Agentic AI and the future of Global Business Services

Speaker A: Your company's future success demands customer focused, agile, resilient and efficient operations. I'm your host, Christian Johnson, and you're listening to McKinsey Talks Operations, a podcast where the world's C suite leaders and McKinsey experts cut through the noise and uncover how to create a new operational reality. With the digital landscape evolving at an unprecedented pace, agentic AI is set to redefine Global Business Services, or gbs. A centralized organization providing shared services across business functions and geographies. We're moving well beyond what traditional automation could achieve. It's becoming increasingly clear that GBS still matters as a capability for driving value across AI powered organizations. Here to talk about the future of Global Business services are heiko Jaimez, a McKinsey partner based in our Cologne office.

Speaker B: Thanks for having me.

Speaker A: And Josh Peters, a McKinsey partner based in our Washington D.C. officer.

Speaker C: Thanks C.J. great to be here.

Speaker A: Thank you both. So, Josh, I'd like to start with you. Agentic AI is bringing us to an inflection point in how work gets done across the board. Can you paint a picture of what's fundamentally changing in global business services?

Speaker C: Global Business Services has been a hotbed for automation for many years. Right. The difference we're encountering now with agentic AI, uh, is the ability to act independently, understand context, adapt and make decisions in real time. This is going beyond very kind of rule based, individualized decisions starting to apply, judgment starting to pull together, um, multiple different contexts and a lot of information. And so the potential for AI to be just an augmentation or an assistant is really for it to become much more of an individual contributor and to reimagine how work gets done. Because of this, you might expect that GBS would be shrinking. And we do see that in some areas there is a lot of automation being applied, but we also see in other areas it's really expanding more people, more scope, more budget, more spend. So AI isn't replacing GBS yet, it's actually augmenting it.

Speaker B: The truly successful GBS organizations, they have this continuous improvement, operational excellence mindset fully embraced and let's say really as part of their culture, mindset and behaviors. And AI, agentic AI is simply kind of the next step on that journey. So I would really say if not gbs, then not a whole lot of other places in most organizations, uh, is the foundation or the basis to really leverage that AI capability which is just evolving.

Speaker A: So Heiko, how is it adding agentic AI affecting the scope of what GBS organizations can do?

Speaker B: AI allows GBS and other parts of the organization to move more into the what we would call advisory, strategic judgment based type of topic areas. So it's moving beyond the more perhaps transactional administrative processes. Think uh, procure to pay, record to report in the finance domain and perhaps think about something like strategic procurement, um, and uh, forecasting and planning on the finance side. So these activities where AI can play a significant role in assisting but also really taking over chunks of work, this is where suddenly GBS can play a much bigger role than in the past. And then the last dimension or way of expansion is also that the frequency of activities can increase. So where in the past we kind of might have seen uh, for example internal controls or auditing only happening irregularly, right? Or kind of in a certain sample size, you suddenly can use AI to really do real time processing, for example in your internal control. So you kind of continuously kind of check transactions for kind of compliance and regularities. And that again could be something where GBS suddenly takes over more significant chunk of work thanks to AI.

Speaker C: And I think the interesting thing Heiko, is we see these two things kind of countervailing each other right at the same time a lot of the work is being replaced by AI, uh, more work is coming into the system. And I think the question on everybody's mind is which one of these forces is going to win out. And we actually believe in the end GBSs are likely to be 20 or 30% smaller but dramatically more productive than they are today.

Speaker A: So in thinking about how agentic AI can help increase the scope of what the GBS organization can do, I think Josh, you had an example from Financial Planning and Analysis or FPA that would illustrate the potential here. Could you share that?

Speaker C: I think a great example of this, uh, and Heiko would love to hear your builds but within the FP and a, uh, process area for finance, the kind of classic thing is how can we accelerate and automate reporting? And GBS for a very long time has had a strong place in consolidating all the reporting work. Thinking about how do we apply more advanced analytics to it? Automation has helped to do that more and faster. I think the interesting twist has been how do you actually not just think about giving an answer to a question but also think about a next best action. An example of what we've started to see clients implement is not okay, what did my year over year or month over month sales look like? And oh, why is, why is this area of the business down? Why is profit down in this business? I think the natural Next step is what should I go do about it? And so, you know, when we've helped clients to develop a copilot for FP&A, it's not just saying, well, I think this is down because of seasonality or there was a weather event. But also here's what I think are the two or three next questions you should ask or the two or three next actions you should take.

