Transcript Disclaimer: This transcript has been generated using automated tools and reviewed by a human. However, some errors may still be present. For complete accuracy, please refer to the original audio.
00:00:00 RIDHIMA BHATNAGAR: Welcome to this very special webinar brought to you by Economic Times and Nasscom, where we discuss the fascinating world of the business process management industry or the BPM industry in India. Now you speak to any leader within the BPM industry or space and they'll tell you one thing. That yes, India has solidified its position as a leader as far as the BPM industry is concerned. But. But really this is just the tip of the iceberg because the next chapter is going to be much bigger and better with the integration of technology and AI. Which means that one conversation that we need to have is how are organizations getting ready both from an employee perspective as well as an employer perspective. I'm Ridma Bhatnagar and I'm so thrilled to be hosting this discussion with a stellar panel who I will introduce in just a bit. So today we are going to discuss about becoming skilled ready. How do we navigate through the transformations that are happening in the BPM industry? So let's get straight to it. Let me introduce our stellar panel. Diwakar Singhal, Global Business Leader at Genpact, has been kind enough to take out the time and join us. Hi Diwakar. Good to have you with us.
00:01:17 DIWAKAR SINGHAL: Good morning, everyone.
00:01:18 RIDHIMA BHATNAGAR: We also have Avishek Chhatopadhyay, Executive Vice President, Global Delivery Head, Digital Process Operations at HCL Tech. Hi Vijay. Good to have you with us.
00:01:28 AVISHEK CHHATOPADHYAY: Afternoon and glad to hear you. Thank you.
00:01:30 RIDHIMA BHATNAGAR: We also have Naozer Dalal, CEO at Alldigi Technologies Ltd. Naozer, good to have you with us. And we also have Gaurav Iyer, SVP and Head of Digital Engineering and AI solutions, EXL. Good to have you with us, Gaurav.
00:01:45 GAURAV IYER: Nice to be here.
00:01:46 RIDHIMA BHATNAGAR: Okay, lovely. So we have set the context of what we planned to achieve as part of this conversation. Of course, the big question now is as the integration goes further, as the integration of technology goes further. Right. So we need to now understand how organizations getting ready, which means we need to understand what is the role of employees and employers at this point of time. So Gaurav, I just want to set a little context to try and understand when we say that India has solidified its position as a leader in the BPM industry. But if I just had to ask you, maybe a ballpark figure for us to just try and understand that the kind of penetration and integration that has already happened as far as AI in the emerging tech is concerned, how much progress do you think has already been?
00:02:32 GAURAV IYER: You know, I think that's a fantastic question, Ridhima. So you know, the BPM industry in India has actually been preparing for this for quite a while. If you think about all of us, we've invested in data and analytics and automation over the last 10, 12 years, right? So we've been preparing for this shift and obviously what's happened in the last two years has been fantastic in terms of the speed of development of AI. If you really think about it from the BPM industry standpoint, there are two kinds of people. There are people who are working on AI and there are people who are working with AI. So I think we've invested in both. We are a little ahead in terms of people who are working on AI. So we have invested in data and analytics, we have invested in engineering, we've invested in automation. So if you really think about the world, right? And if you think about the AI stack big, the technology has given us the box, but it still needs to get integrated into the workflows for any of our clients to use it, right? So the BPM industry, with our legacy of understanding the workflows, how business and customer outcomes are delivered, and understanding the data which are the bookends, is, you know, prime the place to work on the people who work on AI. So I think that's one pillar. The second pillar is just our teams who are working with AI. And I think that's the space where we've had to do a lot of work and there's still some work to be done. But I think from a training standpoint, from a skilling standpoint, I'm sure we talk about it, but functions like AI excellence, AI trainers, the hybrid operating model between AI agents and human agents, all of these are in order, very, very critical for our clients to deliver, you know, to actually get value from AI. And the BPM industry is primarily placed for that.
So I think overall, in terms of both working on AI and working with AI, the BPM industry will lead the, will lead our clients into the future. So that's why, you know, I think we're all very optimistic.
00:04:26 RIDHIMA BHATNAGAR: Well, it's always good to get a conversation on an optimistic note. Diwakar, let me bring you in the conversation. You know, every time you speak about the integration of any new technology, not just, you know, solely for the BPM industry, there is also a sense of slight panic and apprehension, right? Because one, there is always a panic of do we understand this technology? And the other always is, are our jobs going to be replaced? But what is really, really heartening to see in the BPM industry is that there is space actually being made for far and far more jobs. In fact, there is a recent survey that is being done by Nasscom themselves that says about 80% of these organizations are seeking professionals. And which means that new roles in fact will be created. As far as the emergence of this new technology is concerned. Would you say that's an optimistic figure that we are working with and would you actually say from an organization perspective that's actually correct?
00:05:20 DIWAKAR SINGHAL: Yeah. You know, the BPM industry, the way we know it today compared to what Genpact and we all pioneered about 20, 25 years back, has changed dramatically over the years. What we do today is nowhere close to what was being done at that time. So the industry, every industry evolves and the best industries actually embrace change. And I think that the best for the BPM industry, so called BPM, I say so called because the clients are looking for value and solutions. Doesn't matter what name you give, the best is yet to come. The industry has already evolved to a solutions headset, wave technology, analytics, data, process people, they're all bundled together to deliver value. And the industry has been on that journey for a while. The jobs, we all know some jobs will die as they do since the industrial revolution and some jobs will be created. So it's a question of reskilling, which is the million dollar question here, not about jobs per se. And frankly employees, people, companies, countries who embrace the change upskill themselves stand to game because what you can deliver as a combination of AI and the process and tech industry is far superior or will be in the future than what it is today. So I think the best is yet to come where we could bundle AI in the work we do.
