Building Trusted AI at Scale Cities Startups & Digital Sovereignty – Panel Discussion Moderator Amitabh Kant NITI
20 Feb 2026 13:00h - 14:00h
Building Trusted AI at Scale Cities Startups & Digital Sovereignty – Panel Discussion Moderator Amitabh Kant NITI
Summary
The panel at the AI Impact Summit 2026 examined how rapid AI advances are reshaping India’s IT services, SaaS models, and broader economic productivity [6-11]. Arundhati Bhattacharya cautioned that market headlines about a 40 % drop in Salesforce’s valuation and a “AI-agent-replacing” SaaS model are overstated, emphasizing that successful SaaS requires workflow understanding, governance, observability and adoption, not just low-code development [12-23]. She added that the current models of working will evolve and firms must stay agile to add value, noting that many players will emerge and the ultimate test is whether AI improves living standards [30-38].
K. Krithivasan explained that AI will shift many engineers from writing code to orchestrating AI systems, but system integrators will remain essential for testing, validation, requirements and cybersecurity, especially as cloud adoption is still only 30-40 % and enterprises must rationalize data estates and train multiple models [46-70]. Salil Parekh highlighted a $300 billion AI services opportunity for Indian firms, citing AI engineering, legacy-modernisation and the company’s Topaz Fabric IP layer that enables clients to work across foundation models and custom agents [79-102]. C. Vijayakumar described HCL Tech’s unique position with a software product line, custom silicon and high revenue per employee, and said the company will focus on building solutions that bridge the gap between foundation models and enterprise needs rather than becoming a hyperscaler [108-127].
On the talent side, Krithivasan reported a recent workshop where 1,500 schoolchildren built 1,500 apps in three hours, illustrating AI’s potential to upskill non-technical youth and the industry’s collaboration with the Ministry of IT on curricula [135-147]. Arundhati expanded this view, arguing that democratizing AI for MSMEs and blue-collar workers requires addressing skilling, access to jobs, timely payments and marketplace platforms that certify and match workers, thereby raising overall quality of life [157-177]. Salil noted that India is already leveraging its digital public infrastructure to roll out AI pilots in agriculture, health and education, with support from chip, data-center and architectural layers to make AI services widely affordable [183-192].
Vijayakumar warned that capturing the projected $350-400 billion AI services market will demand substantially higher R&D spending, citing a trillion-dollar “physical AI” opportunity and the need to build solution labs ahead of demand [200-215]. Both Krithivasan and Vijayakumar agreed that AI is likely to create more jobs than it destroys, though the new roles will emphasize programming fundamentals, critical thinking and the ability to orchestrate multiple AI agents [299-304][283-296]. Salil also stressed the importance of responsible-AI frameworks to ensure ethical model training and deployment [306-311]. Concluding, Amitabh Kant summarized the panel’s optimism that AI will drive a “Vixit Bharat” by 2047, generating diverse employment and helping India reach a $30 trillion economy [312-317].
Keypoints
Major discussion points
– AI’s impact on the traditional SaaS model and Indian enterprises – Arundhati Bhattacharya cautioned that market hype (e.g., Salesforce’s 40 % valuation drop) does not automatically invalidate the SaaS model; she emphasized that SaaS success still depends on workflow understanding, governance, observability and delivering concrete customer value, and that the “jury is still out” on whether AI agents will replace it outright [12-23][30-38].
– The evolving nature of IT services work – K. Krithivasan argued that AI will not eliminate system-integrator roles but will shift emphasis toward requirements-engineering, context-engineering, validation, security and cloud-adoption; the volume of work will grow rather than shrink, creating “more interesting work” [46-53][58-70].
– Infosys’s AI services opportunity and IP strategy – Salil Parekh described a $300 billion AI-services opportunity across six focus areas (e.g., AI engineering, legacy modernization) and highlighted Infosys’s proprietary “Topaz Fabric” IP layer that abstracts foundation models and agents, signalling a move from pure “builder-for-hire” to owning AI stack IP [79-88][98-102].