Speaker B: And just to build on that, Josh, indeed. Um, I think these planning related activities are the kind of almost most obvious area where suddenly GPS can play a more significant role because AI helps gps, uh, to kind of really think ahead, right? And Josh now talked about the more financial planning and analysis of the financial side of planning and forecasting. You can translate this HR where we're talking about strategic workforce planning for a long, long time and haven't really mastered it, or I would at least argue a lot of organizations haven't mastered that. AI really makes a difference here. And why shouldn't GBs be the one kind of holding the tools in their hands and let's say exactly doing that type of work that the rest of the organization hasn't mastered in the past? Think about supply chain planning, right? And you could go on and on wherever you kind of think ahead and let's say plan next steps and actions. This is where AI suddenly gives you at least assistance, if not kind of independent advice. And GPS is the perfect place to take care of that and think about that at the same time. Certainly also means capabilities within GBS needs to change. Where in the past we might have seen organizations which are very much focused on the more transactional administrative type of activities, in the future this needs to evolve right into the more advisory strategic type activities. And that's something where at least my clients are uh, in the middle of thinking through how that could work, kind um, of what steps are required to make it happen.

Speaker A: So that is a really great lead into the next area of focus for this conversation, which is on talent. So that implies a very different talent model or certainly an evolving talent model. What are the top considerations for organizations now in gbs?

Speaker B: Yeah, when we think about the future state of the talent, you could say setup. In gbs, we think about it as a diamond shaped setup. So which basically means you will have more in the, call it middle layers of the GBS organization simply because we are seeing less need for managing and running the more transactional type activities where automation also in the more classical sense, RPA plus AI will do a significant chunk of the work, will shift more to the analytical decision, judgment based work, uh, that kind of just requires different skills, right, different capabilities. Um, obviously in addition to being able to manage the AI, especially the agentic AI side of the future, uh, so in addition to kind of that general skill set that allows you to run, uh, for example planning processes within finance, uh, strategic sourcing on the procurement side, you also need the people who are able then to manage the agent force. So the set of AI agents which will take over in multiple areas within gbs. So moving away from the pyramid towards a more diamond shaped talent model, that's what we currently expect to see for the coming years.

Speaker C: And in particular I think that trend is going to mean we have to move a lot faster to train and upskill entry level talent. Because we just won't have as long of a cycle for that layer of talent to develop technical expertise and move into the supervisor layer. If a lot of that layer of talent goes away, we're going to have to come up with new mechanisms to train people in different functional areas and get them ready to orchestrate and manage digital talent.

Speaker B: And it will also more fundamentally change the career paths we will see in the organization. And that goes way beyond gbs. And already today kind of we have the issue that in a lot of GBS organizations we see very high attrition levels, which basically means you kind of constantly need to rehire, you need to retrain, uh, you need to find a way to kind of make the organization or this unit of the organization as attractive as possible to kind of keep the attrition to a decent level. Um, this is going to be an even further challenge going forward because you have less of that entry level. So you need to have people from the remainder of the organization outside of GPS to come in, perhaps people from GBS go out. So I think the collaboration between GBS and the non GBS part of organizations needs to further increase so that career paths really make sense and are attractive to people.

Speaker C: I think the lighthouse that I've seen is really in the uh, customer order and account management space. And it was for both inbound and outbound customer contact. And the company developed just an incredible technology for this. They knew like the where and the why of the call. They could really understand the intent of what would make the customer happy. And they just really struggled to get the sales force to adopt it. I think there was a lot of fear, I think there was a lot of, oh, is this really changing the way my job works? And I think in the work we learned a few things. One is just the uh, people side of the equation is as big or bigger than the technological side of the equation. You know, there was some work on um, training the models better, but I think a big part of it is like can you show them how this gets to better outcomes for both them and the client versus can you just show them, oh well, we can divert 50% of the calls and therefore we've driven a lot of savings. Um, and then I think on the flip side of that is how does it enable them to do something more interesting or better with their time? Right. So like can they actually use augmented AI to get to a far better outcome? Something that normally would have been escalated to somebody sort of above their level, but that they're now helping to resolve these calls because one, they have the augmentation, they have the help, they have the script that is nudging them based on what the customer says in the right direction. And two, it's just a more gratifying experience for the employee to be working on something that used to go to my supervisor.