00:06:56 RIDHIMA BHATNAGAR: I think that's very well put that you have to make way for the new changes because one, if you don't, somebody else will and then you let go of that lead that you have and also you understand the full potential of the opportunities going forward as well. Avishek, I want to bring you also in the conversation. As I said, the integration of any emerging technology is always a concern for any industry to try itself see where this is really headed. So I just want to understand, because we just said in context, first run, try and understand from an organization perspective what is the kind of integration that you see.
00:07:32 AVISHEK CHHATOPADHYAY: Yeah, thank you so much. So first of all, I think what we are right now is tip of the iceberg, right? So a lot of the focus has been in what we call as service acceleration. A lot of AI engine. AI has truly been around basic task and then Probably a little bit more around rule based automation. Right. And then probably elevating that towards some amount of personalization. What we have not seen yet is sort of elevating that to either create new products out of it, which is inherently been not possible. That's what we are looking at enterprises. So so far I think the focus on the service acceleration is around using data machine learning and then trying to integrate that with the workflow to deliver a service at a significantly low cost as well as speed to market significantly better. But that's primarily on the service ecosystem itself. What becomes interesting is as you now what we call as rearchitecting the whole operations and the organization structure, the volume of BPM will continue to shift. So we have always been speaking about domain and digital, but the volume, the transaction volume will continue to keep going down and the value quotient of the work will keep going up. Now what that means is there's going to be significant amount of new roles that gets created. We hear about prompt engineers a lot, but there's going to be a lot of focus around creating roles, around adjusting, refining, using domain to actually train those roles around building scenarios. So there was one way of the industry got trained around desktop procedures and SOPs and policies and now coming towards how do you build scenarios to actually do a what we call as deep reinforced learning. Those are the components that will come up and then how do you really create an explainability around it? Because there was certain amount of probably paths that you would give if a human error was made, but to an error that becomes sort of now a sort of a different paradigm in itself. So how do you start building that transparency and explainability? And there are resources and people who are looking at that, using different tools to be able to explain the decision around those model. So unpacking that service ecosystem again through a combination of domain and digital will continue to be important. But I think the real value will be how do you really improve speed to market, create new products out of this. And that's where the Indian BPM as well as the IT industry combined pick together to be able to deliver what we call a significant value to the ecosystem.
00:10:04 RIDHIMA BHATNAGAR: I think that's very well put. I really like the word that he said that there is some sort of rearchitecture that is happening as far as maybe a rejig or redefining the way we knew the BPM industry. Now let me also bring you quickly in the conversation. So when we talk about redefining the next chapter of the BPM industry, if you could just give me. Because today we're speaking about, you know, emerging skills, upskilling, reskilling, so on and so forth. If you could give me the top five areas where this rejig is happening.
00:10:33 NAOZER DALAL: Sure. Thank you. What we have seen in recent times, and it's only accelerating, is that customers are moving away from the FTE base or the time and material based ways of billing and significantly increased focus on value. The value created, the efficiency and how do we impact the end of business and customer outcomes. So as part of that journey, in my view, I think what will happen is we already used to automate a lot of workflows, but these are partially automated workflows. So I mean, that journey towards more intelligent automation or, you know, I mean, where we use rpa, where you use AI, you know, that will continue. So for example, you know, I mean, if I take an example in terms of say the FNA processes, you know, I mean, how do you further automate, you know, the, you know, using AI, how do you handle invoices, detect anomalies? I'll give you an example. I mean, you know, I mean, many of our customers are saying that now can you take, you know, because at all sec, we do a lot of employee claims processing. So can you take that to the next level by actually helping us detect fraud, you know, which sort of helps with the risk management part of, you know, I mean, the customer's business. So that's one example, you know, so we are trying to see how do we get, you know, some intelligent automation around it, you know, where we can get detect anomalies, you know, in terms of, you know, the claims which people may raise. What it also means is, you know, that we will have to continue to, you know, look at a coexistence, you know, So I mean, so the other issue which is happening is it's, it's, it's really not about, you know, man or machine, you know, I mean, we'll.
00:12:09 RIDHIMA BHATNAGAR: Have to look at it in silos, right?
00:12:11 NAOZER DALAL: Yeah. So what we look at it in terms of there are certain tasks which are more repetitive, you know, which, which can definitely sort of be automated, but there will be still a lot of tasks. And a classic example could be in the loan approval process, you know, where we again look at it, you know, so I mean, AI can, you know, rapidly analyze tons of bank statements, multiple accounts, a borrower, a potential borrower may have and provide the risk assessment, but the human officer will still be required because AI can't replicate understanding the customer's Unique requirements, the circumstances, and making judgment calls which is best to customer. So that's a classic case in bpm. We'll, you know, where it will continue to be a man and machine model, you know, to get an outcome. And an outcome in this case is, you know, ensuring that loans written don't turn bad, you know, a couple of quarters down, you know, which is a very, very key metric which even the RBI is driving for, you know, some of the banking we have. Yeah. So in this scenario, what we're looking at is treating AI as a smart assistant rather than, you know, just a tool, you know, and also, if I look at it that way, it's not about dividing the tasks, you know, it's about how do we multiply the capabilities, you know, with. With whoever is best suited, you know, to drive. Drive the customer outcome.