– HCL Tech’s positioning in the AI stack – C. Vijayakumar explained that HCL leverages its product business and custom silicon capabilities to build enterprise-grade solutions that bridge the gap between foundation models and practical use cases, while deliberately avoiding a hyperscaler role and focusing on solution-centric IP [108-118][124-127].
– Skilling, democratization of AI and national digital public infrastructure – The panel stressed that AI must be made accessible to blue-collar workers and MSMEs, requiring new curricula, community-level training, and a DPI-style AI infrastructure (agriculture, health, education) to uplift productivity across the country [135-147][157-176][183-192].
Overall purpose / goal of the discussion
The session was convened as the closing panel of the AI Impact Summit 2026 to assess how generative AI will reshape India’s massive IT services ecosystem, to debate the sustainability of existing business models (SaaS, services), to outline strategic responses (new service lines, IP creation, partnerships), and to chart a national skilling and infrastructure roadmap that ensures AI-driven productivity and job creation for both white- and blue-collar segments.
Overall tone and its evolution
– The conversation began with a formal, probing tone, as the moderator posed a challenging market-valuation question to Arundhati [11-13].
– It then shifted to a balanced, analytical tone, with panelists dissecting technical and workforce implications (Krithivasan’s and Salil’s detailed explanations) [46-70][79-88].
– When discussing corporate strategy (Infosys, HCL) the tone became pragmatic and forward-looking, highlighting concrete IP initiatives and partnership models [98-102][124-127].
– The later segment on skilling and public AI infrastructure adopted an optimistic, inclusive tone, emphasizing democratization and national-scale impact [135-147][157-176][183-192].
– The moderator closed with a hopeful, rallying tone, projecting AI as a catalyst for massive job creation and a “Vixit Bharat” future [312-317].
Overall, the discussion moved from cautious skepticism about market hype to confident optimism about India’s capacity to harness AI through strategic innovation, skill development, and public-sector support.
Speakers
– Moderator – Session moderator for the AI Impact Summit 2026. Role: Moderator of the panel discussion. [S13]
– Amitabh Kant – Host and moderator of the panel. Role: Moderator (referred to as “Mr. Amitabh Kant”). Expertise: Indian IT industry, AI policy. [S6]
– Arundhati Bhattacharya – Former SBI CEO and current technology leader. Role: Former Chairman & MD of State Bank of India; now a tech leader focusing on SaaS and AI. Expertise: Banking, technology, SaaS, AI. [S16]
– Salil Parekh – CEO of Infosys. Role: Chief Executive Officer, Infosys Ltd. Expertise: IT services, AI services, digital transformation. [S9]
– K. Krithivasan – CEO of Tata Consultancy Services (TCS). Role: Chief Executive Officer, TCS. Expertise: IT services, AI-driven workforce transformation. [S11]
– C. Vijayakumar – Senior executive of HCLTech. Role: Senior leader (often referred as “C. Vijayakumar”) at HCL Technologies. Expertise: IT services, hardware/AI chips, enterprise AI solutions. [S18]
– Navneet Kaul – Audience member who asked a question about AI-created jobs. Role: Audience participant. [S5]
– Audience – Various members of the live audience who asked questions (e.g., Mania Sharma, Devika Rao, Kishla, Harswar, etc.). Role: Audience participants. [S1]
Additional speakers:
– Christy Varshan – Referred to as “CEO of TCS” early in the discussion (likely a mis-naming of the TCS CEO).
– Christy Wilson – Mentioned as “the biggest employer in India,” presumably a senior executive of a large Indian IT firm.
– Mania Sharma – CEO of Mono AI, a young entrepreneur seeking mentorship.
– Devika Rao – Representative from the University of Leeds, interested in AI-creative education collaborations. [S5]
– Kishla – Audience member asking about skill development for current IT employees.
– Harswar – Audience member concerned about AI misuse.
– Mamanama Venkatana Rasimahati – Software architect and founder of “Startup Sanatana,” advocating culturally-aligned AI.
– Rupa Arvindakshan – Leader of Salesforce’s startup community, mentioned as a point of contact for startups.
