What's Up with Tech?
Tech Transformation with Evan Kirstel: A podcast exploring the latest trends and innovations in the tech industry, and how businesses can leverage them for growth, diving into the world of B2B, discussing strategies, trends, and sharing insights from industry leaders!
With over three decades in telecom and IT, I've mastered the art of transforming social media into a dynamic platform for audience engagement, community building, and establishing thought leadership. My approach isn't about personal brand promotion but about delivering educational and informative content to cultivate a sustainable, long-term business presence. I am the leading content creator in areas like Enterprise AI, UCaaS, CPaaS, CCaaS, Cloud, Telecom, 5G and more!
What's Up with Tech?
Mastering Enterprise Complexity: Vision for AI and Cloud Technologies
Interested in being a guest? Email us at admin@evankirstel.com
What if you could revolutionize your business by harnessing the power of AI and cloud technologies? Join us for a compelling conversation with Sujatha, the Chief Technology Officer of TCS's Communications, Media, and Information Services Business Unit, as she takes us through her extraordinary 25-year career trajectory. From her early days programming during the mainframe era to her current leadership role, Sujatha provides unparalleled insights into the technological advancements that have shaped the IT landscape. We discuss pivotal shifts from object-oriented programming to cloud-native microservices and the transformative potential of quantum computing and AI—all aimed at simplifying enterprise complexity and driving innovation.
In this episode, Sujatha also demystifies the challenges and opportunities of monetizing AI within enterprise sectors, particularly in the information services and telecom industries. Discover the intricacies of scaling AI from pilot phases to full production and how AI can yield immediate ROI through customer experience enhancements. Moreover, Sujatha shares her perspectives on the importance of diversity in the tech industry, highlighting TCS’s initiatives to mentor women and promote STEM education. This episode is a treasure trove of expert knowledge, practical advice, and inspiring efforts towards a more inclusive tech industry. Don’t miss out on Sujatha’s invaluable insights into the future of technology and diversity in the workplace.
More at https://linktr.ee/EvanKirstel
Hey everybody, really exciting and informative chat today with a leader from the global industry powerhouse known as TCS Sujatha. How are you?
Speaker 2:Hello Ivan, good morning, I'm very well, how are you? Great to be here on your show.
Speaker 1:Thank you so much for being here. Tcs is a company that's absolutely fascinating, as you know better than I, and we have lots of questions for you and about the amazing work you do as CTO of the Communications, media and Information practice at TCS. I guess we used to call that telecom, but it's a little more complex and nuanced today. Maybe introduce yourself your role and your team.
Speaker 2:Sure Thanks. Thanks for having me here this morning, ivan. So I am the Chief Technology Officer for the Communication, media and Information Services Business Unit. As the name goes, it's a conglomeration of multiple different industry segments that we have today. So, of course, telecom, or the telecom service providers, form a significant segment of this. We also have large media companies. Media, of course, is very diverse. We're talking about media, entertainment, distribution segments and gaming companies and multiple different, you know, companies in that sector that we cater to and also information services, which are predominantly the companies which deal with data and decisions driven out of data. So it's a wide segment of industry that we cover today, and so I have completed my 25 years at TCS. I started off as a developer programmer and then grew and played multiple roles, both on the delivery side, on financial services, as well as manufacturing and others, before I took up this role in the communications, media and information services unit.
Speaker 1:Wonderful. What a tour de force 25 years at TCS. Tell us about that journey, maybe a little bit from the beginning to today. Tell us about that journey, maybe a little bit from the beginning to today. You've seen a complete evolution, revolution in the IT and services landscape.
Speaker 2:What was that like? Oh, it's a massive shift. So I joined 25 years back. If I reflect back, I joined during the days when mainframe was the biggest book, so I started off my career with mainframes. So you can imagine the green screens that I started off with and you know.