00:13:26 RIDHIMA BHATNAGAR: Sure, sure. So I think Naozer has actually covered a few points of what I understand. One, of course, he's saying the penetration of automation is going to increase far more. The other point that he's making is that we can no longer. We'll be silly if we see this as silos, as man versus machine. We have to far see both of them coexisting and seeing how this harbors, well, as far as the customer experience is concerned. What I also like Naozer, is giving some sort of reassurance to everyone that there is an emotional value that is added to humans, so our jobs are not at risk. But jokes apart, Gaurav, I want to now get in, of course, to the brass tacks to try and understand a little more specifics. Right. So I started with this Nasscom survey, right, which says that 80% more jobs are going to be created. We will have to look at either hiring or upskilling within the organization. Right. So I want to understand, when we look at this 80% figure from an organization perspective, I want to understand two things from you. From an organization perspective, where are you headed right now? Are you looking at upskilling and reskilling within the current force, or are you looking to hire a new set of workforce because you think that's going to be easy to train? Secondly, what are these specific roles that are asking for this reject or for the new high leads?
00:14:40 GAURAV IYER: That's a very complex question, so I'll try to answer it to the best that I can. So if I just go back to my framework of working with AI and working on AI, the people we are hiring from outside in terms of the new skill sets are mostly the people working on AI.
So if you think about AI architects, if you think about machine learning engineers, if you think about data scientists who can train, fine tune a model, these are skill sets which are fairly new. So you do obviously need to hire from the market and actually build up a very strong leadership base on that in that arena. The second place we are doing is, you know, we obviously hire a lot from the top engineering schools in India. Right. So I think that's continuing. I think the curriculum and what we train them on is actually changing.
So from thinking about coding, we actually thinking about design. Right. Because coding is going to get commoditized with AI. But if you really think about how you design the solution, how you design your system. So system design is what we focused on. So those are the two areas on working on AI. Now, the second pillar is where a massive amount of reskilling is going to happen, which is the working with AI. So these are our operations teams. Now what's happening there is a lot of the very simple processing, as my colleagues were saying, is actually going to get automated. So what we have to skill them on is the more complex pieces of work for our clients. So complex claims adjudication, complex commercial underwriting, FNA exception. So that's the reskilling across the higher value chain of the domain which we are working on. The second part about reskilling is the entire operating model. So if you think about our operating model in bpm, if you think about spans, if you think about layers, if you think about leadership, how you coach, all of that is changing with AI. So styles are going to increase. You're going to have AI coaches, process excellence is morphing into AI excellence. Right. So these are all changes in just the way operations work, which, by the way, we have a very, very good opportunity to take a lead in. Right. If I talk, if I think about my clients, they're not thinking about a broader operating model, vj and these roles getting upscaled. So we have them, they do process excellence, they do training, but all of them are upscaled to an AI plus human world. And that's a big piece of internal training which we are pushing on. Our academies are completely vg and we are also partnering with academic institutions in India and in the US and in Europe. Right. So I think it's a collaborative ecosystem which is working on the reskilling and it will need that for us to make progress at the speed we need to correct.
00:17:11 RIDHIMA BHATNAGAR: So I think very well put, Gaurav. And I'm going to take on from that to ring Diwakarr back in the conversation. In fact, that was going to be my next question. Where is this new talent coming from? So Gaurav is saying there is some sort of partnership happening with educational institutions in the, in India and the United States. So I want to understand where is the demand being fulfilled from an organization perspective?
00:17:31 DIWAKAR SINGHAL: See, the organizations will have to upskill their current people. I mean if you're talking about hundreds and thousands of people in the industry, you just cannot abandon, you know that because they possess a lot of domain knowledge, they do not have certain skills, but that can be taught. So the massive amount of effort will need to go in reskilling the existing people. And by the way, this has happened over the years. It's not new. You know, there are other evolutionary changes that happened in the industry. So organizations have to carve out the training dollars and the time to really upskill the current people. Yes. That has to be supplemented with people from the outside. The good part is that when you go and hire from education institutes, engineering colleges or any other college, they are in tune more or less with what's happening in the world. There is always a, we say there is a industry needs this and the institutes don't produce that. There is a gap, but that has been there forever. You know, that can be bridged. So I think companies will have to do both, invest heavily in upskilling the, the current talent. Just can't abandon it. And second is to embrace and bring in new people who possess the skills and are sharper and agile on their feet in, in working in that environment. And then I think it becomes a very good combination to develop value.
00:19:05 RIDHIMA BHATNAGAR: Okay. And that's exactly what we want to understand. So Avishek, I want to understand what the Bakar is saying is right. Right. You can't just focus on the new hirings that are going to happen. You also have to understand what you're going to do with the existing workforce. So help me understand when an organization says, okay, these are our three top focus, priority areas that we need to have upskilling or reskilling done in these. So are these special programs that are created or certain initiatives that you take to ensure that this reskilling and upscaling happens. And if you could give me the specifics of which areas these are and what or if you can give me an example from your organization perspective where you've had some in house programs or initiatives that, that have helped in this reskilling.
