Innovating through a pandemic, Customer mindset, AI in Insurance — Dipu KV | Stories in AI

I had a great conversation with Dipu KV, President of Customer Experience and Operations at Bajaj Allianz, Asia’s largest health insurer, as we dive into Innovating through the pandemic, aligning customer focus, a six-sigma process mindset and constant iteration to scale innovation, AI in the insurance sector and a lot more. I hope you enjoy this conversation as much as I did.

Ganesh: Welcome to stories in AI. How are you Dipu?

Dipu: I’m fine thank you Ganesh, and speaking to you makes me feel even better.

Ganesh: That’s amazing. You’re so kind. Thank you so much. I know it’s late; thanks for staying up and getting on this thing. I’m going to go right into it. We have a lot of topics to cover, I would love to pick your brain on a bunch of different things. So why don’t you start with giving us your story, your personal story and your journey into AI and technology.

Dipu: Yeah, thanks Ganesh. I think it’s always a good way to start with one’s personal journey. So I am basically from Bangalore, after graduating from IM, I worked with GE Capital for 20 years. And in GE Capital, one of my main strengths was in the area of digital transformation where I got introduced to AI. And then I carried that forward when I joined Bajaj Allianz five years ago, and in my current role, my key mandate is to drive digital transformation. AI is at the center of everything that we do, and AI is an integral part of my life. I’m happy to talk more about it as we go through our conversation.

Ganesh: It’s amazing, I’d love to hear. This is a show about AI, and we started the show: The Stories in AI, as a way to inspire people and more folks into the field of AI. We learn from others, learn from leaders like you, from experiences like yours, and then get into the field and be part of the revolution that’s happening. So tell us about the industry itself. You’ve been in the financial services industry with GE Capital, and now at Bajaj Allianz; how is the shape of the industry changing with these frontier technologies like AI? You’re also into blockchain and a few other frontier technologies, too. So give us a view of what how you see it and what you see happening.

Dipu: Ganesh, interestingly, technology, whether in the form of AI or, blockchain or any other state of the art technology that we see, has obviously made a dent in the industry. Initially, the industry did go the digitization route, and that’s what we’ve seen in many firms; we’ve seen AI come to the fold. And I think when COVID-19 happened, it was a global, unplanned UAT (User Acceptance Test) as one of my friends colorfully put it. And then I think all customers, all partners and everybody else had to come on board. And then I think it became a point of inflection. So today, if you look at the current way of working, not just the way of working, but even the way of living, it’s largely digital. For example, if you look at where customers are getting serviced, AI is at the center of everything that we do, because a lot of servicing is digital. Similarly, if you look at the entire landscape, and if you look at all transactions, from policy issuance to claims, to renewals, AI is cutting across various processes. So, that’s how the industry has taken to AI. And I think the future is very bright for AI as we emerge into the new normal in whatever form and shape that the new normal is.

Ganesh: Interesting. 2020 and the pandemic, I love how you said it is the unplanned UAT for all organizations to get to grow up pretty quickly. But the reality is, I’m sure it was a harsh transformation for most organizations; not everybody was prepared for it. It also was not really the most pleasant time to actually do those transformations. Because changes were everywhere, people and their lives were being upended, and so forth. Give us some examples, I will be actually following some of the work that you did specifically on customer experiences, touchless experiences in the middle of COVID, including, some of the amazing work that you were doing in terms of the socially responsible work. So give us a view of what you specifically at Bajaj Allianz have been doing in the last 18 months or so.

Dipu: Thanks Ganesh. I think history will get reset from BC and AD into before COVID and after COVID. So what we did during COVID: we were and are still on a digital journey, much in advance of COVID-19, because obviously you can’t do everything overnight. But what COVID did was, it gave a huge fillip to our entire digital servicing tribe, so, specifically from customers, because that’s what you asked. Firstly, what we did was, we embarked on a massive communication blitzkrieg. Because we normally underrate communication; it’s very important to reach out to customers and tell them, “Even if there was a lockdown, or even if contact centers are shut, you can reach out to us using a plethora of digital tools.” And I think the good thing is, we were able to ensure that this switch happened without a single glitch, because our customer grievance ratio at that time, when we tapped it, it actually came down by a whopping 90%, which just goes to show the customers we’re extremely comfortable with our digital journeys.

