Achyuta Ghosh — Executive Research Leader, HFS Research[00:06]
Hello, and welcome back to the HFS GCC Advantage. This is a series where we speak with GCC leaders and industry practitioners on how the GCC model is evolving and what needs to change as we move into a more AI-led, software-driven world. In our last episode, we spoke about leadership and the need to rethink how GCCs operate. In this episode, we want to take that a step further and focus on the work itself and what that means for people. As AI starts to reshape how work gets done, GCCs are having to rethink roles, skills, and even career paths. The question is, how much of this is already happening on the ground and what needs to change faster? To talk about this, I have with me today Aparna Rao, Vice President and Managing Director, Head of Cencora Business Services Asia. Aparna, welcome to the show.
Aparna Rao — Vice President & Managing Director, Head of Cencora Business Services Asia[00:37]
Thank you. Thanks, Achyuta. Happy to be here.
Achyuta Ghosh — Executive Research Leader, HFS Research[01:02]
Great, Aparna. So, Aparna, you’ve been closely involved in building and scaling GCCs in the past, and now you’re leading the one at Cencora. Can you briefly share your journey and how your perspective on GCCs has evolved over time?
Aparna Rao — Vice President & Managing Director, Head of Cencora Business Services Asia[01:16]
Sure, sure, thank you for the question. So I’ve spent about 25 years building and scaling global capability centers across different industries—from IT, retail, agriculture, pharma, and now pharma logistics as well. So I’ve worked across six GCCs so far, and I’ve led four of them from the front as the center head. But more than roles or titles, what stayed constant is that I’ve always been drawn to building things up from the ground and building teams that people genuinely feel proud to be part of. And over time, I’ve had the opportunity to do multiple things—lead multi-geography, multi-functional teams, set up global operations, set up global process ownerships, and also drive enterprise-wide transformation. And that exposure has actually shaped how I see GCCs—not just as rigid structures, but actually as evolving, living systems that mature with the business. In many ways, I think my journey has mirrored how GCCs themselves have evolved. Early on, the focus was very much on lift and shift, and then you standardize it, you improve efficiency, and you deliver at scale. So I was also very deeply anchored in that mindset as well. But as the ecosystem matured, I started to see that the most successful GCCs weren’t just focused on delivery. They were building deep expertise. They were developing leadership. They were also influencing how work actually gets done. So if I reflect on how my perspective has changed, Achyuta, it comes down to three shifts, actually. One is from back office to business partner. The GCCs are no longer supporting business. The new models are where GCCs are totally embedded in the business, and that comes with a very different level of ownership. Second, from hiring talent to building leaders. I think earlier the mandate or the focus was to fill roles. Today it’s about developing people who can think globally, who can operate independently, and who can actually influence outcomes. And third, I think from cost to impact. We’ve moved away from just focusing on savings only to asking if we’re actually solving the right problems, if we’re creating business value. So I think it’s truly exciting. We’re at this historic, momentous time where India’s GCCs are transforming into strategic hubs of global value creation. I mean, I’ve never seen so many posts on GCCs on my LinkedIn feed—that itself sort of gives you a view of how much focus and attention it is. And with AI, the shift will only become much sharper, because execution will increasingly be automated, so human in the loop, the business knowledge, the decision-making skills, the judgment is where the real value is going to sit.
Achyuta Ghosh — Executive Research Leader, HFS Research[04:08]
Thank you, Aparna. That gives a great lens on how you are thinking about this today. In fact, as you mentioned, your evolution, your career journey, has closely mirrored the GCC evolution in the past, and we at HFS believe that GCCs are entering into the generative enterprise phase, and many of the things that you mentioned are actually key factors in that stage. The next question is on the work itself. As AI starts taking on more tasks, what actually changes in how work gets done inside your GCC or any GCC? Can you give a couple of examples? I mean, what’s actually happening now versus what was happening earlier?
