Building Trusted AI at Scale Cities Startups & Digital Sovereignty – Panel Discussion Moderator Sidharth Madaan

Thank you. We’re at a very defining moment in the history of work. On one end, we’re seeing new possibilities, new productivity unlocks, new jobs being created. And on the other, there’s a lot of growing anxiety around what would it mean and the kind of disruption it will bring to work, especially the knowledge work, the white collar jobs, as they say. Let me start with Mr. Bagla. How should businesses and policymakers think about this transition?

It’s very interesting. First, I don’t think any of us have any answers. We will try. The fundamental point, you know, and I remember when I joined banking and I take you back to 1986, we went for training and the first thing we were told that the only job which will never change. And is stable and safe in the banking world is that of the teller. You have to go get your. The first job to go when digitization happened was the teller. Because you started taking it out of the machine. Now the challenge which remains for all of us is that we are entering into an era where there’s no playbook. What is it which it is going to move into?

So we’ve got to put it into time spans if I look at it. What is going to happen in the next 5 years, 10 years and then after that no one knows. I think next 5 years is going to be one of the toughest times of disruption. How many of you have ever been laid off? Excellent. You’re the only one ready for the next 10 years. That is the most important thing going forward. And I think one of the things which we are trying to do at the Aatil Tinkering Lag, because I have a team here, Dipali is here and with her she is the one who is putting it. At the school level. we are trying to bring AI and tinkering.

The idea of innovation that you… And what I’ve also started seeing as a trend from there that many of them may not be looking at going to a very formal education system, but getting into a job profile there and then. And it’s more task -oriented. So I’ll start off with this, and I know we’ll go on with the questions. But let me end here. But as I see it, I think that disruption in the next five years and 10 -year period will be a lot for all of us to learn psychologically on how can we be without a job when we are asked. That’s the first most important point. And then tend to see what is it which we can pick up to take on next, because that’s where we all talk about will be that reskilling piece coming in.

Radhika, you have done the research recently on this. Let me ask the same question to you. But let me add, are we overestimating near -term job loss? Are we overestimating the long -term transformation which it’s bringing?

somewhat yes first let’s let me also somewhat endorse what Mr. Bagla said I think that this is there’s immense uncertainty and we really do need to have more granular and more nuanced understanding of what this transition actually entails because you know different segments of the population different segments of the workforce are going to be impacted differentially by this transition now there is this narrative of this doomsday prediction and we’re all going to lose our jobs and we’ve got to be psychologically prepared for losing our jobs I think yes it is indeed the case that most of our jobs are going to be exposed to automation and to gen AI but it doesn’t mean that our jobs are going to be destroyed or that they’re going to be completely dispased because if you go and look at the academic literature and a lot of the research the IMF that the managing director was spoke in the session before at the ILO we know that an occupation essentially entails many different tasks it’s a bundle of tasks now there are some tasks in those occupations which are going to get automated.

And there are others which are not going to be done, not going to be. Now, last year, the ILO, late last year, the ILO actually put out a study where they looked at all the different occupations and they did a gradation of the extent to which they were exposed to automation. Now, if you look at the share of jobs where almost all the tasks had a high likelihood of automation and therefore were likely to be displaced, that number was actually somewhere between 3 % or 4%. And that’s a global average. If you actually break it down and look at it in countries with low income, middle income, it was even lower. In high income countries, that was close to 6%.

But the share of jobs where some tasks were going to be automated, but that also meant that there was more scope for freeing up time to bring in new tasks, enhance their productivity, was actually quite high. That was about 20 % of the jobs. So what I’m saying is that in order to manage this transition, there are two things we’re going to have to do. One, of course, it is indeed the case that a small proportion of people will lose their jobs and they will be displaced. We need to think about how they are going to be absorbed in other sectors. And that, to my mind, is going to require more than skilling and reskilling. It’s also going to require thinking more carefully about industrial policy, about macroeconomic policy, trade policies, labor market policies, in particular, social protection.

