2943: LTIMindtree - How Is Digital Transformation Shaping Our Future?

[00:00:01] How are businesses navigating the complexities of AI and automation in today's digital age? Well, in this episode I'm going to be joined by a very special guest. His name is Sudhir and he's the president of LTI Mindtree and they are a leading provider of technology

[00:00:19] and consulting services across diverse industries. And by that I mean everything from financial services to retail. As a company right at the forefront of digital transformation and helping companies build resilience and foster growth through innovative technologies, I

[00:00:36] want to learn more about the kind of conversations they're having with business leaders. What are their challenges? What are the opportunities that are being presented by things like generative AI? And what is the impact of digital transformation on industries and workforces? And if we've

[00:00:54] got time, I want to learn more about why investing in advanced technologies in everything from AI, quantum computing and robotics is essential for both sustainability and long-term success. It's a huge topic this one. So I want to learn more about how businesses can

[00:01:11] effectively harness these technologies and ultimately stay competitive and resilient. So buckle up and hold on tight as I beam your ears all the way to London here in the UK where my guest

[00:01:25] today has done a lot of travelling but luckily for us is immune to jet lag. So let's get him on the podcast now. A massive warm welcome to the show. Can you tell everyone listening a little about who you are and what you do?

[00:01:40] Thank you Neil, my pleasure to be here today. I am Sudhir Chaturvedi. I am the president of markets at LTI Mindtree. I'm also a member of the board. What that essentially means is that we have 10 business units

[00:01:53] in the company that provide services to clients and my role is to ensure that the promises that we make to our clients are kept as we serve them. I represent LTI Mindtree which is a consulting and digital solutions company.

[00:02:08] We have just over 82,000 people globally. Our revenue is north of 4.3 billion dollars and we've been one of the growth leaders in the industry for the last five years or so.

[00:02:21] Well it's a pleasure to have you on the podcast today and I'm interested in diving into some of your insights and also you've got the ear of so many businesses and professionals around the world. I'd love to hear more about some of the

[00:02:33] technologies and trends in the conversations that you're hearing at the moment. And of course we are at a time where we're witnessing this surge in generative AI and automation technologies and I'm curious to begin with,

[00:02:47] what are the primary concerns you hear from business leaders about integrating these technologies into their operations? We've heard about the hype but I'd love to hear about some of the concerns too.

[00:03:00] That's a great question Neil and frankly this is the number one topic of discussion with leaders whether they're technology leaders or business leaders in the world today. Frankly let me start by saying that AI and generative AI is truly transformative

[00:03:15] technology. I would say after the internet this is the biggest change in technology that we have seen and this is here to stay.

[00:03:23] But there are issues with the wide scale adoption of generative AI especially in businesses and I would break it up into sort of four broad areas.

[00:03:33] The first one is trust. I think the accuracy of the output that is generated by AI is still under question. So AI does have hallucinations which essentially means that when generative AI is good at generating answers but when it doesn't have the right answer

[00:03:49] it will still generate some answer which is not right and that's it doesn't say that I don't know and that itself is an issue.

[00:03:58] So it causes hallucinations and that is something that clients of mine are concerned with. It also has biases and some of these biases are based on

[00:04:06] the learning models that have been adopted because the data sets in some cases are more representative of a certain group of people than others. So certain groups of people might get inadvertently discriminated against simply because there wasn't enough data to train the large language model on that.

[00:04:25] And those biases have to be looked at. The third is explainability. Many of our industries are regulated industries where you have to explain a decision.

[00:04:32] For example if a client makes an investment decision you need to explain as to what was the reasoning behind the investment decision or in the life sciences

[00:04:40] industry where it's been significantly adopted in terms of molecule management. What prompted the move to or the selection of a certain molecule in drug research for example.

[00:04:50] So all of those things need to be explainable and right now the explainability is still not completely there. So all of these areas cause essentially a showdown trust

[00:05:00] completely trusting the technology. But it is getting better and we will reach a stage where these things will be overcome. There are security and confidentiality concerns as we as clients look to

[00:05:13] for example put their own data into using generative AI especially in some of our clients are using it to write code for example. You're putting an intellectual property in a tool.