Speaker 2:Then we started the. You know. We saw the evolution of object-oriented programming and distributed systems coming into the Vogue then, and then we got into the era of, you know. Then you know service-based architectures coming into the foray. There, you know the SOAs and the others of the world. We started talking about reusable components and things around that. And then we saw the shift with cloud coming into the picture there. Then cloud native microservices landed on the screen. There, of course, ai, with the classic AI of course, started to take shape there and we started, you know, leveraging a lot of AI traditional AI as traditional as we call it today, with generative AI in the mix and right now, of AI as traditional as we call it today, regenerative AI in the mix and right now, of course, we are on the cusp of regenerative AI and lots evolving in that space. So massive, of course, from a technology perspective. A huge, huge shift, I would say, and lots of learning on the way. And you know always keeps me on my toes and I enjoy that.
Speaker 1:Wonderful and give us a snapshot of your mission within your team and beyond. Of course, we used to talk all about digital transformation. We're still not there. But what else do you do beyond consulting and services and products and so much at TCS? Give us an up-to-date perspective.
Speaker 2:Absolutely Sure. So, as a CTO, of course, anything and everything to do with technology in terms of helping our customers, as well as our larger teams, embrace emerging technologies for our, you know, helping our customers in terms of their digital transformation, or you know, the business transformation that they underway in their organizations that's the the core of the work that I do. And as we speak, you know, as you rightly pointed out, we are still living in an era where we see a lot of, you know, legacy technologies continue to exist. We see, you know, a lot of room for efficiencies and modernization, which is simplification, in fact, fact. So one aspect as enterprises grew and developed into new businesses, the complexity grew manifold, as you know, right. So simplification always becomes the most paradigm need for every enterprise, right? And the new technologies are, in fact, adding more to the complexity as we speak. So simplification, by employing the right technology in the mix, is a big focus area.
Speaker 2:And cloud, as we know it, you know, while we work with all you name it all the cloud service providers across the globe and partners, and we have great, strong partnership with everybody you know you name. But in terms of helping customers, how do they adopt cloud in the judicious manner, keeping a view with respect to not just what the best of cloud can bring to them, but also, but also, a view into how to control and manage the governance around the entire hybrid cloud aspects of it right, and how to judiciously use the cloud in the mix uh, you know, and, of course, all the emerging technologies. In fact, with respect to why quantum is emerging in a big way, we are already working on quantum in terms of where we can look at quantum technology in optimization specific to customer problems, Of course, with more virtual reality and more embedded systems and technologies around that.
Speaker 2:How can we help customers more in terms of the edge-driven ecosystem, as you call it right, so it can bring more use cases to life, closer to the edge or closer to where the transactions or the action really happens? And of course, now with AI as the biggest talk of the town and there's a lot of work that I'm personally driving with respect to AI adoption, both internally within TCS, within our teams, as well as how we are helping customers to scale the adoption on AI. So it's a wide gamut of things, Ivan.
Speaker 1:To say the least. Yeah, wide gamut, so much interesting work. Let's dive into AI adoption, both internally and what you're seeing with clients. Beyond the headlines and the hype and the news that you see every day, what are you seeing firsthand?
Speaker 2:Yeah, Sure See.
Speaker 2:So the segment that I currently work for, which is the communications, media and information services the industry per se is not new to AI. So we have been helping customers adopt AI in the last few years, whether it is in terms of driving more efficiencies in how they are managing networks behind the scene or in the facet of customer experience, so to say, et cetera. So now generative AI has brought in a lot more opportunities in terms of making that more explainable and more personal to the end user. That is what the whole facet of change that has come in. So the bigger while, as you rightly said, there is a lot of use cases out there in the market and so much of literature around it as well, I want to highlight, to me personally, the biggest use cases are the ones which will have a significant material impact in terms of a revenue shift for the customer, or that which will directly impact the customer experience and their customer lifetime value. These are the two important facets of that. So the bigger use cases where generative a adoption per se that you know I'm seeing biggest happening today is in terms of wherever there is a customer touch point, whether you talk about a contact center as a premise wherein you have, you know, providing more cognitive capabilities, like right. So how do we uplift the cognitive capabilities you know, provide more intelligence to the agent who is actually interacting with the customer so that you know to take off that load of cognitive you know, load off the agent and provide them more intelligence so that they are able to better serve the customer, right, and, in fact, helps solve the issues in the first-pass resolution, right?
