siloed efforts.
Guided the panel to address each domain (design, manufacturing, policy, talent) and prompted subsequent speakers to position their insights within this integrated view.
Speaker: Jaya Jagadish
We don’t need to chase the 2 nm GPU/CPU node. India can create value in niche areas like co‑packaged optics and other critical interconnect technologies that are not globally abundant.
Redirects the conversation from the daunting goal of leading‑edge fabs to realistic, high‑impact niches where India can compete now.
Shifted the focus from a ‘catch‑up’ narrative to a ‘strategic specialization’ narrative, leading the panel to discuss supply‑chain gaps and opportunities beyond traditional chip scaling.
Speaker: Thomas Zacharia
The US and China built their AI capabilities on long‑term supercomputing missions. India’s supercomputing mission should be planned not where we are today, but where the ecosystem will be when the infrastructure is deployed.
Draws a clear lesson from other nations, linking HPC investment to future AI leadership and emphasizing forward‑looking planning.
Prompted Vivek and others to consider policy timelines and the importance of aligning research, infrastructure, and industrial capacity well ahead of deployment.
Speaker: Thomas Zacharia
We need strategic autonomy: decide which components we must indigenize for security, and where we can stay open to global collaboration.
Addresses the tension between national security and openness, offering a nuanced policy approach rather than an all‑or‑nothing stance.
Steered the discussion toward concrete policy mechanisms, influencing later remarks about public‑private partnerships and the need for clear rules on indigenization.
Speaker: Vivek Kumar Singh
India has become an extreme fast‑follower; the lag from global product launch to Indian adoption is now weeks. The next move is to scale ambition beyond the domestic market and mobilize billions of dollars of public‑private capital.
Highlights a unique competitive advantage (speed of adoption) while identifying the missing piece—global scale and capital depth.
Reoriented the conversation from capability building to financing and market expansion, leading Thomas to discuss de‑risking mechanisms and large‑scale public‑private funding.
Speaker: Rahul Garg
The Genesis Project is a model where government invests in compute infrastructure, software stacks, and lighthouse problems in an open, collaborative framework, de‑risking the ecosystem without directly subsidising private ventures.
Introduces a concrete, actionable framework for public‑private partnership that balances risk, innovation, and market independence.
Provided a tangible policy proposal that other panelists referenced when talking about funding, talent pipelines, and scaling ambition, moving the dialogue from abstract ideas to a potential implementation plan.
Speaker: Thomas Zacharia
Sustainability should be a core design goal, not a trade‑off. We must be humble, acknowledge we won’t get everything right, and continuously course‑correct as we flatten the energy curve of our products.
Elevates the discussion to include environmental responsibility as integral to AI and semiconductor strategy, linking technical decisions to broader societal impact.
Added a new dimension to the conversation, prompting participants to consider long‑term ecological implications alongside economic and strategic goals.
Speaker: Thomas Zacharia (in response to audience question)
Overall Assessment

The discussion was shaped by a series of pivotal remarks that moved it from a broad, aspirational overview to a focused, actionable roadmap. Jaya’s integrative framing set the stage, while Thomas’s emphasis on niche technological strengths and forward‑looking supercomputing strategy redirected attention to realistic competitive edges. Vivek’s call for strategic autonomy and Thomas’s Genesis partnership model provided concrete policy pathways, and Rahul’s insight on fast‑following coupled with the need for massive public‑private capital highlighted the financing challenge. Finally, the sustainability comment broadened the agenda to include environmental stewardship. Together, these comments created turning points that deepened analysis, introduced new topics, and aligned the panel around specific, implementable ideas.

