Keynote-Rishad Premji
19 Feb 2026 12:30h - 12:45h
Keynote-Rishad Premji
Summary
Rishad Premji opened by describing AI as a generational technology that will reshape what societies must do, noting that India’s response will affect its economic trajectory and ability to solve problems for over a billion people [15-18]. He said the AI conversation has moved from speculative possibilities to practical adoption, emphasizing that value arises only when technology is responsibly applied at scale [24-26]. Premji highlighted India’s unique position to become a leading environment for AI deployment, not just as a creator but as a testing ground for real-world challenges [28-31].
He cited the success of UPI, which processes over 20 billion transactions monthly, as proof that inclusive, reliable technology can scale rapidly in India [42-44]. The country also boasts a rapidly growing AI talent pool of about 650 000 professionals, expected to double by 2027, supported by government training initiatives and industry-university partnerships [45-49]. A vibrant deep-tech startup ecosystem, with more than 4 000 AI-focused firms, is translating this capability into applications across sectors such as education, healthcare, and public services [52-54][35-38]. Concrete examples include AI-driven early pest alerts that cut crop losses by up to 25 % and platforms that help artisans automatically catalogue and market products across languages [58-62].
Premji stressed that large enterprises require AI models tightly aligned to specific workflows, which makes systems more predictable, governable, and effective [79-82]. He argued that technology alone is insufficient; organizations must invest in reskilling workers and redesigning roles so people can collaborate with AI responsibly [84-88]. India’s long experience with complex enterprises and its pragmatic governance approach provide a foundation for deploying AI safely while maintaining accountability [64-66][90-92]. The speaker warned that a country’s AI advantage will be defined by the choices it makes about where and how AI is applied, not merely by model size or infrastructure [93-96].
He illustrated this with a pilot in Tamil Nadu where portable X-ray devices and AI enable early tuberculosis screening at home, demonstrating how AI can multiply scarce expertise in health care [104-112]. Premji concluded that solutions built in India-low-cost, multilingual, and resilient-can be exported globally, allowing the nation to contribute significantly to solving problems for enterprises, its own citizens, and the world at large [117-119][120].
Keypoints
Major discussion points
– AI as a generational shift from possibility to practical impact – Premji frames AI as a once-in-a-generation technology that is moving the conversation from “what can it do?” to “how do we apply it at scale responsibly” [15-18][23-26].
– India’s unique strengths that enable large-scale AI adoption – He highlights the country’s proven digital-payments infrastructure (UPI), a rapidly growing AI talent pool, government training programmes, and a vibrant deep-tech startup ecosystem that together create a fertile ground for AI deployment [41-48][49-53][54-60].
– Concrete, sector-specific AI use cases – Examples are given of AI improving learning in local languages, early disease screening, smarter public services, pest-alert systems for farmers, AI-enabled cataloguing for artisans, and a TB-screening pilot that brings portable X-ray analysis to rural homes [35-38][58-62][109-112][113-115].
– Enterprise-level integration and people-centric change – Successful AI rollout requires aligning models with specific workflows, modernising legacy systems, curating data, and, crucially, reskilling staff and redesigning roles so that humans and AI can work together sustainably [75-82][84-88][90-92].
– A call for responsible, inclusive, and globally-impactful AI deployment – Premji stresses that India’s advantage will stem from the choices it makes about where and how AI is applied, emphasizing responsible governance, AI fluency beyond engineers, and the potential to export low-cost, multilingual solutions worldwide [64-66][94-98][118-119].
Overall purpose / goal
The discussion aims to persuade policymakers, business leaders, and the broader public that India is uniquely positioned to lead the next AI era-not merely by building technology, but by deploying it responsibly at scale to solve real-world problems. Premji seeks to rally support for continued investment in talent, infrastructure, and governance while showcasing concrete examples that illustrate AI’s societal benefits.
Overall tone
The speech begins with a visionary and optimistic tone, celebrating AI as a transformative force [15-18]. It then shifts to a pragmatic, evidence-based tone, detailing India’s existing assets and concrete use cases [35-38][58-62]. Midway, the tone becomes instructional and cautionary, focusing on the challenges of enterprise integration and the need for reskilling [75-88]. It concludes with an inspirational and rallying tone, urging decisive action and highlighting India’s potential to make a global impact [101-119]. The progression reflects a movement from broad excitement to detailed practicality, ending with a hopeful call to action.