But for those who are actually in the middle, where some tasks will be automated and others will not, we need to think carefully about how those occupations can actually augment their productivity, how they can engage more meaningfully with Gen AI and enhance their productivity. Because remember, all of this then also has an implication that enhanced productivity, which has an implication in wages and prices. All of that also boosts demand in the economy, which then drives more job creation and investment. And that virtuous cycle of growth, investment, job creation. So I would say that, you know. So, yes, support those who are, you need policies to support those who will be displaced, but at the same time, augment productivity in the other jobs, which are somewhere in the middle, and there is some buffer against automation.

Sanjeev, with Naukri, you have a front seat to what’s happening in this space. Like, are you seeing structural shifts?

You know, there’s a lot of feedback we get from media, from social media, from panelists. But you know what, as of now, Naukri growth has not been impacted. So on the ground, we are not seeing a reduction in hiring. But at the same time, we are careful and cautious and say, what will happen now? Answer, I don’t know. Right. And the truth is, nobody knows. And anybody who is telling you he knows is… is wrong. They don’t know. So because there’s so much happening, and it’s so chaotic, that you can’t really figure out, right, what is going to happen. Right. But I’ll go back in history a bit. 1982 I was in college Deepak was in college we were in college together actually in Delhi University and these two new companies were set up Aptek and NIIT saying we are going to teach you how to use a personal computer nobody cared a few cared but it was not mainstream it was not ok so most people didn’t care by 1985 you know it had become somewhat a requirement that if you go and learn how to use a computer maybe your prospects of getting a job go up or if you got a job maybe you will become more productive at your job in 1985 to the Rajiv Gandhi government the government said we are going to introduce computers in banks at that time banks mostly public sector banks the All India Bank Employees Association which is one of the most powerful trade unions in the country then went ballistic so you got to lose jobs you are going to lose jobs government said never mind we are putting them in anyway so computers came into banks they weren’t used for a while then they began to get used and guess what nobody lost jobs people got more productive people got MIS that they weren’t getting earlier they served their customers better nobody lost jobs so new technology increased productivity did not cause job losses now I am not saying that is exactly what will happen this time but you know maybe now will some jobs or tasks be get automated possibly so but will others come up almost certainly yes so what I tell individuals never mind policy guys and governments and you know multilaterals what I an organization what an individual is look you don’t bother about will jobs be lost will my job be lost will I lose my job and will I get a new job will I get a new job Then my answer is simple.

Learn how to use three AI platforms every quarter. By the end of one year, you know 12 AI platforms. Believe me, you will be employable. I’ll give you an illustration of this. I finished business school in 1989. By then, I had finished college. I had done three years of work in an ad agency and had done business school. That’s very important year. Why is it an important year? Because the classes of 1988 and 1989 were the first two batches to have graduated from the IIMs who had actually used PCs at the IIMs because the PCs came into the IIMs in 1987. So I walked into my job as PC literate. There were two PCs in the marketing department at the company where I was working.

All the other people were senior, very highly qualified. IITs were senior. But I was the only guy who was PC literate. Believe me, if they were sacking then, I would have been the only guy who was PC literate. in that department, I would have been the last to go. I knew how to use that technology. So if AI is coming, it has come. It is inexorable. It is relentless. It will come. It has come. Learn how to use it. So if you don’t do AI, AI will be done to you.

Very insightful. I think if you optimize local optima, we are somewhere going to find the global balance. Prashant, with that, let me Radhika referred to, you know, job is a bundle of tasks. Tasks will get disrupted. But the role might shift for all of us. Let’s make it real. You are closer to the medical community. How does the role of a doctor or a nurse change going forward? Can we envision an AI doctor in the future? What would the job look like?

I think healthcare is slightly different from a lot of other industries. I think it is highly regulated, number one. So I think about three things from a healthcare perspective. From a futuristic perspective as well. One is that we have to be able to able to make sure that we are able to able to the capacity is limited especially if you’re talking about the global south right india has i mean we operate in the radiology ai space we automatically interpret radiology images with ai and if you look at india india has got one radiologist for every hundred thousand people which is about and us has one radiologist for 10 000 people kenya if you look at kenya has the same number of radiologists as marginal hospital so um and and many african countries have like one or two radiologists very very small number right and so there is not enough capacity to meet that demand so when you look at job loss per se i mean there is not enough capacity to meet the demand that is there for health care so in many ways i mean you’re not going to lose jobs it is going to upskill people health care workers and doctors who are on the ground supporting patients so that’s that’s one is about upskilling uh people right and supporting uh making health care workers able to uh support patients maybe there is an ai doctor that can do primary care i mean primary care is something that can be significantly automated i mean you’re looking at three things that you’re doing in primary care one is to understand patient symptoms so ai can prompt the patient can understand what symptoms they might have Second is to recommend tests, which again, AI can identify the right tests and recommend what testing should do.

