Building Trusted AI at Scale Cities Startups & Digital Sovereignty – Panel Discussion Moderator Amitabh Kant NITI

20 Feb 2026 13:00h - 14:00h

Session at a glance

Summary

This panel discussion at the AI Impact Summit 2026 featured prominent leaders from India’s IT services industry, including executives from TCS, Infosys, HCL Tech, and Salesforce, discussing the transformative impact of AI on their sector and the broader Indian economy. Moderated by Amitabh Kant, the conversation addressed concerns about AI disrupting traditional business models, particularly the SaaS industry, with Salesforce’s Arundhati Bhattacharya arguing that while markets may overreact, successful companies will adapt by continuing to add value through understanding workflows, governance, and addressing customer pain points.

The panelists unanimously rejected predictions that AI would eliminate jobs in the services sector, instead forecasting significant growth opportunities. TCS CEO K. Krithivasan emphasized that AI will shift roles toward requirements engineering and system validation rather than eliminating positions, while noting the long tail of cloud adoption and modernization work still needed. Infosys CEO Salil Parekh highlighted six key AI service areas representing $300 billion in opportunities, including AI engineering and legacy modernization, and announced continued hiring of 20,000 college graduates annually. HCL Tech’s C. Vijayakumar stressed the importance of bridging the gap between foundation models and enterprise applications, focusing on specialized services like physical AI and agentic AI.

The discussion emphasized the critical importance of democratizing AI beyond Fortune 500 companies to reach MSMEs and blue-collar workers, with potential applications in agriculture, healthcare, and education through digital public infrastructure. The leaders advocated for increased R&D investment and responsible AI development, expressing confidence that India’s IT industry will create more jobs than AI eliminates, driving the country toward a $30 trillion economy by 2047.

Keypoints

Major Discussion Points:

– AI’s Impact on Traditional Business Models: Discussion of whether AI will disrupt existing SaaS models and software services, with market volatility around companies like Salesforce, and debate over whether traditional per-seat software models will survive the shift to AI agents.

– Future of Employment in the AI Era: Extensive debate about whether AI will eliminate jobs or create new opportunities, with industry leaders arguing that AI will generate more jobs than it destroys, though requiring different skills and roles focused on orchestrating AI systems rather than manual coding.

– Skills and Workforce Transformation: Focus on the need for reskilling and upskilling strategies at both individual and national levels, emphasizing the importance of programming fundamentals, critical thinking, and the ability to manage AI agents and tools effectively.

– AI Democratization and Accessibility: Discussion of how to make AI tools accessible beyond Fortune 500 companies to MSMEs (Micro, Small, and Medium Enterprises) and blue-collar workers, including the potential for AI-powered digital public infrastructure similar to India’s successful digital payment systems.

– Industry Evolution and R&D Investment: Examination of how Indian IT services companies are positioning themselves in the AI landscape, with emphasis on the need for increased R&D spending, building proprietary solutions, and moving beyond traditional “builder for hire” models to create intellectual property.

Overall Purpose:

The discussion aimed to address the transformative impact of AI on India’s IT services industry, exploring how major companies and the workforce should adapt to remain competitive while leveraging AI to drive economic growth and job creation.

Overall Tone:

The discussion maintained a consistently optimistic and forward-looking tone throughout. Despite acknowledging significant disruptions and challenges posed by AI, all panelists expressed confidence in the industry’s ability to adapt and thrive. The tone was professional yet accessible, with leaders providing practical insights while maintaining enthusiasm about AI’s potential to create opportunities rather than just eliminate jobs. The moderator kept the pace brisk and focused, and the audience engagement at the end added energy and real-world relevance to the theoretical discussions.

Speakers

Speakers from the provided list:

– Moderator: Event moderator for AI Impact Summit 2026 panel

– Amitabh Kant: Panel moderator

– Salil Parekh: CEO of Infosys

– Arundhati Bhattacharya: Former banker, currently a tech leader at Salesforce

– K. Krithivasan: CEO of TCS (Tata Consultancy Services), leads company with over 600,000 engineers

– C. Vijayakumar: CEO of HCL Tech

– Audience: General audience members asking questions

– Navneet Kaul: Audience member who asked a question

Additional speakers:

– Mania Sharma: CEO of Mono AI, 27-year-old entrepreneur from small town, based in Bangalore

– Devika Rao: From UK University of Leeds, working on AI creative education and art health and well-being concepts

– Kishla: IT sector employee asking about skill development

– Harswar: Audience member asking about AI misuse prevention

– Venkatana Rasimahati: Software architect and founder of startup called Startup Sanatana

Full session report

This panel discussion at the AI Impact Summit 2026 brought together India’s leading IT industry executives to address AI’s transformative impact on the technology services sector. Moderated by Amitabh Kant, the session featured Arundhati Bhattacharya from Salesforce, K. Krithivasan (CEO of TCS), Salil Parekh (CEO of Infosys), and C. Vijayakumar (CEO of HCL Tech) – representing companies that collectively employ millions of Indians.

Business Model Evolution and Market Response

The discussion opened with Kant questioning whether AI threatens traditional business models, citing Salesforce’s recent market decline and broader SaaS sector volatility following AI product launches. Bhattacharya provided a measured response, acknowledging that “models will change” but arguing that markets often overreact. She emphasized that successful enterprise software companies offer more than just coding capabilities – they understand workflows, address customer pain points, ensure governance, and manage adoption processes. “End of the day, people who add value are the ones who are going to stay, who are going to survive, who are going to be sustainable,” she stated.

The industry leaders unanimously rejected predictions that AI would eliminate the services model. Krithivasan noted that system integrators remain essential due to complex legacy systems, with many organizations still only 30-40% cloud-adopted after a decade. Parekh directly contradicted predictions about the services model’s demise, citing the real opportunity in execution and addressing legacy tech debt. However, Bhattacharya cautioned about “circular money” in AI investments and advised companies to “read the fine print” when evaluating AI opportunities.