Ganesh: Was it also because you were more prepared than most other organizations?

Dipu: Yes, we were actually prepared. Because our digitization drive, as I told you was much in advance of COVID-19, and we were able to ensure customer servicing in a completely unencrypted manner, through the usage of our bots, WhatsApp, mobile apps and customer portals. And even today, the combination of man and machine continues. And since COVID-19 also made people very wary of touch, nobody wanted to press the button in the ATM or the key in the elevator. What we did was, we basically ensured that our UI UX became touchless. So on the one hand, when customers walked into our branches, we told them to just can QR codes, and then a URL opened up, and they could carry out the request for fulfillment. And then on the other end of the spectrum, what we also did was we integrated our bot with Alexa and Google Assistant. So which means voice based servicing. So if you have Alexa at home, you could just say, “Alexa, can I get a copy of my insurance policy?” Alexa would speak to our bot, and the bot would then send the policy copy to the registered email id. So I think we’re a combination of strong technology and digital intervention across the entire lifecycle. And of course, empathy and the healing touch, which is also required. We were really up to it, and we need not just to survive, but we actually thrived through the entire COVID-19 period.

Ganesh: That’s amazing. Can you touch upon it? You mentioned a few things. One is the pairing of humans and machines. It’s a fundamental tenet, I believe in that too. AI should have been augmented intelligence, not so much artificial, there’s nothing artificial about it. And you mentioned empathy and stuff like that; and you’ve talked about it. I’ve listened to you talk about putting the customer experience at the center of everything before you actually start detailing out, “Hey, here’s a bot technology, how can I use it? Here’s NLP, how can I use it?” Can you talk a little bit about that: that customer first approach that your organization took?

Dipu: Yeah, sure, Ganesh. In fact, what I’ve done is, I’ve combined my Lean Six Sigma expertise in GE, with a customer first approach to adopt what we call a five step process. So what we don’t do is come out with the digital solution as the first step. Our first step is to listen to customers. And while it may sound cliché, if you miss this crucial step, you could end up barking up the wrong tree. So what we do is, we get customer feedback. We’ve been in existence for two decades. So we have plenty of customer feedback coming in. And the other is, we also conduct focus group discussions and Net Promoter Score surveys to get feedback from customers, which is research based. So through a combination of proactive and reactive feedback, we get an understanding of customer needs.

Now, the second step, which is very important, is, once you get customer feedback, it’s important to go through that to figure out not only the customers’ stated needs, but also the latent, unarticulated needs of customers. Because many customers have needs which they can’t articulate, and I’ll explain unstated needs with some examples as we go through our conversation.

Then the third step is to basically take an inventory of our current landscape of processes and systems. And typically, we would find across organizations that processes were initially set up keeping the department as the center of everything that we do. If a customer goes to a universal organization, he’s not going to find a customer centric model, he’ll be asked to go from one department to the other, depending on his needs.

So then the fourth step, using Lean Six Sigma is to re-engineer this entire landscape and make it as lean and customer centric as possible.

And then the fifth step which could be the first step for many organizations is launching the live no digital solution. Now, when you launch the digital solution, what is very important is, whether it is AI, whether it is IOT, or whether it is block blockchain, it’s very important not to get caught up with the latest buzzword in town. Because sometimes the best solution is a simpler solution. The solution has to fit the need and not the other way around. So I think by doing this five step process, we have not only ensured customer first, but we have also ensure that we use technology exactly where the need has failed. Which is why in whatever deployments we have had, we have hardly had any roll back, and we’ve only been able to take them forward.

Ganesh: It’s amazing Dipu, and if I summarize it, one is, start with a customer. Definitely ensure that you center everything like you said around the customer. Then you actually understand the business process outcomes you’re looking for and the input that you have to put in. And then after you engineer or re-engineer that, look at the fitting technologies that can actually drive that. It’s pretty amazing that you write more than just a theory. Because there is a huge value realization gap in technologies like AI today and across the industry. And more so, we see that it’s not so much the lack of technology not working, but it’s about the business outcome focus not really happening or you didn’t really think about, “What am I really trying to do?” You started with, “I have a piece of technology, let’s make this work.” Instead of taking a top down approach, you took a bottoms up approach on it right? Talk a little bit on understanding the customer aspect. And you said the stated needs and the unstated needs. So how do you identify that? Is there an opportunity to engage machines and algorithms to do that too?

