Saurabh Gupta — HFS Research[00:21]
Welcome, everyone. Welcome to today’s edition of HFS Unfiltered. And today I’m super excited to unpack the insights from one of our recent research studies where we partnered with Infosys BPM. The study explored the business objectives and challenges enterprise leaders are facing in this AI-led, technology-driven era. We interviewed 20 C-level executives across finance, HR, supply chain, marketing, and IT, and what I found fascinating was that it revealed a significant disparity between the potential that we think is out there and the practical implementation. But before we go on, I am excited to welcome Prasanth and Hari from Infosys BPM, and also our very own Ashish, who did a lot of heavy lifting for this study. So welcome, gentlemen. Let’s start with some intros, and maybe we can go around this virtual room, but also tell me about one key takeaway from the study that really resonated with you.
Prasanth Nair — Enterprise Service Transformation Lead, Infosys BPM[01:25]
Thanks, Saurabh. So, hi everybody. This is Prasanth Nair. I lead what we call Enterprise Service Transformation at Infosys, managing transformation for various GBS services across our clientele across the globe. This study that we did a few months back, I feel, has thrown light into many areas which have happened in the last three to four months. Today I was seeing the pace at which Grok 3 was released by Elon and team, and the way Sam has already promised us GPT-4.5 within the next few weeks, or GPT-5 within the next few months. So the velocity of change that we are seeing is something that’s going to impact the enterprise. Now, some of the fundamental things that came out from the study about adoption of technology itself — when we were talking, we were not talking about the frontier models or a mixture of expert models as such, but those things are still fundamental and applicable even for deploying a frontier AI model. So that’s something that really gave me some thought on how to help clients navigate this fast-paced AI transformation journey that they’re going to embrace in the next few months or years.
Saurabh Gupta — HFS Research[02:45]
Yeah, fantastic, Prasanth. Hari?
Hariprasad BK — Global Digital Transformation and Digital Services Lead, Infosys BPM[03:04]
Thanks, Saurabh and Ashish. My name is Hari. I lead globally digital transformation and digital services for all of our Infosys BPM clients. Fantastic white paper and study, Saurabh and Ashish. And while at a level GenAI and AI is all about technology, one key takeaway for me from this study is it’s as much about a mindset and culture shift as it is about technology. Of course, as Prasanth mentioned, a lot of GenAI is moving at rocket speed, and organizations need to embrace and adopt it, and service providers such as us need to help them in this journey. But it’s also about how enterprises look at this in terms of the culture shift that they need to make. And also, with so much buzz around AI and GenAI, look at AI — while there are areas of disruption — not as a disruptor, but as a co-pilot and a collaborator to achieve greater outcomes.
Saurabh Gupta — HFS Research[04:10]
Oh, that’s fantastic. Ashish?
Ashish Chaturvedi — Practice Leader, HFS Research[04:14]
Yeah, hello everyone. This is Ashish Chaturvedi. I’m a practice leader at HFS Research and primary author for this study. So the key finding for me was that the most impactful AI and automation use cases that we came across during this study had a one-office mindset. Now, for nearly a decade we have been advocating for a seamless connected enterprise, but legacy systems, siloed mindsets, and rigid hierarchies have continued to hold businesses back. But that’s changing right now. There were at least two such cases. One was where supply chain and finance teams collaborated for integrated financial planning, which led to optimizing the supplier relationships. There was another very interesting one where marketing insights were used to improve demand forecasting for supply chain. So I think we are gradually getting there, moving from silos to a one-office mindset, and that would be required for building successful enterprises of the future.
Saurabh Gupta — HFS Research[05:11]
Yeah, look, I think there’s so much to unpack in what you just said, but let me pick on what Ashish said and ask you this question, Prasanth. Here at HFS, at least, we’ve been talking about one office for, I don’t know, donkey’s years now — 10 years or so — and while clients are enamored by it, very few, if any, have been able to achieve it. Why is this thing so hard?
