326. M&A heading into Q4: How AI is reshaping value creation

0:01Tobias Lundberg: For McKinsey & Company, I'm Sean Brown and welcome to Inside the Strategy Room. Today, we have an exciting two-part episode. First, we'll discuss the latest M &A macro trends as we enter the fourth quarter, including the emergence of the mega deal, which we define at$10 billion or more. We'll also explore how AI is informing M &A as a driver of activity and value creation, what that means for deal teams, and how companies might take the transaction as an opportunity for transformation. We're joined today by Benjamin Hussar, a partner in our Paris office and co-leader of our global M &A AI initiative.

0:42Tobias Lundberg: Cameron Cordestani, a senior partner in our New York office and leader of our North America merger management practice. Tobias Lundberg, our managing partner in Sweden, who also co-leads our M &A practice across Europe. and Alex Liu, a distinguished partner in our Minneapolis office and a leader in our M &A practice. Welcome, everyone. Cam, I was hoping maybe you could set the stage for us first in terms of M &A activity. What are some of the tailwinds driving deals forward as we enter the fourth quarter? And what are some of the headwinds causing continued market hesitation? Thanks, Sean. You know, we're seeing a sustained amount of activity across different geographies, different types of activities and different types of M &A activity as well.

1:29Tobias Lundberg: Many corporates in North America, for instance, where I'm based, are looking at opportunities and they're taking the through cycle mindset as they think about whether this is the right time to invest or whether this is frankly the right time to divest. We're also seeing in several sectors, notably in energy and minerals, a sustained burst of activity. You also see this in the technology space, where a lot of potential corporates are looking at how do they tap into and jumpstart their AI capabilities. Of course, if you think about some of the headwinds that we see in the marketplace, and this goes for around the world, this has been a year of uncertainty.

2:14Tobias Lundberg: There's geopolitical uncertainty. Of course, organizations are looking to strengthen and solidify their supply chains. And so they're thinking differently in terms of how they activate their M &A to achieve that. Got it. Thanks. And what are some of the macroeconomic trends that are driving the market right now? And do they differ by geography or sector? As we look across the macro space, there are a number of trends that are impacting M &A around the world. It doesn't matter sector, it doesn't matter geography. We see consumer sentiment, particularly under pressure in many major countries around the world, there are significant elections that are underway that are putting some of those consumer sentiment trends at the fore.

3:00Tobias Lundberg: We see upward pressure on interest rates, which is the efforts of the central banks to tackle inflation. And we see a lot of interest around what will be the arenas of competition into the future. Of course, AI is expected to change how we operate, how companies operate around the world. And as I said, geopolitics is not just a governmental issue anymore. It's an issue in the boardroom as companies think about how to solidify and strengthen their supply chains. Finally, I'd be remiss not to mention where we see private capital, but we see that there are historic levels of dry powder, an opportunity as we think about where this global private equity capital might be deployed in the near future.

3:48Tobias Lundberg: And so, as I mentioned, this year has been an upswing. We've seen an upswing. And what you're seeing is global activity as we think about the number of deals and the deal value, but an upswing in the deal value. Coming out of the pandemic, of course, if we go back now, what seems only yesterday, but in fact now was five years ago, we saw a spike, a big, big burst of activity. And then following that into 22 and 23, a relative dip. But what we're seeing is levels almost at par with, at least in deal value, with where we were in that bumper year of 2021. That's interesting, Kim. Thanks. And how's the balance between corporate M &A and sponsor-led deal activity evolving?

4:32Tobias Lundberg: You can see that the vast majority of activity still continues to be dominated by the global corporate M &A activity. And this is definitely what we see across different sectors. And we see that sponsor-led deals have fallen. And I think this then further reflects the notion that private equity is still waiting on the sidelines, thinking about where and how to engage and where and how to activate. So are you seeing any hints that this activity might be picking up going forward? Well, I'll tell you anecdotally, and I'll maybe invite Tobias to offer his thoughts as well. But anecdotally, from where I sit, I start some weeks quite optimistic.