Speaker 2:So this is one you know. So this is being done in different ways in terms of what I would say. This doesn't displace the human in the mix, but it actually augments or it kind of equips the agent to better serve the customer. So this is one area of a generative AI adoption we are predominantly seeing in this industry sector. Secondly, one of the other areas that I see biggest adoption with respect to Gen AI as such is around the whole personalization scenario, right, In terms of the content. Whether you're talking about content, you talk about the whole value chain with respect to, you know, the whole, whether it's campaign creation to campaign execution, A lot of interventions that generative AI is able to bring in to both improve the productivity as well as bring more context-driven personalization into that scenario? Right, and if I were to talk about the revenue generation bit, particularly if I see talk about one of our large broadcaster customers here, particularly, they want to go global, as you call it, while bringing in a facet of localization, but at the same time cater to new geographies as well.
Speaker 2:Right, so the language translation, as we used to call it right, it's not, while you think it's straightforward, but how do we contextualize and personalize the content along with the language translation for the audience, right? So this is where you know a lot of tools that Generative AI is bringing in can actually bring in that facet of contextualization. So contextualization is one very key aspect of it, right? So anything to do with knowledge work, anything to do with knowledge work is the biggest area that we're seeing. You know generative AI, you know primarily getting adopted, but in the realms of it, we are also working with certain customers specifically around. How do we infuse AI into the core product, for instance, to bring in a product differentiation, particularly some of the customers in the information services sector who sell softwareized products to the customers right In the B2B segment.
Speaker 2:I am talking about how do we infuse generative AI capabilities to make it more contextual to those softwareized products, so to say. And, of course, from the telecom side, in the core network, I mean we are also talking about autonomous networks heavily in the core network. You know the I mean we are also talking about autonomous networks heavily in the industry today. So a lot of aspects with respect to you know, while it it requires a mix of both classic AI as well generative AI. The whole generative AI has brought in that whole aspect of, you know, providing information in an easily understandable manner, whether it is to the network operation personnel or the consumer of the particular data right. So management, network intelligence, for instance, and things like operation management, for instance. So these are all some of the areas that we see in terms of the topics, I would say in terms of the adoption.
Speaker 1:Fantastic. A lot to unpack there. So many killer apps, amazing use cases. I use at least eight or 10 different Gen AI tools in my little business every day. So I can only imagine, as we scale that, the impact it will have on the broader, real big enterprise, sme world, big enterprise, SME world. But let's talk about scaling. I mean, it's no small task to scale in a big enterprise, even like a company like TCS, with hundreds of thousands of employees. To scale those use cases from experiments and trials to full production. What does it take to get that successfully done? Technology, economics-wise, security, compliance, all those things that you have to think about in the large enterprise.
Speaker 2:Absolutely, Ivan. So the last several months, as you would have seen, there has been a biggest phase of experimentation across the globe, and TCS is no different. So we have both internally within TCS, some of the areas that we are internally adopting AI as well as for the customers. We have been in the, you know, done thousands of hundreds and thousands of pilots, basically, both from the perspective of, you know, experimentation of the technology, as well as looking at the feasibility of the use case, right? So now we are at the cusp of what I would say scaling from the POCs and the pilots into production, right, and one of the biggest facets is basically what we have done in the POCs, specifically with respect to whether it is on the tools or the technologies and the architecture.
Speaker 2:I'll call it architecture because the wider gamut of mix here. It's very distinct from what is required to scale in production. Production architectures require a wider gamut of capabilities, right? So when we talk about, you know, capabilities around, you know, model models are not trained, you know, just for a single instance, right? So we need to have a way to manage the models for a continuous basis the model operations and the model management, the scaling of the model itself is a continuous activity, right, and it requires aspects around end-to-end observability to be brought into that whole mix there, right? Second aspect of it is basically the whole realm of the enterprise, guardrails and the compliance side of things, right. What we do in the POC architectures touches upon a smaller facet of the guardrails, etc. But when you talk about going into production, there are a lot of other aspects nuances, that needs to be done, and the quality assurance and the testing aspect.
