Keynote by Vivek Mahajan CTO Fujitsu India AI Impact Summit

20 Feb 2026 16:00h - 17:00h

Session at a glance

Summary

Vivek Mahajan from Fujitsu delivered a presentation focused on AI sovereignty and how his company is positioning itself to provide sovereign AI solutions, particularly for countries like India seeking independence in AI technology. He defined sovereignty as having flexibility, security, ownership of data, and the ability to control and modify AI models without overwhelming reliance on third parties. Mahajan emphasized that Fujitsu, with its 90-year history of technological innovation, offers a Japanese alternative to American technology companies for organizations requiring privacy and security in sectors like defense, government, healthcare, manufacturing, and finance.

The presentation outlined Fujitsu’s comprehensive approach built on three key pillars: software, compute, and networks. In computing, Fujitsu is developing the world’s first 2-nanometer ARM-based servers powered by their Monaca chip, with plans for a 20 exascale AI supercomputer and future 1.4-nanometer processors featuring NPUs for AI inferencing. The company is also heavily invested in quantum computing, announcing a roadmap for 250 logical qubits by 2030 and planning to integrate quantum and HPC systems for mission-critical AI workloads. Their networking solutions include 1.6 terabyte photonic switches and wireless systems designed for power efficiency and long-range transmission.

Fujitsu’s AI software stack, called Takane, focuses on domain-specific models that can be fine-tuned for specific enterprise needs while maintaining high security standards. The company envisions convergence in physical AI platforms through their Kozuchi physical OS, targeting applications in robotics, drones, and medical devices. Mahajan concluded by highlighting strategic partnerships with companies like NVIDIA, AMD, and Lockheed Martin to deliver complete sovereign AI solutions from compute infrastructure to end-user applications.

Keypoints

Major Discussion Points:

– AI Sovereignty and Independence: Vivek Mahajan emphasized the critical importance of technological sovereignty for countries like India, defining it as having ownership and control over data, flexibility to manage and modify AI models, and reduced reliance on third-party solutions.

– Fujitsu’s Computing Infrastructure: Detailed presentation of Fujitsu’s advanced hardware solutions, including their 2-nanometer ARM-based Monaco servers, upcoming 1.4-nanometer processors with NPUs for AI inferencing, and plans for a 20 exascale AI supercomputer powered by Japanese-made technology.

– Quantum Computing Leadership: Discussion of Fujitsu’s ambitious quantum computing roadmap, including plans for 250 logical qubits by 2030, a 10,000-qubit machine in three years, and integration of quantum computing with HPC for mission-critical AI workloads.

– Complete Technology Stack Integration: Presentation of Fujitsu’s comprehensive approach combining three pillars – software (open-source AI stack), compute (processors and quantum), and networks (photonics and wireless solutions) – to provide end-to-end sovereign AI solutions.

– Physical AI and Future Applications: Vision for convergence toward physical AI platforms, including the Kozuchi physical OS for robotics with persistent memory capabilities, and partnerships with companies like NVIDIA, AMD, and Lockheed Martin for various applications from defense to healthcare.

Overall Purpose:

The discussion served as a corporate presentation by Fujitsu to showcase their comprehensive AI sovereignty solutions, positioning the company as an alternative to American technology providers for countries and organizations seeking independence in AI infrastructure, particularly in sensitive sectors like defense, government, and healthcare.

Overall Tone:

The tone was consistently professional and promotional throughout, with Mahajan delivering a confident, sales-oriented presentation highlighting Fujitsu’s technological capabilities and competitive advantages. The tone remained formal and informative, focused on establishing credibility through technical specifications and partnership announcements, without any significant shifts in mood or approach during the presentation.

Speakers

– Vivek Mahajan: Discussed AI commerce and sovereignty, representing Fujitsu. Focused on sovereign AI solutions, computing technology, quantum systems, and AI platforms.

– Moderator: Session moderator who introduced speakers and managed the event flow.