Speakers
– Rishad Premji – Executive Chairman of Wipro; AI thought leader; discusses AI transformation and India’s role in AI adoption[S1][S2]
– Speaker 1 – Event host/moderator who introduces the panel and the next speaker[S3][S5]
Additional speakers:
– Nandan Nilekani – (role/title not specified in the transcript)
– Dario Amote – (role/title not specified in the transcript)
– Rahul Mattan – Moderator (mentioned as moderating the conversation)
Speaker 1 opened the session by thanking the AI pioneers - Nandan Nilekani, Dario Amote and moderator Rahul Mattan - and noting that the forthcoming discussion would feature “pioneers and thought leaders of artificial intelligence” who would share “profound perspectives” on the technology [1-6]. He then introduced the next speaker, Mr Rishad Premji, describing him as the executive chairman of Wipro, the son of a beloved Indian business leader, and a “thoughtful steward of Wipro’s transformation into an AI-native technology services company” who is also “unusually candid” about the responsibilities of business leaders during technological disruption [7-12].
Premji began by characterising artificial intelligence as a once-in-a-generation technology that does not merely expand what can be done, but fundamentally changes what must be done [15-18]. He argued that India’s response over the next few years will shape both its economic trajectory and its capacity to solve problems that affect more than a billion people [19-22][23-26]. This framing set the tone for a shift from speculative enthusiasm to a focus on practical, scalable impact.
He observed that the global AI conversation has moved from “what can it do?” to “how do we apply it at scale responsibly”, marking an inflection point where experimentation gives way to adoption and pilots to scaled impact [24-31]. Premji asserted that this moment offers India the chance to become one of the world’s most consequential environments for AI-not only as a creator of the technology but as a testing ground where AI is applied to complex, real-world problems at scale [28-31].
To substantiate India’s readiness, Premji highlighted several strengths repeatedly cited by analysts. He cited the Unified Payments Interface (UPI), which now processes over 20 billion transactions each month, as proof that technology can scale rapidly when it is accessible, reliable and inclusive [41-44]. He then pointed to the country’s rapidly expanding AI talent pool – roughly 650 000 professionals today, projected to double by 2027 – and noted that this talent is bolstered by government programmes to train ten million young people in AI, industry-university partnerships, evolving curricula and apprenticeship opportunities that provide real-world exposure [45-50][51-53]. Complementing this human capital, India hosts the world’s third-largest technology-startup ecosystem, with more than 4 000 deep-tech and AI-focused firms translating capability into practical applications [52-60].
Premji noted that “the real constraint is not access to technology, but integrating AI into large, complex organisations” and that “one more factor that I believe positions us uniquely is our long engagement with global enterprises” [75-78]. He explained that successful AI deployment requires modernising legacy architectures, curating fragmented data, and creating highly specialised, context-aware models that align with specific workflows. He added that the same dynamics that determine success inside organisations will also shape how countries navigate this moment [84-88]. Accordingly, organisations must invest in change-management, reskilling staff, redesigning roles and building confidence in AI use so that AI becomes not just deployable but sustainable at scale [84-88][90-92].
Premji further underscored the importance of responsible AI governance. India is putting early guard-rails in place, balancing accountability with innovation, to ensure that AI can scale safely and with confidence [64-66]. He argued that AI fluency must extend beyond engineers to teachers, nurses, administrators, supervisors and small-business owners [96-98], and warned that the dividing line will not be “human versus machine” but “between those who adapt and those who hesitate to adapt” [99-100].
Illustrating AI’s societal impact, Premji described tangible outcomes across sectors. In education, AI supports learning in local languages and helps mitigate teacher shortages; in healthcare, it enables earlier disease screening and strengthens rural care; and in public services, it contributes to smarter, safer infrastructure and reduces welfare leakages [35-38]. In agriculture, AI models trained on satellite imagery provide early pest alerts, cutting crop losses by up to 25 percent in states such as Karnataka, Maharashtra, Telangana, Andhra Pradesh and Punjab [58-60]. Artisans in Gujarat, Tamil Nadu and Uttar Pradesh use AI-enabled platforms to automatically catalogue products, translate descriptions across languages, optimise pricing and coordinate logistics, thereby opening markets that were previously out of reach [61-62].