Speaker 2:There's a lot of effort that is required to go into testing, right from testing for hallucinations, testing for biases, testing on model compliance, for instance, ensuring that there are no IP infringements, for instance right, and a lot of aspects that needs to go into the entire guardrails side of the things, right.
Speaker 1:So so many opportunities to monetize AI. You talked about the contact center and customer experience, immediate ROI on implementing that for customers in all kinds of environments. Beyond that, how do you see enterprises potentially monetizing AI and getting that return on what would be a pretty big investment in tools and process and platforms?
Speaker 2:Sure. So I'll take a specific industry in context here, in this case the telecom industry. We've all known that the telcos, you know, while they, you know, the core of the business is connectivity and selling connectivity to the customers, whether it's residential or for the enterprises. But telcos have also traditionally sold telco cloud right. And today, if you look at, you know, large B2B enterprises, connectivity alone is not the ask of them from telcos. They require more, closer to edge computing infrastructure, specifically those going on private networks, and you know capabilities like that require more of infrastructure as well. Right. So, since telcos have been in the business of selling, you know telco cloud.
Speaker 2:Now, if you look at the AI spectrum of things you know there is also, as you would know, in a lot of you know, geographies where there is a lot of demand for sovereign infrastructure. Right, Sovereign infrastructure, very localized infrastructure infrastructure and the computing infrastructure for AI is there's a huge demand for it right, both from enterprises, small and medium companies, as well as even startups, for instance. Right. So, where they require more localized, you know, ai computing infrastructure coupled with connectivity right, coupled with connectivity as a relic. We are seeing a few of our customers embarking on this proposition where, in terms of combining the power of AI as providing AI infrastructure combined with connectivity, as a proposition to both whether it is a startup or the enterprise localized.
Speaker 2:So this brings in both basically more secure, more sovereign infrastructure, which the enterprises feel more secure about in terms of putting the AI workloads and developing the use cases for themselves or for what they are selling to the enterprises. So the AI factory, as we call it, is kind of a proposition that we are seeing emerging. Particularly, telcos are quite well-placed to monetize that and we are. It is kind of a proposition that we are seeing emerging. Particularly, telcos are quite well placed to monetize that and we are at the early stages of that and we are seeing early stages where the partnerships are there specifically happening today and we are also partnered with a few of our customers as well as the infrastructure partners to bring together this capability. So that is one realm of monetization beyond what the enterprise uses is what I'm seeing.
Speaker 2:The second, as I talked about specifically, to take media as an instance, right. So, for instance, a lot is happening in the ad tech space or the advertisement space, right. So, specifically around how do we increase the whole base of the ad tech industry and move into more realms of? We increase the whole base of, you know, the ad tech industry and you know, move into more realms of, you know, platformizing the whole, you know advertising realm, right? So here AI brings in a lot of capabilities in terms of the personalization of the advertisement, which can be used to lure more marketeers to come onto the platform, right?
Speaker 2:So we are seeing a lot of customers get into the realm of providing, you know, ad tech as a platform with infused very with the AI becoming a core of it, where it provides marketeers the best option to you know, provide, you know, personalized marketing to their audience segments.
Speaker 2:Right, there's a lot of new media in the mix there, particularly on the ad tech space, so which essentially becomes a monetization of the platform which is enabled via AI.
Speaker 2:So that's again another element of monetization that we see in terms of customers adopting and you know, as I mentioned, the third segment of our industry, which is the information services side, which is providing insight as a service, predominantly right, and where a lot of software products are continuing to up the game there, where AI is generative, ai is plugged as a core component of the product itself, right, which allows customer to have more contextual leverage with respect to the core product itself. So that is creating a product differentiation for them, right, it essentially becomes a product differentiation allowing them an uptick with respect to the core product itself. So that is creating a product differentiation for them, right, it essentially becomes a product differentiation allowing them an uptick with respect to revenue. These are some of the examples, you know, that you know would highlight in terms of monetization and, of course, as we speak today, the lot of adoption of generative AI is happening in the augmentation space, but I think the next realm of transformation, where we will see this whole aspect of monetization, will take a bigger leap.