Prasanth Nair — Enterprise Service Transformation Lead, Infosys BPM[05:43]
Yeah, I think Ashish alluded to it. See, one office as a theoretical concept is a very good concept. But like in all the fundamental laws of physics, there are always other elements which are disrupting your experiment, other forces of nature which are impacting this perfect picture in a way. Some of the things that have so far prevented this one office, if I might call it that — one is about cultural mindset and organizational silos. Historically, in our mind also, while we have worked with multiple clients to set up that one office, and most of our clients, I would say, see the merit of one office, especially at a CXO level, the biggest challenge to implementing that is the organizational silos or the cultural ones. Once that is done, I feel 80% of the difficulty is achieved. Then obviously there is the question of legacy systems, data fragmentation, and I would say even a little bit of skill shortages. So these would be the other three elements which are hindering one office.
Saurabh Gupta — HFS Research[07:05]
So Hari, let’s take all the easy challenges that Prasanth threw at us. What can we do to address them? In your experience, what’s some of the practical advice that you give to your clients?
Hariprasad BK — Global Digital Transformation and Digital Services Lead, Infosys BPM[07:23]
Sure. As Prasanth mentioned the friction to one office, that’s where and how we are looking at trying to help customers. One is there are lots of siloed systems and data fragmentation in organizations, and the boardroom is looking at outcomes from enterprise leaders. And enterprise leaders are stuck in a conundrum of pilot paralysis, if you will. A few of the things that we look to help customers with: identifying, in this journey of GenAI adoption, the right use cases that will power the outcomes that enterprises are envisaging is as critical as just jumping onto the bandwagon. So that’s very important, and that’s one area where we have created assets such as AI Navigator, where we are helping clients navigate this journey. Second is around data. AI is all about data, so enterprise data readiness is very, very critical, and that’s an area where enterprises struggle for all of the reasons that Ashish and Prasanth mentioned — siloed data, do you have the right data, and so on. So again, we have created accelerators, bringing expertise from an AI perspective to make enterprises data-ready. Third is that in this journey to scale up into production, there’s a little bit of cautiousness that we see around responsible AI. From an enforcer standpoint, we have created RAI frameworks and guardrails that help customers navigate this quagmire and landscape and be able to accelerate that readiness. Technology, in my view, is the least of the challenges. It’s these larger ecosystem challenges that customers are grappling with. And finally, going back to my point on boardroom expectations, we are focused on creating accelerators in finance, HR, procurement, and customer service, and bringing those accelerators to bear so that we can accelerate the enterprise journey into AI. So that’s the way we are looking at how we can help convert the promise to reality.
Saurabh Gupta — HFS Research[10:09]
Yeah, I like where this conversation is going, because ultimately it’s not really about AI. It’s about all the things that you guys mentioned. There’s a talent debt that we have, there’s a data debt that we have, there’s a technical debt that we have, there’s a cultural debt that we have. And at some point in time, we have to pay those debts, right? How much can you borrow on the credit cards? The bank is going to come knocking at your door. So, Ashish, the other thing that I found very interesting is we’ve started to call global business services, GBS, generative business services. And while that’s an interesting play of words, is there something more deep in that? How are you seeing our evolution to generative business services?
Ashish Chaturvedi — Practice Leader, HFS Research[10:48]
First of all, this isn’t just a rebrand. I think it’s a fundamental shift in mindset. GBS has long been about standardization and efficiency, but if you look at the tech era that we are right now in, it must become an engine of innovation — constantly learning, adapting, and generating new value. So for us, moving from global business services to generative business services, AI shouldn’t just be automating tasks but augmenting decision making and co-creating solutions. I think for this future to become a reality, three things need to be done. First is outcome-driven KPIs. I’ll give you an example. Right now, for marketing, customer acquisition cost is a KPI. This needs to be transcended to something called customer lifetime value improvement. Similarly, cross-functional intelligence — we need to break those silos between functions. There was a very interesting case that came up during this study, where a global manufacturing company consolidated their inventory, procurement, and finance in a single cloud-based platform, and the kind of benefits they reaped were like a 50% reduction in error cost and 30% improvement in operational efficiency. So cross-functional intelligence is second; first is outcome-driven KPIs. Third, I’ll say self-evolving operations, where essentially you don’t require an external stimulus to adapt to the latest technology — it should be an AI-driven adaptability spectrum that you should be on. So once you get to these three, which many companies are trying to get to, then obviously you can say that GBS is now my generative business services, which is beyond just standardization and efficiency.