Employment Impact and Skills Transformation

All panelists argued that AI will create more jobs than it destroys, though these will require different skills. Krithivasan explained that work will shift from writing code to orchestrating AI systems, emphasizing requirements engineering, context engineering, and system validation. He provided concrete evidence through a TCS workshop where 1,500 non-technical students from NCR schools, many not fluent in English, successfully built applications using AI in their native languages within three hours.

Vijayakumar stressed that programming fundamentals and critical thinking remain essential, but workers can now amplify their output by 4-5 times through managing AI agents. He described how junior engineers could immediately manage multiple coding agents to deliver outcomes traditionally requiring years of experience.

The employment optimism was supported by hiring data. Parekh announced that Infosys recruited 20,000 college graduates this year and plans similar numbers next year, with headcount increasing by 13,000 in the first three quarters. The industry leaders are actively collaborating with the Ministry of IT on university curriculum development to prepare the workforce for these changes.

New Market Opportunities and Industry Positioning

The panelists identified substantial opportunities emerging from AI adoption. Parekh outlined six key AI service areas representing significant market potential, including AI engineering, legacy modernization, and new application development. AI makes previously expensive modernization projects economically viable by reducing costs and implementation time.

Vijayakumar highlighted opportunities in physical AI and infrastructure refresh, noting that the entire global IT infrastructure landscape will require refreshing over the next five to eight years. However, he acknowledged that capturing these opportunities requires companies to invest significantly in R&D ahead of returns, building solutions rather than providing straightforward services.

When addressing competition with hyperscalers’ massive infrastructure investments, the Indian IT companies positioned themselves as bridges between foundation models and enterprise applications. Vijayakumar explained HCL Tech’s unique positioning with its software product business and deep engineering heritage, including work on two-nanometer custom silicon development. The focus is on building intellectual property that makes foundation models more scalable within enterprises, partnering with rather than competing against hyperscalers.

Democratization and Broader Impact

A crucial theme was extending AI benefits beyond Fortune 500 companies. Bhattacharya argued that AI must be accessible to micro, small, and medium enterprises and blue-collar workers to truly benefit India. She outlined how AI could address challenges faced by blue-collar workers, including skills certification, job access, and payment systems.

Parekh described ongoing work to create AI-focused digital public infrastructure in agriculture, healthcare, and education, similar to India’s successful payment and identity systems. This approach would make AI capabilities available without prohibitive costs.

Audience Engagement and Practical Concerns

The session concluded with audience questions from young entrepreneurs, academics, and IT professionals. Questions ranged from accessing mentorship opportunities and developing specific skills to preventing AI misuse and incorporating cultural values into AI development. Bhattacharya directed entrepreneurs to Salesforce’s startup community programs, while panelists emphasized the importance of building ethical considerations into AI systems from the ground up.

Future Outlook

The panel expressed confidence that India will successfully navigate the AI transformation, with leaders emphasizing that success depends on adapting and adding value rather than resisting change. The key themes were proactive business model transformation, strategic R&D investment, and ensuring AI benefits extend throughout Indian society.

The discussion provided both strategic insights for industry transformation and practical guidance for career development, positioning AI as a tool for economic inclusion and national development rather than a threat to employment. The leaders’ measured optimism, backed by concrete examples and hiring data, offered a counter-narrative to fears about AI-driven job displacement while acknowledging the need for significant adaptation and investment.