Follow-up Questions
What concrete steps should India take to build its intellectual foundation for AI and semiconductor leadership?
Establishing a strong knowledge base is essential for long‑term competitiveness and informs education, research, and talent policies.
Speaker: Jaya Jagadish
What specific manufacturing depth and supply‑chain resilience investments are needed for AI hardware in India?
Identifying targeted investments will help create a robust domestic ecosystem capable of scaling AI compute resources.
Speaker: Jaya Jagadish
What actions are required to achieve a credible sovereign AI capability for India?
Sovereignty over data and AI services is a strategic priority; clear actions are needed to translate policy into practice.
Speaker: Jaya Jagadish
How effective are the recent tax holidays for data centers and the AI Coach platform in accelerating AI adoption?
Assessing policy impact will reveal whether incentives are driving the intended scale of AI infrastructure and applications.
Speaker: Vivek Kumar Singh
What is the detailed roadmap and milestones for the India AI Mission (₹10,000 crore over five years) across its seven pillars?
A transparent timeline will enable tracking progress and aligning public‑private efforts.
Speaker: Vivek Kumar Singh
What strategies can India adopt to acquire and retain semiconductor IP ownership to enhance credibility?
IP ownership is critical for a self‑reliant semiconductor ecosystem and for attracting global partnerships.
Speaker: Vivek Kumar Singh
What are the sources, terms, and timelines of the reported $100 billion+ private capital commitments for AI deep‑tech and data centers in India?
Understanding the financing landscape is vital to gauge whether capital is sufficient and sustainable for long‑term projects.
Speaker: Rahul Garg
Which niche technology segments (e.g., co‑packaged optics, interconnects) offer realistic value‑creation opportunities for India in AI infrastructure supply chains?
Targeting specific high‑impact areas can allow India to contribute without needing to master leading‑edge process nodes.
Speaker: Thomas Zacharia
What is the feasibility of India developing a supply chain for advanced interconnect optics, including potential partnerships with the US, Japan, and Malaysia?
Exploring partnership models will clarify how India can fill global gaps and build domestic capability.
Speaker: Thomas Zacharia
What is the structure, funding model, and implementation plan for the ‘Genesis Project’ public‑private partnership?
A clear description will help replicate successful R&D collaboration frameworks and attract stakeholder buy‑in.
Speaker: Thomas Zacharia
How should India balance strategic autonomy with openness and global collaboration in AI and semiconductor sectors?
Finding the right equilibrium is crucial for national security while still benefiting from international innovation.
Speaker: Vivek Kumar Singh
Should Indian semiconductor manufacturers pursue vertical‑stack integration or evolve toward horizontal ecosystem models, and what are the trade‑offs?
Understanding optimal industry structure will guide investment decisions and partnership strategies.
Speaker: Rahul Garg
What mechanisms can help Indian startups transition from domestic focus to global platforms, especially regarding capital and market access?
Scaling globally is necessary for India to be a top AI/app developer; identifying pathways will inform policy and investor support.
Speaker: Rahul Garg
How can massive skilling and reskilling programs (e.g., NASCOM’s Future Skill Prime) be measured for effectiveness in meeting future AI job demands?
Evaluating program outcomes ensures that talent pipelines align with industry needs and reduce skill gaps.
Speaker: Vivek Kumar Singh
How can sustainability be embedded as a core design principle in semiconductor and AI hardware development, with clear metrics and accountability?
Integrating sustainability is essential to meet climate goals while maintaining competitive technology development.
Speaker: Audience (moderator)
What data is needed to assess the environmental impact of AI compute infrastructure in India and what mitigation pathways should be pursued?
Quantifying impact will enable targeted policies and industry practices for greener AI deployment.
Speaker: Audience (moderator)
What public‑private de‑risking mechanisms can be employed without direct subsidies to stimulate private sector investment in AI and semiconductor R&D?
Designing effective de‑risking tools will attract private capital while preserving fiscal responsibility.
Speaker: Thomas Zacharia
Which ‘lighthouse’ or grand‑challenge problems should be prioritized under India’s Genesis‑style initiative to maximize AI and semiconductor breakthroughs?
Focusing on high‑impact challenges ensures efficient use of resources and accelerates breakthrough innovations.
Speaker: Thomas Zacharia
How do recent ease‑of‑doing‑business reforms affect the translation of university research into marketable products in India?
Assessing policy impact will reveal bottlenecks and opportunities for improving the innovation pipeline.
Speaker: Vivek Kumar Singh
What are the requirements and timeline for India to establish a national supercomputing mission comparable to those in the US and China?
A clear plan is needed to build world‑class compute infrastructure that underpins AI research and industrial applications.
Speaker: Thomas Zacharia

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