Building Trusted AI at Scale Cities Startups & Digital Sovereignty – Keynote Kiran Mazumdar-Shaw
20 Feb 2026 12:00h - 13:00h
Building Trusted AI at Scale Cities Startups & Digital Sovereignty – Keynote Kiran Mazumdar-Shaw
Summary
The Impact AI Summit opened with Kiran Mazumdar-Shaw framing the keynote around “biotech sovereignty embedded in AI” as a new strategic priority for India [2]. She argued that just as the 20th century was defined by the Internet and the early 21st by digital data sovereignty, the coming decades will be shaped by the convergence of biological and artificial intelligence, which she terms biotech sovereignty [4-5]. Mazumdar-Shaw stressed that mastering this convergence is not merely an opportunity but a geopolitical imperative for the nation [6-8].
She described biological intelligence as the product of 3.8 billion years of evolution, where living cells sense, compute, and respond through complex signaling networks and built-in guardrails that maintain homeostasis [9-16]. Using the immune system as an example, she showed how memory T and B cells store pathogen information and rapidly mobilise a response upon re-exposure, illustrating efficient information processing without massive energy consumption [19-24]. By contrast, conventional AI learns from data at machine scale, and the true inflection point lies at the intersection of AI and biology, enabling applications such as protein-structure prediction and generative drug design [33-36].
She highlighted the next frontier of reprogramming cells-turning cancer cells benign or repairing bone tissue-contingent on a deep understanding of cellular signalling, gene regulation, and immune memory [38-43]. Mazumdar-Shaw warned that reliance on offshore foundational AI models for drug discovery and genomics would create strategic dependence, making sovereign control over biological data, AI models, and computing infrastructure essential for national resilience [54-57]. She called for embedding AI across the entire biotech value chain-from foundation models for proteins and cellular circuits to in-silico trials, digital twins, and AI-driven manufacturing-to accelerate discovery, reduce risk, and ensure regulatory processes keep pace [60-66].
Achieving this transformation, she said, requires a “triple helix” of government investment in sovereign AI bio-infrastructure, academia’s rollout of computational biology and AI-first curricula, and industry’s co-creation of shared platforms and scalable biomanufacturing clusters [71-77]. Ethical, transparent, energy-efficient, and bias-aware AI systems must be built to be globally interoperable yet rooted in public interest, allowing India to offer a model that blends technological leadership with equity and access [81-86]. She concluded that biotech sovereignty is a foundation of health security, strategic autonomy, and economic resilience, and that India possesses the scientific talent, AI expertise, scale, and values to lead if it builds sovereign platforms today [88-90].
Overall, the keynote positioned AI-enabled biotechnology as a decisive lever for India’s future global standing and public-health security [2][5][88-90].
Keypoints
– Biotech sovereignty powered by AI is a strategic and geopolitical imperative for India.
Mazumdar-Shaw argues that the next decade will be defined by “biotech sovereignty that is embedded in AI” and that nations mastering the convergence of biology and AI will shape critical sectors such as health, food security, and bio-security [4-5][6-8]. She stresses that reliance on offshore AI models for drug discovery and genomics creates strategic dependence, making sovereign control over data, AI models, and translational platforms essential for national resilience [54-58][87-90].
– Understanding “biological intelligence” reveals why AI-biology convergence is transformative.
She describes living systems as “the original intelligent machines,” highlighting their billions-year evolution, multimodal learning, memory, and energy-efficient computation [9-13][14-17]. Examples such as the immune system’s rapid recall of pathogens [19-23] and the Arctic tern’s DNA-encoded navigation [29-33] illustrate how biology processes, stores, and retrieves information far more efficiently than conventional data centers [24-28]. This biological intelligence, when paired with AI, can accelerate protein folding, generative drug design, and ultimately enable re-programming of cells for therapies [36-38][40-44][46-48][50-52].
– A concrete AI-enabled roadmap across the biotech value chain is needed.
She outlines actions for each stage:
• Discovery: develop foundation models for proteins, RNA, cellular circuits, and systems biology [62-63].