Session transcript

Moderator: With a big round of applause, kindly welcome the panelists of this last panel of AI Impact Summit 2026. Mr. Salil Pareek, Mr. K. Kritivasan, Mr. C. Vijay Kumar and Ms. Arundhati Bhattacharya. With the moderator, Mr. Amitabh Kant. A big round of applause, ladies and gentlemen, to welcome them all to the stage. Well, it’s over to you, Mr. Amitabh Kant. Amitabh Kant: So let me welcome these very distinguished leaders of the Indian IT. tech service industry and we have with us Arundhati Bhattacharya who is both a banker and a great tech leader now. The three of them amongst them they are leaders of an industry that represents over 300 billion in market value over 25 lakh crore and they employ millions of Indians. We are actually meeting at a point of disruption. I’m not going to take much time in introducing the panel or I’m not going to take much time in giving my own introduction. I will straight away move to asking them questions and then open it up to all of you so that you can ask the questions. I’ll try and start with the lady in the panel and I’ll also try and end with the lady in the panel Arundhati Bhattacharya was probably the most distinguished of us all so let me, Arundhati, let me try and be as direct as possible so Salesforce has lost roughly about 40 % of its market value in just 12 months a single AI product launch wiped almost 285 billion of SaaS stocks in a day the market is saying that AI agents will replace per seat software subsystems is the market wrong or is the traditional SaaS model genuinely under threat and what does that mean for thousands of Indian enterprises that have built their operations on Salesforce platform? Arundhati Bhattacharya: First and foremost, thank you very much for asking that question. I’ve been answering that question so many times in the last few days that it’s almost like rehearsed, you know, as to how I should go about it. But having said that, you know, markets will say a lot of things. Not all of it comes true. And when you talk about the SaaS model, it’s not only about vibe coding. It’s not only about creating an application. It’s also about, you know, understanding what the workflows are like. It’s about realizing what the customer’s pain points are and ensuring that you are addressing those particular pain points. It’s about observability about what your agents are doing. It’s about governance. It’s about auditability. It’s about adoption. There are so many pieces to making something really work in an organization that to just say that because I can vibe code, that means, you know, everything else goes out of the window. I think that’s being a little too, you know, little too hasty about totally, you know, rejecting a way of doing business. Also, I must say that, you know, which I’m not very true is correct, but people have to sometimes pump up values given the kind of money that is going in over there. And by the way, some of that money is circular money that’s going in over there. So I’m not too sure that the market is actually giving the right message that it should. And like for everything that the market gives people, investors especially are requested to read the fine print. And obviously, you know, exercise their discretion in the matter. Having said that, is it true that the models that we have today will remain exactly the same? They won’t. I’m very clear about one thing, which is that all of the models that we have today, and I mean not the LLM models, but I mean the models of working, the ways of working, whether it be in respect of the SaaS companies or it be in respect of any of the other companies, even intra -companies or any of the other companies, things will change. And we have to be very agile about the way we look at these things and realize where are the changes going to come and how can we ourselves change in tune so as to remain relevant, so as to be able to actually add value to your customer. End of the day, people who add value are the ones who are going to stay. who are going to survive, who are going to be sustainable. And therefore, adding value is what we need to do. And for adding value, whatever it takes for us to do, we need to do those things. So I think, you know, the jury is out and will remain out for a while because the race is on and we don’t know who’s going to win the race. But this much I do know that, you know, it will not be one individual unit or one individual kind of unit. There will be very many players in this whole thing. But at the end of it all, as long as it improves our standards of living, as long as it gives us results and answers which we never had before, it is for the good of humanity. And I hope that will definitely happen. Amitabh Kant: Thank you. Thank you for that very detailed answer to that question. I now turn to Mr. Christy Varshan, the CEO of, TCS. Yes, Mr. Krishnivasan, the industry consensus is that AI will shift work from writing code to orchestrating AI systems. What does TCS look like to you in 2030? What will be the headcount and what will be the revenue per employee? And how is TCS communicating that transition to its workforce and to the country? K. Krithivasan: Thank you and good afternoon to everyone. See, this is the topic that everyone has been discussing in the last few days and few weeks. And like Arun has explained, the market also has been contemplating. But there will be a few things that will change. Many things may not change or the other way. Like if you look at the role of what most of us do as a system integrator, the role of system integrators come into play because there are complex, complex systems and many of them have a lot of legacy. you it’s not that one day you can have a llm understand everything and auto generate code and the software engineers will go away but not to say like arunthi said there will be more and more productivity that will be brought in and at the same time you need system integrators who can test validate verify what is being generated and so that’s one part of it the second is as you also look at today the role will shift towards more and more requirements engineering context engineering how do you know whether you are building the right system how do you validate a system is doing the right thing does it have cyber security does it do some harm all those things are to be validated you like you may not know all the roles that you will have five years down the line but we don’t envisage a situation where there will be a significant shrinkage of hope Now, the other areas that we have somehow not looked at when we get excited about generating code is for many of the, for instance, cloud came into play about maybe 10 years ago. But if you ask most organizations, they will tell you that 30 -40 % cloud has been adopted. There is so much to be done. So, this is going to be a long tail. And even within that, you would see many organizations, they have to prepare for deploying or adopting. It’s not a trivial job. They have to get their data estate right. They have to get their applications rationalized, modernized. So, there is a certain amount of work to be done. They need to train their models like Arunthati was saying or somebody was mentioning. You will have some large models, many small models in every enterprise. They have to be trained. And the last part of it, which you are not… Again, looking at is what is it new that you can do with all these LLMs? There will be many interesting things. Somebody has to build. Somebody has to think through that. So, if you look at another 30, I don’t envisage a time that there is a significant shrinkage of hope. but there will be more volume of work that will be produced. More volume of work. More volume of work that will be produced and more interesting work that will be done. Amitabh Kant: Thank you. Thank you. So that’s an interesting perspective. I turn to Salil, who is the CEO of Infosys. Salil, one of the very provocative statements made by one of the Bay Area leaders and investor actually was that, which attracted a lot of news coverage, was that services model is dead within five years. Your chairman, Nandan Nilikani, just I was reading, in fact, I went through his interaction, and he said that this is not an opportunity gap, but this is an execution gap and that the real money isn’t clear. He’s cleaning up trillions of dollars of legacy tech debt. who is right? Is Nandan right or is it this Bay Area leader? Who’s right according to you? Salil Parekh: That’s an easy answer Nandan’s of course right. There’s no question. So simply because he’s your chairman because I think Nandan I’m sure everyone has a view. Nandan is a visionary who has a view on this business for years. I think the way we see it is and we shared this a few days ago there are several areas of opportunity that come from AI services and there are six that we have highlighted recently just a few days ago and those in aggregate we have shared some data are about 300 billion dollars of opportunity over the next several years and then we’ve gone into a little bit of of the detail in each. I’ll give just a couple of examples. There’s one which is like AI engineering, which is the building of agents, orchestrating, integrating some of the points what Kriti was mentioning. There’s another which you alluded to how Nandan has said it of legacy modernization, which is basically saying there were some things which were 15, 20 years old with large companies. How can we bring it to the more current? And there because of AI agents, the cost is lower, the time is less. And so there’s an easier economic rationale for companies to do it. So as we put all these together, we see these what we call AI services, which will give us the growth. And