Building India’s AI Talent Ecosystem with Sanjeev Jain
Exploring Wipro’s Strategy for Scaling AI Across Industries and Upskilling Employees
From upskilling employees to driving innovation, AI is revolutionizing the way companies operate. In this episode, Sanjeev Jain, Member of the Executive Board and Chief Operating Officer at Wipro, shares how the company is preparing its 240,000 employees for the future of AI. From creating personalized learning paths to integrating AI into business operations, Sanjeev discusses Wipro’s approach to AI adoption and the broader impact on the workforce. He also highlights India’s growing role as a global AI talent hub and how the country can stay ahead in the race for AI expertise. Tune in for an in-depth conversation on the landscape of AI in India and how businesses are gearing up for the future.
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Debjani Ghosh: I do believe that AI needs India. Because one of the biggest problems with AI, I mean, given the kind of investment that has gone in, the voices questioning returns is going to get louder. And justifiably so, right?
This is where the world has to start thinking about to get the kind of returns that is needed to justify the investment that's going into building AI. We have to drive population scale deployment. That's the only way you can get these kind of returns.
I think India is one country that has figured out how to crack that. This is NASSCOM Conversations, hosted by Govindaraj Ethiraj.
Govindraj Ethiraj: Hello and welcome to NASSCOM Conversations. The big question today is, how do we scale the next billion plus people in the age of artificial intelligence? There are a lot of things that companies and individuals can do.
Educational and training initiatives necessary to prepare a billion people for a future AI-driven economy. The question that you could ask as an individual is, are core tech courses and foundational skills still relevant for students or educational institutions who need to adopt a newer and more balanced approach to scaling future generations? So let's look at it from a company's point of view and a particularly large one at that.
I'm joined today by Sanjeev Jain, member of the Wipro Executive Board and Chief Operating Officer based in Bangalore. Sanjeev is responsible for improving organisational and operational efficiency to drive sustainable, profitable and delivery-led growth with client centricity at Wipro. He also leads the functions of global business operations, delivery excellence, IT, information security and enterprise risk management.
He's worked for over 30 years in leading large, diverse teams and scaling up global capability centres, deploying Lean Six Sigma and business transformation. So let's talk about Wipro and how is Wipro equipping its employees and keeping up with the disruption artificial intelligence is causing in the technology landscape.
Sanjeev Jain: Out of the 240,000 employees that we have in Wipro globally, 230,000 have already completed what we call Gen AI 101. And what 101 does is creates an awareness to every employee on not only AI, but we believe that the responsible usage of AI is a very important component of AI. So we have all gone through it, including our senior management, including some of our board members.
That is one. Second is, having done the 230,000 Gen AI 101, we started launching advanced learning pathways. It's natural curiosity for human beings.
Our employees started asking after 101, where is my 201, 301, 401? So we now had about 44,000 of our employees who are in advanced AI certified category. That has been a significant achievement for us.
And as we went through it, you would understand Go is, it's not one size fits all. You have to get into persona-based certifications. When I say persona-based, if you are in sales, if you are in a healthcare industry, if you are in financial services.
So we created almost 40 plus persona-based learning pathways. Okay. So that we have folks on domain knowledge and relevant AI infusion in that.
To do this, how did we go about it? Step one, we created an AI academy. We need an AI academy internally to withdraw, who actually could curate the content, launch this learning pathways, and then get this training cascaded to all our employees.
It has been on a e-learning module. We also partnered with a lot of our hyperscaler partners. We have strong partnerships with Microsoft, Google, IBM, Amazon, Nvidia.
So we actually work as an ecosystem, leverage each other's learning modules, and that helped us bring it to life. In addition, what we have done, and this is all learning, okay, as we go around, we learn every time. So a lot of our employees also wanted to do much more deeper learning and certifications.
So we have tied up with the Indian Institute of Science, Bangalore. And that's a very unique programme, where actually we have an online masters in AI and data science. So that means Wipro employees will be assessed by IISC.
There is no dilution of standards. They will go through the same aptitude, the same knowledge assessment that they would do for any other candidate they take. And then Wipro will enable flexible work-integrated learning programme with IISC over a period of two to three years, where our employees will graduate.
The undergraduates will enrol and graduate as masters. So I think to me, these are multiple things we have done. I would say we are still learning, what more to do.
Govindraj Ethiraj: So companies like Wipro are obviously rolling out workshops, programmes, and courses, which are aimed at their employees and upskilling them and reskilling them. But what are the learning outcomes? Who are the people who are being addressed across the spectrum?
And how do they receive this training differently if they do? And how are AI tools themselves being used to optimise learning and processes?
Sanjeev Jain: So as we evolve in this, we are talking to our clients. We are talking to our partners. We are understanding wherever clients are going.
There are clients who would like us to do some use cases, for example, in financial services, fraud detection, as an example. Someone in healthcare may want us to do something on claims processing. Within our own company, if I take Wipro as a client, zero for ourselves.