• Development: create in-silico trials, digital twins, and AI-driven trial design to de-risk pipelines [63-64].
• Manufacturing: implement smart biomanufacturing for yield optimization and “quality by design” [64-66].
• Regulation: build AI-augmented, science-first regulatory pathways that integrate real-world evidence [66-70].
She warns that without synchronized regulatory speed, the accelerated discovery timeline will be wasted [69-71].
– Realizing this vision requires a “triple-helix” collaboration and supportive ecosystem.
Government must invest in sovereign AI-bio infrastructure, trusted data architectures, and mission-mode programs [74]; academia should mainstream computational biology and AI-first life-science education to create a new cadre of translational scientists [75]; industry must co-create shared platforms and globally benchmarked biomanufacturing clusters [76]. Capital markets need to provide patient capital for long-cycle biotech innovation, delivering exponential societal and economic returns [77-80].
– Ethical, equitable, and globally interoperable AI is central to India’s leadership model.
Sovereignty is framed not as isolation but as building transparent, energy-efficient, bias-aware AI systems rooted in public interest [81-84]. By embedding equity, affordability, and access into AI-driven biotech, India can offer a “new model of innovation combining technological leadership with social purpose” [85-86], positioning itself as a global public-good provider in health security and economic resilience [88-90].
Overall purpose:
The discussion is a persuasive call to action for India to establish a sovereign, AI-native biotechnology ecosystem. It explains why the convergence of biological intelligence and artificial intelligence is critical, outlines the technical and policy steps required across the entire biotech value chain, and frames the effort as essential for national health security, strategic autonomy, and global leadership.
Overall tone:
The speaker begins with an enthusiastic, visionary tone, celebrating the AI summit and the promise of a new era [2-5]. She then shifts to an explanatory, scientific tone to demystify biological intelligence [9-34]. This transitions into a pragmatic, urgent call-to-action, detailing concrete roadmap items and emphasizing the need for coordinated government, academia, and industry effort [62-71][72-77]. The closing returns to an inspirational, hopeful tone, emphasizing ethical leadership and India’s capacity to lead the world [81-90]. Throughout, the tone remains confident and forward-looking, moving from description to urgency to inspiration.
Speakers
– Kiran Mazumdar-Shaw
– Role/Title: Chairperson, Biocon Group; Keynote speaker
– Areas of Expertise: Biotechnology entrepreneurship, healthcare innovation, AI-enabled biotech, philanthropy in health access
– Citation: [S1]
– Speaker 1
– Role/Title: Event moderator/host (role not specified)
– Areas of Expertise: (not specified)
– Citation: [S4]
Additional speakers:
(none identified beyond the listed speakers)
The Impact AI Summit opened with a brief welcome that invited the audience to applaud Ms Kiran Mazumdar-Shaw, Chairperson of the Biocon Group, before she began her keynote address [1]. She expressed enthusiasm for the inaugural summit, noting that India’s first-ever Impact AI Summit signalled the nation’s entry onto the global AI journey [2-3].
Mazumdar-Shaw framed her talk around biotech sovereignty, drawing a historical analogy: the 20th century was defined by the Internet, the early 21st century by digital data sovereignty, and the coming decades will be shaped by the convergence of biology and artificial intelligence [4-5]. She argued that this convergence is a strategic and geopolitical imperative for India, essential for future dominance in health, food security, bio-security and related sectors [6-8]. She warned that continued reliance on offshore AI models for drug discovery and genomics would create a strategic vulnerability; sovereign control over trusted biological data, indigenous AI models and computing infrastructure is therefore a matter of national resilience [54-58].
To illustrate why such sovereignty is needed, Mazumdar-Shaw described biological intelligence as the original form of intelligent machinery, evolved over 3.8 billion years and capable of multimodal learning, memory and ultra-efficient computation [9-13]. Living cells sense, compute and respond through signalling networks, gene-regulatory circuits and immune memory, all operating within built-in homeostasis guardrails [14-17]. When these guardrails fail, disease emerges, showing how biology embeds its own ethics and governance in the pursuit of health [18-24].