To exemplify AI’s health impact, Premji described a pilot run by the Azeem Premji Foundation in rural Tamil Nadu. Community health workers carry portable X-ray devices to homes, where AI instantly analyses the images to detect signs of tuberculosis, allowing early screening and faster referral without the need for patients to travel to distant hospitals [104-112]. Given India’s doctor-to-population ratio of roughly 1 to 800, AI “does not replace care; it multiplies scarce expertise” and can address last-mile health challenges not only in India but also across Asia, Africa and Latin America, home to more than four billion people [113-115][116-118].
Premji concluded by asserting that low-cost, multilingual, resilient AI solutions developed in India can be exported globally, enabling the nation to contribute “vastly, not just in building AI, but in applying it to solve problems for enterprises, for our own country and for the world at large” [119-120]. He called for decisive action, reminding the audience that technology shifts inevitably create uncertainty but also opportunity, and that India’s history of embracing such shifts positions it well to lead the next AI era [101-104][119-120][S21].
Overall, Premji’s address combined a visionary framing of AI as a generational inflection point with a pragmatic roadmap that leverages India’s inclusive digital infrastructure, burgeoning talent pool, vibrant startup ecosystem and emerging governance frameworks. He urged policymakers, business leaders and the broader public to invest in workflow-specific models, robust change-management and widespread AI fluency so that the country can harness AI responsibly, at scale, and with global impact.
Thank you so much, Mr. Nandan Nilekani and Mr. Dario Amote. And thank you, Rahul Mattan, for moderating it. Well, it was quite an engaging conversation, I must say. And they are the pioneers and the thought leaders of artificial intelligence. And they shared their profound perspectives. I thank our panelists. Ladies and gentlemen, our next speaker is Mr. Rishad Premji. He is the executive chairman of Wipro, the son of one of India’s most beloved business leaders. Rishad Premji has carved out his own identity as a thoughtful steward of Wipro’s transformation into an artificial intelligence. artificial intelligence native technology services company. He’s also an unusually candid voice on the responsibilities that business leaders carry in times of technological disruption.
Ladies and gentlemen, please welcome the Executive Chairman of Wipro, Mr. Rishad Premji. A warm welcome once again. That’s Mr. Rishad Premji.
You know, thank you for those of you who are here for being here. Once in a generation, a technology emerges that doesn’t just change what we can do. It truly changes what we must do. AI for me is certainly that technology. And how we as a country, how India responds in the next few years, will shape not just our own economic trajectory, but our ability to solve problems that matter to over a billion people. For the past several years, the conversation around AI has focused just not on the possibility. What can it do? How powerful could it become? How quickly could it evolve? But we are now at an inflection point. The conversation has fundamentally shifted from possibility to practicality.
From experimentation to adoption and from pilots to scaled impact. This shift matters and it matters tremendously because technology creates value only when it is applied to solve real world problems responsibly and at scale. So what does this moment mean for India? It means India has the opportunity to become one of the world’s most consequential environments for the application of AI. Not just as a builder of the technology. But as a place where AI is tested against real world problems. complexity and made to work at scale. Our context as a country is demanding. Systems here must work across multiple languages, across urban and rural settings, and across populations with very different levels of access, need, data quality, and infrastructure.
That raises the bar, but it also makes success meaningful. We already see what this looks like in practice. In education, AI can support learning outcomes in local languages and help address teachers’ shortages and skill mismatches. In healthcare, it can enable earlier disease screening and strengthen rural care, especially where access is limited. And in public services, it can help build smarter, safer infrastructure and reduce leakages in welfare delivery. Which brings me to India’s strengths and why I believe India is a great country. India is well -placed today to take advantage of all of this. Let me just highlight a few that matter most and have been highlighted by many. One of the most significant is our experience with DPI.