And third is around diagnosis and treatment, right? Again, which AI can potentially do or even sort of triaging to the specialist. So these are things which AI can do. So I think in general, AI is going to upscale doctors and healthcare workers to do better and meet more patients and save time, right? One of the things that we are seeing across the world is you are using AI agents to scribe and take notes of the doctor -patient conversations, which is a task which, I mean, if a doctor is meeting 40, 50 patients a day, and after every one of those conversations, they have to write down, take notes from that conversation, AI can do that automatically. We use that, we use note takers in our meetings.

Why can’t you use note takers in a doctor -patient conversation? So we are seeing that, I mean, upscaling sort of one area. Second area, I think, which is going to, at least from a healthcare perspective, I see is a tough one is around regulation, right? Everything that… AI does today in… healthcare across the world. In the US, it’s FDA cleared. You have to get FDA cleared to be able to actually provide a clinical decision support to a doctor. So that is not going away right now. And that FDA equivalent, India, CDSCO, every country has its own regulatory body. So you have to figure out how to cross that barrier. That hurdle is still there. And that is not something that is going away right now.

And that brings me to the third point, which is that today, I mean, if a doctor is taking a decision on a patient saying that this patient has tuberculosis, for example, or lung cancer, or any of those, right, they are taking liability for that decision. And till AI is going to be able to take that liability, that is going to be a decision that doctors will make. And so what I see today, and for the next at least five to 10 years, is that AI is going to be supporting doctors in making better decisions. It is helping, it is providing all the data in the right format. For example, what we do is we are able to bring in the right data, and we are able to bring in the right data.

And so that is going to be bring data from electronic medical records, PAX, basically imaging data of the patient, pathology data of the patient, bring all of that together into one place for the doctors to help. diagnose better. So you’re providing that support to the doctor in making a clinical decision and also providing treatment planning, sort of automated treatment planning of treatment plans, which they can use to then provide the treatment plan for that patient. So it is a supportive tool and I see that for the next several years, AI is going to be upskilling doctors in providing better care and providing more care to patients, especially in the global

If, you know, multiple areas or multiple playgrounds where action is happening, like there’s startups, there’s infra, there is energy, you know, yesterday our Honourable Minister spoke about the five layers of AI. Where do you see most amount of action needed? Like if you had to pick one area to double down on, what does India need?

Within the AI stack or generally?

Within the AI stack.

I think on the application side is where we will have… a very interesting play on actually the small ones and actually getting them executed. That’s where we’ve had some strength in any case. But let me just step back a minute beyond this question, if I may, with your permission. You know, one very interesting thing. Yesterday, the plenary, I was sitting right there and next to me was a professor from an Ivy League. Let me not just say it, but one of the top five Ivy Leagues. And I was asking the professor, when are you going to go back and start teaching? Because he was taking a break to do it. He told me a very interesting thing.

One of the big things which is happening in this university is that the master’s students are feeling that they don’t longer need to pay that big tuition fees because they are no longer getting challenged. Because AI is giving them all the answers. Now see the repercussion of that. When we say that we have a million people coming into the job market every year, every month in India. that is because we go through a bachelor’s and a master’s and then they’re coming in so let’s say like sanjeev and i started 22 23 24 one of the most interesting elements which was pointed out was that maybe that age barrier no longer remains you may have somebody who’s 13 year old and ready to do a job in a task and that is another trend which might just picked up because the moment you’re going to see a complete change in the educational system think of two industries which have so far withstood or been having a pushback on the huge change which can come to them the financial industry is one and the education industry but now they’re being challenged on it in a big way you’re four years master of two years master’s four years bachelor’s maybe nobody needs to do it but they’re being challenged on it in a big way you’re four years master of two years master’s so see the number of people which will get into the task creation and the task doing force that is another element which we’ve not yet been able to quantify