She gave two vivid examples of this natural efficiency. First, the immune system’s coordinated use of cytokines, antibodies, killer T-cells and memory T-/ B-cells enables rapid recall of pathogen information and instant action on re-exposure [19-23]. Second, the Arctic tern’s 70 000-km migration-performed without prior learning or guidance-demonstrates DNA-encoded navigational intelligence [29-33]. Both cases show that biological systems process, store and retrieve information with energy consumption far lower than conventional data-centre AI, which relies on gigawatts of power; biology instead uses distributed “data centres” that sip energy only when needed, exemplified by the human brain’s super-computing capability [25-28].
The inflection point lies at the intersection of this biological intelligence and artificial intelligence [33-36]. AI-powered biology already accelerates discovery through protein-structure prediction, generative drug design and the creation of digital twins-AI-generated virtual replicas of cells and organs used for simulation-compressing timelines and reducing development risk [36-38]. Looking ahead, she envisioned a new frontier of programmable biology, where deep understanding of cell signalling, gene regulation and immune memory could enable the reprogramming of cancer cells into benign forms or the repair of otherwise irreparable bone tissue [39-44]. She linked this vision to personalised CAR-T therapies, autoimmune-disease interventions and longevity research that seeks to modulate senescence, metabolic ageing pathways and tissue-repair mechanisms, potentially extending human health-span by decades [46-48][49-52].
Realising these breakthroughs, however, requires sovereign AI-bio infrastructure. Mazumdar-Shaw stressed that if foundational AI models for drug discovery, genomics and cellular engineering remain owned abroad, India would face strategic dependence in the most critical domain of national resilience-human health [54-58]. Sovereign control over trusted biological data, indigenous AI models, compute resources and translational platforms is therefore essential for both economic competitiveness and preparedness against pandemics, antimicrobial resistance and emerging bio-threats [55-57].
She then laid out a concrete road-map across the biotech value chain. In discovery, India must develop foundation models-large-scale AI models trained on biological data-for proteins, RNA, cellular circuits and systems biology [62-66]. In development, AI can enable in-silico trials, digital twins and AI-optimised trial design to de-risk pipelines and boost probability of success [63-64]. In manufacturing, smart biomanufacturing driven by AI should optimise yield, implement “quality-by-design” and integrate real-world evidence into regulatory decisions [64-66]. Crucially, she emphasized the need to develop a system of biomanufacturing and also a system of biotech regulation that can keep pace with accelerated science [64-66]. She added that AI can map these regulatory circuits at scale, enabling target interventions that preserve homeostasis [33-36]. She also clarified that AI alone will not create economic opportunities; the delivery of AI through manufacturing and products will [71-77].
Achieving this transformation cannot rely on industry alone. Mazumdar-Shaw called for a triple-helix collaboration among government, academia, industry and capital markets [71-77]. The government should invest in sovereign AI-bio infrastructure, trusted data architectures, regulatory sandboxes and mission-mode programmes in cell-gene therapy, immuno-oncology and longevity [74]. Academia must mainstream computational biology, neurosymbolic AI and AI-first life-science curricula to create a new cadre of translational scientists [75]. Industry is tasked with co-creating shared platforms, translational pipelines and globally benchmarked biomanufacturing clusters that can scale discoveries [76]. Capital markets must provide patient, long-term financing for high-risk biotech innovation, delivering exponential societal and economic returns [77-80].
Ethical considerations were positioned as central to India’s leadership model. Mazumdar-Shaw clarified that sovereignty does not mean isolation; instead, India should build AI systems that are transparent, energy-efficient, bias-aware and globally interoperable, yet rooted in the public interest [81-86]. By embedding equity, affordability and access into AI-driven biotech, India can present its outputs as global public goods [85-86].
In conclusion, Mazumdar-Shaw asserted that biotech sovereignty is the foundation of health security, strategic autonomy and economic resilience; nations that master the language of life augmented by the language of machines will shape humanity’s future, and India possesses the scientific talent, AI expertise, scale and values to lead-provided it builds sovereign platforms today [88-91].