Additional speakers:

– Vivek Kaneja: Executive Director, CDAT (mentioned for upcoming fireside chat session)

– Nitin Bajaj: Director, Sales and Marketing, Intel (mentioned for upcoming fireside chat session)

– Aman Khanna: Vice President of the Asia Group (mentioned as moderator for upcoming fireside chat session)

Full session report

Vivek Mahajan from Fujitsu delivered a presentation on AI sovereignty at what appears to be an India-focused technology conference, positioning his company as an alternative for nations and organizations seeking technological independence in artificial intelligence.

Defining AI Sovereignty

Mahajan defined AI sovereignty as the combination of flexibility and security, emphasizing the need for organizations to maintain ownership and control over their data while possessing the capability to modify and tune AI models without overwhelming dependence on third-party providers. He positioned this as particularly relevant for sensitive applications in defense, government, healthcare, manufacturing, and finance sectors.

Mahajan highlighted Fujitsu’s position as a Japanese technology company with a 90-year history, suggesting this provides a trusted alternative for organizations seeking independence from dominant market players. He specifically mentioned opportunities for American companies and other international clients seeking alternatives to traditional suppliers.

Three-Pillar Technology Approach

Central to Mahajan’s presentation was Fujitsu’s integrated approach built upon three fundamental pillars: software, compute, and networks. He argued that effective AI implementation requires all three components working together, and that true sovereignty demands independence across each area.

Computing Infrastructure

In the computing domain, Mahajan detailed Fujitsu’s hardware roadmap, beginning with their 2-nanometer ARM-based servers powered by the Fujitsu Monaco chip. These servers, scheduled for initial deployment within two months of the presentation, feature confidential computing capabilities built into the hardware architecture. He also mentioned plans for what he described as “20 AI exascale AI supercomputer” to be operational within two years, though the transcript is unclear on the exact specifications.

Looking ahead, Fujitsu’s roadmap includes 1.4-nanometer processors in two configurations: a 256-core CPU variant and a 128-core CPU with integrated Neural Processing Unit (NPU) for AI inferencing applications. Mahajan emphasized the growing importance of local inferencing using smaller, domain-specific language models rather than relying on cloud-based large language models.

Quantum Computing Initiatives

Mahajan positioned Fujitsu among the top quantum computing companies globally, with a roadmap targeting 250 logical qubits by 2030. He mentioned near-term milestones including a 1,000-qubit machine scheduled to go live in Kawasaki, Japan, within a month of the presentation, and a 10,000-qubit system planned within three years.

The quantum strategy involves integrating quantum systems with high-performance computing infrastructure for AI workloads, creating hybrid computational approaches accessible through transparent software stacks.

Networking Capabilities

Mahajan discussed Fujitsu’s networking solutions, though portions of this section were unclear due to transcript quality issues. He mentioned the company’s capabilities in both photonics and wireless technologies, including switches designed for power efficiency and long-range transmission. He specifically noted the relevance of power-efficient solutions for data center deployments in regions like India where power consumption is a critical constraint.

Software Platform

The software component centers on Fujitsu’s Takane large language model platform and Kozuchi AI agent technology. Mahajan emphasized that their software stack maintains openness to avoid vendor lock-in while providing optimization for AI, data center, and HPC workloads. This approach allows organizations to fine-tune models for specific requirements, particularly in sensitive applications where data cannot be deployed on public clouds, such as nuclear plant operations and healthcare applications.

Physical AI and Future Applications

Mahajan outlined Fujitsu’s vision for physical AI through their Kozuchi physical OS development, addressing the convergence of AI with edge devices including robots, drones, and medical devices. He specifically mentioned addressing memory retention challenges in robotic systems where robots lose learned behaviors over time.

Strategic Partnerships

Throughout the presentation, Mahajan emphasized partnerships with major technology companies including NVIDIA, AMD, and Lockheed Martin. He highlighted a partnership with NVIDIA announced in October, featuring a joint appearance by Fujitsu’s CEO and Jensen Huang, focused on physical AI applications and robotics manufacturing.

Market Positioning and Conclusion

Mahajan’s presentation positioned Fujitsu as addressing growing concerns about technological dependence and data sovereignty affecting governments and enterprises worldwide. The emphasis on domain-specific applications and local inferencing capabilities suggests an approach where sovereignty and performance can coexist through innovative architectures and integrated system design.