Aparna Rao — Vice President & Managing Director, Head of Cencora Business Services Asia[04:52]
That’s a great question, and I think the biggest shift that we’re seeing in GCCs is this: that work is now less organized around steps or tasks. It’s now becoming increasingly organized around decisions—what work should humans do and what work should AI do? And just to give you a couple of scenarios: so earlier, a lot of time in GCCs went into processing—what you would call processing—pulling data, validating it, preparing reports, building decks, and today AI can do all of that in a few minutes. So what’s really changed is not efficiency, it’s the nature of the work itself. The expectations from teams have also changed. It’s no longer focused on processing. It’s an expectation that you’ve already done all of that using AI and you walk into a meeting and say, you know what, this is what is changing, this is what matters, this is what we should do next, this is what I think. So I think that’s the first shift that I see—from executing or doing to actually adding value and bringing your own perspective. So I think that’s something that I feel is fundamentally changing how teams operate. Earlier, systems would support how humans would do the processing. Now systems are doing the processing and humans are expected to interpret, to challenge, to guide decisions. So that’s a much higher bar, but also a much more meaningful role for our teams. Another shift that I see is around knowledge and access. Earlier, a lot of value sat with individuals who knew how things worked. There was effort in gathering information from different people, in stitching together information. We all know of these couple of SMEs in every company that has the historical knowledge and the context and has been very critical because he or she knew everything. Today, with AI-enabled access and summarization, information is far more democratized. So I think the expectation has changed here too. The reward is not for being the keeper of information; it is that we expect people to use that and add value through your perspective, through your business knowledge, through your recommendations. And to just make it very real for you, one of the things we’re doing in our company is democratizing AI across the organization, so AI is accessible to everybody and not just a few people. So to give you an example, Achyuta, we have our own internal generative AI environment. We have access to co-pilots for everybody. We have structured trainings on how you use them, so teams would actually be comfortable using it in their day-to-day work. At the leadership level also, we’re investing in AI governance capability, because knowing what and how to use AI responsibly is becoming just as important as using it itself. We’re building this into our skills, into our capability framework, so it’s not ad hoc, it’s actually deliberate. And a good example of how this is coming together—we ran a GCC-wide hackathon recently, Achyuta, in February. We had over 102 ideas coming in in two weeks, and in the finals, five out of the six teams actually used AI as a solution. But here’s the important part: we didn’t start by saying, hey, we want to use AI. We started with the business problem. So whether it was improving supply chain resilience, whether it was accelerating access to life-saving medicine, whether it was strengthening compliance, AI became the enabler, not the starting point of these hackathon solutions. And I think that’s the key distinction. If I step back, work has not reduced, it’s actually elevated. The expectations from teams, like I said, are elevated. So I think the industry is moving from processing, from doing to problem solving; from lists of activities to actually what’s the impact of this; and from supporting the business to actually being part of the business and solutioning together, shaping it together.
Achyuta Ghosh — Executive Research Leader, HFS Research[08:46]
Thank you, Aparna. So if the work itself is changing, I think the next obvious question is what happens to roles and skills that we are used to. So when the work changes, what are the two or three specific shifts that you’re already seeing or driving in terms of roles, skilling, or hiring? What skills are you prioritizing? What roles do you think are becoming less relevant? How’s the shift looking now?
Aparna Rao — Vice President & Managing Director, Head of Cencora Business Services Asia[09:14]
Yeah, that’s a very pertinent question, and you’re absolutely right. When work changes so fundamentally, roles and skills also have to evolve with that. And what we’re seeing is not a small shift. I think it’s a fairly structural reset of what talent in the GCC looks like. So to simplify it, I’ll call out a few shifts. Like I mentioned, from processing to judgment. A lot of roles, I think, were designed around processing—you do these tasks. The measure of those tasks also were, if you think about it, turnaround time or accuracy. We’ve all seen those phases where targets were, you do 10 number of things that you complete by this time and do it with so much accuracy—that is no longer relevant with AI taking on most of the execution. The expectation from people is about interpretation, connecting dots across functions, recommending actions as well, and not just producing these outputs. So analytical thinking, judgment, strong business knowledge have become far more critical. Second, from deep silos moving towards the T-shaped capability. Earlier, you could build a strong career by just staying in one function, going very deep in that one function, and that’s no longer sufficient. You’re expecting that people would have a strong functional grounding—in the T shape, a strong background—but also have the ability to work across those boundaries, across adjacent areas, and operate with a broader, enterprise view, and most importantly, a level of comfort with digital, because being able to work with data, tools, and increasingly AI is becoming very, very important. In a global environment, the ability to connect across functions is often where the real value is created. But I think the third and the most important one is mindset, because if you go back to the history, the GCC journey, GCC roles progressed because you became better at the service you were providing. But that’s no longer enough today. There’s a stronger expectation around stakeholder management, around influencing skills, around the ability to influence, and also learning agility. Can we ask better questions? Can we co-create solutions? So the shift is more from “tell me what I can do” to “here’s what I think we should do better.” And there are a lot of new roles emerging, frankly. I see a requirement for people who are designing AI-enabled workflows, who validate the outputs of these AI workflows to ensure that decisions are ethical, compliant. So you see AI governance roles, you see team leaders of team leaders, AI-focused leaders. So if I step back, I think the real differentiator going forward is not, can we do the task? It’s more like, can we frame the problem? Can we use AI intelligently where it’s required, and can we drive a business outcome? So GCCs will need people who can rethink, who can redesign, and who can elevate these processes. In all honesty, digital skills like AI, data, cloud, automation are now the baseline expectation, but they’re not going to be the differentiators anymore. What sets high-impact GCCs apart is how you combine that tech depth with the human judgment, with curiosity, with problem solving, adaptability, and like I mentioned, learning agility. So as GCCs move more and more from execution engines to value creators, I think that cross-functional thinking and business understanding become more critical. Leadership becomes much more critical. It’s evolving too, because AI can do all the work for you—it can crunch data, etc.—but AI cannot inspire teams or build trust. So I think, in short, if AI is going to take care of all the routine work, then GCC talent should spend more time on innovation, should spend more time on insights, and more time on driving real business outcomes. Openness or context, understanding of and being part of the organization—purpose, objectives, business, challenges—I think those become far more important than just becoming functional domain experts.