what I think the point you made, what Nandan said, if we can pivot our company to serve these big six areas for our clients, that execution path. then the opportunity is good. And again, some data on that, like this year, which will end in March, we have recruited 20 ,000 college graduates. Next year, we are on track and we’ve announced we are recruiting 20 ,000 college graduates. This year, our headcount has increased in the first three quarters by 13 ,000 people. And my sense is that will continue. So what it’s opening up really is new set of opportunities. And there is some productivity benefit that comes with if like specifically in Infosys, but I’m sure in general, if we execute and serve our clients, there will be more opportunity. Amitabh Kant: So tell me, do you at any stage aspire to own intellectual property in the AI stack or will you remain a builder for hire? Salil Parekh: So then the approach, I’ll speak a little bit for Infosys, our approach is, we have a lot of opportunities. We have tremendous IP. So like in AI, we built this IP layer called Topaz Fabric. which has the ability for clients to work with any of the foundation models, plus the agents that we have built, that Infosys has built, plus any third party agents. So that’s the layer that we are, let’s say, pretty good at and that we will build and continue to build the IP on. That’s the approach on the IP that we’ve taken. Amitabh Kant: OK. CVK, let me turn to you because HCL Tech has a software product business. It has a design custom AI chips in Bangalore and you operate across the full stack, actually. Is HCL Tech positioning as an AI builder at any stage? And if so, how far up the stack are you willing to go into models and to compute, into infrastructure? Infrastructure that at any stage will compete with the hyperscalers rather than just partner with them. C. Vijayakumar: Thank you and good evening everyone. HCL Tech, as you kind of gave some pointers, we are uniquely placed because, first of all, we have a software product business which delivers 10 % of our revenue. And we also have a very deep engineering heritage where we service top 50 of the 100 R &D spenders doing a lot of work, including some cutting edge work. Like we have built a two nanometer custom silicon for one of the technology companies. So we have these unique capabilities. And this also reflected in our high. Highest revenue per employee amongst the IT services companies. So with this backdrop, our AI strategy is one of them is. heavily indexed on building because of course, our core services, we will continue to modernize and evolve our services to be relevant for the future. And even if it means it takes away some revenue streams, we are proactively doing it. But I think the biggest focus is there are these large language models and the foundational models. They cannot be applied most efficiently for enterprise use cases. There is still a gap between what a foundation model can deliver and what is the ultimate efficiency and innovation that’s possible. So we are really trying to bridge the gap and building IPs that will bridge the gap which helps enterprises to scale AI adoption. And we’re also focused on a lot of specialized services like even Salil mentioned, like physical AI, AI factory. agentic AI. All of these new solutions we are very focused on. And of course, the partnership ecosystem becomes extremely critical. So we are partnering with almost all the large solution providers. I don’t think we are building anything to become a hyperscaler. I think we missed the bus many, many years ago. And we’re not building models, but we are building solutions which will make the models much more scalable and applicable within enterprises. Amitabh Kant: Thanks. Thanks. Thanks for that. I just wanted to turn to Mr. Christy Wilson because he’s the biggest employer in India. He employs over 600 ,000 engineers. You know, India produces millions of engineering graduates a year and many of them are trained for exactly the kind of work AI is now going to automate in a very big way. So what should be a skilling strategy of this country? I mean, how do we do reskilling and skilling at an individual level or should we do it at a national country level? I mean, what is the view of India’s leading CEO in terms of skilling and reskilling? K. Krithivasan: This is, to my mind, a major national challenge. It’s a challenge and an opportunity. Because, in fact, three days ago, here we ran a workshop with about 1 ,500 kids from all the schools in the NCR region. Most of them are, in fact, all of them have non -technical background and many of them could not even speak or not fluent in English. And we taught them how to use their native language, how to do coding. And, in fact, within a span of about three hours, almost 1 ,500. Apps were built. So that’s the power of AI. You can… You can worry about how AI is going to take away the jobs at the entry level. I think AI also enables all these people to develop and imagine new areas where software can make the lives of people better. And it creates more and more opportunity. You can be afraid and not do anything. I think we should be forward leaning and train as many people as possible. In fact, all three of us are working with the Ministry of IT in creating the curriculum for the students coming up in all these universities. Amitabh Kant: Wonderful. Wonderful. Thanks. Thanks for that very positive and constructive perspective. Arundhati, just let me turn to you again and ask you if AI is to drive India’s productivity. It cannot remain just a Fortune 500 story. How do we make it? AI tools accessible. to millions of MSME? How do we raise productivity? How do we build for the market? Even if unit economics looks slightly different from enterprise contracts, how do we scale it up in a big way for MSME to make the difference to Indian economy? Arundhati Bhattacharya: So thank you for that question, because I personally believe that unless we can democratize any technology, it doesn’t really serve the purpose of that country or for that people. And AI is something that is not meant for the white -collar worker alone. In fact, it’s one of the things that can actually empower the blue -collar, just as you were talking, Mr. Kritivasan, it can actually empower the blue -collar workers. Now, if you look at the blue -collar workers, in fact, in NEETI, we did one report taking into account the blue -collar workers like carpenters, plumbers, hospitality workers, Anganwadi workers. So a lot of these, you know, personal… personas we had taken. And what we realized is that they have multiple challenges. One challenge, of course, is the way that they have been skilled. So they have a skilling challenge. But more than skilling challenge, they have an access challenge in the sense that they may be very well skilled, but they don’t know that the job exists within the village or in the next village. So they have an access challenge. The second thing that they have is the challenge of ensuring that they are getting paid on time. Even that is not available. So they have several challenges of this nature, that of skilling, that of access, that of payments, that of ensuring that they are parts of communities which actually enable them to be supported during times of distress or during times of need. Many of these are actually challenges that can be solved if we can use AI in the proper way, in a proper marketplace to get the right kind of opportunities to them, the right kind of certifications to them, the right kind of assessment of their skills to them. If all of this can be done, actually speaking, we will be doing the country an enormous favor. And you will find that the quality of life of not only these people, but the quality of life that, you know, that they serve, of the people they serve, people, you know, who are actually taking their services, even that is going to become much, much better. So I think, you know, AI is not something that is meant only for the white collar workers or for people in tier one, tier two cities. It’s meant for the SMEs. It’s meant for the MSMEs. It is what is going to empower them to get into a league which they were not able to access earlier. It is also meant for the blue collar workers because it can empower all of them. Amitabh Kant: Salil, we’ve had a India has done something unique in digital public infrastructure It’s been transformational in terms of identity payment, credit You know, the Bank of International Settlement said that India achieved in seven years what it would have taken 50 years to achieve. How do we create a DPI, a digital public infrastructure for artificial intelligence? How do we take computing power to the common citizen? How do we scale? How do we make a difference using the power of AI? Salil Parekh: Absolutely. I think there’s already work going on. Specifically, there are three big areas where there’s thinking going on. There’s actual projects on the ground in agriculture, in healthcare, in making sure that everything that is being done for education is helping within the country for the citizens. Also in that area, There are examples where we have shown some of it. And now the way that, as you mentioned, the India stack or the digital public infrastructure was created, where essentially it was fully available without exorbitant costs or any cost, is what the approach is being driven today. There are various components of the architecture which are being discussed. And working closely with the ministry, with the government, those will be rolled out. Today, of course, you have seen that there is tremendous support at the chip layer, at the data center layer, at the infra layer. And now there will be more at the