The AI Impact Summit 2026 closed with a panel of senior leaders from India’s IT services sector, moderated by Amitabh Kant. Kant introduced the four panelists – Salil Parekh (CEO, Infosys), K. Krithivasan (CEO, TCS), C. Vijayakumar (CEO, HCL Tech) and Arundhati Bhattacharya (Senior VP, Salesforce) – and set the tone by noting that the industry was “at a point of disruption” [1-11]. He also highlighted that the Indian IT services industry “represents over 300 billion USD in market value and employs millions of professionals” [1-3].
Arundhati Bhattacharya responded to a market-driven narrative that AI agents could wipe out the traditional SaaS model. Amitabh Kant’s opening question referenced the recent ≈ 40 % fall in Salesforce’s market value over the past 12 months [11-13]. Bhattacharya warned that such headlines often over-state the impact because SaaS success depends on more than low-code generation; it requires deep workflow understanding, governance, observability, auditability and genuine customer-value delivery [14-23]. She noted that some of the capital flowing into AI-driven SaaS is “circular money” and that investors must read the fine print [24-28]. While acknowledging that current working models will evolve, she argued that the “jury is still out and may remain so for some time” on whether AI will fundamentally overturn SaaS, and that the ultimate test will be whether AI improves living standards [30-38]. When asked about startup support, she directed interested founders to contact Rupa Arvindakshan, whose details are publicly listed on Salesforce’s website [280-282].
K. Krithivasan, CEO of TCS, shifted the focus to the future of IT-services work. He argued that AI will not eliminate system-integrator roles; instead, engineers will move from writing code to orchestrating AI systems, emphasizing requirements-engineering, context-engineering, validation, cybersecurity and testing of AI-generated outputs [46-53]. He highlighted that cloud adoption in Indian enterprises remains only 30-40 % after a decade, meaning a long-tail of migration, data-estate rationalisation and model training will generate a larger volume of more interesting work rather than a headcount shrinkage [58-70].
Salil Parekh, CEO of Infosys, outlined the company’s view of the AI-services opportunity. He cited a $300 billion market across six focus areas – AI engineering, legacy modernisation, AI factories, AI agents, physical AI and AI-driven analytics – and presented internal data showing aggressive hiring: 20 000 graduates recruited this year [91] and 13 000 added in the first three quarters [92]. Parekh also described Infosys’s proprietary “Topaz Fabric” IP layer, which abstracts foundation models and custom agents, allowing clients to work with any model while retaining Infosys-built capabilities [98-102]. This signals a strategic move from pure “builder-for-hire” to owning a reusable AI stack.
C. Vijayakumar, CEO of HCL Tech, explained his firm’s positioning. He noted that HCL’s software-product business contributes about 10 % of revenue and that the company has built custom silicon – a two-nanometre chip – for a major technology client, giving it a high revenue-per-employee metric [108-113]. HCL’s AI strategy is to bridge the gap between foundation models and enterprise use-cases, developing IP that makes large models scalable for businesses rather than attempting to become a hyperscaler or to build its own foundation models [118-127]. This pragmatic focus aligns with HCL’s decision to stay “solution-centric” while partnering with major solution providers [124-125].
Krithivasan then turned to talent development, describing a workshop in the NCR where 1 500 schoolchildren, most with no technical background, built 1 500 apps in three hours using AI-assisted native-language coding [130-138]. He framed skilling as a “major national challenge” and said the workshop was part of a broader collaboration with the Ministry of IT to design AI curricula for universities [130-138].
Bhattacharya expanded the democratisation theme, arguing that AI must be made accessible to blue-collar workers and MSMEs. She listed the challenges faced by carpenters, plumbers, hospitality staff and Anganwadi workers – skill gaps, lack of job visibility, payment delays and weak community safety nets [158-166]. She suggested AI-driven platforms could certify skills, match workers to opportunities and improve quality of life for both workers and their customers [170-176].