Dipu: Yeah, it’s a good question Ganesh, and I’ll tell you how we do that. As I said, the first step is collection of customer feedback through whatever means we have at our disposal. And then, it goes back to your classic reading between the lines ability. So for example, let’s say when customers write to us right now, customers would write to us saying that, “Can you help me with my health insurance?” And very often customers add a context. The context could be that, “Nowadays, I’m not able to go to hospitals; there is a lockdown. Or the health care system in general is prioritizing COVID-19.” Now look at the context. And that’s why I said, No, you don’t look only at the stated problem, you look at the context, then you figure out if there is an opportunity to help customers here. So for example, let’s take this example itself, customers can’t go to hospitals, right? Now, what we did is, we came up with a very simple digital solution, but very effective. So we told customers, “We can help you out here.” We are of course, an insurance company, and we are in health insurance. So we have a set of doctors. So we came up with a very simple tool called doctor on chat, all customers had to do was to log in using our mobile app, and then get into a video, chat or voice consultation with our doctors, and the doctors would give their advice. It’s all digital consultation. Then all you need to do is just to go and buy medicines. And medical stores are always exempted from any form of lockdown. So customers just loved it. Similarly, when people were very wary of COVID-19 in the initial stages, and they wanted to get themselves tested, now, ironically, you don’t want to go to hospital, because in the quest to get tested, you can get infected, because hospitals are hotbeds of infection. So what we did is, we came out with an AI-driven bot by which customers could then get to test themselves. And we offer this in multiple languages. The adoption was amazing; it just kicked off instantaneously. And we got a lot of positive feedback from customers: giving us a doctor on chat option or giving us a COVID-19 self-assessment tool. It’s not the exclusive preserve of insurance, and it’s also not a primary product. But I think the fact that we met unstated needs gave us a lot of goodwill with our customers. And when we got an independent NPS study done through a third party market, which is a market research agency, we found that we enjoyed the highest scores in the marketplace.

Ganesh: That is amazing, what a beautiful story. I think in a few things: one is simplicity or Occum’s Razor, making sure that most of the complex problems usually have the simplest solutions. What you called out that I really liked was: some of the things around how to really delight customers, and it’s often hidden in the context of their communication not in the communication itself. And it gave you the opportunity to actually use powerful machine learning. Now, one of the things that this also did last year was, it changed the way we all work: our employees, the engineers who are working on this product, the servicing people and stuff. I know you did some work on the virtual service rep, or some work where you paired both humans and machines to deliver better service and also delivered a better experience for employees. So talk to us a little bit about that.

Dipu: Sure. So there are two aspects there Ganesh. One is in terms of how we leverage the combination of man and machine. So for example, we started the AI driven bot. Now, the AI driven bot can be taught based on all our experiences, let’s say till yesterday. But human beings being human beings, there are customers who can throw up some unprecedented questions, and what we have seen in our NPS studies show that customers want a one-step solution; the NPS can be as high as 96. Just break it into two steps, it can follow up to 65. Now, you don’t want a customer being told by a board, “I’m sorry, I can’t answer this query, why don’t you just call up the call center? Why don’t you go to the website? Or why don’t you use any other means?” So what happens here in a very seamless manner, the query gets transferred from the bot to a human being. So we deployed an assistant automation, the customer is told, “We’re now transferring to a human being, because we are transparent.” And then the human being takes over and takes it through to completion. From a customer’s perspective it’s seamless, the bot answered in the initial queries, where it could not answer it went to the human being. And then back end what we do is, we maintain an inventory of all these unanswered queries. Then on a periodic basis, using AI and NLP, we keep teaching the bot. So the bot is learning all the time, and its own percentage of first time query resolution is on the increase. So that was on the combination of man and machine.