In my own company, I would like my HR function to really use AI for real-time employee touch processes. We may want to standardise or automate job description creation, background verification. We may want our sales team to have content creation, which is very personalised to our clients.
IT will want to have helpdesk, right? Why do I need an agent in helpdesk? My level one support could be done out of helpdesk.
So these are ideas that are actually coming from our employees as well. As they're getting trained, there's a huge ecosystem where the ideas are pouring in. And we are able to do that.
And the way we have defined AI, now we have a little more sharper focus going, as I was saying. AI is three components for us. It's all about mindset, skillset, and toolset.
Okay? When I say mindset, that's what I spoke about. Where can I apply mindset?
Which industry? Which function? So it has to be constantly on the back of our mind.
Do I need a human to do this? Or can I augment a human to do it better with AI, right? Something like in a flight you have a co-pilot.
So similarly, we kind of add a co-pilot to your job, make it efficient, plus innovation, right? Human has to do innovation. Repetitive tasks is efficiency.
So combine the power of the two. That's about mindset. When it comes to skillset, I spoke about all the certifications, all the learning paths, learning journey.
There's a plethora of learning paths we have now. And I'm sure it will evolve based on what we see in the marketplace. Third is on the toolset, which is very important in my mind.
When I say toolset, what are the tools I can give to our associates? For example, Microsoft has this GitHub co-pilot. Google has Code Assist.
Amazon has Code Whisperer, right? There are many and more AI tools that are emerging in the market. OpenAI has a bunch of tools.
So basically, we are really encouraging the use of the tools. So the combination of mindset, skillset, and the toolset comes together to really have, you know, people at Playground to play with, do proof of concept, working with the clients, working with partners. I think that's how we see the evolving ecosystem of this.
Govindraj Ethiraj: So looking from the outside and then into the inside, how has Wipro, for example, incorporated AI into its own systems? And this is very important because herein lie the lessons for other companies as well, whether you're in IT or not in IT, because it's also where, in some ways, AI rubber meets the AI road. And let's understand how Wipro is using AI to map out additionally learning paths for its talent and what are the benefits that arise out of that.
Sanjeev Jain: When we work with clients, there's a lot of partnership and collaboration required because many times we are working on the client systems, client platform. It could be wealth management. It could be retail and the product catalogue management, pricing.
When you spoke about manufacturing, it's our predictive maintenance. It could be supply chain planning. So there are many, many use cases that we are coming across.
Now coming to me, I come back to Wipro as a client zero because for us, that is in our control. So we have many live cases today. So for example, Govind, if I want my payslip today, on the system, I just have a chatbot.
I just say payslip for this month. It just mails it to me. If I want to process my leave, I have a chatbot who does it.
Earlier I would have had to go somewhere, log in, download or send an email to someone. So there are many use cases where our expense processing, all the travel reports expenses, all our lease processing, all our queries with HR, queries with IT help desk, I think have actually gone live. We are actually seeing real benefits of these cases in production today.
So it is real here and now. That's very important because people have to feel the power of AI going live. It's not just a theory anymore.
And once they know, I think they are getting more advanced now into getting structured data and unstructured data together. For example, let me tell you, we have now embarked on a talent marketplace, having such a large company, 240,000 you can imagine. We want to make sure we are, in my mind, uberizing our talent marketplace.
What do I mean by uberizing our talent marketplace? There are a set of jobs, demands that come and there are our employees. So I have to marry both, right?
So what we have done is we have asked each one of our employees to update their profiles. Once you update your profile, you can be matched to the next job that you want and you can define your career aspiration. You could say that going this year today, going wants to be there tomorrow.
And the AI engine will actually match based on your current profile and current skills, the desired skills. It will give you a learning path. And then you follow the learning path and you apply for that job.
And then once you're selected, you can move. So these are, to me, examples people are seeing that it's helping them in their career aspirations. It's helping them, drive them to a learning path which they would have been blindsided.
Even today, our kids ask after 10th, what to do after 12th, what to do after engineering, what to do. So we're trying to fix that gap to actually help people define their career ambition and enable them through various programmes that we have to meet their career aspirations.
Govindraj Ethiraj: And then the inevitable question. If AI is replacing and eliminating some kinds of job roles, what happens to those employees and how do companies plan ahead? How do companies structure their organisations going forward knowing that these organisations or their organisations will not be the same or at least will not be what they were earlier?
Sanjeev Jain: So I would say that the structure, when I say structure, we would have added some AI-specific practises for technology. We would have added more AI talent or we would have upskilled more talent. Yes, there have been reduction in some of the roles which were more repetitive, which were more into, code testing, maintenance, call centres, but those roles have reduced.
But to me, those employees have been upskilled and moved to roles of higher capability. So it's both, right? Employees moving to higher order roles and adding new capabilities in the business in line with the technologies that are emerging.