architecture, how it can be distributed. And at least these three big areas, agriculture, education, healthcare, are being looked at today. Amitabh Kant: Thanks. Thanks. CVK. One last question before I open it up to the floor. You know, the hyperscalers, Microsoft, Google, Amazon, they’re spending close to about $600 billion this year alone on AI infrastructure. Spending almost about close to 50 to 55 % on CapEx. And if AI services opportunity is really in the range of about $350 to $400 billion, can Indian IT companies, can all of you together, capture it without adequate R &D? Does it not require greater level of R &D intensity? And what will it take all of you to put in more resources into R &D for the future? C. Vijayakumar: Yes. First of all, this big CapEx. Spend also triggers a lot of services spent, like building all these data centers, AI factories. The entire IT infrastructure landscape in the world would get refreshed over the next five to eight years. That itself is a huge services opportunity. Then there is this physical AI. It’s a completely new spend. Today, there is very, very little physical AI deployed in the world. It’s believed that one of the studies by Zeno says it’s a trillion -dollar opportunity. That would mean at least $200 billion of services opportunity. I think we are looking at some very big services opportunities. Even to really encash on these big services opportunities, the companies like us will need to invest in building solutions because it’s not straightforward services. You need to build solutions, which will mean we will have to put in more money into R &D. Right? Right. Building solutions. building labs and kind of POCs, a lot of pre -work needs to be done. And also there is a lot of opportunities to create solutions which will really make the foundational models much more scalable for enterprise. So I personally believe we should increase the R &D spend. And I do think the industry model will support us because as more and more AI is infused, more outcome -based contracts would come, which also helps us to deliver a higher profitability, which means we can very comfortably invest more in R &D. But the timing of that, we might need to invest a little ahead of the curve before the real benefits come. Amitabh Kant: Okay, wonderful. Wonderful to hear this perspective. I’m going to open it up to this house. We’ll ask about, I’ll open it up for five questions. Please. Name yourself. just be very direct and blunt. Please don’t ask long winding questions. To the point, very matter of fact all young people, any ladies here will be given preference. The lady there. Yeah, the lady here. Audience: Hello everyone. Thank you so much for giving me opportunity. No introduction, just name and shoe. Mania Sharma, CEO of Mono AI. Saving my two years to reach out to you from here till here. First question, how can I come and meet you as a young entrepreneur, 27 years with no network? My first question. Saving my lot of marketing money. Second question is, as a young Indian, 27 year old coming from a small town but being in Bangalore for seven years, what is your view or idea that we can be work with you guys and your support and mentorship so that young India can go somewhere else and we can also show the Silicon Valley that 25 year, 27 year standing here in a suit talking to you can do something. Amitabh Kant: Okay. You know, I’ve allowed two questions because she’s a lady but no two questions. I will ask the five questions and then I’ll open it up for responses. Second, there’s a lady there. Go ahead. Audience: My name is Devika Rao. I’m from UK University of Leeds. Trying to do this stage for AI creative education and art health and well -being concept and how the case study can be presented in six month time and I would like to co -create and collaborate with you. Amitabh Kant: Okay. Anyone at the back? Yeah, go ahead. No, no, please there. Yeah, yeah, the blue shirt. Get up and ask. Audience: My name is Navneet Kaul. and I have a three -part question. Amitabh Kant: No, just ask one question. Don’t ask three in one. No, no, don’t ask three in one. Ask one question. Audience: One question. Amitabh Kant: Yeah. Navneet Kaul: How will AI create jobs? What kind of jobs and what kind of skills do we need? Amitabh Kant: You’re asking the question which I’ve already asked. Audience: I want the panelists to answer very specifically and directly. Amitabh Kant: All right. Anyone at the back, that side? Yeah, that gentleman there. Audience: Hello. Kishla here. And my question is, as any employee who is currently in the IT sector, what skills he should plan to develop in the next five years to boost his employability? Amitabh Kant: Okay. No, no, not front row. Back. I want to go right at the back. Anybody right at the back? Some back venture. huh who’s who’s the backest pitch yeah that gentleman in the black suit yeah go ahead ask yeah yeah shoot yeah please sir Audience: sir my name is harswar than my question is what can be done to stop misuse of ai for example some people use grok you to unrest people Amitabh Kant: okay so one last question to that yeah shoot in one line Just shoot. Audience: Yeah, namaste. Mamanama Venkatana Rasimahati. Intentionally, I’m speaking in Sanskrit. One line. Yeah, I will come, sir. I’m a software architect. I’m a founder of a startup called Startup Sanatana. Though we are talking about so much of AI and AI is the limelight, unless and otherwise we built on AI on our culture, rich culture, tradition, heritage kind of thing, probably it will be a different kind of thing. Amitabh Kant: Thank you. Thank you. Okay. So we got the question. We got the question. Now I’ll open it up. I’ll starting from we start with Arundhati’s response and then move on. You can you can respond to one of the questions and then move on. Arundhati Bhattacharya: In respect of the question that this lady. gave and also others who are startups in this particular organization. Salesforce has a very vibrant startup community. The lady who leads it for us, her name is Rupa Arvindakshan. Her coordinates are available on our website. Please get in touch with her. She will get you in touch with our entire community. The community is supported to develop on Salesforce and also, you know, to ensure that you can take your products to market. So all of that is done. So please, you are more than welcome to communicate with us and get whatever support we can definitely give you. C. Vijayakumar: Maybe I’ll take up the question on what skills are needed in the future. I think there is a big misconception. That software, coding, programming skills are not going to be relevant. I think the fundamental conceptual skills. in software development, programming is very, very essential if you really want to build a long -term career in the software industry. It could be in services or in product companies or AI. All of that requires sound programming skills. The second aspect is, I think, just the critical thinking, analytical skills. How do you really orchestrate work? A lot of standard work that many of you do or initially the younger engineers do, some of that or a lot of it can be done with the AI tools that are there today. But how can you now think of yourself as an orchestrator and deliver maybe four or five times the output that you would deliver without these tools, right? I think just orchestrating the work with multiple coding agents, I think that’s really a skill. Or while you may take three, four years to manage a small team, but on day one, you have an opportunity to manage several agents to deliver an outcome which is 5x of what you would normally do. That’s just an example. And that’s how you need to think of every role. You can amplify the value that you can create using AI skills. Amitabh Kant: Mr. Kristinasan. K. Krithivasan: That was his question once again about will AI take away jobs or will AI? My view is it has been discussed for the last few days. Eventually, AI will create more jobs than destroy jobs. And you would find, but it may not all of them need not be programming jobs. That would be jobs of different categories, different classifications. But on the whole, we find it’s going to create more jobs and create more employment. Amitabh Kant: Sal. Salil Parekh: Thanks. I think there was a question really focused on can we build AI with views of our culture or views? Of responsibility. And that’s absolutely essential. we’ve also put together and I know many others have a framework on responsible AI and there were a couple of questions which sort of were on that line. It’s absolutely critical so in fact the way the agents are built, the way the foundation models data, the way they learn all of that needs this approach of responsible AI and that’s the approach that we’ve recommended. Many others are working on it and as an overall industry we should focus on that and that will give us as good an outcome as we can get and even that after that outcome we will have to refine and modify. Responsible AI is critical in that. Thank you. Amitabh Kant: So ladies and gentlemen we’ve heard the captains of the industry we are in the midst of disruption as I said but these leaders bring great optimism, they bring hope and according to them actually The wave of AI will end up creating many more jobs for India, but there’ll be jobs of a different kind. And we need to skill ourselves for the new emerging jobs of tomorrow. But with these leaders, I’m absolutely confident that India will ride this wave to greater progress and prosperity as it becomes a Vixit Bharat by 2047. It’ll create many, many more jobs. And these leaders will drive India to a 30 plus trillion dollar economy with jobs in the coming years. Thank you very much, ladies.