And now coming to your point around how to manage employees during this pandemic, because we all talk about customers, but at the end of the day, we also have to manage employees, right? Because they are the ones who are actually serving customers and transacting day in and day out. What we did was, we basically converted adversity into opportunity. And I’ll tell you how we did that. We realized people are at home, and they’re all basically socially and physically distanced. But we needed to keep them digitally and emotionally connected. So what we did was, we said, “When you have employee engagement in the office, you only include employees, right? But now that they’re working at home, why don’t we include families?” And I think that one step went a long way. So for example, we had a vacant master chef, and we opened it up not only to employees, but even to the family members: somebody, his wife, somebody’s mother, somebody’s sister, somebody’s daughter and all of them. And it was done on WhatsApp. They all started posting mouth-watering recipes, and photographs of their dishes. And then we announced prizes. Similarly, on Mother’s Day, we had a live concert, organized by mothers and only mothers were participants or the classic democracy definition: “Of mothers, by mothers, for mothers.” That was a huge hit. Then we had digital painting competitions, and digital singing competitions where families were involved.

And when we got employee engagement scores, I think we stood out in this regard. Ironically, our employee engagement scores during the pandemic turned out to be higher than our scores pre pandemic, because family’s were involved. So I think it just went a long way; our employees were absolutely motivated. So I think keeping motivated employees and using a good combination of man and machine helped us thrive over this.

Ganesh: One thing that really stands out in all the approaches you’re mentioning is the focus on simple solutions: focusing on the solution than on the technology layer itself; it’s coming out very clearly. Let’s talk about the industry in general: so the insurance industry, and the insure tech industry. I mean, you have two big industries: you have servicing on one end, and you have underwriting on the other: the two big industries. There are other things too, but these are the things that drive the business if you will. It’s one of the oldest industries, and I think in the last few years, we’ve actually seen a lot of things. In general, how do you think the state of digital transformation or the state of adoption of technology like AI has been in the insurance industry?

Dipu: Ganesh it’s a fundamental question. If you were to ask people before the pandemic, I think you would have had a lot of queries where you could have said, “The jury’s still out, and we can keep debating until the cows come home.” But I think especially after the pandemic had set in, AI has established itself firmly. And you spoke about underwriting and servicing. So I’ll give you some examples on both of these fronts. Firstly, if you look at servicing, we already know AI driven bots clearly kick in and ensure that they give the same level of service. Today, it’s not just about the usage of AI, but I think we are also moving to a stage where we’ll be moving from not just digitizing the physical, but also humanizing the digital. How do you make AI more human centric? Because ultimately, AI is science. So how do you blend the science of AI with the art of customer centricity to make it human centric AI, before bringing in conversational AI, ensuring that robots start mimicking human beings, and so on and so forth. So if you are in that stage, it obviously shows that AI has established itself.

Similarly, coming to underwriting, and they are bringing in data and analytics, I think what a lot of people sometimes don’t remember is that we have something known as the actuary in the insurance industry, he’s the original data scientist, the only difference is, everything is in his head, whereas data analytics, etc we talk about platforms. So if you look at underwriting, AI plays a significant role. Now, the classic problem that sometimes firms face is, the underwriting model can be a one size fits all model. So when AI comes in, you can slice and dice and you can get as granular as possible, and then you’re able to give a far sharper solution. So I think clearly, that’s an area which comes in, because pricing can be complex, you could have several pricing models, and you may look at loss ratios across locations, and across various segments. So AI is clearly coming in. Similarly, if you look at a lot of the roles performed by actuaries and underwriters: some of the very complex transactions, as AI kicks in, not only are you able to ensure that your addressible market has reduced dramatically, but also you’re able to come out with solutions which were not possible before the advent of AI. So that way, I think it has firmly established itself. And I think going forward, AI is going to be intricately linked with insurance.