Ladies and gentlemen, please put your hands together to welcome Ms. Kiran Mazumdar -Shaw, Chairperson, Biocon Group.
Good afternoon, and let me say how delighted I am to be a part of this wonderful summit, the Impact AI Summit that India… is launching and hosting for the first time, which I think heralds a big signal that we are part of the AI journey that the world is on. I’ve basically taken off from where the last panel talked about sovereignty, and I thought I should talk about why India must build biotech sovereignty that is embedded in AI. And let me start with this first slide that basically says that if the 20th century was defined by the Internet and the early 21st century by digital sovereignty, which was all about data being the new oil and the new fuel, the coming decades, I believe, will be…
…be shaped by… biotech sovereignty that is embedded in AI. I believe that nations that command the convergence of biology and AI, or what I like to call the convergence of biological intelligence and artificial intelligence, will define the future of healthcare, food security, education, biomanufacturing, sustainability, biosecurity, and much more. For India, this is not merely a cutting -edge opportunity. It is a strategic and geopolitical imperative. Now, let me really touch upon what I mean by biological intelligence. Living systems are the original intelligent machines. And why do I say this? Because biological intelligence has evolved and has been built over 3 .8 billion years. It is different in the way it learns, memorizes, builds and processes information from multimodal signals and circuits.
Cells sense, they compute and they respond through intricate signaling networks. They also then interface with gene regulation and gene regulatory circuits and immune memory. These systems operate within inbuilt biological guardrails, which form a network of cells that are connected to each other. They focus on feedback loops and control mechanisms that maintain what we refer to as homeostasis. or health equilibrium. Disease arises when these guardrails fail. So when we talk about ethics, when we talk about governance, living systems have an inbuilt sense of guardrails and governance, which is about keeping you healthy, which is about homeostasis, which is a wonderful way of making sure that it compensates, it repairs and makes sure that you can still live in a health as healthier way as possible.
And to illustrate this, let’s look at the way our immune system responds to pathogens. The immune system responds through immunological ammunition like cytokines, antibodies and killer T cells. It also memorizes the identity of the pathogen in memory T cells and B cells. And years later, when the pathogen reinvades, the memory cells rapidly retrieve this information and translate it into instant action. This is the marvels of biology in the way it receives information, processes information, stores information, retrieves information and acts. And the inference of all this information is done at speed and with energy efficiency that we can’t even imagine. We don’t need those gigawatts of data centers. We have distributed data centers that take sips of energy when it needs to use it.
Our brain, which is the biggest supercomputer known to man, does this. So efficiently that we need to understand how biology works. Another great thought -provoking example of biological intelligence is the migration of the Arctic tern. This little bird, that is the size of a tennis ball, undertakes a 70 ,000 -kilometer journey between the Arctic, the Antarctic and back with no prior knowledge, with no older bird to guide it, and yet it does it with astonishing precision and speed. How does it do it? This is about navigational intelligence embedded in its DNA. AI, by contrast, learns from data to optimize decisions at machine scale. So therefore, the true… The true inflection point lies at their intersection. AI -powered biology…
from protein structure prediction and generative drug design to digital twins of cells and organs. AI is compressing discovery timelines and reducing development risk. And therefore, I believe that the next frontier is even more profound. The reprogramming of cells themselves to restore biological balance. But for this, we need to understand how biological intelligence operates. Imagine reprogramming cancer cells into non -malignant cells. Imagine repairing bone tissue that is damaged and irreparable. Biological intelligence is built on an intricate network of cell signaling, gene regulation and immune memory that works symbiotically, as I mentioned, to maintain homogenization. And so, we need to understand how biological intelligence operates. And so, we need to understand how biological intelligence operates. And so, we need to understand how biological intelligence operates.
now if we now come to what i’ve just spoken about which is reprogramming and re -engineering we are moving from static one -size -fits -all drugs to programmable biology which is the new frontier we need to learn how biology learns stores data retrieves and processes data in such an agile and energy efficient way once we understand the computational models of living systems we can use ai to accelerate with predictive precision the most advanced present -day therapies today we are all excited about personalized carti therapies that basically eliminate tumors with precision autoimmune disease interventions that are used to eliminate tumors with precision that recalibrate immune tolerance rather than broadly suppressing immunity And then the most exciting part of longevity and health span.