00:19:47 AVISHEK CHHATOPADHYAY: Absolutely. I think there's a lot of, you know, drive towards first awareness. So while BPM as an industry obviously was prepared, it also meant working with our clients. Because this is one such area where you need to experiment internally and build the muscle it's not possible to acquire because a lot of enterprises we thought they're, you know, sort of, you know, doing small POCs, use cases and then thinking of probably we'll do an acquisition when something gets tested in the market and build that capability in. But we know how integrations work and in this case it's going to be even more so. Unless we truly weave that in inside the operating model, it's going to be very, very difficult to be successful. So what that means is a lot of push towards driving internal training. So a from a service catalog per se, obviously we are a $14 billion full stack organization at CL Tech. So the way we have looked at AI is in four areas. So first is what we call as AI Force, which is totally focused around training people for what we call as service transformation and service acceleration. So it can be around transactional processing area, it can be around software coding, build optimization, development path, all of that. The second area is training people around what we call as AI foundry, which is more on building the ecosystem ready. So it means data readiness, training people around data structures, data taxonomy, data acceleration as well as getting the cognitive infrastructure ready. The third element of training which is very important, we are an engineering company as well, which is around the chip per se. So we are working around the hardware side of AI as well as building for companies, inference accelerators. And that means actually training people on those components. Finally the lab aspect where we are helping both enterprises as well as our internal organization to try what we call as POCs. Use cases to an MVP. So experiment to an MVP. Now this gives people a real life ecosystem to go and do some simulation per se. Now what we are doing is across levels. So for freshers, because this ecosystem has to be built across the country, it's not just in tier one locations per se. There's a lot of partnerships with both academia as well as with the government to ensure that we bring in the right kind of pressures and train them then the learning pathways. So as somebody said, we are looking at what we call as AI creators, producers and then the whole consumers, right? So segregating those and then important aspect around the operating model is how do we build a set of what we call as AI champions. Because today the BPM industry is working as a custodian for clients. They're delivering to clients, but that means ability to partner Drive change, build relationship and influence certain policies and procedures on the client end. That becomes a very different skill per se. It's not just hard technical skills. It's about having a conversation to be able to alter the operating model per se, the partnership and relationship and driving changes because of AI in the client organization is a unique skill in itself which we have got a program around AI champions per se. And then comes the normal career pathways around the prompt tuning, prompt engineering. There's a lot of focus around domain per se and cross functional because what we are now seeing is there is no point in looking at accounts payable and accounts receivable as two separate silos. When you combine and build a cash control tower and now you're looking at how do you look at the overall receivables and payables and inventory and start putting that on an AI and build simulations out of that. You need a very different skill set to be able to now work on that data set and able to drive the cash position and discuss that out. It's a unique combination of mathematics, programming and doping to actually bring it all of that and then finally the gamification and success. Because we do need to ensure that career pathways because what we should not, you know, fall into the trap of, is just getting into. I've got 50,000 AI certified people. A lot of times, you know, you make market facing, you know, announcements. But what really was that training about? Is it just getting familiar or actually the applicability of that to be able to deliver a use case? So those badges and elevation profile sharply dovetail towards this training pathways becomes a very important chapter as we need to elevate the organization operating model.
00:24:17 RIDHIMA BHATNAGAR: Sure. Avishek, we'll talk about what you said in the later bit in just a bit. But I just want to take on because we just talking about where this new talent is coming in and especially for the entry level talent, what is this domain talent and analytics skills that you were also referring to. So now that if I can bring you in to just try and understand exactly this one, of course, as Gaurav was saying, one is within the ecosystem, how you're reskilling, how you're maybe redistributing these people to try and understand the demand, the other is the new talent that is coming in. So for an entry level applicant today, what is this data analytical skill or domain knowledge that we're talking about? If you could give me two or three big highlights and skills that you're looking out from an organization perspective.
00:25:01 NAOZER DALAL: Sure. Thanks Ridima we are a slightly different organization. So compared to what Avishek mentioned in terms of that is a 10 part of it. We are a BPM organization, you know, ingrained stack into, into everything we do. So I would put it this way. I mean, you know, today, I mean there are three kind of key skills which an individual needs to figure out. You know, one is, I mean, how do they work with AI? Yeah, so you know, the emotional maturity, the empathy, you know, to work with AI tools. Yeah, so that's one part of it. The other part is once they work with the AI tools, you know, how do you make sense of the data these tools provide and then build the final sort of value for the customer. And then of course, as I said in an earlier answer also, and then they need to continue to excel at things which AI can't do that well, like thinking out of the box, improving relationships, et cetera. So what we have done is to sort of help this process, we have set up an AI center of excellence. And as part of that process, the reskilling of individuals is a very, very key task. So one is of course you have the entry level contact center person who as I said, should have the ability to work with AI as required. So for example, the whole quality monitoring system has completely changed and that's where we are seeing more AI and agentic intervention there. So how do you sort of respond to that and get there. Then of course there are other skill sets which are required, you know, which in terms of people who can actually work with some of these tools, you know, in the context of the bpm. But in my mind currently those skill sets are a bit distinct. I mean, you know, I mean, I mean they don't come together. So, so we, no, I'm saying we need agents who are very comfortable working with digital and AI tools, ecosystem of people who actually work on those tools. You know, that's where your typical, you know, AI skilled technical people come in. Not to run your, you know, run your quality processes, to run your processes, you know, where you nudge individuals to improve sales productivity. That's the second piece we are doing. And then of course there is a whole governance layer which comes on top of the AI, you know, in terms of, you know, how do we ensure that, you know, the outcomes are accurate? How do we ensure, you know, that the outcomes are reliable? So that whole assurance piece is a third piece, you know, which we are investing the skill sets in. But I mean that again is very niche, you know, so that of Course is a mix of, or largely we rely on getting people from the market who have those skill sets. You know, in terms of they could be either domain specialists or data analytical training data and analytical skills, etc. So I would say it in three large buckets. You know, one is how do we get, you know, the existing, you know, the larger population, you know, of the contact center agent, you know, I mean, attuned to AI, you know, then of course there are people who sort of, you know, who sort of ensure that the, you know, the AI, the digital machinery works in place. And the third bit is how do we govern this whole piece, you know, that it gets the, you know, the customer outcomes in an ethical manner.