Saurabh Gupta — HFS Research[12:52]
So, Prasanth and Hari, you’ve had a very successful history at a leading service provider. As enterprises move to this generative business services model, how should service providers change? How should Infosys BPM change to cater to these demands?
Prasanth Nair — Enterprise Service Transformation Lead, Infosys BPM[12:55]
Good question. So our purpose as a service provider, as a company, is to help navigate these clients to their next transformation journey. I just highlighted generative business services — that’s where the world is going. I would approach it from two cohorts of clients. There is a set of clients for me who are digitally native, who have been born in the last 10 to 15 years on the cloud with platforms, so they have less technical debt. And then there are obviously digitally naive companies who have been digitally enabled by companies like us. For both of them there are slightly different approaches to the way we are helping them navigate to this new AI-first world. Especially for the older, traditional industries, there is obviously the cultural debt that needs to be addressed, and the data and digital debt that need to be addressed. So we are hand-holding them through each step of the journey and helping them leapfrog into an AI-first world. Now, where I look at the digitally native companies, for them it’s about bringing the latest model and deploying it in the right fashion. While they have been digitally native, they have gone the way of their predecessors in the sense that they have silos across the finance and procurement organization, or finance and supply chain organization. So there, our play would be to integrate and create that one office and quickly help them leverage the data that they have, in the right format, to deliver maximum value. That’s how I would see we are approaching it.
Hariprasad BK — Global Digital Transformation and Digital Services Lead, Infosys BPM[15:11]
So, picking up from where Ashish started, with GenAI and, as we’ve given this name of generative business services, the pivot for GBS from being centralized and looking at operational efficiency to the outcome-based model is a pivot. And as service providers, we also need to adapt to it. Generally we have been slow to it; we’re always focused on looking at cost takeout and reducing the cost to serve. That’s a big pivot at Infosys BPM. What we are doing is, in terms of models, looking at services-as-software, which is all about bringing the confluence of technologies such as GenAI and AI, but also the BPM layer — and can the sum be greater than the parts and be able to drive outcomes? That’s also a culture change for providers such as us, but we are looking at those kinds of models where we can use the power of technology and our expertise to drive outcomes for customers. Of course, the cost takeout is a given in today’s world of AI and agentic AI. That’s one. Second, truly for generative business services to happen, one big shift that I see is that there will be a move from centralized operations to distributed intelligence, which is all about looking at the data, the process, the domain, and being able to create AI-embedded microservices that will enable and power real-time decision making at the action of business, rather than a centralized GBS organization of the past. And how can service providers such as us, and indeed Infosys BPM, do it? That’s an area we’re focusing on. To me this is the real value of generative business services. Can we really look at this kind of distributed intelligence with the progress and advancements — if you look at decisioning and reasoning models and the progress we have made, this is a huge opportunity for us to drive this shift in terms of distributed intelligence, outcome-based models, and things like that. And finally — and this is getting a lot of press in recent days — we always had automation and those kinds of things all along, but can we pivot to an agentic AI model? However, the other part is equally important, and that’s where we’re focusing a lot from an Infosys BPM standpoint, which is human-AI collaboration. Because now the talent refactoring is going to happen: if agentic AI does all of the transactions, then the human is all about AI orchestration, strategically leveraging AI, exception management, and of course culture management. So that’s an area where enterprises need help and we all need to focus, in terms of how do we bring this culture change in the context of outcomes, as well as a whole new operating model, which I believe is the true promise of generative business services.