very insightful answer jiv this will allow me to go back to the first question i asked you are you seeing a structural shift like for example are people now instead of asking degree pedigree asking for more afluency basic skills instead of

oh i people talk about it i’m not sure how many people actually do it right at the end of the day if you’ve got a credential it matters see uh what does an iit degree mean at what level it means you’ve learned something another level it means boss you were you you have demonstrated commitment to a prepare to get it so you you are able to work hard you know some level of physics chemistry maths that’s how you cleared the entrance exam right and you were at the top of the academic heap and that’s how you got into the place in the first place So when we go to IIT to recruit, we don’t hire for the specific knowledge they got at IIT.

We hire for the fact that it’s a fantastic filter on several accounts, right? Also, right? And to some extent, you know, a 13 -year -old, you know, ready for work. Look, business is about people. Business is about people and managing people and working with people and selling to people and, you know, running teams, being a good team player, being a good leader. So that comes with at least some years of experience, some years of, you know, maturity, right? So can I be a forex trader in front of a computer at 16? If I’m technically good enough, answer is yes. But can I be a forex trader in front of a computer at 16? Can I lead a team of salespeople out in the field?

who are calling on clients who are 20 years older than me, I don’t know. Maybe you can, maybe you can’t. So, you know, some stuff, I mean, people are still people.

Nadeka, what does it mean for the gig workers and the temp workforce? And, you know, the labor laws were written long back. What would it mean as we move ahead? How should we even think of the labor laws or the role that the temporary labor brings in? Like, we are done with the age of working in the same organization for 30 years, as I just mentioned.

So you’re talking about temp workers and gig workers. And before I answer that more directly, I just want to reflect on the comments that have been made by the other panelists. You know, the conversation that we’re having here on displacement and productivity enhancement, including the comments that I made earlier, we’re really talking only about 10 % of India’s workforce at this point. The conversation on AI is right now, you know, today we are having this summit in the global south. And the Global South still, vast proportion of the workforce is in the informal sector. For India, 45 % of its workforce is still in the agricultural sector. 55 % of the people are self -employed. 95 % of employment is in enterprises with less than 10 workers.

So, you know, that part of the conversation, we are completely missing out in the future of work. And I think we need to bring that in here as well, because a lot of the gig work and the casual work that you’re referring to is essentially what we see in the informal sector. And for that sector, the risk is not excessive automation. They might completely miss the bus and not realize any of these gains or productivity gains from AI. So we also need to think more carefully about how all of this can enhance productivity in the agricultural sector. How there could be greater AI adoption amongst micro and small. All enterprises, which are basically the engines of job creation in India.

and that’s again going to require a lot more than skilling and credentials but also they’re going to need a lot of financial support for adopting AI they are going to need digital infrastructure access to broadband so on and so forth and now going back to your question on the changes in the world of work and labor regulations indeed there is no denying the fact that labor regulations have not kept pace with the changes in the employer -employee relationships we now live in a world of work where there is a proliferation of non -standard employer employment arrangements the platform economy is a manifestation of that as well and certainly there’s a need to update that at the ILO for example there is a conversation for two years which is happening on what are the kinds of conventions and recommendations that are required to bring decent work into the platform economy and of course India is leading in that conversation with the code and social security which seeks to provide social protection even to platform workers so that’s a very forward looking ambition.

Yes well we’re at time but I’ll just say that I think it’s a very important point that I think it’s a very important point to just end with one last question rapid fire one word maximum five second answer a lot of still unknowns what does success look like in 2030 what would you be proud of we’ll go in a row

most critical point when everyone works together the government the society the people the academia i think that joining the dots is absolutely core to seeing any element of success for anyone and last point i think the biggest benefit of the delta multiplier of ai is india or will be india

krishan i think success for ai is the world’s gdp growing at 10 or more by 2030

i think uh if there is net job increase which means the jobs lost if any are less than the jobs created i think that is success

i think an inclusive ai transition where we have better jobs, more productive jobs, and where the agricultural sector and the MSME sector have benefited from this transition and we don’t leave the informal sector behind.

With that, we’ll wrap this panel discussion. Thank you so much for the insightful comments.