00:28:17 RIDHIMA BHATNAGAR: Okay, okay, fair enough. So, Diwakar, you know, we've established the fact that there is need for upskilling and reskilling within the ecosystem. That's one part of it. The other part that I actually want to address in the later part of the conversation now is one, how do you retain that talent? Since there is of course some sense of competition as well. So from an organization perspective, what can you offer? Is there a, you know, in house program that you run? Do you have some sort of a mentorship program that you run? I just want to understand how do you retain this talent as well? Right, because all of you represent the industry leaders, right? So you're all technically vying for somewhat the similar talent. Right. So how do you ensure that from an organization perspective you also get that top talent, but most importantly, you retain that top talent as well.
00:29:05 DIWAKAR SINGHAL: Yeah, see, first I like to start by saying that AI is actually easier. Okay. What we are dealing with in terms of technology is easier than, let's say robotic automation we dealt with four or five years back, programming, coding, or, you know, all the languages and computers that we learned over the period of time. AI is actually very easy, as long as you have a curious mind and you want to work with it, it's very easy to do. I mean, because the machine does a lot of things, all you have to do is frame the query. It's actually easier than working on Excel. Ultimately what you have to do is you need to have access to the right technologies. You should be able to frame a question properly. You should know what you're looking for. So if you're going to be scared of AI, then we'll never make progress. The question is, okay, I have a spoon available to eat food, let's call it that, how do I use it to the best advantage? Rather than saying, I'll not Use it. And that I think is the fundamental point. We have to strengthened with our teams that please don't run away, use AI. And if you use AI, it's actually so simple once you get adept at it that you can keep getting better and better and the technology will keep evolving. And of course India will be the AI factory of the world because it is producing all the technology people who are going to create these programs on AI, whether that is embedded in a software or it is available as point solutions. So just giving the comfort to the people that this, you can bridge the gap, you can evolve from here. You will have a better work life balance, you will work on higher end stuff, you will have a more exciting job. And giving them the tools for them to use it I think is one way to solve it.
00:31:03 RIDHIMA BHATNAGAR: Okay, so I'm actually this is very interesting and I'm going to just make a slight deviation when I bring Gaurav back in the conversation. You know, many viewers will be watching it saying. So you're discussing only the employee perspective. What about the employee perspective? Right. So because you have a lot of interaction with your employees team leads to try and get their feedback as well. One, you know, we'll talk about challenges in integrating, adapting to new technology. But when Debakar says, you know, these are the three things, if we ensure this can retain talent. But when you speak to an employee, what are their top three priorities for them? That says that okay, this is an organization that will work in because for somebody who has been in the industry from what we initially knew as the BPO space to the BPM space, that entire range has changed drastically. So obviously the expectation of the employee would have also changed from an employer. Right.
00:31:55 GAURAV IYER: I think that is very fair. So the top three things that we hear from our employees are one as always, right. They want to feel as though they are adding value. So I think that's number one.
00:32:07 NAOZER DALAL: Right.
00:32:07 GAURAV IYER: Anybody who does their job wants to feel, you know, when it by this, you know, it might be conversation with your clients, it could be with your team leader, it could be with your leadership. They want to feel as though you're doing something which is important.
00:32:18 NAOZER DALAL: Right.
00:32:19 GAURAV IYER: Which is clearly the case. So I think that's point one. Point two is I think everybody is a bit, you know, I would say anxious about are they going to get future skilled, are they going to be relevant in the future?
00:32:30 NAOZER DALAL: Right.
00:32:30 GAURAV IYER: So that's where Dewakar's point about, you know, taking that fear out, saying that look, you have tools, you have, you know, A lot of capability development that EXL or any of the companies will do. So I think that's a very important aspect which is, you know, getting them future ready and seeing that. And they should see that you are investing in them.
00:32:47 NAOZER DALAL: Right.
00:32:47 GAURAV IYER: So I should do that. And obviously then the third is they're all, they obviously want to understand their compensation and whether it will obviously grow and do right. So I think, look, AI is not actually a threat to all three. In fact, to me, it's a tailwind to all three. Right. Number one, if you just think about the value. So as we were chatting about contact centers, typically in the past, the agent has to be very focused on the call, getting the call done, ensuring that they follow certain procedures and they follow certain guidelines. They've been focused today with an AI assistant, they can actually focus on the customer problem and actually solving it. So, you know, whether it's a claim, whether it's finance and accounting, whether it's detail, they can figure out, you know, what's the real problem and how can I empathetically solve it for the customer so it's higher value. I can tell you that they go back feeling that they have done a much better job than to have handled a call, entered, you know, copious notes, followed a standard operating procedure like a robot.
00:33:41 NAOZER DALAL: Right.
00:33:41 GAURAV IYER: So it's clearly something that they feel they are adding value two ways. From a future skilling standpoint, I think all of us have talked, all of the organizations, we have something called Renew, where they can go there, they have a self paced learning, they can learn AI, they can learn data, they can learn process, they can learn leadership. All of that's available digitally for them on a self paced manner. And then the third is from a compensation standpoint. I think as we move into the solutions world, we deliver more value to our clients, we can charge more value. And obviously that means we can obviously pass on some of that value back to our employees.