Arundhati Bhattacharya

Speech speed

159 words per minute

Speech length

K. Krithivasan

Speech speed

178 words per minute

Speech length

773 words

Speech time

259 seconds

Services model remains viable due to legacy system complexity and need for system integrators

Explanation

Krithivasan argues that the role of system integrators will continue to be crucial because enterprises have complex legacy systems that cannot be instantly understood and automated by AI. He emphasizes that while AI will bring productivity gains, human expertise is still needed for testing, validation, and verification of AI-generated solutions.

Evidence

Salil Parekh

Speech speed

149 words per minute

Speech length

789 words

Speech time

316 seconds

AI creates new service opportunities worth $300 billion, contradicting claims that services model is dead

Explanation

Parekh directly challenges predictions about the death of the services model by presenting concrete data about AI-driven opportunities. He identifies six specific areas of AI services that collectively represent a $300 billion market opportunity over the coming years, suggesting the services model is evolving rather than disappearing.

Evidence

Agreed with

– K. Krithivasan

Agreed on

Industry-government collaboration is essential for AI transition

Responsible AI frameworks are critical for ethical development and deployment

Explanation

Parekh emphasizes the importance of building AI systems with cultural values and ethical considerations embedded from the ground up. He argues that responsible AI approaches must be integrated into agent development, foundation model training, and data handling to ensure positive outcomes for society.

Evidence

Mentions Infosys has put together a responsible AI framework and recommends industry-wide adoption of such approaches

Major discussion point

Skills Development and Education Strategy

Topics

Human rights and the ethical dimensions of the information society | Artificial intelligence | Building confidence and security in the use of ICTs

Agreed with

– Audience

Agreed on

Responsible AI development and governance are critical

C. Vijayakumar

Speech speed

136 words per minute

Speech length

831 words

Speech time

365 seconds

Programming and critical thinking skills remain essential for future careers

Explanation

Vijayakumar counters the misconception that coding skills will become irrelevant in the AI era. He argues that fundamental programming concepts and analytical thinking abilities are more important than ever for building sustainable careers in the software industry, whether in services, products, or AI development.

Evidence

Emphasizes that sound programming skills are essential for services, product companies, and AI development

Major discussion point

Future of Employment and Workforce Transformation

Topics

Capacity development | The digital economy | Artificial intelligence

Agreed with

– K. Krithivasan

Agreed on

Programming and technical skills remain essential in the AI era

Workers can amplify their output 4-5x by managing AI agents and tools

Explanation

Vijayakumar presents a vision where workers become orchestrators of AI systems rather than being replaced by them. He suggests that by learning to manage multiple AI agents effectively, individual workers can dramatically increase their productivity and deliver outcomes that would normally require much larger teams.

Evidence

Disagreed with

– Amitabh Kant

Disagreed on

Scope of R&D investment requirements for Indian IT companies

Amitabh Kant

Speech speed

131 words per minute

Speech length

1327 words

Speech time

607 seconds

References India becoming a Vixit Bharat by 2047 and achieving a $30+ trillion economy

Major discussion point

Future of Employment and Workforce Transformation

Topics

Social and economic development | The digital economy | Artificial intelligence

Agreed with

– K. Krithivasan
– Salil Parekh
– C. Vijayakumar

Agreed on

AI will create more jobs than it destroys, though job types will change

Audience

Speech speed

162 words per minute

Speech length

Skills Development and Education Strategy

Topics

Building confidence and security in the use of ICTs | Human rights and the ethical dimensions of the information society | Artificial intelligence

Agreed with

– Salil Parekh

Agreed on

Responsible AI development and governance are critical

AI development should be grounded in cultural values and traditional heritage

Explanation

A software architect and startup founder argues that AI systems should be built upon India’s rich cultural traditions and heritage rather than being developed in isolation. This represents concerns about cultural preservation and value alignment in AI development.