Govindraj Ethiraj: So we have some understanding of how Wipro is using artificial intelligence within its own organisation and to some extent how organisations outside are doing it. But what are the big client requirements at this point of time and how are they incorporating AI into their systems and how is AI a value add? What are the industries and sectors where AI applications become more apparent and evident and something that people can experience, particularly you and I?
Sanjeev Jain: So one is in terms of financial services. Complete imagination in terms of how do you manage your wealth. So it's absolutely looking at your portfolio, looking at your 360 degree, your entire portfolio with the financial services industry, not just the banking system, right?
And then coming out with recommendations that help you plan your wealth better. I think those have been significant, I would say, life cases for us. Then into predictive maintenance, right, with manufacturing industry.
So you see something happening somewhere, it could be an incident and how could you have a faster response time and make sure that you have the systems to manage it proactively. So these are, I would say, significant use cases. Even in healthcare, we have seen there are times when our healthcare industry will have to launch products faster or make changes faster.
So it means that we have to deploy our tools, the skills, the tool set, which I meant, to drive productivity. Productivity is not just to reduce the headcount, but productivity is to do it faster. Right?
So you have to reduce the turnaround times so that the products can be launched faster. So we have seen those use cases where actually they're actually adding to the faster rollout and faster revenue realisation for our clients. Like more of a top line versus we keep thinking of this as a cost reduction or a bottom line initiative.
And that's where we are seeing that happen.
Sanjeev Jain: To put it in simple words, the way we think this will happen is A.I. will have three components. Think of it like any other infrastructure project. When you want to create infrastructure in the country, you need a highway, then you need vehicles to go on it and you need services like your restaurants or restrooms on the way.
So you need all the three. Similarly for A.I., we need an infrastructure which is your data centres, which is your compute capability and then you need a lot of your software which is your platforms, your products and you'll see that with a lot of e-commerce sites, your agri-tech, health tech, fintech, all that has come in. And then you need services.
Services is where actually we need talent. End of the day, all this needs talent. A.I. will not happen on its own. There is a human in the loop. There is a human that you need definitely in all this. So these three will come together.
So the way I see that coming is, of course, a lot of us across the industry will play in all the three areas, whether it is infrastructure with data centres, whether it is in having our platforms, products, to help the clients or to really have the talent. All the three, it's a playing field for all the three areas for us. The way I see coming is, India today has about 5 million software engineers and we churn about 1.5 million every year. Out of that, we have about 400,000 or so, of which about 425,000 and odd is about AI specialised folks. It's roughly about 9 to 10 percent. That is growing to about 6 million software engineers and about 1.25 million AI, right?
So you can see that the AI number is going to triple and the software engineers are going to be increasing at a rate of 25 percent. So to me, the way I see it is, the industry will grow with the digital adoption. The need for software engineers will grow and within the software engineer, the need for AI skilled engineers will actually triple.
So what do we do about it or what are we doing about it today? Apart from each company will do what they have to do. But I am saying together with Nasscom, we are actually having this great programme which was launched a few years back called Future Skills, which is now called Future Skills Prime in the new avatar.
So we have identified few niche technologies as part of this Future Skills Prime technologies like RPA, IoT, blockchain, AI, ML, data science, cloud computing, cybersecurity, etc. And these are being provided, the curriculum of these is being provided to 100 plus colleges. And the goal is to train the faculty on these.
So ultimately, the students get access to these courses, get the guidance from the faculty and they're more industry ready when they graduate. We have seen significant win here. We have seen that with this programme along with NASSCOM that we have done, we have had about 3000 plus faculty who has been trained across 100 plus colleges.
About 65,000 students have taken the courses and about 25,000 have got certified. And this is actually helping in increasing employability of students. And I'm not talking about private colleges or metro, right?
And this I'm talking about the tier 2 and the government institutions. I think we need that kind of mass pool to come out of India that can really help the world. See, today, India is the second largest provider of IT talent to the world.
As I said, we have 5 million folks. We just recently surpassed US. US had 4.5 million. China has 7 million. So we are actually on a great path here and it's for us to take these steps to really democratise AI learning. Industry has to work very closely with academia.
And really, we are in the process of setting up centres of excellence in the academia for some of these niche technologies where the intent is to just provide the capability and where the students join is their aspiration. There is no obligation for anyone to join a particular company if you are building that capability.
Govindraj Ethiraj: So India has the manpower and now we're building out the learning and skill set to be a global competitor and service in the AI space. So in a broad sense, courses and curriculums are often not on par with the current job market and particularly with AI. So there is a challenge for both the people who are creating and doing the skilling as well as, of course, on the demand side.
So to bridge the gap, as Sanjeev Jain has said, industry and academia need to walk the path together holding hands quite tightly to stay relevant in this fast-evolving field.