00:34:16 NAOZER DALAL: Right.
00:34:17 GAURAV IYER: So there's a, you know, I would say a good vicious cycle that will allow us to make more value and hence our employees to get more value out of that. So I think it's a tailwind to all the three typical questions they would ask. And that's my perspective.
00:34:33 RIDHIMA BHATNAGAR: It's the first time that I'm hearing the quote a good vicious cycle. But it's interesting to hear that. But Gaurav, before I go back to the other panelists, because you said something about a call being taken, right. So I'm just going to try and simplify this because we're also assuming that a lot of people who are freshers who would want to join the BPM industry. So I want to take an example. Say you have a call and just compare that to me right before the integration of a technology like AI, I would assume when the call happens, there are some notes that the, you know, customer executive has to quickly look into the history, the orders placed, so on and so forth. Now cut to the current call that is happening. So what has changed in terms of making it far more efficient? Am I assuming there are more prompts that are available for the executive to take a look, to quickly compare and then have a more wholesome solution?
00:35:20 GAURAV IYER: Yeah, I think you have hit it correctly on the head. So just think about it. Right now there's an AI assistant. So the AI assistant is first of all transcribing the call. So even if you could not understand the customer, the accent is difficult. The AI is helping you understand, right? So first of all, you have a better conversation. Second, the AI also gives you a next best action, right? So instead of you remembering everything, let's say you're an entry level new person. Then you have to ensure that you remember everything and now the AI can help you with that next best action. Three is there's an entire knowledge bank where again, the search becomes much easier. Previously the knowledge banks would be outdated. You would have to go to three systems, maybe four systems. Now it's all there in one place for you to have a seamless. And the fourth thing is post call. You know, you do a lot of work around what did you hear? What was the, you know, action you did, you know, what's the resolution? All of that is again, can be summarized with an AI. But you as an agent basically now are more of a validator, right? So you validate whatever the AI told you or done is right. So that's one part of the call. But think about it. It's not only handing the call and the return of the good, right? You can actually go and you can put a note into an agent in the warehouse to say, look, why are there 40% returns on a particular kind of good? There may be something that is going wrong in the warehouse from a tagging standpoint, right? Where wrong goods are getting shipped although the customer is buying, right? So you can actually almost interact with the broader part of the supply chain which, you know, in the past you, you either didn't have the time or you didn't have the tools, or you didn't really have the, you know, focus on, right? So to Dakar's point, your curiosity can go further.
00:36:54 RIDHIMA BHATNAGAR: Yeah, perfect. Very well put. And thank you for that. But Avishek, let me come to you now. Now that we've got to move to the third part of our conversation, which is, you know, whenever we speak about potential and opportunity, there are of course challenges as well. And we have to address them to try and streamline the next chapter of this BPM industry in India. So, you know, we're speaking about reskilling, we're speaking about rejigging the current workforce. But that also means that there will be challenges. They can be challenges, for example, from an infrastructure point of view. They can be challenges from a commercial or cost point of view. So if you could give me like three challenges as this integration happens or as the penetration goes deeper.
00:37:37 AVISHEK CHHATOPADHYAY: Let me start with the positive side first. I think this is a great opportunity to reposition the BPM industry per se in terms of employee value proposition and attracting talents. A lot of time between IT and vpn, they're having challenges in terms of how this industry is perceived. The amount of visibility the AI operations has received, right, from the CEO of the organization, I think this is so that level of visibility, the quality of work. So every work item that, be it a contact center agent, be it a finance and accounting person, be it an underwriter, there is a source of value and then there is an administrative activity. Now what AI provides is the amplification of that source of value and all of the other periphery, which you may not have liked to do, is getting it done. So everybody has sort of an admin assistant, right? And the amount of mentor support. Now from a challenges standpoint, right? So the first thing is the, the first big thing is around cybersecurity. I think as we look at, you know, the whole from an industry perspective, that's a big issue. And in terms of having skilled people to be able to, you know, address that becomes one issue. Which means that, you know, participating with the colleges, the ecosystems and creating a talent pipeline. Because if you look at the high quality cybersecurity professionals availability in a country like India today, we have to build that talent pipeline. We have a handful probably that's sort of, you know, one area that, that becomes a challenge. The second area is around pricing model. Okay? Now as an industry we have been, you know, sort of moved into from a FT based model to a transaction based model. Today, probably 15% of our contracts are in an outcome based model. The whole industry needs to shift towards that risk reward sharing model. And that Means ability to put a significant amount of your output at risk in terms of, I mean you can ignore the input part of it. So the cost structures are going to change. Now that's an uncomfortable shift per se, not knowing what you will really, because a lot of us are listed organizations like that predictability standpoint on a quarterly quarter basis. Now that's going to have a, you know, go through a change, but that's exactly where to be addressed. Significant amount of domain needs to be wired in as well as the technical skills to be able to take a lot more calculated risk is where we are creating what we are calling as industry replicable solutions. This is where an accountant or an agentic underwriter comes into being. An ability to repurpose that across industries and have a risk reward model. So commercial models are going to have a shift. The third element is the boundaries itself are blurring. So a lot of times you had the whole industry shifted, there was IT stacks, the ERPs and there would be obviously gaps in those IT stacks. There would be SaaS companies that would come in and then BPO as an organization would be the orchestrator and they would find those gaps and sort of act as the bridge between the technology and the outdoors and get or try to get a share of that. We are seeing competition from ERPs that are changing. We are looking at CRM and SaaS providers changing and hyper customizing now because coding is sort of becoming cheap. Right? So the competition profile of BPM industry also is not just other VPNs but there are going to be significant amount of other industry competitors that will come up. So working all of these things towards again keeping a sharp focus on the business value and getting a share of that business value and not being a bottom feeder is probably the number one focus item for this industry to truly reposition and attract the best talent.