Parekh linked corporate strategy to national policy by describing an emerging digital public infrastructure for AI that mirrors India’s earlier DPI achievements (Aadhaar, UPI). He cited pilot projects in agriculture, health and education that are already being rolled out with support from chip, data-centre and architectural layers, and noted ongoing work with ministries to make AI services affordable and widely available [188-192].
Vijayakumar warned that capturing the projected $350-$400 billion AI-services market will require a substantial increase in R&D intensity. He pointed to a trillion-dollar “physical AI” opportunity, estimating at least $200 billion of services revenue, and argued that Indian firms must invest now in labs, proofs-of-concept and solution-building before demand materialises [200-209][210-215]. He added that outcome-based contracts will eventually fund higher R&D spend, but a proactive investment is needed to stay ahead of the curve [211-215].
All panelists agreed that AI will be a net job creator. Krithivasan asserted that AI will generate many new jobs in India, albeit in different occupational categories [299-304]; Vijayakumar reinforced that while programming fundamentals remain essential, the critical future skill will be orchestrating AI agents, i.e., managing multiple AI agents, applying critical thinking and delivering outcomes at several-fold the speed of manual coding [283-297]; and the moderator closed with optimism that AI will help India become a “Vixit Bharat” by 2047, driving a $30 trillion economy and massive employment growth [312-317].
During the audience segment, Kant repeatedly asked participants to keep questions brief, limit themselves to one per person, and be direct, emphasizing gender-balanced participation [250-260]. Questions from young entrepreneurs Mania Sharma and Devika Rao prompted Bhattacharya to direct them to the Salesforce startup community contact (Rupa Arvindakshan) [274-280]. Queries about future job types and required skills were answered by Krithivasan and Vijayakumar, who both stressed the rise of orchestration, analytical thinking and AI-tool proficiency [283-297][299-304]. Concerns about AI misuse, such as disinformation, led Salil Parekh to reiterate the need for responsible-AI frameworks, governance, cultural alignment and ethical model training [306-311][262-267].
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.
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?
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.
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?
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.
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?
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.
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?
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.
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.
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.
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?
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.
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?
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.
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?
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.
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?
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.
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.
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.
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.
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.
Okay. Anyone at the back? Yeah, go ahead. No, no, please there. Yeah, yeah, the blue shirt. Get up and ask.
My name is Navneet Kaul. and I have a three -part question.
No, just ask one question. Don’t ask three in one. No, no, don’t ask three in one. Ask one question.
One question.
Yeah.
How will AI create jobs? What kind of jobs and what kind of skills do we need?
You’re asking the question which I’ve already asked.
I want the panelists to answer very specifically and directly.
All right. Anyone at the back, that side? Yeah, that gentleman there.
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?
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
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
okay so one last question to that yeah shoot in one line Just shoot.
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.
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.
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.
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.
Mr. Kristinasan.
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.
Sal.
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.
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.
An audience member raised concerns about whether AI democratisation would genuinely benefit small enterprises or primarily advantage large technology companies. Bhattacharya addressed this by emphasis…
EventSabharwal contends that the traditional hourly pricing model ($20-40 per hour) in Indian IT services will become obsolete as AI reduces workforce needs from 100 people to potentially 2-10 people. He a…
EventArundhati Bhattacharya from Salesforce highlighted how her company established an office for humane and ethical use of technology in 2014, reviewing every product before market release. She emphasized…
Event“AI will come, jobs will go, mass exodus will happen in corporates”<a href=”https://dig.watch/event/india-ai-impact-summit-2026/building-trusted-ai-at-scale-cities-startups-digital-sovereignty-panel-d…
EventThe 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 or…
Event200 years later, we are like, okay, let’s clean it up. Even in the Internet revolution, you know, we have the problems with social media, you know, mental illnesses, all kinds of things, good and bad….