Speaker A: Great. So knowing right now that we aren't dealing with an or, it's more of an and decision. How do organizations strike the right balance between what they've been doing with traditional GBS levers and how they apply AI?

Speaker C: We have for a long time seen a bit of a right shore first element or strategy to how GBS organizations think about migrating and improving on work. There is not a one size fits all answer, but we think there are kind of two pure tones. We'll continue to see many organizations pursue right shore first which involves getting the work into GBS for talent, for scale, for standardization, for capturing value quite quickly and then driving further improvement through application of AI once the work's been standardized. We think that'll in particular be really useful for organizations that are seeking to accelerate value capture. I'd say in parallel we see this automate first pathway and especially for organizations that are thinking about uh, building a long term digital capability in certain areas and more kind of core strategic processes, how are you going to unlock a lot of enterprise value? We think that this actually understanding and completely reimagining a uh, process flow before migrating some of that work into GBS will be a high value proposition. But I think the important thing is it's not one size fits all. It's actually a little bit more horses for courses. Some parts of a process may benefit from moving to GBS first, other parts of a process may benefit from automate first.

Speaker B: And there is certainly kind of a Number of factors coming together in order to decide which path to take. Uh, it starts with your own experience. So kind of what, what is your current setup within GPS or with GPS in general? What's your experience in leveraging AI and leveraging technology to improve processes? It's also about what's your expectation in terms of impact. So kind of when do you need to achieve what? Right? And impact can be a lot, but it can be cost efficiency, benefits, it can be uh, creating broader value, higher quality of outputs, more stable operations, etc. And then lastly it also depends on the type of processes. So some organizations naturally start where they already have GPS quite involved. Um, so again think about procure to pay, order to cash, record to report if I stick to the finance domain. And uh, all these processes are a bit different uh, to the extent in which AI can be more easily or less easily be adopted. So I think that combination of factors actually needs to be considered uh, for the automate first versus the right shoring GBS first approach.

Speaker A: And what are examples you can think of or perhaps client contexts that you're seeing or where you're seeing the decision being directed by some of the considerations, the factors you've identified here?

Speaker C: I think a big one. We have just repeatedly gotten the question, well shouldn't we just always automate first? Is GBS even still relevant? Is there even a relevant right, short first path? I think in client situations where we see a greenfield approach, they really don't have a lot of shared services today. Really strong urgency for value unlock, uh, and in particular just what I call a lot of low hanging fruit processes that are not incredibly standardized and mature today we are still absolutely seeing people choose the GBS first path or the rent or first path to unlock value. I think the really interesting context that I've seen where people are starting to deviate from that and think about automate first has been when they are uh, identifying use cases for enterprise value unlock. So rather than just oh, I can eliminate some headcount, I can reduce some process cost, I can increase throughput of a process by a little bit, are there other levers that allow me to reduce the amount of revenue leakage that I have, improve the amount of price realization that I have, squeeze out a few more basis points of ebitda, uh, those are the places that we're seeing a lot of clients choose to automate first because of the value unlock, uh, available.

Speaker B: I think that that's part of the beauty of the whole AI discussion we are having today that we are moving Away from a mere efficiency debate. So how do I get cost reduction done quickly, um, to a more holistic set of ambitions? And I always think about the three E's efficiency, effectiveness and experience as in customer, uh, so take the order to cash process, uh, which is actually the one where I think we also right now are doing a lot of our work when it comes to leveraging AI in a GBS context. This is yes about running the process more efficiently so having less resources involved, but it's also about, and Josh referred to that, um, creating a better outcome in terms of for example revenue leakage. So make sure that people uh, kind of pay on time, uh, as originally aligned. But then this is a process which is customer facing. So if you do it right, if you kind of run it seamlessly smoothly, you can even increase uh, kind of your customer experience levels, thereby create much more bonding between you as an organization and the customer. So kind of really optimize all the three E's um, and thereby create massive impact for the company which goes beyond um, reducing a couple hats, uh, reducing a bit of cost here.