UPI today processes over 20 billion transactions every month and has transformed how individuals and businesses participate in the digital economy. It has demonstrated that technology can scale rapidly when it is accessible, reliable, and most importantly, inclusive. India also has one of the largest and fastest growing pools of AI talent in the world. We are truly the AI and talent destination of the world. Approximately 650 ,000 professionals in India work in AI -related roles today, and this number will double by 2027. This talent brings not only technical capability, but importantly, practical experience in applying technology in complex real -world situations. and in real -world environments. Equally importantly, many of the foundations to build out this talent are already in place.
Government initiatives to train 10 million young people in AI, along with industry partnerships with universities, are expanding access to practical, job -ready training. Curricula is evolving and people are giving opportunities as apprenticeships to get exposure to real -world applications. This capability is reinforced by a vibrant innovation ecosystem. India is home, as many of us know, to the world’s third -largest technology startup base, including more than 4 ,000 startups in the deep tech and AI space. Together these companies are helping translate technological capability into practical, real -world applications. We are already seeing what this looks like on the ground. In agriculture, for example. We are already seeing what this looks like on the ground. We are already seeing what this looks like on the ground.
We are already seeing what this looks like on the ground. farmers across Karnataka, Maharashtra, Telangana, AP and Punjab are using AI systems trained on satellite imagery and local crop data. These systems provide early pest alerts and in some regions have reduced crop losses by nearly 25%. In small commerce, artisans in Gujarat, Tamil Nadu and UP are using AI -related platforms connected to open networks. Products are automatically catalogued, descriptions translated across languages, prices optimised and logistics coordinated, allowing small sellers to reach markets that were once out of reach. And we are also seeing deliberate investments in the future. National initiatives are expanding access to compute infrastructure and building capacity across the AI stack in our country. At the same time, an equally important we as a country are taking a very pragmatic approach to governance.
We are also seeing a rapid growth in the AI industry. putting early guardrails in place, but balancing accountability with innovation, so AI can scale safely and with confidence. All of this lays a strong foundation for India to lead in the AI era. But there is one more factor that I believe positions us as a country uniquely, our long engagement with global enterprises. Today, the constraint, as many have said, is not access to technology. The real world begins when AI is introduced into large, real -world organizations. In those environments, technology has evolved over many years. Application landscapes are complex. Data is fragmented. Workflows are siloed. Processes vary across geography, business units, and regulatory regimes. Decision -making is rarely uniform.
Making AI work in this environment means modernizing legacy architectures. It means curating and labeling data to create highly specialized context -aware models. It means orchestrating across agents in ways that are reliable and secure. And it means earning confidence of security teams, risk leaders, regulators, and critically, the people who are expected to use these systems every day. This is where a more practical pattern has emerged in enterprises. Models designed for specific processes or decisions tend to deliver the most reliable results. When AI is closely aligned to a defined workflow, it becomes more predictable, easier to govern, and more effective over time. What enterprises need today is not a model that does everything, but models that do the right thing consistently, inside how work actually happens.
But technology alignment alone is not enough. For these systems to deliver value in organizations, organizations themselves will have to invest in change. Taking people truly along, helping them adapt to new ways of working, redesigning roles and decision making, and building confidence in how AI is used. That includes reskilling people, reskilling teams to work effectively with AI tools so that they understand the outputs and exercise judgment where it matters most. When models are well aligned to workflows and people are supported through the transition, AI becomes just not deployable, but it becomes sustainable at scale. And that plays directly to India’s strengths. We have decades of experience. We have experience working inside complex enterprises, helping them modernize systems, manage risk, and take people along through this change.
And that works in environments like these is not just deployable, it is resilient, responsible, and truly scalable. The same dynamics that determine success inside organizations will also shape how countries navigate this moment. As we look ahead, India’s advantage in AI will not be defined only by the size of our models or the scale of our infrastructure. It will be defined by the choices we make. About where we apply AI, how we diffuse it, how responsibly is it deployed, and whether we can translate capability into real impact for governments, citizens, and enterprises. India’s advantage will come from developing talent at scale, not just people trained on AI, but people who can apply it with context, judgment, and an ability to adapt to change.