[00:05:23] You want to make sure that it's completely safe and secure. And I think this in this place we made a lot more headway. I think security and confidentiality concerns will be addressed quite shortly.

[00:05:35] Regulation is still a big one. I think this is where I find many of the business leaders quite concerned because frankly the technology is far ahead of the regulation today.

[00:05:45] There is regulation in the EU. There is some in the US as well. There are guidelines that have been provided by the Biden administration. There is a rules coming out of India China and various other. So there is firstly the harmonization of regulation itself will be something that we will need to look at.

[00:06:01] But this is a key for us. Financial services is 38 percent of our revenue about banking and insurance. And these clients are in heavy heavily regulated industries. So this is key. And last but not the least though this sometimes gets overlooked in the hype is the cost.

[00:06:18] So the cost of AI is quite high. If you look at the costs because we pay for the usage of these large language models based on tokens and tokenization can be quite expensive especially as the way different large language models charges. There's a very wide variation in what you pay for a chat GPT-4 versus what you pay for some other large language models.

[00:06:42] So I think that is increasingly as clients look for wide scale adoption because once you go in then there's no going back. So you need to worry about the costs in the long term as well. So quite a few areas of concern but the technology is headed in the right direction. We are actually I think my biggest my personal view is that the regulation will be the one that will need to catch up soon enough for us to enable wide scale adoption.

[00:07:06] Yeah I completely agree with you about regulation and also the arrival of AI and how it's the biggest thing since we've seen since the arrival of the Internet and it's not going anywhere. And with digital transformation already becoming a strategic necessity for every business I'm curious how do you see this reshaping the workforce particularly in sectors like retail and financial services because again there's equal excitement and concern and caution.

[00:07:34] There's so many different conversations around this too isn't there.

[00:07:37] There is absolutely. In fact I would say that you know when we especially see we since if you mean the thing is COVID was the moment where digital transformation really took off right. And it took off because now suddenly we had to provide especially the customer services part had to be done remotely and every aspect of the business had to become a combination of hybrid models that were had to be adopted.

[00:08:07] And that supercharged essentially cloud and the adoption of cloud digital technologies. And that now we have AI coming to take this two steps further. I think the biggest impact in my experience has been in the customer experience area. If we look at what the clients of ours are doing I'll take some of our financial services clients as an example.

[00:08:29] Insurance clients for example deal with claims and some of these claims are being dealt with in quite difficult circumstances because people may have just had an accident and they're speaking to the insurer just to make sure that they looked after that they're covered. There's a lot of anxiety that they're facing. And what is what would be great is if that if these people were able to reach a human the moment or a person to speak to the moment they made the call rather than going through an IVR system.

[00:08:57] That the person was engaged with them was speaking to them without necessarily having to put them on hold for multiple times to just type out what was the conversation or to understand what's going on to really provide reassurance in mostly sort of difficult circumstances for the customer.

[00:09:15] And if you look at how AI is helping with this one of the things that we're doing with one of our insurance clients is that the AI is essentially transcribing the conversation and is able to understand what actions need to be taken. So the agent can actually converse directly with the customer and not worry about taking notes or taking actions.

[00:09:36] And at the end of the call it summarizes like a copilot summary to say, okay, these were the agreements that this is what we agreed with this customer on the call. If they agree with it, they can just take it and they move on. Now the advantage of that is that the call time reduces as well as the customer experience improves.

[00:09:52] Now businesses can use this one of two ways. They can say, I can have less of fewer agents to provide this service or I can get to a stage where every customer calls does not need to go through an IVR because they need to, they can directly connect with a person because I have more time available because these calls are now shorter duration.

[00:10:12] And I think our clients are taking the second approach because they're finding that, you know, the people who are calling in or especially contact centers do really expect that experience to be first time, the experience to be a personal. So I think this is a, though it is seen as one of the examples where AI will have a negative impact, I think AI will have a very positive impact on this as we essentially the agents are super agents because they've been powered with AI.