00:41:14 RIDHIMA BHATNAGAR: Okay, okay, well put Avishek. Naozer, I want to ask you a very specific question. When we talk about moving forward in retaining talent, is one skill redundancy, is that a real challenge?
00:41:28 NAOZER DALAL: No, definitely. See what, what we try to do is, you know, as I said, it's not about skill redundancy, but how do you sort of ensure that, you know, there are enough adjacencies, you know, where the people are sort of trained about, you know, so for example, what are the typical skills of a BPO person? You know, I mean maybe process automation, analytics automation. But that same person, you know, I mean, we may have to teach him about say cross functional domain expertise, you know, or consulting Skills, you know, or how do we sort of he learn about technology integration. So, so we, we constantly sort of look at that, you know, and we have built learning modules around those. We also look at micro learning modules, you know, where the person can learn at his or her convenient time, you know, and, and absorb. So, so definitely I think we need to make a lot of effort to ensure that the skill redundancy does not set in, you know, and that, you know, our people, you know, are continually ahead of the curve, you know, in terms of, you know, how do they adapt, you know, to this sort of, you know, man plus machine operating environment.
00:42:33 RIDHIMA BHATNAGAR: That's very interesting. What, what you said that, you know, they can take it at customers times. Could you give us a little more example of how this work?
00:42:40 NAOZER DALAL: The modules?
00:42:41 RIDHIMA BHATNAGAR: Yes, yes, the modules, yes.
00:42:43 NAOZER DALAL: Yeah. So for example, we have an app based product, you know, which is called Logo, you know, which is learning on the go. Yeah. So what, what we do is, you know, because we also see, for example, typically in some of the large metros, you know, I mean, I mean the commute time to office itself could be anywhere between two and two and a half hours and at least an hour each way. So we also know something. So it started from that need to say that, you know, of course, I mean, that's their personal time, but it's also a good opportunity for them to upskill and it may not necessarily be modules linked to their current job. Yeah, and that's where we try to encourage people to say that, you know, that you're spending two hours a day commuting. You know, why don't you use that time to sort of upskill yourself, you know, which will not only make you more effective on your current job, it could open up doors within the organization and dare I say, I mean it sort of also looks at their employability. So there is a selfish interest also to ensure that they continue to sort of remain ahead of the curve and upscale themselves. So that's a very classic example. So it started in our feet on street business. So as you know, I mean, you know, the wider ecosystem within Quest also has a collections business. So it started from that in terms of, you know, a micro need, in terms of how do we get learning to our collection agents because they are mostly on the field. But from that it actually mutated to the fact, you know, that learning based app which we develop could actually be used even, you know, for people who typically are within the Contact center or within the office for eight hours, but includes that, as I said, their commute time to learn more. So it's a consider of constant evolution, you know, thinking ahead of the curve, you know, and seeing how do we ensure, you know, that our people constantly, you know, remain ahead of the curve. The other bit which my colleague also mentioned was about the whole, you know, CX Champions or Digital Champions. Yeah, so that's the other initiative which we have, you know, which we have done through the organization. And, and of course that's completely voluntary, but of course it's also linked, you know, to some financial rewards, you know, to some career development opportunities coming faster than, you know, for the normal, you know, career and job development track. So that's the other piece we have said, you know, where people again, can voluntarily, you know, up their game and you know, I mean, then, you know, get faster career development, faster growth, you know, and, and be regarded as a more well rounded individual rather than only a contact center person or a back office person.
00:45:11 RIDHIMA BHATNAGAR: Correct. Very interesting. And I do see a lot of these, you know, people, as Naozer is rightly pointing out, to try and make either using the commute time or, you know, an extra time on weekends or when you have a low work day to try and take up these, you know, courses or modules to try and upscale yourself. But Diwakar, I want to bring you back in the conversation you spoke very well about, you know, the talent that's coming in from education institutions, so on and so forth. One of course is what do you do to them when they've already joined an organization? I'm just thinking outside the box and moving two steps behind and saying, are there certain initiatives that can already been put in place before while they're already studying so that in a way it becomes a part of the curriculum and they have some sort of knowledge by the time they join the organization?
00:45:55 DIWAKAR SINGHAL: Yeah, I think that is already happening. I mean, you know, because the, the students nowadays are more aware than many of us. So they are already picking and the knowledge availability is so easy that even if you don't insert in, in curriculum, they grasp it.
00:46:15 RIDHIMA BHATNAGAR: Okay.
00:46:16 DIWAKAR SINGHAL: The one challenge I do see is that overall execution is hard. So it's not that tomorrow we are going to wake up and It'll be an AI world. Everyone is still dealing with only POCs and pilots. AI at scale has not happened. It will take time and it is not easy to do. Five years back they were saying that autonomous cars will replace all traffic on the roads and there will be no radiologists needed. But if you go to any hospital anywhere in the world, there are radiologists still driving a car to work. So this is going to take time to reach what it promises, but it will happen. And I think we have time on hand to move towards that future and embrace it and spend time and energy on using it rather than running away from it.