Speaker 1:Yeah, we're just at the tip of the iceberg. So much opportunity ahead of us. At TCS you work with really who's who and blue chip global companies. You really have quite a bird's eye view of what's happening within your clients, any learning or you might be able to share any insights. In working with these clients across the globe, you know what are the challenges they're encountering, what are the opportunities they see. At this early juncture, what say you?
Speaker 2:Sure, sure See, while everybody wants to, all the enterprises want to embrace generative AI and use generative AI for you know, their enterprise, whether it is around improving productivity, efficiency or, for the case of you know, looking at revenue uptake or customer experience, etc. One of the biggest learning that we have seen is that you know the use cases are very easy. The business case is very hard. Okay, so how do we crack the right business case right in terms of what provides the you know, the real value to the enterprise? So this is where careful curation of what are the, what essentially, is a thoughtful implementation. What are those best use cases? What are those best solutions which needs to be taken up to productionize and implement which will kind of really hit the nail with respect to impacting business metrics?
Speaker 2:So this is where a lot of enterprises are kind of still laying the uh.
Speaker 2:You know, um, you know, I would call that. You know the, the uh, the pathway towards you know the, the whole business dimension of you know, what are the uh areas that they will need to really put their money on investing. So that is a one aspect that I have seen across even large enterprises across the globe. Right, the second aspect of it is, um, when the technology provides, uh offers you so much to explore and do, it of course comes with a big cost. So it's very, very imperative that FinOps, or the financial side of it, what goes into not just fine tuning the model or contextualizing the model how do we run the inferences? In fact, the computing infrastructure for the model and the ongoing management of it, also right a lot of aspects of the cost in in mix here. So setting up a good phenops model uh is very, very crucial, uh, you know right at the beginning. So because otherwise you know, uh, you know the, the cost management becomes a very, very, uh, you know, big you know aspect right and governance around this becomes very, very key.
Speaker 2:So that is one area that I see as a learning that, in terms of from FinOps, setting up the foundation of FinOps, is very, very crucial, right In terms of that.
Speaker 2:And the third one is, of course, we have seen where, you know, governance aspects are absolutely, very critical and things are not put in place and right in terms of the governance, whether it is overall, from an adoption standpoint, from the enterprise, security, privacy, the guardrails surrounding that, the usage of the AI, privacy aspects around it, and those are all very, very things can go wrong if those are not completely, you know, clearly addressed, you know, right from the start.
Speaker 2:So governance is a big you know area and, as with any technology adoption event that we have seen across the globe, technology is easy. Change is hard, so obviously it goes with a lot of change as well, and, of course, generative AI use cases are not standalone. It needs to be integrated into the core fabric, whether it is the applications or the systems or the business process itself, right. So the integration is very, very key and getting that whole change done right with respect to whether it is training the users, the skillset, all of that becomes a very, very big aspect. So these are some of the challenges, but there are ways to overcome this challenge with the right strategy and the right roadmap in place.
Speaker 1:So many challenges, so many opportunities. We're all going to be very busy as technologists over the next years. Speaking of the future, let's talk a little bit about the future of work relative to AI. There's been a lot of media hype, a lot of fear, concern, but also excitement generated. How do you see the future of work evolving, maybe personally as well as in the wider tech world, given you know all this change?