Achyuta Ghosh — Executive Research Leader, HFS Research[13:26]
Right. I think it also brings us to the practical side on what people should start doing differently. So if in our audience we have GCC leaders, if I’m a GCC leader or an individual listening to this discussion, what are the two or three things I should start doing this quarter itself to stay relevant?
Aparna Rao — Vice President & Managing Director, Head of Cencora Business Services Asia[13:26]
So if you’re listening to this and you feel like the pace is really overwhelming, and there’s a lot happening, you’re not alone. I think most leaders, when we get together, are also asking the same question: are we moving fast enough? But if you reflect, I think that’s actually not the right question. The better question is, are we focusing on the right things? Because today, increasingly, it’s not about speed, it’s also about clarity and where we’re focusing. Here are a few suggestions that I would recommend starting this quarter if you’re new to it. One is, start small. Redesign work, but don’t just automate it, because I think a lot of organizations are still looking at AI to automate a few things. I think the better question is what should humans do? What human decisions can we elevate, and what should AI do? I think what needs to be done is to step back and look at work end to end and consciously strip out layers of reviews, manual work, unnecessary handoffs, and where processes are not optimal. And if AI can handle the processing, then humans should be focused on what humans do best. So I think that would be the first step. And I think, look at optimizing tasks to actually redesigning the whole process. That is a fundamental shift. The value is not in having AI or adopting it. The value is in making AI work for both the business and the end user simultaneously. I feel very strongly about this. If it does not improve speed or cost or outcomes to the end customer—for example, for patients—then we’re just doing it for the sake of doing it. It’s just noise. AI does not fix bad fundamentals. It actually amplifies them. So if your operating model, if your delivery model is not right, if it’s broken, if talent is not engaged in this journey, if culture is not working, then AI just scales the dysfunction. It’s not a magic wand that will solve all of these problems for us. So, in short, GCCs that are really on top, who are staying relevant, are doing a couple of things differently. One, they’re not looking at AI as an experiment or adding it on top of their process. They’re actually embedding AI into core operations. They’re also building capability and culture together, not just technology. They’re ensuring that talent and change management actually evolve alongside technology, so all three of them need to move together. They’re also focusing on moving from managing run-the-business processes to owning the build-the-business product roadmap. GCCs today are not just using AI tools built elsewhere, they’re actually creating them themselves. And I think, focus on becoming the enterprise’s AI factory and then redesign work, like I mentioned, around the human-AI operating model. These are a few things. The next thing I would say is, I think there’s a lot of noise around which tools to learn. There’s a lot of investment in tools. But tools will change every six months. I know that’s an exaggeration, but tools keep changing, so I think let’s focus on investing in our people versus the tools, because what will not change is the ability to ask the right questions, to interpret the outputs, and actually bringing the business knowledge. So I think we need to focus on some of these things: understand our businesses better, stakeholder influence, can we do data storytelling better? Can we really have this critical thinking and analytical thinking focused on? Because some of these are what will be the differentiator in the future. And very importantly, I think focusing on the comfort of working with AI—not as a specialist, but at least the baseline comfort of working with AI—I think is going to be important. And if I were to start today, I would not try to transform everything. I would again start small. I would pick one, maybe two high-impact workflows, redesign them end to end, embed AI in the core of how decisions get made, and I would build from there. So if I could leave you just with one thought: staying relevant in the GCC today is not about doing more with AI. It’s being very clear on where humans have the most value, where AI has the most value, and then designing everything else around that.
Achyuta Ghosh — Executive Research Leader, HFS Research[18:01]
Thank you, Aparna. I think if organizations follow these guidelines, they will look very different, they will perform very differently. Just one quick last piece, and this is more at you personally, Aparna. Now, what is the one thing that you are consciously investing more in and one thing that you have deprioritized for this shift?
Aparna Rao — Vice President & Managing Director, Head of Cencora Business Services Asia[18:20]
If I had to distill it down to one thing, I would say invest in people capability, because I think somewhere we need to invest in human learning as much as we invest in machine learning. And I think what I would consciously deprioritize is unnecessary complexity, because in today’s world it does not create value. It actually slows us down. It actually diffuses accountability. So removing steps that don’t add value, and redesigning roles that are purely focused on execution to actually moving towards adding value—I think that’s one thing. So simplify what machines can handle, double down on where humans can actually make a difference. I read this somewhere, and it really stuck with me: the winners in today’s world will not be those who adopt AI the fastest, they’ll be the ones who use it the most thoughtfully. I think that’s it.
Achyuta Ghosh — Executive Research Leader, HFS Research[19:19]
That’s an awesome closing, Aparna. Thank you for sharing these insights. These are steps leaders and individuals need to start taking right now and not wait for the right time to come. The time is already upon us. Viewers, stay tuned for the next episode of the HFS GCC Advantage. Thank you.
Aparna Rao — Vice President & Managing Director, Head of Cencora Business Services Asia[19:19]
Thank you. Thanks, Achyuta. Thanks so much. It was such a pleasure talking to you, Achyuta.