[00:10:40] And I think this is a great way to look at it. And there are several industries, whether it's financial services, it's retail, it's telecom, where customer experience is a, and these customer, these contact centers or customer service operations are extremely important part of their business in terms of loyalty that they create with their customer base.

[00:10:58] The other areas, operational efficiency. I think many of these areas, I'll give you a simple example in trade finance, which sounds like a very boring topic, but you know, when you put something on a ship from one part of the world and ship it to another, there is a whole host of financial instruments that are actually going to making sure that the supply chain of any product works. Right? So trade finance is very critical in the past because it involved a company on the other side, which was supplying the product, a shipper, what a, maybe a supplier.

[00:11:26] A shipping company on the other side, a clearing company, multiple people involved. You will be surprised that I think the last use of fax machines that I ever saw in banks was actually happening in trade finance as people were financing these, faxing these documents over for people to look at and read and then provide credit or insurance or whatever was needed with trade finance.

[00:11:53] And in COVID, certainly as post COVID or during COVID, as none of these were available, suddenly we found that the people were able to digitize this much faster and able to use these technologies. Today, a lot of trade finance, which used to take three or four days sometimes to process is being processed in seconds, if not minutes actually.

[00:12:12] So the speed at which these things are happening, simply because we've digitized the entire process and now with AI, it also getting, we can add some intelligence in the decision-making to the process. We are saying that this is fantastic news for, actually because supply chains, we saw supply chain disruption lead to increase in prices across the board.

[00:12:32] So the more efficient you make a supply chain, the better it is for the end consumer. They benefit from lower prices and better product availability. So I could keep going on and on because it's one of my favorite topics, but I think what I feel from a customer perspective, digital transformation technologies have truly benefited them in multiple ways in terms of making our life easier and potentially, I think going forward, even sort of much more.

[00:12:59] I mean, obviously the cost effective part is very critical. We live in difficult economic times. So I think any, as one of the greatest retailers in the world says, every little helps. I think this is how technology has also, especially digital transformation technology has evolved.

[00:13:16] And I think your passion for this topic really shines through in our conversation today. When I was doing a little research on you, I know that also something that you're very passionate about is the importance of investing in technology for resilience and growth. And just to bring that to life, are you able to share an example of where strategic technology investments have actually significantly benefited an organization?

[00:13:42] Because there's so much talk at the moment about tech projects, delivering ROI and generating business value. And it'd be great to bring that to life with a use case or example if you have one.

[00:13:52] In fact, I'll stay with the retail example that I just gave because omnichannel commerce became is now we're used to it. We're used to buying products over the internet and being able to pick it up somewhere in a store or being able to return it in a store. The various models of omnichannel that are available across the board.

[00:14:10] But I think one of the things that we did with one of our clients is when we integrated these all these channel experiences, we also moved them to some technology that enabled people to buy in installments, buy now pay later kind of thing. And though I know sometimes there is a little bit of controversy around this, but as long as the product is structured well and the way it is sold appropriately, it can be very beneficial to consumers, especially that are making large purchases.

[00:14:40] We enabled this for a UK based electronics retailer and their sales of certain product categories went up by 35%. And some of these product categories I think are quite critical to quite basic. I mean, things like refrigerators, for example, are usually bought when a previous refrigerator or the existing refrigerator is has literally died.

[00:14:59] So you're not, it needs an immediate response. You need to get something in quite quickly. So I think it's very beneficial from a quality of life perspective that some of these instruments are available to customers. And there are several such examples. I give you the trade finance example as well that has really investments at this have delivered ROI, which is far beyond what was expected.

[00:15:21] I would say that from a looking at it from a LTI mind tree perspective, one of the things that we believe is very critical is the training of people in AI, the investment that we make in training. So we've just trained, we've trained right now just over 42,000 people in our employees and we are planning to train all 82,000 employees. But what we are doing is we are offering this training to all our clients as well.