Speaker 2:No, absolutely so. It has impacted all of us individually, at a personal level, in terms of you know, how do we use these tools for our own you, our own daily, day-to-day tasks. To simplify a task, definitely, right, and from across the globe. If you look at, if I specifically talk about the knowledge work, the industry of knowledge work, where the decisions are still made heavily by humans here, right, and you know, and AI will come to augment them. Right, in terms of AI doesn't displace them per se, but AI is kind of augmenting them so that they are able to take better decisions. Right, there are scenarios wherein AI would be able to do a part of the work that a human does. But, you know, but there will always be a human in the loop, you know, because, while the technology comes with a lot of possibilities, uh, in terms of, uh, uh, leaving the decisions completely in the hand of a machine or an ai is not something that I have not seen many enterprises ready to take that gamble yet. Right, so it'll always be a human in the mix there. And particularly the knowledge industry specifically, I've talked about, you know, uh, people who are in the operations field, operations, personal contact center agents, so to say, or people providing customer support, etc. Heavily relies on the tacit knowledge. So there are a lot of knowledge existing with the people in their minds, right, which is not captured when they're by the enterprise. So ai provides the opportunity to capture that tacit knowledge, yeah, and bring that, uh in a, in a, in a document that bring that and surface that in a very, uh, you know, understandable way, right, in plain, common, understandable english language, which helps the knowledge worker to to do their uh, you know work, or their service, in a much better fashion, right. So that definitely is one.
Speaker 2:Yeah, I see, and specifically from the technology industry side, as from from the software development or the operations perspective, and we at cs uh, you know, we provide services to uh you know customers across the globe and we are heavily invested and we are, you know, can embrace generative ai for our own, you know, ways of work in terms of the entire value chain of the software development, whether it is software development, right from design to architecture, through development to testing, quality assurance, as well as operations. So you know, so we've already embraced that and you know, and we have a large workforce, which we are, you know, continuously training and equipping them who are able to work, you know, and provide those services to the customers. So big, big shift there. Ivan, and adoption is everybody. There's nobody left out of this game, so everybody is on the cusp of it.
Speaker 1:Wow, exciting times. I can't wait to see how this unfolds. One final thought on a separate note. You've been a business and technology leader at TCS for 25 years. As a woman in tech, how do you think about getting more women into tech, more women software engineers, developers and technologists of all kinds? You must have thoughts on that. Any suggestions to the industry? How we can embrace more change, more diversity here?
Speaker 2:Wow, you picked up my favorite topic, ivan. Thanks for that. Yeah, so I would say many years back, when I chose this domain and was in the you know technology, many instances I found myself to be the solo woman in the, you know, took up technology. In many instances I found myself to be the solo woman in the room. But I'm happy to say that of late, that's not the case.
Speaker 2:I see a lot of women, you know, embracing technology and you know, taking up technical roles within the industry, but a lot more needs to be done. So, on a personal front, as well as within TCS, I can say that you know, I'm championing a lot of initiatives which is about promoting women into more of technology roles. So I do a lot of personalized mentoring as well as coaching programs, both for not just for women, but men as well. Right, in terms of aspire to move into leadership roles in technology uh, we do that. And, of course, uh you know uh in, specifically in north america, we have invested a lot in the stem program as well. Right, in terms of encouraging uh more uh, you know participation and more uh diversity into of of, you know, the young aspirants who come into and adopt a stem uh based curricula in their pursuits as well.
Speaker 2:But I think more than all of it in terms of you know, the talent is out there and I'd see no bars for anybody in terms of who's keen on the technology, who's interested to learn. Absolutely the opportunities are out there for everybody and I think, organization-wise also, we are doing a lot to facilitate women, encourage more women to come up with the technology leadership roles, and it's a continuous process. Siva and I'm doing my bit and we're doing a lot as TCS, as a company as well, and, of course, the wider ecosystem also. A lot needs to be done.
Speaker 1:Well, wonderful sentiment, very nice to hear we're headed in a positive direction and thanks for sharing your time and insights and I'm sure we'll have a chance to meet at one of the many industry events out there. Thanks so much and thanks everyone for watching Reach out to TCS. They put out amazing content and amazing reports and insight and information. Lots to learn. Thanks, sujata.
Speaker 2:Thank you, ivan, nice to talk to you. Thank you.
Speaker 1:Likewise Bye-bye.