That is why AI fluency must extend beyond engineering. For more information, visit www .international .com to teachers, to nurses, to administrators, to supervisors, to small business owners, among everyone else. The dividing line will not be human versus machine. It will truly be between those who adapt and those who hesitate to adapt. Technology shifts inevitably create uncertainty. But for countries that act decisively, they also create opportunity. India has embraced such shifts in the past, and I believe we are really well positioned to do so again. I want to close by sharing a personal story from the work of the Azeem Premji Foundation, which is also the majority shareholder of our company, Wipro. India sees 2 .7 million tuberculosis cases every year, making it one of the country’s most serious public health challenges.
Early detection is essential. But confirming TB often requires patients to travel to distant public hospitals for sputum or molecular tests. For many, the real barrier is not medical capability, but it is access. To address this, our foundation is running a pilot in a rural community in Tamil Nadu. Community health workers carry portable x -ray devices directly to people’s homes. AI analyzes the x -rays instantly and identifies signs consistent with TB, enabling that early screening and faster referral without requiring patients to travel. If successful, this approach can help detect TB earlier and extend the reach of healthcare into communities that need it most. With a national doctor -to -population ratio of roughly 1 is to 800 and even deeper shortages in rural India, AI does not replace care.
It multiplies scarce expertise. AI is able to address these challenges infinitely. The same last -mile challenges exist across other countries in continents of Asia, Africa, and Latin America. home to more than 4 billion people. Solutions that work here in India at scale, low cost, multilingual and resilient can travel far beyond our own borders. If we can do that, India’s contribution can be vast, not just in building AI, but in applying it to solve problems for enterprises, for our own country and for the world at large. Thoughtfully, inclusively and with impact at scale. Thank you for listening to me.
“Speaker 1 thanked the AI pioneers – Nandan Nilekani, Dario Amote and moderator Rahul Mattan”
The knowledge base lists Nandan Nilekani, Dario Amote (spelled Amodei in some entries), and Rahul Mattan as participants in the AI discussion, confirming their presence and roles [S1] and [S2].
“Rishad Premji is the executive chairman of Wipro”
The transcript introduction explicitly welcomes Rishad Premji as the Executive Chairman of Wipro [S2].
“Dario Amote is an AI pioneer and thought leader featured in the session”
The knowledge base refers to the participant as Dario Amodei, founder of Anthropic, indicating a misspelling in the report [S53].
“India can become a testing ground where AI is applied to complex, real‑world problems at scale”
Additional sources highlight India’s unique position as a large market and testing ground for technologies that can be scaled globally, supporting the claim about India’s potential role [S66] and noting its critical part on the global AI stage [S67].
The discussion shows a clear consensus that AI is a transformative, generational technology for India, and that the country’s existing digital infrastructure, talent pool, startup ecosystem, and emerging governance measures position it to lead responsible, large‑scale AI deployment. Both speakers underscore the importance of visionary leadership and inclusive, multilingual solutions.
High agreement on AI’s strategic importance and the need for inclusive, responsible deployment, suggesting strong alignment among the participants and reinforcing India’s potential role in shaping AI for development.
The transcript features only an introductory remark by Speaker 1 and a single, uninterrupted keynote by Rishan Premji. Consequently, there are no explicit points of contention between speakers. The sole area of overlap is a shared affirmation of AI’s significance, with no substantive disagreement on policy, implementation, or governance.
Minimal – the discussion is largely consensual, indicating strong alignment on the strategic importance of AI for India. This suggests that, at least within this session, stakeholders are unified in framing AI as a generational opportunity, which may facilitate coordinated action rather than debate.
Rishad Premji’s remarks steered the discussion from abstract enthusiasm about AI toward a grounded, responsibility‑centric narrative. By first framing AI as a generational inflection point, he set a moral backdrop that justified his later focus on practical adoption, inclusive scalability, and governance. Concrete Indian examples such as UPI and the TB‑screening pilot served as proof points, reinforcing his claim that India can lead by applying AI to real‑world challenges. His critique of ‘one‑size‑fits‑all’ models and emphasis on targeted, workflow‑aligned solutions shifted the conversation toward enterprise pragmatism, while the call for reskilling and cultural change added a human dimension. Collectively, these pivotal comments redirected the audience’s attention from hype to actionable, inclusive, and responsible AI deployment, shaping the overall tone from celebratory to purposeful.
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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