[00:15:47] So the same training materials are available to all our clients free of cost so that we believe that education, the investment that clients will make in understanding this technology, because I think Jensen Wong said it right, that today your job will not be replaced by AI. It will be replaced by a human who knows AI. And I think that is a very good way to look at AI.

[00:16:12] And therefore it is important for the entire workforce, for all of us, whether we are in technology or in business, whether we are a customer service agent or we are working in a warehouse or we're providing services to clients in an office, it doesn't matter what your work environment is. There is an element of AI that will have an impact. In fact, there is a recent study done in the US which said that 80% of jobs will have at least a 19% impact of AI.

[00:16:42] That's the best, most comprehensive study that I've seen which talks about that not all, the entire job will not be impacted by AI but aspects of that job will be impacted by AI. And as long as, just to continue with that example, if 80% of employees know that 19% of their work content is going to be impacted by AI, it's better that they understand the AI themselves so that they're able to use it for their own benefits and in terms of their own productivity, in terms of their own quality of life and providing a better service.

[00:17:12] And it's also worth highlighting, I think that we are in a period of economic uncertainty. We're seeing it all around the world. How do you see digital transformation enabling companies not just to adapt but maybe even thrive in today's rapidly evolving market conditions and almost use it as a growth lever too?

[00:17:43] So, typically all our clients look at the three types of revenue growth. So, we call it H1, H2, H3. So, H1 is how do you make sure that your existing revenue base doesn't start to decline? So, classically in the media industry, for example, churn, right? You want to keep churn to a minimum or to avoid it completely so that you keep your existing revenue base.

[00:18:08] The second area is how do you grow adjacencies? So, keep your existing core. How do you grow in adjacency? So, which areas that are just around your core that are more easily accessible for growth, how do you do that? And how do you enter major new markets?

[00:18:22] So, I'll give you an example. One of our clients is in the HVAC space. Now, sounds very boring. This is large-scale air conditioning. But again, as we move to hybrid work environments, some offices are only really occupied three days a week or in some cases, certain floors are occupied, etc., etc.

[00:18:41] So, how do you make sure that the HVAC is actually used when it needs needed to be used? And for that, because the hardware will continuously keep running, it's the software that will change that. The software will detect, okay, what's the occupation in the office today? Therefore, what time is people coming in? When do we make sure that the AC or the HVAC systems are working appropriately? Make sure that the quality of air is appropriate.

[00:19:08] All of that is done through essentially through software. So, this initially, by the way, started as an ESG mandate, but they found that it's a very critical part of their sales strategy in order for the clients to say that, hey, we're not just providing you HVAC, we are actually providing you the most intelligent air conditioning system that you can have. And frankly, it is cost-effective, it is sort of more ESG-friendly, etc., etc.

[00:19:35] And this could only happen… So, this leads to new markets for them because some of these buildings, and especially with LEED certification, etc., etc., when they look at these technologies, these are technologies that are suddenly now available to them.

[00:19:49] So, I think these are new revenue streams on existing product lines that are created, which I always find fascinating. I love so-called boring industries, which do really cool things with technology that actually make them grow much faster. In this case, this company added about 15% to their top line simply in terms of how they were able to do that and frankly change the positioning of the company because they're suddenly now seen as this digital HVAC company.

[00:20:15] And I think that is quite an interesting example of how people have achieved this. The other part that I've seen in keeping hold of existing markets is that clients want to do this more cost-effectively. So, the way some of the marketing strategies to this using AI, we have seen some of our clients, especially in financial services who, in wealth management, for example, use very personalized messaging on…

[00:20:42] If there is, for example, an interest rate change or there is a world event and they want to hold a webinar around it or a briefing for their wealth management clients around this, they'll actually be able to send them an email to say, this event, if this is an increase in interest rates, it impacts these asset classes. You happen to own some of these asset classes and therefore, it would be good for you to attend this webinar because it has a direct bearing on some of your returns.