EventKrishan positioned this challenge within a broader context, noting that the key lies in focusing on value creation and protection for clients, addressing complex challenges that require contextual und…
Event-Srikrishna Ramakarthikeyan- (Role/title not clearly specified, but appears to be from IT services sector based on discussion context)
EventDiscussion point:Evolution of banking services while maintaining core functions Discussion point:Evolution of work rather than job displacement Discussion point:Institutional evolution rather than r…
EventOur first major research vertical is in structured foundation. A field that a recent Forbes article estimates at a $600 billion market opportunity. Often overlooked, a vast majority of the world’s dat…
EventBlair presented evidence from surveys conducted with the World Bank and Intuit of 3,000 women entrepreneurs, showing that 40% are already using AI for customer access, marketing, and business processe…
EventIT clientsare keen to adoptAI technology, but the high cost is causing them to take a cautious approach, according to Satish HC, executive vice-president and co-head of delivery at Infosys. Infosys Li…
UpdatesDiscussion point:Global talent acquisition for Indian IP development Discussion point:Strategic pivot from services to product development
EventThank 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. …
EventThank you. Thank you for inviting me here. So it’s a very valid question. And I will not answer it in a very technical way because I’m sure all of you have covered all the aspects around technology, a…
EventPervinder Johar: Absolutely. So I think our focus is on what we call the physical infrastructure of the world. So when we talk infrastructure these days, people think data centers. When we talk in…
EventSo future of AI I think will depend on the market. We’ll also depend on the people. We’ll also depend on the trust in us. The institutions like the data protection, the institutions as well as the law…
EventArtificial intelligence | Information and communication technologies for development Garg frames AI itself as a possible digital public infrastructure that must be trusted, interoperable and shareabl…
EventSaibal argues that India is approaching AI with the same ethos as DPI – treating it as shared public infrastructure that can trigger innovation. This includes providing affordable access to compute re…
Event“It needs to be interoperable and shareable.”<a href=”https://dig.watch/event/india-ai-impact-summit-2026/building-trusted-ai-at-scale-cities-startups-digital-sovereignty-panel-discussion-moderator-am…
EventImpact:This comment fundamentally reframed the discussion from focusing on solutions to focusing on execution mechanisms. It challenged the entire panel to think beyond ideation to implementation, and…
EventThese key comments fundamentally shaped the discussion by challenging assumptions, introducing new frameworks, and grounding abstract concepts in lived realities. Arundhati’s accountability challenge …
EventThe discussion maintained a consistently collaborative and solution-oriented tone throughout. It began with formal introductions but quickly evolved into an engaged, practical conversation focused on …
EventThe discussion began with a formal, academic tone but became increasingly critical and urgent throughout. Speakers expressed frustration with the status quo, particularly the lack of meaningful divers…
EventThe discussion maintained a consistently thoughtful and collaborative tone throughout. While panelists acknowledged serious challenges and risks (declining public funding, regulatory bottlenecks, conc…
EventThe discussion maintained a consistently optimistic and collaborative tone throughout. Speakers demonstrated mutual respect and shared commitment to partnership, with practical examples and concrete i…
EventThe tone was thoughtful and analytical, with panelists offering differing perspectives in a respectful manner. There was a sense of cautious optimism about education’s ability to adapt, balanced with …
EventThe tone was optimistic yet realistic throughout. The panelists demonstrated enthusiasm about recent breakthroughs and near-term possibilities while maintaining scientific honesty about current limita…
EventThe tone was thoughtful and exploratory rather than alarmist, with participants acknowledging both the transformative potential and genuine risks of AI in education. While there were moments of concer…
EventThe discussion maintained a constructive and collaborative tone throughout, with speakers building upon each other’s points rather than disagreeing. There was a shared sense of urgency about the need …
EventThe tone was generally optimistic and forward-looking, with panelists highlighting opportunities for innovation and progress. However, there were also notes of caution about hype and unrealistic expec…
EventThe discussion maintained a consistently professional and collaborative tone throughout. It began with formal introductions and technical explanations, evolved into an enthusiastic presentation of pra…
EventThe discussion maintained an optimistic yet pragmatic tone throughout. While acknowledging significant challenges around infrastructure, energy, skills, and governance, speakers consistently emphasize…
EventThe discussion maintained a professional, collaborative tone throughout, characterized by constructive problem-solving rather than confrontational debate. Speakers acknowledged both the challenges and…
EventThe tone was consistently collaborative, optimistic, and forward-looking throughout the discussion. Speakers maintained an enthusiastic and inclusive approach, emphasizing partnership over competition…
EventThe tone is optimistic and collaborative throughout, with speakers sharing concrete examples of successful implementations and expressing confidence in achieving ambitious goals. There’s a sense of ur…
EventThe tone was consistently optimistic and collaborative throughout, with speakers expressing excitement about AI’s potential and India’s opportunities in the space. The discussion maintained an educati…
EventThe tone was consistently celebratory, inspirational, and optimistic throughout the discussion. Speakers expressed pride in young innovators’ achievements, excitement about India’s AI future, and grat…
EventThe discussion began with a technology-focused, optimistic tone about AI’s transformative potential but gradually shifted to a more pragmatic, human-centered perspective. The tone became increasingly …
Event“The AI Impact Summit 2026 closed with a panel of senior leaders from India’s IT services sector, moderated by Amitabh Kant, who introduced Salil Parekh (CEO, Infosys), K. Krithivasan (CEO, TCS), C. Vijayakumar (CEO, HCL Tech) and Arundhati Bhattacharya (Senior VP, Salesforce).”