Ganesh: Yeah. That’s a really good way. You touched on a lot of things and I don’t even know where to go from here because there are so many open threads I have. One of the things I’ve actually always wondered about is the lemonade example, how they came in, especially in most places, because underwriting takes time, either the actuary is maybe on vacation, or it’s things in his head. Yes, you have models, algorithms and statistics that help you get through some level of things. I’m not an expert in the industry, but I’ve seen the need for people; people are all looking for instant gratification right now. So it’s servicing: when you’re actually trying to get a quote for insurance, “I want it now. I don’t have time for you to actually go and call your actuary, work on this, publish it and give it to me.” So what I’ve seen honestly is this move towards underwriting to the edge. How do you get it closer to the customer integrated within servicing? If you’re doing a lot of servicing, it gives you opportunities to upsell, cross sell, and do other things too, then you can make quick decisions. What have you seen in that space? Is this helping? Are we still where we are trying to make intelligent systems learn from actuaries now, once that is done, you can move it to the edge? Where do you see this happening right now?

Dipu: Ganesh you did ask me a question, and you answered your own question. So I think that’s precisely what’s happening: what you mentioned about moving to the edge. Because I think the whole idea is that if you are able to empower the customer, and if you are able to ensure that the customer has not only the information at his fingertips, but he is able to carry out transactions at his end, I think that’s really what firms need to focus on. Because Ganesh, if you look at various models today, the days of asking the customer to submit some information, then you submit it via this nervous system or from the nervous system to a central repository, then they will churn out an output, and then go back to the customer. I don’t think today’s customers are in tune with those models. Because that’s one status quo which is getting busted. So clearly, it’s about taking decisions as much as possible to the edge. However, we should keep one thing in context here, especially in insurance, unlike a lot of products, it’s a push product, it’s not a pull product, you still need to convince customers, and there was a reason for that. As human beings, you know how we are wired, when you wake up in the morning, nobody thinks, “I’m going to crash my car today. You know what? I’m going to feel unwell, I’m going to fall ill, and then I’m going to go to the hospital,” because insurance is something we should think of only when you go through your tough times. Because ultimately you buy it because you want to file a claim, and claim reimbursement at the time when it is required. So insurance happens to what we call a conversational sale; you need to have a conversation with customers, which is why you still find a lot of human touch in insurance. And that’s why their business also continues to be distribution-led. If you look at various global markets, the direct business now varies directly between the consumer and the end carrier, it’s limited and it’s largely to distribution. Whether it’s brokers, banks, the traditional agent, ecommerce partners, or your various forms of distribution, it’s still distribution-led. So to that extent, you’ll have this human touch when it comes to selling, but that’s the same point that we discussed, right? You enjoy conversations and everything else has to be automated. That is where this entire thing will kick in. So you can make the sale, and you’d like to automate everything else. I think your own model is the best example of how it can possibly run.

Ganesh: Yeah, it’s actually true. I think we are going into a world where it’s a bot for everyone, like the RPA companies say. But it’s an intelligent agent, everybody has their own Jarvis suits that will just do all the things that you don’t want to do, and you’re going to just automate all of that. And then you can just focus on the things that you really enjoy, that’s meaningful, that’s high impact, and so forth. Now, this has been a fascinating thing.

One more question on what other lands and what you are doing in this thing. Talk to me about your organizational approach to setting up this technology capability and the customer centric capability. Can you give us a glimpse on that? I know it wasn’t an 18 month journey, it probably started before that. But AI, and especially technologies like machine learning is a team sport, there are multiple people involved. I can very well see that you have a design person at the center of everything. But explain to us your approach, and how you get the team together to go make this all this possible.

Dipu: It’s a very interesting question Ganesh, and I think you’re basically talking about the whole approach to AI. How do you basically go about institutionalizing it? So if you look at how a lot of insurance companies were established, they were as we said, an insurance is one of the oldest businesses globally. And that’s where we also come in. You basically start with what’s available. Which means over a period of time, it becomes a legacy system. Because the firm is at least 20 years old, right? It was the best system when it started. But over a period of time, because it acquires bells and whistles, we realized the need to replace it. So that’s one.