00:47:13 RIDHIMA BHATNAGAR: Okay. So gentlemen, as we now begin to, you know, somewhat wrap up the discussion, there is one important aspect that we still need to discuss which is we discuss the challenges but we also want to understand the way forward, right? Because we're also discussing say what the next 10 years of the BPM industry in India will look like. So Gaurav, I want to go around the panel beginning with you. I want to try and understand one, if you could give me top three trends that you think will dominate as far as the skill workforce in the BPM industry is concerned.
00:47:48 GAURAV IYER: Yeah, sure. So I'll gaze into my crystal ball and tell you the top three. So look, number one, I think as we've talked, right, I think the BPM industry will go much more or will go beyond the process towards data, right? And really understanding the data that drives a lot of our clients workload, right? So I think there'll be a big move towards people who can understand, work with data for our clients. So I think that's number one. Number two, I think the BPM industry, you know, given we've already and we've always focused on domain expertise and how we can actually deliver good business outcomes to our clients customers, that skill will remain super important. In fact, it will get even more important, right? So I think one of the advice I give most people is when you join our industry, understand the domain, understand the operations and understand it really well in terms of how it makes an impact, right? Because that's going to be the differentiator of how AI gets embedded well or it doesn't get embedded well, right? So one of two Diwakar's point, AI is there, models are there, but whether they get used and whether the outcomes get delivered is because of the BPM or the workflow layer, right? Which is where we say. So I think that's number two and that's going to become super important. So people are going to be data experts, AI workflow embedding experts. So I think that's true. And I think number three is, I think, I think the point that Diwakar again said is the curiosity, right? So the industry has to move beyond thinking about a process or a transaction or A set of transactions. And the more that we can have our people think about that end to end business outcome. Right. Whether it's, you know, in the F and A world or the contact center world or claims or healthcare, the more we'll be able to add value. Right. Because today our clients look at us as not outsourcing partners but AI transformation partners. So we have to do justice to that. And so I think these are the three big trends from an employee skill standpoint that I think if we focus on and if we make progress, I think we will, you know, it will be a big tailwind to the industry person.
00:49:50 RIDHIMA BHATNAGAR: Sure, sure, sure. Avishek, what about you top three trends according to you?
00:49:54 AVISHEK CHHATOPADHYAY: Yeah, the first one I think as an organization we will see a lot of delayering and specialization. What that means in a Traditionally organizations have all grown up managing spans and people. We will see a lot of focus into specialization, narrow creating micro verticalization. So in specific areas trying to deepen the domain versus managing people. So the skill profile and obviously rewards will sharply shift towards that versus managing. The second thing is around platform based thinking and engineering, the technology and ability. While we at a very high level, we call human in the loop, things like that. But how do you really architect and integrate the AI workforce or the gentech workforce with the human and the tech stack to create that total outcome or business value or economic value is going to be a second re architecting standpoint which is going to be very, very important skill set going forward. The third thing I think is while agentiq will, since you asked a question about 10 years, so there's a little bit of a Runway towards that. But the ability to communicate partnership and influence and drive war room like thinking is going to be a very, very important skill. So a lot of focus around that right from high school, college education, being able to be influenced and drive change is going to be a third most important skill profile for this industry to tap onto. To me those are the top three things that I would call out.
00:51:14 RIDHIMA BHATNAGAR: Okay, Naozer, according to you, maybe top two top three trends that you think will dominate.
00:51:19 NAOZER DALAL: So I think the increasing use of agentic AI across the value chain. So it's not only about what we do with the end customer but right from and in fact we have just recently done a lot of POCs with a new product called Pulse AI, you know, which sort of marries agentic AI, you know, with a command center approach. So right from, you know, the time of hiring, you know, so I'm saying it also integrates the Backend processes which we run, you know, so to how do we sort of, how do we hire, how do we train, how do we ensure, you know, that we get the right kind of people coming through our doors? How do we parse cvs, you know, how do we facilitate the interview process and streamline that further? So starting with that, so starting at, you know, at the sort of, at the Fountainhead, so to say, of an agent's life journey with an organization and then of course, you know, getting married, you know, into, you know, as sort of he gets trained, gets on the floor and then how does he use, you know, I mean, AI assisted tools, you know, to, you know, as somebody else also mentioned, you know, get the customer outcomes in terms of performance nudges or quality nudges. So I think. So that's one. So I think there'll be a lot of integration across the agent lifecycle also to be able to sort of deliver value to the end customer. The second piece which I see, as I said, is that increasingly as for various processes, the component of AI versus agent may vary. So for example, definitely we see that some of the very basic repetitive tasks may get disenformated to a greater extent. But what we'll also see is that we have also seen, so while we have seen maybe about a 30, 40% reduction in some of our DAU volumes, as I said, in some of the repetitive tasks, but we have also seen about 110 to 120% kind of volume compared to where we were in tasks where we use a lot more AI to get customer outcomes. So for example, in some of the sales processes where we sort of look at, you know, I mean, individual contributions, you know, we sort of do a bit of champion challenger, you know, methods, you know, using AI. So we have also seen that. So overall what I do see is that, you know, I mean, just to get a sense of sanity, yes, I mean overall volumes will look lower, but you may get higher. Some of the more value added work, you know, which would also sort of, you know, add, you know, to the sort of the more profitable queue, so to say, how do we run in the BPO industry? So, so I think it's going to be a mix of, you know, some volume reduction, but, you know, but definitely higher volumes and a lot more work, you know, in the more the agent agentic infused queues, so to say, so that overall, I think, you know, it'll all be in the right direction.