[00:21:06] Now, if you think about it, it's a phenomenal tool because anybody who reads that, assuming they don't get completely creeped out by like, oh wow, this is a little too personal for a webinar invitation, but this is a trusted relationship with the bank, I would assume. So, your likelihood of attending this webinar is much better. And if you do that, then your likelihood of speaking with your advisor to make better decisions about how you manage your wealth is also better.

[00:21:36] It benefits everybody all around and that's a great example of how you can essentially use very hyper-personalized technology to keep hold of your existing base and perhaps even grow it. So, I think those are the kind of examples that clients get very excited by to say, this was not possible before. Before, you were not able to send an individualized email to every client, but today, you are able to do that.

[00:21:59] And one of the things that stood out for me about the work that you do here is you work across various sectors and everything from manufacturing to entertainment. So, I'm curious, how do digital strategies vary across these multiple industries and are there any unique challenges or particular successes that you may have observed?

[00:22:19] Yeah. In fact, let me take the media and entertainment industry, Anil, because I think that's one that we're all very familiar with. We consume content all the time. I'm hoping that this podcast will be consumed very widely as well. But I think if I reflect on this, I was at the Super Bowl this year. I was lucky enough to be invited by a client of ours, Paramount, that actually broadcasts the Super Bowl there.

[00:22:46] And of course, it was really all about the broadcast and the streaming. And streaming has taken up a lot of the – in fact, most of the conversation around digital technology in media has been around streaming. But I think, as I said, I love boring, more boring aspects of technology.

[00:23:02] But the way broadcast technology itself has changed, broadcast has gone from these – essentially satellites and all of these antennae in various places to actually moving to the cloud, which has resulted in a massive change in the way content is made available. The same content is made available to various people across the world.

[00:23:22] And that has really led to the change. In fact, the combination of that has created an entire new area called the content supply chain. It always existed, but now it is a digital supply chain of content that is available. And that has an impact on people who create content. So content creators essentially get paid through a concept called rights management. And now that rights management also gets digitized.

[00:23:45] Now, why this is important is now when you stream a certain piece of content anywhere in the world, say a television series, the rights management determines as to which part of the world you can see it in, which part of the world you can't see it in. It also determines how that supply chain is made available. If some places there's advertising with it, then it goes with advertising. Some places there's no advertising, so it goes with subscription.

[00:24:08] So all of these various combinations are now available to everybody around the world. It's only enabled because of digital technology. In the past, with traditional broadcast technology, traditional supply chain, traditional rights management, you would never be able to do this.

[00:24:23] And I think this is it. I think because we are in a content creator world where content creators are essentially driving this revolution, and the better the rewarded they are and the more widely available their content is, it'll actually make the streaming business grow faster. So I think you can look at the streaming business in terms of tech, but you can look at it in terms of content creators to say, okay, how do we best help content creators to create this?

[00:24:49] And that's our mission, to actually take great content and make it as widely available as possible with every bit of technology that is involved in that process, which is essentially digital technology. And now we are, of course, in all of these aspects, infusing AI in it.

[00:25:04] So I could go on again. Media is a very, it's a fascinating industry because it has adopted new technology very quickly. I'll just end by saying that our focus is on making sure that people create great content and other people who actually benefit most from it and therefore keep creating even greater content for all of us to enjoy.

[00:25:23] And in terms of boardroom priorities and AI investments, a lot of businesses are challenged with doing more with the same budget at the moment. So when it comes to executive decision making, how high is AI investment on the agenda from the conversations that you're having? And have you noticed any shifts in boardroom conversations over the last year?

[00:25:44] I know from the tech conferences I went to last year, there was a lot more caution and concern. And let's see how this pans out. This year, things seem to be moving much quicker. But what are you seeing?

[00:25:56] Absolutely. I completely agree with you. I think we are seeing an acceleration towards this. A lot of this conversation is led by AI, that is because clients are asking, for example, our chief information officers and chief digital officers, who are our chief marketing officers, who are our main clients, are getting asked these questions by the board as to what is our AI strategy.