Speaker A: So I think that lends us nicely to the next question here. We've talked a lot about the potential for AI to be transformative. What right now is being widely adopted? What's kind of the state of the land at your clients right now thinking, especially if you're more advanced clients.

Speaker B: If I look at my client portfolio, um, everyone is thinking about AI and let's say using AI also in the GBS context, I would say roughly half have started to pilot and work on it and let's say leverage AI, uh, create the first use cases. The lighthouses I have observed in the last 912 months. So in the time where really AI has started to make a difference, they actually happen in the more classical uh, finance process domains and finance again uh, broader than the functional silo but more in where the end to end processes are being allocated. I have one client where um, GBS for a long, long time was certainly in charge of the back end of the source to pay process. So the typical invoice comes in, needs to be processed, um, checked kind of against purchase order etc. And then eventually paid oftentimes in interaction with the suppliers, the AI adoption within that back end but also connecting it to the front part of the process. So when the purchase requisition comes out, so somebody wants to buy something, uh, there is a starting conversation with preferred suppliers, a purchase order needs to be created. So this organization has kind of reimagined the process in a way that AI takes over a good chunk of the supplier identification, supplier selection, uh, which now is being managed by gbs, um, and thereby also putting GBS more in charge of the front end, which very much determines how smoothly you can run the back end of the process. So giving more accountability to gbs, um, and thereby creating less friction, just making the whole process more seamless. Um, and that again in this case also then has an effect on your external counterparts which are the suppliers, which are just much happier is perhaps a too light word, but more satisfied with how the overall process runs and let's say how they get paid on time, uh, and as planned.

Speaker C: I think a really important thing to uh, consider is not just getting started and sort of testing things out. Uh, I have a client who asked us to kick the tires on their AI strategy and a lot of it was what are the set of 10, 20 use cases in each area that we think might have the most potential, that we may go drive the most ROI from? I actually think it's very important to set a North Star and not just sort of experiment, but to actually think about what is the value we're going to create. So what is the domain that we think has the most business value is that order to cash? Uh, as we were talking about earlier, what are the different interventions across that process, some of which may be heavily AI enabled because the ability to reach out to customers is a lot more able to be done in a more automated way because of the judgment that agentic can apply. But also what are the other interventions that need to be made to a process that are not AI enabled? So I would still say if the first step that you're taking is not do we have the right materiality threshold in place for how many of these things that we go after? And is there any low value work that we can just eliminate? You're still just automating the wrong work.

Speaker A: So I think that's actually a pretty good call to action right there. But any other actions that you would say. So you've talked about not automating the wrong work. That's pretty important.

Speaker B: What other messages bringing the GBS and the AI aspects together? GBS in my eyes should be an accelerator, um, for the AI journey of any organization. When we think about, call it service operations more broadly, GBS typically is the one place where you already have a good tech foundation, uh, where in the ideal case you already kind of look at processes more end to end. So not in functional silos but kind of really across uh, that gives you the foundation to fully reimagine and how you run certain things. And that's the basis you should build on, bring it together, leverage uh, both GBS as an organization, as an entity within your uh, broader company and then uh, see what AI can do. Don't start too small, don't start too large. Find that kind of sweet spot in the middle, uh, where you kind of really create a lighthouse without uh, overburdening your organization with too much complexity.

Speaker C: I remember uh, 2017, 2018 era, right after kind of RPA got mature. A lot of people, including all the consultancies, a lot of the sis said GBS is dead. And I just think I hear a lot of that sentiment now, uh, people making proclamations that agentic AI means, you know, GBS's time is short. I would just say I think that the death of GBS is greatly over exaggerated. I think it still can be the center where a lot of this sort of process, reimagination, end to end sort of workflow, orchestration, uh, can live. And GBS has the capabilities to do that. I would also say just ensure you're pursuing both sides of the coin, the next gen levers to apply AI and reduce work as well as some of the classical levers to think about, uh, what more scope can we move into gbs and it should always be a two way street. And that's the way that we see GBS organizations that are succeeding move away from just transactions and cost and more towards outcomes and value.

Speaker A: You've been listening to McKinsey Talks operations with me, Christian Johnson. If you like what you've heard, subscribe and stay tuned. Another great episode. Episode starts now.

Speaker C: Um,