The panel composition and moderator are confirmed by the transcript of the closing panel where Amitabh Kant introduced Mr. Salil Pareek, Mr. K. Kritivasan, Mr. C. Vijay Kumar and Ms. Arundhati Bhattacharya as the four panelists [S4].
“Arundhati Bhattacharya warned that SaaS success depends on more than low‑code generation – it requires auditability, adoption, deep workflow understanding, governance and genuine customer‑value delivery.”
The knowledge base includes remarks emphasizing auditability, adoption and the many pieces needed for an AI solution to work in an organization, echoing Bhattacharya’s warning and adding nuance about practical utility [S22] and about sustainable value creation depending on user adoption [S19].
“Amitabh Kant’s opening question referenced a ≈ 40 % fall in Salesforce’s market value over the past 12 months.”
Salesforce’s recent market performance described in the knowledge base shows the company’s shares soaring to a record high of $368.7, indicating a strong rise rather than a 40 % decline, contradicting the claim of a steep fall [S110].
The panel reached strong consensus on four core themes: (1) AI will be a net creator of jobs, especially for blue‑collar and MSME workers; (2) the traditional services and system‑integrator model will persist and even expand with AI engineering opportunities; (3) large‑scale upskilling and capacity‑building are essential to equip the workforce for new AI‑augmented roles; (4) AI must be developed responsibly, inclusively and with cultural relevance. These agreements cut across the digital economy, capacity development, AI governance and social development domains.
High consensus – the speakers largely reinforce each other’s positions, indicating a shared vision that policy, industry investment and education should focus on inclusive, responsible AI deployment rather than fearing displacement.
The panel shows broad consensus that AI will be a net creator of jobs and economic growth, but there are notable disagreements on implementation pathways: the role of system integrators versus product‑centric solution building, the degree to which market hype should be trusted regarding SaaS disruption, and whether the traditional services model is still viable. These divergences reflect differing strategic priorities among Indian IT firms and between industry insiders and external market narratives.
Moderate – while the overarching goals (AI‑driven growth, job creation, democratization) are shared, the speakers differ on key strategic approaches, which could lead to fragmented policy recommendations and varied investment strategies across the sector.
The discussion pivoted around three core insights: (1) AI will transform—not eliminate—existing SaaS and services models, as emphasized by Arundhati and Krithivasan; (2) the workforce will evolve, requiring new orchestration and validation skills, a point reinforced by Vijayakumar and Krithivasan’s skilling examples; and (3) India can leverage AI as a public‑good infrastructure, a vision articulated by Salil. These comments collectively shifted the tone from alarmist market speculation to a constructive, forward‑looking roadmap, prompting the panel to explore concrete opportunities (new service domains, IP development, R&D investment) and inclusive strategies (MSME empowerment, national DPI). The interplay of these thought‑provoking remarks shaped a narrative of optimism, responsibility, and strategic action for India’s AI future.
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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