[00:26:19] But I think now what I'm saying, Neil, is more recently is, how does AI change the technology strategy and the business strategy of the company? I think it has moved from knowing what to do with AI to making sure that AI is part of everything that we do in business and technology. And that is a very good way to look at it. And that makes those investment decisions more long-term, more sustainable.

[00:26:41] Because if purely AI, if you just looked at AI and started playing with it, it led to a lot of proof of concepts. And it became what I call the shiny object thing. You do a few shiny object projects and you get very excited about them. But in reality, you're not deploying them large-scale in production.

[00:26:57] And unless you deploy them large-scale in production, it doesn't really generate new revenue or it doesn't really make an organization more operationally efficient. So therefore, I think infusing it with the technology and business strategy is the best way forward. And that is what I'm seeing today.

[00:27:15] Clients are obviously interested in the revenue growth aspects that we just spoke about. There is operational efficiency to be gained. There are lots of tasks that are done, which, and again, I'll stick, I come from a financial services background. So I have a little bit of bias towards examples from that. But if you look at the speed of underwriting today in terms of insurance, especially of a large commercial property, it takes a few weeks, if not a month or a couple of months sometimes to underwrite.

[00:27:41] Now, if you've got better technology availability, especially AI, which is fantastic at information summarization, the ability to read through multiple documents and summarize them is one of the best attributes of AI. Then you can underwrite faster. You can automate that process faster. And it helps again, it helps all, it helps the underwriter, it helps the insurance company, and it helps the company that is seeking insurance as well. So all of those aspects.

[00:28:09] So operational efficiency, very high on the agenda, but also the downside risks. So what if we don't do this? Or what if we don't do this fast enough? Or what if we do this and we get this wrong? And I think it is good to have this well-rounded discussion around, yes, we see the opportunities and we should capitalize on it, but let's also understand the risks and address them appropriately, which is why we keep telling our clients that create a very strong Gen AI foundation.

[00:28:37] It's creating a technology layer within an organization, which is the foundation for AI. And that then becomes infused in everything that we do. In our own, in the LCI Mindtree model, we have 23 building blocks to create foundational technology for AI. And I think this is very important for clients to adopt. There are other options also available, but it's important for clients to build that AI foundation within their organization.

[00:29:05] Then they'll be able to address some of these boardroom priorities in a much more effective manner.

[00:29:35] Absolutely. I think if you look at the combination of cloud data, digital and AI, in fact, even the tech footprint, right, in terms of government footprint has gone up because these are expensive. Not just know that the cost of processing a simple AI query can be quite high in terms of not just, I'm talking in terms of from an ESG perspective, power consumption, et cetera, this is significant.

[00:30:05] But let me, I'll give you perhaps a couple of examples just to illustrate. So we are working with a utility and we've reduced 2 million metric tons of carbon emission for them through better use of technology and through deploying some AI technology as well in that. So the combination of cloud data, digital and AI has led to this. And that is a significant reduction for this particular utility.

[00:30:28] And utilities themselves are sort of high carbon in industry, even now as we move to renewables, as that shift is happening. So you can do it through two ways. You can reduce your own carbon footprint and you can then add more green energy so to become carbon neutral. And that's the combination that we're working in.

[00:30:47] I spoke to you a little earlier about my own travel and I think travel is again, a major source of carbon emissions. So we've launched something along with Thomas Cook, which is called Green Carpet. And Green Carpet essentially measures individual carbon emissions through flights all over the, that one takes and as people are able to then calculate what their personal carbon footprint is like, what the organization carbon footprint is that.

[00:31:18] So if you have a watch which counts your steps, you're more likely to do something about it. So it's continuously giving you information as to what the carbon footprint is and therefore how to address it. And if you can get millions of travelers to which corporate travelers, which are our target market here to even reduce their carbon consumption by a bit, you can see that the benefits will be significant. So, and this is easily deployable technology.

[00:31:42] And last but not the least, I think that the whole, see we have a lot of operational technology, which we call OT or which is the Internet of Things for example. So there are factories, there are refineries, there are generation, power generation plants. Many of these are very old. Some of these are high carbon generating facilities.