One thing which we have done Ganesh is, we have also gone for a core transformation: our core platform, we are right in the middle of the journey, we have already migrated to large lines of business and we are migrating other lines of business as we go on. So that’s one thing, because that is the center of everything that we do. The other thing which we have done is, apart from our core transformation, we have also basically moved to cloud. And that’s a significant step which we do because of the standard benefits: you want to avoid hardware obsolescence, you want to move from siloed data Mart’s to a single data lake, and all the standard benefits which you get when you move to the cloud. But I guess we were in the news, because we were not the first players to transform the core and simultaneously watch it on the cloud. So that was the second step.

The third is, apart from the core and moving to the cloud, we also have these larger separate systems. So for example, let’s take our customer relationship management software or middleware. We basically revamped recently just before COVID-19, and it really helped us during the COVID-19 phase. When it comes to AI, we have a lot of them, which are customer facing, like our bots and portals. And we also have a lot of automation in the back office. So for example, we use RPA in our back office. So this is a landscape, and as I said, over a period of time, we kept reinventing ourselves. Now, to your point around how we go about doing this, as we said, what we do is we start with the customer. And then based on my experience in GE, we basically classify any business case which we build into three buckets.

One is we look at what we call soft metrics. The soft metrics are the obvious ones: maybe your turnaround time comes down, maybe your customer grievance ratio reduces, maybe you get real time fulfillment, so you get all those, which are obvious benefits from the new technology, which comes in. So that’s one.

The other is what we call hard benefits, and this is where the classic capex versus opex discussion happens, you indulgent capex today, but it plays it out through OPEX savings, or millions of transactions over a period of time.

And lastly, you look at a CVA positive equation. And the third thing is, and that is most likely intangible: that’s when we start looking at brand. So for example, we take pride in the fact that we have been the player with the highest NPS scores in the marketplace, which is done by a third party agency, and also the lowest grievances, which is tracked by the regulator. So from both perspectives, and both are third parties. As in, we do not measure it ourselves. So then we look at the impact on the brand. So I think a combination of soft metrics, hard metrics, and brand: the intangibles. I think we use this to get everybody on board.

And one more thing, one strategy which I have deployed to the point that you made is, very often, initiatives don’t see the light of day, because the heavy lifting is not done upfront. You need to do the heavy lifting upfront, you need to figure out who the stakeholders will be for the project, whether the stakeholders will have opposition, how you will handle an objection handling, so on and so forth, so that by the time you come closer to the launch, everybody is aligned. I think this is a strategy which has worked for us.

Ganesh: I love the way you split out the metrics around soft metrics, hard metrics, and then more strategic brand related values. One of the areas that I’ve been exploring deeply is, the pace of technology-led transformations have grown so much, that somewhere down the line, it’s getting harder for us to track the metrics, the hard metrics especially and its impact. Just like you would do in a stock market or in your trading system, you will do some What if analysis, you will do some analysis on, “Okay, let me back test and see how this strategy plays out.” I really think there is an opportunity, because technology is now part of the operating system for organizations, and I believe that that’s an area. So let me flip the question back to you. It wasn’t a question, but then my question to you is, what’s one problem you would like everybody in the industry, in data and AI to focus on that will help you and your organization?

Dipu: I think there two aspects since you spoke about data and AI. From a data perspective, I think it’s about ensuring that we get data. And I think one of the primary problems of the industry is to get holistic data. Because it’s not distribution-led. And very often, it’s a b-b-c model, it’s not necessarily a b-c model. So from that perspective, how do you get full data? Sometimes, you may find that you have minimal data, so I think access to data itself is clearly a problem and another wish list for the entire industry.

Coming to AI, I think the benefits of AI are far too obvious. And AI permeates every single space of what we do. But now for business, empathy and a healing touch are equally critical. Because when customers call you, they basically call you when they’re in bad times and they need human support at that time. So the whole perspective is, how do we ensure that we leverage AI but with the focus on this Barnegat human skill of empathy? So I think if we can get that combination absolutely right, I think we’ve just explored this entire industry.

Ganesh: That’s amazing. Servicing is so core to not just this, but to many other industries too. And even traditional industries that were away from customers through a distribution channel or somebody, they all have to now pay attention to really understand the customer and then provide that direct servicing to them. I think that’s a really good call out.