The presentation was part of a larger conference program and was concluded by the moderator transitioning to the next session. While some technical details were unclear due to transcript quality issues, Mahajan’s systematic approach demonstrated how Fujitsu aims to provide concrete solutions for organizations seeking AI independence while maintaining access to advanced capabilities.

Session transcript

Vivek Mahajan

AI commerce. What I’m going to talk about is something that was discussed in the plenary session yesterday as well about sovereignty. And I believe something like sovereignty is very, very important for countries like India, which are trying to eke out a path in leading AI and being dominant in AI. Now, what is sovereignty, first of all? For us, it is being flexible. And being secure, right? So you want ownership of your data. You want to control that data. But you also want to have flexibility to manage that data, create models that meet your needs, that doesn’t have to be reliant on third party overwhelmingly. And you can modify and tune that data, right? Modify and tune those models.

So Fujitsu is on a path to – we’ve always been an innovative company, and we have a long history, and I’ll talk briefly. But how do we make that sovereign? And that’s what I’m going to talk about today. So Fujitsu, some of you might not know it. I mean, we have a 90 -year -old history, right? So we are a pretty old company. We have our roots all the way in technology. And if you look at some of the things that are demonstrated here, one megabit DRAM, for example, right? Of course, we were one of the pioneers of mainframe business along with IBM. In recent past, we’ve announced, which we will be shipping very shortly, the world’s first two nanometer servers, ARM -based servers.

We announced for quantum, if you are not aware, which I will be talking about shortly as well, we have the world’s leading quantum roadmap here that we are going to deliver. Same on networks. And our U.S. brand that we created in 2021, that effectively brings all of Fujitsu’s solutions. to be consumed by our customers. Now, how does this work in the context of AI? And why is this relevant in the context of AI? And that’s what I’m going to talk about. So, to effectively drive artificial intelligence, you need three key components, right? You obviously need software, you need compute, and you need three networks, right? If you don’t have those three, you can’t really build an AI platform that will suit your enterprise needs.

And our focus on sovereignty here is really being independent in all of these three areas and give customers a choice. We are a Japanese company. Our technology is made in Japan and that’s where we find ourselves at a very interesting point because we are a choice to a lot of American companies as an alternative. So if you’re looking for leading edge computing technology, leading edge quantum technology, leading edge network technology, leading edge AI software technology, agentic technology, and there’s an end user application on which you can build an AI platform in the area such as defense, government, healthcare, manufacturing, finance, where you do care about privacy, this becomes very, very important. Now how do we actually drive that?

Some of the speakers talked about commerce, which are big, but at the end of the day, if you don’t have a platform that helps you deliver that, you’re never going to be sovereign, you’re never going to control the AI business. Fujitsu has a couple of areas that we are focused on, as I mentioned, computing. If you think about CPUs, you think about AMD, you think about Intel, we were, until two years ago, we had the fastest supercomputer in the world for five years running. And we announced that we will be building a 20 AI exascale AI supercomputer in about two years from now, which will be driving pretty much AI application, AI workloads. This will be powered by our Fujitsu Monaca chip, which is a two nanometer chip.

It’s built in Japan, and it is completely ARM -based, highly power efficient, focused on data centers to reduce power efficiency. Okay, and it has confidential computing built at the hardware level to drive security. Now, this comes out, the servers come out in about two months from now, the test servers. It’s ARM -based. The follow -up of this is a 1 .4 nanometer, and that will also be the world’s first 1 .4 nanometer, which has two versions, 256 -core CPU plus 128 -core CPU plus an NPU to drive exactly what India needs, sovereign AI models focused on inferencing. And this is something that I believe we will drive a lot of value in countries like India as well as Europe.

I’m not going to go into this in detail, but this stack is a completely open software stack. I just want you to remember, it’s a completely open software stack. There’s nothing locked in. There’s nothing. You don’t get locked into a Fujitsu stack. All the software that you see here, it’s completely open. It’s focused on AI. It’s focused on data centers, and it’s focused on HPC. This is what you need for AI, right? All the key areas are a lot of open source software that we have fine -tuned to work on this process. This can help you drive your AI workloads today on the Monaco servers. As I mentioned, what’s coming? There are two versions, the 256 -core CPU plus 128 -core CPU with the NPU on it.