These are areas where we must understand how senescence is modulated, metabolic pathways of aging are created and cellular repair mechanisms to delay biological aging and restore tissue resilience happens. If we understand all this, as the last speaker said, we may be able to live for another 50 years and more. Flucially, these approaches seek not to overpower biology but to reinforce its inbuilt guardrails or regulatory circuits which focus on repair, feedback control and immune surveillance. AI can map these regulatory circuits at scale, enabling target interventions that preserve homeostasis. That is the excitement of new science led by AI, new biology led by AI. This represents a paradigm shift from managing disease to re -engineering biological systems to sustain equilibrium.
So, India’s future health security will depend on how optimally we combine the code of life and the code of intelligence. If foundational AI models for drug discovery, genomics, cellular engineering and clinical decision making are owned offshore, India risks strategic dependence in the market. This is the most critical domain of national resilience, which is human health. Biotech sovereignty embedded in AI must therefore mean sovereign control over trusted biological data. indigenous AI models, computing infrastructure, and translational platforms from discovery and development to manufacturing and delivery. This is essential not only for economic competitiveness, but also for preparedness against pandemics, antimicrobial resistance, and emerging new bio -threats. Now, I really believe this is a very important aspect of what AI can do for biotech and the economy.
AI alone will not create economic opportunities, but the delivery of AI in our field through manufacturing and products will do that. India’s global role must evolve from being the pharmacy of the world, to becoming the biotech platform of the world, a nation that offers AI -native discovery engines programmable therapy platforms and scalable biomanufacturing as global public goods. And this requires embedding AI across the biotech value chain. When it comes to discovery, we need to develop foundation models for proteins, RNA, cellular circuits and systems biology. When it comes to development, I think there are huge opportunities to develop in silico trials, digital twins and AI driven trial design to really de -risk the success of pipelines and probability of success.
When it comes to manufacturing, smart biomanufacturing using AI for yield optimization and most importantly, quality by design is going to be a great opportunity for all of us. Now, when it comes to the biotech value chain, we need to develop a system of biomanufacturing and also a system of biotech regulation. It has to be a science -first approach, tech -enabled regulatory pathways, integrating real -world evidence through AI validation. I think that’s going to be a huge opportunity which we must do right now. What is important is for regulations to keep up with technology. If we compress timelines of discovery and development to a fraction of what happens today, and if regulatory speed does not keep up with it, then we miss out on a huge lost opportunity.
So working in tandem, working in synchronization is the need of the hour. This transformation cannot be driven by industry alone. It demands a triple helix of government, academia and industry. Government, academia and industry. Government must invest in sovereign AI bio -infrastructure. trusted data architectures, regulatory sandboxes, and mission mode programs in cell and gene therapy, immuno -oncology, and longevity science. Academia must mainstream computational biology, neurosymbolic AI, and AI -first life sciences education to build a new cadre of translational scientists. Industry must co -create shared platforms, translational pipelines, and globally benchmarked biomanufacturing clusters that convert science into scale. Capital markets must also evolve to support long -cycle, high -risk biotech innovation that is so rampant in startups in our country.
Deep science requires a lot of research and development. It requires patient capital. But the societal and economic returns from reduced disease burden to global platform leadership are exponential. Now coming to ethics, trust and global leadership. Sovereignty is not isolation. India must build ethical, transparent, energy efficient and bias aware AI systems for biology that are globally interoperable yet rooted in public interest. And I think this is the unique model India can create. By embedding principles of equity, affordability and access into AI driven. AI. AI driven biotech, India can offer the world a new model of innovation combining technological leadership with social purpose. For India, biotech sovereignty embedded in AI is not a sectoral ambition. It is a foundation of health security, strategic autonomy and economic resilience.