Saurabh Gupta — HFS Research[18:38]
Yeah, I couldn’t agree more. In fact, here at HFS we’ve just launched our 10-year market forecast and vision, and we expect services-as-software, built on agentic AI as a foundation, is going to be a $1.5 trillion opportunity, which will absorb revenue both from the existing services model as well as the existing software model. And who’s going to be the winner is anybody’s guess as of now. But I think what you all have pointed out makes me really excited for the future, but also makes me a tad bit nervous, because there’s so much that we have to do. So, before I let you go, if we can go around the room and ask you: if you had a magic wand and could change one thing — let’s not wish for five things, because we can’t grant that many, but let’s say one thing — what would that be to make this vision that you’re all trying to articulate around generative business services and services-as-software real? What’s that one thing that you would make disappear? And maybe we’ll go in reverse order this time. Ashish, let’s start with you.
Ashish Chaturvedi — Practice Leader, HFS Research[19:35]
So instead of one thing that I would like to disappear, I would like a data spine and a disruptive mindset to appear. And I’ll take one minute to explain why. If you take finance, most of the pilots or POVs that are happening are in fraud detection or contract analysis. I want enterprises to have a disruptive mindset where they think about using AI for financial decision making, or AI-powered pricing, where an agent can take a call based on the market situation. So it’s not just about moving from pilots and POVs to production. It is: what are you moving from pilots to production, and is it impactful enough for your business? For that you need to have that disruptive mindset, and until you have a data spine, you won’t be able to do it even if the intent is there. So a disruptive mindset and a data spine, the two.
Saurabh Gupta — HFS Research[20:40]
I like the data spine angle of it, for sure. Hari?
Hariprasad BK — Global Digital Transformation and Digital Services Lead, Infosys BPM[21:06]
Yeah, look, I was going to say what Ashish mentioned, but let me talk about something else. In this journey of AI, I think talent is going to be very critical, and if there’s one thing I would like to disappear, it’s the dearth of AI talent — quality AI talent — especially with the advancements that are happening in AI and AI models. Our ability to power this journey and accelerate it is in equal measure about AI talent, and that’s an area where I’m quite worried in terms of where we are versus what we need.
Saurabh Gupta — HFS Research[21:30]
Fantastic. So AI talent. Prasanth?
Prasanth Nair — Enterprise Service Transformation Lead, Infosys BPM[21:30]
Yeah, maybe should I ask for a one-million Blackwell cluster or something, Hari, to develop a site? If there was a magic wand, that might be what everybody would want this year. But more importantly, I’ll go with a point close to Hari’s. It’s about talent, and while Hari highlighted AI talent, what we are seeing on day-to-day operations itself — AI, the current models, and things can evolve — it’s like a very super-smart intern or analyst. It’s giving a lot of data, but we need process experts. Even if I look at my tax process, financial planning process, HR benefits process, or sourcing process, I see that AI is giving us a lot of intelligence, but I need experts who are well versed in using AI, leveraging the power of AI to drive the transformation within the client. So again, talent is my point — talent as domain experts with a good appreciation of the ability to use AI. For me, that’s my constrained resource. So that’s where I would want.
Saurabh Gupta — HFS Research[22:59]
No, fantastic. I think what I would wish for is more such conversations. So I hope we continue this dialogue, gentlemen. It was a pleasure interacting with you. There’s so much — we could do this like a five-hour podcast and still not get through all the topics, but it was a fantastic conversation. Thanks a lot for spending some time with us today.
Hariprasad BK — Global Digital Transformation and Digital Services Lead, Infosys BPM[23:24]
Absolutely. I echo your thoughts. Saurabh and Ashish, thanks for having us here.
Saurabh Gupta — HFS Research[23:29]
Thanks, thank you both. It was a pleasure talking to you.