Okay, one other question, and then we’ll get to some rapid fire questions. One quick question on this is India. I think what COVID-19 did geographically is, it removed the geography requirement for economic activity as a whole from a worldwide perspective, right. I was talking to some friends back in southern India yesterday, and code is a common language right now. So you don’t need to know different languages to speak, as long as you can speak it through your code. Give us a view on that. I know that India has gone through a lot in the last year and a half, or in the last two years. But the resilience is just really inspiring from the people. So give us a view of India in terms of technology and talent. What do you think when you see the market today and going forward?

Dipu: Firstly, I think India is the hub when it comes to usage of technology, as well as the availability of talent. We’ve seen so many Indian firms from here go and make an impact globally. And India has always been the place for talent, which is why we have a lot of back offices in India as well. And I think clearly talent availability in India has been amazing. That’s something which is a well-established fact.

Secondly, coming to the usage of AI, I think what happened with India like we all have seen is, it has leapfrogged several evolutionary stages. And India’s a mobile country; people use mobiles. So, today, what is happening is, because of the availability of mobiles, the availability of the Internet, the availability of even multilingual versions of digital apps, and various other tools, I think India has exploded. In fact, you may be surprised to know that when Allianz had a mobile conference, and we had people from all over the world, I had gone there to showcase our digital capabilities, including AI, and the people were learning from us. I must mention one thing; very often, people ask, “Okay, fine, is this a PLC or is this just the pilot group of a small group of customers?” And then when I tell folks that our customer base could be bigger than your country’s population, then they realize that it’s happening at scale.

And I think going forward Ganesh, there are two or three aspects which will kick in. One is multilingual, because obviously, in India, people speak multiple languages. And we had one success story here; we launched an app exclusively in Indian languages for farmers. And it turned out to be a major hit. It just shows how you can digitize even in rural areas.

And the other is, in India, sometimes given the variation in bandwidth, it also calls for versions of apps; maybe you can have a light version in some places, and you can have an enhanced version in some places. So, I think India is rocking it from a usage as well as a talent point.

Ganesh: Absolutely. You’ve touched upon something. I grew up in India, so it is near and dear to me. Historically, the population of India was used as a talent pool for providing back office and other services. But the vibrancy comes in when more people are coming online. For technologies like AI, you need a lot of data, and there’s a lot of people. So now, as an addressable market where people are consuming these services, from a cultural diversity perspective, it’s way more diverse than China.

And then for the availability of talent, I think the golden era of India is ahead of us. And I do believe that it’s already been a golden era, but I think it’s going to just even go bigger. Dipu, thank you for your thoughts here.

I have a couple of very quick, rapid fire questions, and then we’ll get your thoughts on it. Artificial general intelligence AGI: machines taking over the world, do you fear it? Do you worry about it? What worries you if you do?

Dipu: Well, I don’t fear it Ganesh. I think the benefits are far too obvious. As I mentioned earlier, we just need to ensure that the human touches or impact are aligned with it, and, then I think we are on.

Ganesh: One personal question Dipu. What is one practice that you do every day or often, that keeps you at the top of your game?

Dipu: Good question, Ganesh. This goes back to my learning. At work, the one question I ask myself every day is, is your job driving you or are you driving your job? And from that one question, I figured out my answers, and I think that’s what drives me to be different and stay ahead of the game.

Ganesh: Amazing Dipu. Thank you for that. How can the viewers and listeners get in touch with you online? Where can they find you online?

Dipu: Yeah, so people who want to connect with me are free to do so using social media. I’m available on LinkedIn, Twitter, Instagram, and Facebook. So social media: people can connect and I am always happy to share knowledge.

Ganesh: Awesome Dipu, thank you so much. Thanks for taking the time. Fantastic discussion and I’ll be in touch.

Dipu: Thanks so much Ganesh. And I think your warmth and your easy flow made it very easy for me to feel absolutely natural. So thank you so much.

Ganesh: No, it was a great conversation. Thank you so much. I’m sure everybody who’s listening in can really see the depth at which you’re making it sound so simple, and I can only imagine how hard it is to pull each one of those things in there. And thank you for sharing your wisdom and knowledge and your experience here.

Dipu: Thanks Ganesh. If I’ve been able to make it feel or look simple, then I think I’ve done my job.