The NPU is focused on AI inferencing. You will see a lot of work going into inferencing moving forward. And especially when you talk about sovereign, this will become extremely important, especially with small language models and medium language models. So you can contain that in a private or a semi -private environment that you can choose. Obviously, if you want large language models, you can choose what is going on on GPUs. And you can obviously choose the Monaco GPU hybrid architecture as well. Now, for those of you who might not be aware, we are extremely highly invested in quantum. We need quantum in Japan. I would say we are probably one of the top three players in quantum worldwide.

We have announced a 250 logical qubit roadmap by the end of 2030, which is ahead of any other company in the world that I know of. We make our own control systems. We are going to focus on driving the cooling systems as well. And this is going to become extremely important as you go ahead. Quantum plus HPC together driving mission -critical AI workloads. The 10 ,000 -qubit machine will go live in about three years from now. Next month, the 1 ,000 -qubit machine goes live in Kawasaki, Japan. As I mentioned, you would have HPC and Quantum working together to drive AI workloads. This is how computing will be consumed moving forward. And the software stack that we are working on, it will make transparent to you and users to use to consume compute and the workload can be optimized to whichever computer you want.

Now, I’ll briefly talk about the networks because that’s the other part of the puzzle. And finally, I’ll talk about the software for AI. photonics and wireless we’re one of the probably want two companies that does both no cares another one right and we are doing a 1 .6 terabyte switch that travels that is highly power efficient that drives about a thousand kilometer this distance distance on this long range transmission low latency low power consumption that’s the beauty of the switch right and and we are we will go on to 3 .2 tera this is very strong implicate implications and data centers that are being built in India as that would be highly highly power hungry and you would need to connect that through optical fibers and same with the wireless mobile systems okay now what we do is we also connect with open RAN and the network orchestration stack to bring the AI workloads move them in a highly efficient manner and we’re going to do that by using the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the RAN and the This is the third part that really brings everything together, the AI software stack.

Fujitsu, as I mentioned at the very beginning, we are focused on sovereign. When we talk about sovereign, it’s got to be domain specific, something for defense. If you’re making nuclear plants or submarines or healthcare, this is not the data you want to put on public cloud. You want to define and build these domain specific models. Second, you need to have flexibility. You, as a company, should be able to fine tune these models to your own benefit, to your own needs. They need to be highly secure. These are the three key areas that we are focused on using what we call our Takane, the large language model platform, as well as our AI agent tech model from Kozuchi, powered by the security platform that we have built within our own research teams.

It’s a complete platform that you can use to build your own applications. Thank you. Again, I won’t go into details on this. but this is a platform that also uses third -party tools and you see on the extreme right where we have issue with their government manufacturing health care finance applications so Fujitsu has a fairly large business and services which brings all of this together so we are not just selling you pieces of technology we are selling your total solution or we are asking you to use a total solution here from compute all the way to networks and the application stack together and this is our vision that we want to continue to build on this continue to bring this to other to the end customers as well as users now where are we headed right we see all this converge in the physical AI platform space and what we are building is Kozuchi physical OS which will have the intelligence based on the brain intelligence for the robot and what that means is robots tend to forget And what we are working on, some intelligence work and research so that robots can continue to remember.

But then this technology, the compute networks, as well as the AI platform stack, comes together in edge devices. Robots are one example, but even drones or medical devices or your healthcare on your iPhones. That’s where it will all come together. And that’s the world we are aiming for. That will bring together the AI agentic platform together. That will bring the security platform together in the complete platform that could be consumed for our end users, our companies. And you can choose to play in a part that is comfortable for you. And we are obviously going to partner with a lot of different companies on this. So, as I mentioned, the software, compute, network, the three pillars.

And we are going to be able to do that. We announced in October last year, our CEO Tokita and Jensen were on stage together announcing a huge partnership on physical AI, where we’re partnering with different robotics manufacturers. So it’s working with AMD, working in defense with Lockheed Martin, Supermicro. So this is something

Moderator

Thank you. Thank you so much. For the next session, we have a fireside chat between Mr. Vivek Kaneja, Executive Director, CDAT, Mr. Nitin Bajaj, Director, Sales and Marketing, Intel, and the session will be moderated by Mr. Aman Khanna, Vice President of the Asia Group. May I request all the speakers to join us on the stage, please? I also request everybody to please clear the pathway. May I request the audience to please clear the pathway?