Those who master the language of life augmented by the language of machines will shape the future of humanity. India has the science, the AI and life sciences talent, the scale and the values to lead provided it builds the sovereign platforms of tomorrow today. Thank you.
“Kiran Mazumdar‑Shaw is the Chairperson of the Biocon Group.”
The knowledge base identifies Kiran Mazumdar-Shaw as Chairperson of the Biocon Group, confirming her role mentioned in the report [S1].
“Mazumdar‑Shaw framed her talk around “biotech sovereignty” and described it as a strategic and geopolitical imperative for India’s future dominance in health, food security and bio‑security.”
Her vision of biotech sovereignty and its strategic importance for India is echoed in the knowledge base, which highlights her comprehensive view on India’s positioning in global biotechnology leadership and the need for coordinated policy frameworks [S2].
“Reliance on offshore AI models for drug discovery and genomics creates a strategic vulnerability; sovereign control over trusted biological data, indigenous AI models and computing infrastructure is essential for national resilience.”
The knowledge base stresses the sovereignty dimension-control over data, models and security measures-as a core requirement for responsible AI development, aligning with the report’s warning about offshore dependencies [S7] and the three-pillar sovereignty framework (data, infrastructure, talent) [S39].
“India’s AI strategy is built on three pillars of sovereignty: data sovereignty, infrastructure sovereignty, and talent sovereignty.”
While the report mentions biotech sovereignty, the knowledge base provides additional detail on India’s broader AI sovereignty strategy, outlining the three pillars that underpin the country’s approach [S39].
“India’s large human capital pool is central to its global AI strategy.”
The knowledge base notes that India’s talent pool (over 350,000 employees) is viewed as a key asset for global AI initiatives, adding nuance to the report’s emphasis on strategic advantage [S36].
“Biological risks and bio‑security are critical global concerns that require resilient, sovereign capabilities.”
The Global Risks Landscape 2019 highlights the evolving nature of biological risks and the importance of resilient, inward-looking strategies for global health security, supporting the report’s emphasis on bio-security as a strategic priority [S58].
The discussion shows strong internal consensus within Kiran Mazumdar‑Shaw’s remarks: she consistently links AI‑driven biotech sovereignty to strategic security, economic growth, ethical governance and environmental efficiency. The only external agreement is the moderator’s public recognition of her leadership, reinforcing the narrative of national ambition.
High consensus on the core vision (AI‑enabled biotech sovereignty) among the speakers, with broader implications that India’s policy agenda should integrate data sovereignty, ethical AI, and cross‑sectoral AI deployment to achieve strategic autonomy and sustainable development.
The transcript contains only an introductory welcome by Speaker 1 and a comprehensive keynote by Kiran Mazumdar-Shaw. No substantive policy or conceptual conflict is expressed between the two speakers; Speaker 1 merely acknowledges the speaker’s expertise ([1]), while Kiran Mazumdar-Shaw outlines a vision for biotech sovereignty, AI-driven discovery, and related policy actions ([2-91]). Consequently, there is essentially no observable disagreement, and the dialogue is uniformly supportive of the AI-biotech agenda.
Minimal – the interaction is collaborative rather than contentious, implying smooth consensus on the overarching goal of advancing AI‑enabled biotechnology in India.
The discussion was driven by a series of strategically placed, high‑impact statements from Kiran Mazumdar‑Shaw that progressively broadened the conversation—from a historical framing of technological epochs to a deep dive into biological intelligence, then to concrete AI‑enabled biotech applications, and finally to national‑level policy, governance, and ethical considerations. Each thought‑provoking comment acted as a pivot, introducing new dimensions (technical, economic, security, collaborative) and steering the audience toward a holistic vision of ‘biotech sovereignty embedded in AI.’ Collectively, these remarks shaped the dialogue into a compelling call for coordinated, sovereign, yet globally responsible action in the emerging bio‑AI frontier.
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.
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