Evidence

Founder of ‘Startup Sanatana’ deliberately speaks in Sanskrit and emphasizes building AI on cultural foundation

Major discussion point

Skills Development and Education Strategy

Topics

Human rights and the ethical dimensions of the information society | Social and economic development | Artificial intelligence

Navneet Kaul

Speech speed

138 words per minute

Speech length

17 words

Speech time

7 seconds

Moderator

Speech speed

81 words per minute

Speech length

62 words

Speech time

45 seconds

Agreements

Agreement points

AI will create more jobs than it destroys, though job types will change

Speakers

– K. Krithivasan
– Salil Parekh
– C. Vijayakumar
– Amitabh Kant

Arguments

AI will create more jobs than destroy jobs

AI creates new service opportunities worth $300 billion, contradicting claims that services model is dead

Workers can amplify their output 4-5x by managing AI agents and tools

AI will drive India toward a $30+ trillion economy with significant job creation by 2047

Summary

All speakers agree that AI represents a net positive for employment, creating new opportunities and transforming rather than eliminating jobs, with particular optimism about India’s economic growth potential

Topics

The digital economy | Artificial intelligence | Capacity development

Programming and technical skills remain essential in the AI era

Speakers

– K. Krithivasan
– C. Vijayakumar

Arguments

AI will shift roles toward orchestration and requirements engineering rather than eliminate jobs

Programming and critical thinking skills remain essential for future careers

Summary

Both leaders emphasize that fundamental programming concepts and analytical thinking will continue to be crucial, with roles evolving toward orchestration and higher-level functions rather than disappearing

Topics

Capacity development | Artificial intelligence | The digital economy

AI democratization is essential for broader societal benefit

Speakers

– Arundhati Bhattacharya
– K. Krithivasan
– Salil Parekh
– Amitabh Kant

Arguments

AI must be accessible to MSMEs and blue-collar workers to truly benefit India

AI enables non-technical people to build applications using native languages

Digital public infrastructure for AI should focus on agriculture, healthcare, and education

India’s digital public infrastructure success model should be replicated for AI democratization

Summary

All speakers agree that AI’s benefits must extend beyond Fortune 500 companies to include MSMEs, blue-collar workers, and common citizens through accessible digital public infrastructure

Topics

Closing all digital divides | Social and economic development | Information and communication technologies for development | Artificial intelligence

Services model will evolve rather than disappear due to enterprise complexity

Speakers

– Arundhati Bhattacharya
– K. Krithivasan
– Salil Parekh

Arguments

SaaS model faces disruption but won’t disappear due to complexity of enterprise needs beyond coding

Services model remains viable due to legacy system complexity and need for system integrators

AI creates new service opportunities worth $300 billion, contradicting claims that services model is dead

Summary

All three agree that while AI will transform the services industry, the complexity of enterprise needs, legacy systems, and new AI-driven opportunities ensure the services model’s continued relevance

Topics

Artificial intelligence | The digital economy | Information and communication technologies for development

Responsible AI development and governance are critical

Speakers

– Salil Parekh
– Audience

Arguments

Responsible AI frameworks are critical for ethical development and deployment

AI governance and misuse prevention require urgent attention and regulatory frameworks

Summary

Both emphasize the importance of building ethical considerations and governance mechanisms into AI systems from the ground up to prevent misuse and ensure positive societal outcomes

Topics

Human rights and the ethical dimensions of the information society | Building confidence and security in the use of ICTs | Artificial intelligence

Industry-government collaboration is essential for AI transition

Speakers

– K. Krithivasan
– Salil Parekh

Arguments

Industry leaders are collaborating with government on university curriculum development

Digital public infrastructure for AI should focus on agriculture, healthcare, and education

Summary

Both speakers highlight active collaboration between IT industry leaders and government ministries to develop educational curricula and AI infrastructure, demonstrating coordinated approach to AI adoption

Topics

The enabling environment for digital development | Capacity development | Social and economic development

The enabling environment for digital development | Financial mechanisms | Artificial intelligence

Unexpected consensus

Market skepticism regarding AI disruption claims

Speakers

– Arundhati Bhattacharya
– K. Krithivasan
– Salil Parekh

Arguments

Markets may be overreacting to AI threats against established business models

Services model remains viable due to legacy system complexity and need for system integrators

AI creates new service opportunities worth $300 billion, contradicting claims that services model is dead

Explanation

Despite representing different companies and potentially competing interests, all three major IT leaders show remarkable consensus in pushing back against market pessimism about traditional business models, suggesting coordinated industry confidence in their adaptation strategies

Topics

Artificial intelligence | The digital economy

Cultural grounding of AI development

Speakers

– Salil Parekh
– Audience

Arguments

Responsible AI frameworks are critical for ethical development and deployment

AI development should be grounded in cultural values and traditional heritage

Explanation

Unexpected alignment between a major corporate leader and a cultural advocate on the importance of embedding values and cultural considerations into AI development, showing broader recognition of AI’s social implications

Topics

Human rights and the ethical dimensions of the information society | Social and economic development | Artificial intelligence

Proactive workforce transformation approach

Speakers

– K. Krithivasan
– C. Vijayakumar
– Arundhati Bhattacharya

Arguments

Reskilling represents both a major national challenge and opportunity

Workers can amplify their output 4-5x by managing AI agents and tools

Startup ecosystems provide pathways for young entrepreneurs to access mentorship and markets

Explanation

All speakers demonstrate unexpected unity in viewing AI-driven workforce changes as opportunities rather than threats, advocating for proactive adaptation rather than defensive strategies

Topics

Capacity development | The digital economy | Artificial intelligence

Overall assessment

Summary

The discussion reveals strong consensus among industry leaders on key AI transition issues: job creation over destruction, continued relevance of services models, need for AI democratization, importance of responsible development, and value of industry-government collaboration. There is notable alignment on viewing AI as transformative rather than destructive, with emphasis on adaptation and opportunity capture.

Consensus level

High level of consensus with strategic implications for coordinated industry response to AI disruption. The unified messaging suggests industry confidence in their adaptation strategies and collective commitment to inclusive AI development that benefits broader Indian society beyond just enterprise clients.