Vivek Mahajan

Speech speed

157 words per minute

Speech length

Vision of integrated physical AI across edge devices

Topics

Artificial intelligence | The enabling environment for digital development

Moderator

Speech speed

102 words per minute

Speech length

Session framing and participant introduction

Topics

The enabling environment for digital development | Capacity development

Agreements

Agreement points

Similar viewpoints

Unexpected consensus

Overall assessment

Summary

This transcript represents a single-speaker presentation by Vivek Mahajan from Fujitsu, with only a brief moderator transition at the end. There are no areas of agreement, similar viewpoints, or consensus points to identify since only one substantive speaker presented arguments.

Consensus level

No consensus analysis possible – this is a monologue presentation rather than a multi-speaker discussion or debate. The content focuses on Fujitsu’s technological capabilities and vision for AI sovereignty, but lacks the multi-perspective dialogue necessary for consensus analysis.

Differences

Different viewpoints

Unexpected differences

Overall assessment

Summary

No disagreements identified in the transcript

Disagreement level

The transcript contains only a single speaker (Vivek Mahajan) presenting Fujitsu’s AI sovereignty solutions without any opposing viewpoints or debate. The moderator’s brief interjection is purely procedural, introducing the next session. This represents a presentation format rather than a discussion or debate, making disagreement analysis not applicable to this content.

Partial agreements

Similar viewpoints

Takeaways

Key takeaways

AI sovereignty requires three core components working together: software, compute, and networks, with emphasis on data ownership, control, and flexibility without over-reliance on third parties

Fujitsu positions itself as a Japanese alternative to American technology suppliers, offering 90 years of innovation including world-first 2-nanometer ARM-based processors and leading quantum computing capabilities

Domain-specific AI models are essential for sensitive sectors like defense, healthcare, and nuclear applications that cannot rely on public cloud infrastructure

The future of AI computing will integrate quantum and HPC systems working together, with Fujitsu planning a 250 logical qubit roadmap by 2030

Physical AI represents the convergence point where computing, networking, and AI software stack come together in edge devices like robots, drones, and medical devices

Open software architecture without vendor lock-in is crucial for maintaining sovereignty and flexibility in AI implementations

Resolutions and action items

Fujitsu will ship world’s first 2-nanometer servers in approximately two months

20 AI exascale supercomputer to be built within two years powered by Fujitsu Monaca chip

1,000-qubit quantum machine will go live next month in Kawasaki, Japan

10,000-qubit quantum machine scheduled to launch in three years

Continue building partnerships with NVIDIA, AMD, Lockheed Martin, and robotics manufacturers for comprehensive AI solutions

Unresolved issues

Specific implementation details for how the open software stack will integrate across different customer environments

Detailed technical specifications and performance benchmarks for the upcoming quantum-HPC hybrid systems

Pricing and availability models for the sovereign AI solutions in different markets including India and Europe

Specific use cases and deployment strategies for the Kozuchi physical OS in real-world applications

How the transition from current systems to the new 1.4-nanometer processors will be managed for existing customers

Suggested compromises

Offering flexible platform choices where customers can select components that suit their comfort level rather than requiring full stack adoption

This comment crystallizes the practical implications of AI sovereignty by providing concrete examples of sensitive applications. It’s insightful because it moves beyond theoretical discussions to identify specific use cases where sovereignty isn’t just preferable but essential for security and compliance reasons.

Impact

This comment grounds the entire technical discussion in real-world applications and security concerns. It explains why organizations would choose Fujitsu’s more complex, integrated approach over simpler cloud-based solutions, providing the business justification for their sovereignty-focused strategy.

Overall assessment

Explanation

Mahajan mentioned power-efficient 1.6 terabyte switches and their importance for power-hungry data centers in India, but specific efficiency metrics and cost-benefit analysis were not provided

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.