[00:32:03] So we, there is this whole move to industry 4.0, but what we believe is that the IT and OT integration, if you integrate information technology with operational technology and do it well, infuse some AI in it, you can modernize these plants at a much lower cost and with a very significant ESG footprint.

[00:32:20] So if you imagine the basic, the millions of factories all over the world can all produce a little less carbon if you just use better OT and IT integration. And that is one of the things that we are working on. Again, on the less glamorous part of the world, but if you calculate the cumulative impact of what can be achieved, it is very significant.

[00:32:40] So today we're working with about 20 refineries all over the world to reduce their carbon consumption by 10%. And that's tens of billions of metric tons of carbon reduction. And those are the kinds of things that we are focused on. This is a very clear agenda for us as a group as well. We won an award recently for our ESG reporting. And as you said, our employees are very passionate about this.

[00:33:04] I think what I love about getting to work every day at LJM-Ientry is that we essentially leverage new technology to grow, but what we're looking at to see is what are the benefits of new technology? It's not technology for technology's sake. How does it really benefit society? So one of our mantras is how do you solve for society? So when we look at anything that we do for our clients, we always have that lens to say, how is this solvent for society?

[00:33:30] And if you permit me, I have an example from AI actually. I feel in a way a little sad to even describe this, but it is the reality of the world that we live in. Unfortunately, there are millions of refugees all over the world today for various reasons.

[00:33:47] And each refugee, most of these refugees are housed in refugee camps and in certain locations all over the world. And each of these locations, refugee camp locations or these refugee zones has their own rules and policies and funding mechanisms and what do the government that is hosting these refugees has agreed to or not agreed to, what the funding agencies have agreed to or not agreed to.

[00:34:11] There are various policies, rules, regulations that determine every refugee camp and zone. And what happens is the people, for example, and this work is for the UN High Commissioner for Refugees, this is the work that we're doing for them, is to see that the UNHCR employees in any refugee camp or zone are able to make sure that they know exactly what budgets are available, what rules are there, what policies are there, what they can do, what they can't do, and they have this real-time availability.

[00:34:41] So because the moment sometimes they make an error inadvertently and some funding agency will pull some funding back because it didn't fit that in. And that's essentially a small error can lead to a large impact. And we want to make sure that we are compliant at all times. But by doing so, what it does is it makes sure that the camp, these refugee camps, we make life a little easier for the refugees by making sure that all the UNHCR employees have access to all the information that they need to carry out their tasks.

[00:35:11] Without error. And this is, I mean, it's an information summarization use case as we call it in tech terms. But in reality, it is making the life of every refugee in that camp a little easier. And we are doing this work right now for 2 million refugees. It is not exactly ESG, but I think it is socially very important that we also use technology to do things that benefit those who are most in need of help.

[00:35:39] That's a powerful moment to end on. But before we do, if I ask you to look ahead, we're already halfway through 2024, which blows my mind, but looking ahead, what do you think the next big innovations in technology will redefine industry standards and business practices? Where do we go from here? What's next?

[00:35:59] What's next? Great question, Neil. I've been in this business for over 30 years. I can tell you, I've never been more excited to be in technology. I think this is the most exciting time to be in technology. I'll just paraphrase, I mean, in fact, quote Sam Altman when he says that chat GPT-4 is the worst version of chat GPT you will ever see. I think AI is literally getting started. Somebody described it as a toddler right now and very fast moving to becoming an adult.

[00:36:29] I think we will see massive leaps in AI itself. In addition to this, I'm very excited about quantum computing. I think people have today, of course, the biggest fear. One of the fears of quantum computing is that existing encryption is likely to be broken by quantum in the next three to five years and we have to protect ourselves on it.

[00:36:47] I think there's a very important role for governments to play in terms of making sure that encryption, which is the cornerstone of all security and information security in the world today, is not impacted by quantum negatively. But quantum will make massive leaps in optimization technology, which is needed in order for us. We just had this ESG conversation. I think quantum can play a huge role in that in every aspect of life.