Differences

Different viewpoints

Market assessment of AI threat to traditional business models

Speakers

– Arundhati Bhattacharya
– Amitabh Kant

Arguments

Markets may be overreacting to AI threats against established business models

Market volatility around AI reflects genuine concerns about traditional business model viability

Summary

Bhattacharya believes markets are overreacting and potentially manipulated by circular investments, while Kant presents market reactions as reflecting genuine concerns about business model disruption

Topics

Artificial intelligence | The digital economy

Scope of R&D investment requirements for Indian IT companies

Speakers

– C. Vijayakumar
– Amitabh Kant

Arguments

Companies must invest in R&D ahead of the curve to capture AI service opportunities

Indian IT companies need greater R&D investment to compete with hyperscaler infrastructure spending

Summary

Vijayakumar advocates for strategic R&D investment in solutions and labs, while Kant questions whether current R&D levels are sufficient given hyperscalers’ massive $600 billion infrastructure spending

Topics

The enabling environment for digital development | Financial mechanisms | Artificial intelligence

Unexpected differences

Fundamental viability of SaaS business model under AI disruption

Speakers

– Arundhati Bhattacharya
– Amitabh Kant

Arguments

SaaS model faces disruption but won’t disappear due to complexity of enterprise needs beyond coding

Market volatility around AI reflects genuine concerns about traditional business model viability

Explanation

Unexpected because both speakers represent leadership perspectives on digital transformation, yet they have fundamentally different views on whether market reactions to AI represent genuine threats or overreactions to established business models

Topics

Artificial intelligence | The digital economy

Overall assessment

Summary

The discussion revealed surprisingly limited direct disagreements among industry leaders, with most conflicts occurring between the moderator’s challenging questions and panelists’ responses rather than between panelists themselves

Disagreement level

Low to moderate disagreement level with significant implications – while speakers largely agreed on AI’s transformative potential and job creation capabilities, their different approaches to market assessment, R&D investment, and democratization strategies could lead to divergent industry responses and policy recommendations

Partial agreements

All speakers agree that AI will transform rather than eliminate employment opportunities, but they differ on the mechanisms – Krithivasan focuses on new job categories, Parekh emphasizes service opportunities, and Vijayakumar highlights productivity amplification through orchestration

Speakers

– K. Krithivasan
– Salil Parekh
– C. Vijayakumar

Arguments

AI will create more jobs than it destroys, though they will be different types of roles

AI creates new service opportunities worth $300 billion, contradicting claims that services model is dead

Workers can amplify their output 4-5x by managing AI agents and tools

Topics

The digital economy | Capacity development | Artificial intelligence

Both speakers agree on democratizing AI access, but Bhattacharya focuses on marketplace solutions for blue-collar workers and MSMEs, while Parekh emphasizes government-led digital public infrastructure in specific sectors

Speakers

– Arundhati Bhattacharya
– Salil Parekh

Arguments

AI must be accessible to MSMEs and blue-collar workers to truly benefit India

Digital public infrastructure for AI should focus on agriculture, healthcare, and education

Topics

Closing all digital divides | Social and economic development | Artificial intelligence

Both agree on the importance of skills development, but Krithivasan emphasizes broad national reskilling initiatives and government collaboration, while Vijayakumar focuses on maintaining core technical competencies and individual skill amplification

Speakers

– K. Krithivasan
– C. Vijayakumar

Arguments

Reskilling represents both a major national challenge and opportunity

Programming and critical thinking skills remain essential for future careers

Topics

Capacity development | Social and economic development | Artificial intelligence

The enabling environment for digital development | Financial mechanisms | Artificial intelligence

Takeaways

Key takeaways

AI will transform rather than eliminate the IT services industry, with leaders projecting $300+ billion in new AI service opportunities

The workforce will shift from coding to orchestrating AI systems, with workers potentially achieving 4-5x productivity gains through AI agent management

AI will create more jobs than it destroys, though these will be different types of roles requiring new skills like requirements engineering and critical thinking

Programming fundamentals and analytical skills remain essential for long-term careers in the AI-driven software industry

Democratizing AI access to MSMEs and blue-collar workers is crucial for India’s economic transformation

Digital public infrastructure for AI should focus on agriculture, healthcare, and education sectors

Responsible AI frameworks are critical for ethical development and deployment

Legacy system modernization becomes economically viable due to AI reducing costs and implementation time

India’s IT industry leaders are optimistic about riding the AI wave to create a $30+ trillion economy by 2047

Resolutions and action items

Industry leaders are actively collaborating with the Ministry of IT to develop AI curriculum for universities

TCS conducted a workshop training 1,500 non-technical students to build apps using AI in their native languages

Salesforce offers startup community support through their dedicated program led by Rupa Arvindakshan

Companies are increasing R&D investments ahead of the curve to capture AI service opportunities

All major IT companies are recruiting significant numbers of college graduates (20,000+ annually) despite AI automation concerns

Unresolved issues

Specific timeline and implementation details for India’s AI digital public infrastructure remain unclear

Exact mechanisms for democratizing AI access to MSMEs and blue-collar workers need further development

Detailed strategies for preventing AI misuse and ensuring responsible deployment require more concrete frameworks

The balance between investing in R&D ahead of returns versus maintaining current profitability margins needs refinement

Specific pathways for young entrepreneurs to access mentorship and funding from established IT companies need clearer definition

Suggested compromises

Companies should proactively modernize their services even if it means losing some traditional revenue streams in the short term

Investment in R&D should occur ahead of immediate returns to position for future AI service opportunities

Focus on building solutions that bridge the gap between foundation models and enterprise applications rather than competing directly with hyperscalers

Though brief and somewhat unclear, this comment introduces the crucial concept of cultural grounding in AI development. It challenges the assumption that AI should be culturally neutral and suggests that Indian AI development should reflect Indian values and traditions.

Impact

This comment, despite being from the audience, prompted Salil Parekh to discuss responsible AI frameworks and cultural considerations in AI development. It shifted the conversation toward the importance of building AI systems that reflect local values and responsible development practices.

Overall assessment

Explanation

This requires detailed architectural planning and policy framework development to create AI infrastructure that serves all citizens, similar to India’s successful digital payment infrastructure.

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.