[00:37:14] And quantum technology is going to be here sooner than most people think. I think it's going to be here. And I would say robotics, I think robotics is going to come back. I mean, I know there is lots of usage of robotics and we work with industrial robots all the time, but I think looking at robotics in the home and in healthcare is going to become, we're going to reach that stage where this becomes, you know, there are several examples.

[00:37:37] I recently saw something about how a robotic seal is being used in care homes with patients with mid-stage dementia or Alzheimer's and it's actually having very positive impacts. This is like a, it's a very cute baby seal. So maybe listeners can look this up. But I actually think that there will be, so the combination of AI, quantum and robotics is at least what excites me.

[00:38:01] But I always tell people that, especially people who are looking, I have an 18 year old and people are looking to say what to study next. And I keep saying any education in the field of technology or even if it's studying liberal arts, but understand the impact of technology on liberal arts, I think will go a long way in having rewarding careers in the future because technology was, is, as I think, the most exciting thing.

[00:38:31] So I think the next big phase of technology is still to go. What would you like to leave and why?

[00:39:32] And I always have this book in mind, which is Thinking Fast and Slow, the Danny Kahneman book, which gives us an idea as to why human beings sometimes make seemingly irrational decisions because we are at the end of the day, very emotional beings.

[00:39:48] And it's very important to understand the basis of decision-making for any leader. I totally recommend this book. And last but not the least, I think one does tend to sometimes look back at their careers and Clayton Christensen wrote a great book called How Will You Measure Your Life?

[00:40:04] So I leave you with these three books, which I think have had a very profound impact on me. And the song, I just came back from India, but it was very hot. It was very hot in New York when I left as well. So I guess the song of the moment is probably Heat Waves by the Glass Analysts.

[00:40:21] Great song. Well, I'll add the three books to our Amazon wishlist, the song to the Spotify playlist. But for anyone listening, we covered so much there. So anyone listening wanting to dig a little bit deeper, maybe want to find out more information about you, the work you're doing at LTI Mindtree. Where would you like to point everyone listening?

[00:40:39] So yeah, but calm is a great resource. We are revamping the website I might add at this point. But I am on Twitter as well. Oh, sorry, x I should call it as at Sudhir underscore chat. I should do more. But LinkedIn is perhaps the best place I do post there and I actually meet a lot of clients. I attend a lot of events.

[00:40:59] So I do make it a point to share some of the learnings from that on LinkedIn. And I'd love to connect with any of the listeners. I still believe almost 30 years down the line, I'm still a student of technology, still a student of business. So I'm happy to learn from anybody and happy to share my perspectives and insights with anybody.

[00:41:17] Well, there's so much I loved about talking with you today from the considerations and challenges of businesses as the use of gen AI and automation increases how digital transformation is reshaping the workforce and entire industries such as retail, financial sectors and everything in between. And also why investing in technology is a must for resilience, sustainability and growth.

[00:41:41] We even had time to talk about AI, quantum computing, robotics, three books and a great song in heat waves. But more than anything, just thank you for sharing your time with me tonight. Thank you, Neil. Such a pleasure.

[00:42:23] So thank you for joining me in this insightful conversation because the future of technology with advancements in AI, quantum computing and robotics, I think it promises to reshape industries and drive sustainability. But more than anything, you've heard from me, you've heard from today's guests.

[00:42:41] What are your thoughts on the transformative power of these technologies? The good, the bad, maybe even the ugly and the things that you're concerned about. And how is your organization preparing for these changes? I'd love to hear your perspective. So please email me techblogwriteroutlook.com. You can get me on X, LinkedIn and Instagram just at Neil C Hughes.

[00:43:04] So let's keep this conversation going and please stay tuned for more episodes where we will continue to uncover the latest trends and insights in technology and how they're impacting business. And hopefully together we can all learn from one another. But until next time, keep innovating, stay ahead of the curve and meet me here same time, same place tomorrow morning. Speak to you all then.