5:14Tobias Lundberg: And then busy weeks are tended to be followed by one or two weeks of slowdown. And I'm not sure yet we're at a point where we're going to see that tipping point. Honestly, Sean, I look to diligence activity and kind of the upstream. And that still is muted compared to where we've seen it in the past. But Tobias, I'd invite you to offer thoughts as well on this.

5:41Alex Liu: Yeah, Cam, I think it's fair to say that on the private equity side, it's a bit of two stories of two halves in parallel. Indeed, we have a massive amount of dry powder that's looking to get deployed in the right way. At the same time, we've also looked at vintages and holding periods of these investment firms in terms of what they're holding today in the stock and their inability to fully sell off those assets. Well, within holding periods, I think are up about two and a half years over the last decade or so. So it's a bit of a contract where they need to weigh how quickly they can deploy versus also offloading the oil.

6:12Alex Liu: But I think it's fair to say we're also seeing private equity becoming more creative, looking at new ways to deploy capital, perhaps buying away from some of the trends they saw before, be that around sustainability or some elements of software, but also looking at more complicated deals, whether it's corporate carve-outs or taking minority stakes, as well as also looking at public to private type of transactions. So I would say there are definitely players, and we look at them in the different regions. There's still high activity, but there's also a fair amount of uncertainty that they're trying to battle through.

6:42Tobias Lundberg: Thanks, Tobias. And Cam, let's talk a little bit more about the broader activity, maybe from a global cross-border perspective. What are some of the big shifts you're seeing? Great. For many organizations, especially global organizations, are looking to gain a foothold in markets around the world. This is an important dimension. One of the frequent questions we get when clients are looking for outside support is, I'm going to make a different type of acquisition. And many times a different type is driven by a geography. And so you're seeing a significant amount of U.S. activity. I think, as I said earlier, some of this is driven by thinking about how to solidify and fortify supply chains and opportunities around that.

7:27Tobias Lundberg: You see inflows into the European and Middle Eastern space, and you see outflows from Asia buying out from a net perspective. So I think, Tobias, maybe handing back over to you from the European perspective as we think about what you're seeing on the ground and this experience from across geography.

7:46Alex Liu: Yeah, thanks, Cam. Let me pick up briefly on the EMEA side of this equation here. So if we wind back to our annual report back in February, we were showing that EMEA was the net exporter of capital. And we look now, of course, the tables have turned on this one, and we're now seeing record inflows coming in of some 37 billion or so. And the fact that that money is coming then both from the Americas in particular and to some extent from Asia, you could be tricked into saying that we're seeing an overarching shift in terms of the money flows. The reality is that EMEA is not getting structurally larger as such.

8:19Alex Liu: I mean, I think EMEA's share of global activity on the M &A side is steady at around 24%, 25%, which is bang on the middle of the historical averages. So the direction of capital has not really changed, nor has the size of the region. But I think what has changed is that we have seen a couple of tail end, extremely large transactions. So if we strip out the two largest deals that have gone from the Americas into the EMEA, that's about a$60 billion deal value between the two of them. You reverse those two out, and EMEA is back into a net outflow position. So there are a couple of just tail end transactions that are driving this here.

8:53Tobias Lundberg: And so just on those big or mega deals, if we could talk a little bit more about what kind of trends you're seeing there and how big does a deal really need to be to be defined as a mega deal, at least in your analysis?

9:05Alex Liu: Cam, you alluded to it already, but we have seen a consistent trend now over some time of large deals and mega deals becoming larger and larger. So deals above$10 billion is what we have defined as mega deals. They have reached some$1.1 trillion in the first half of this year. That's up almost 140 % versus the same period a year ago. And it's the strongest half year that we've seen on record. 36 of these deals happened in the last six months. And you compare, if we look at the full year of 2025, that would have been 60 for the full year. So we're already way ahead of that. And also we see a massive concentration on these deals.

9:41Alex Liu: So 42 % of the global deal value sits now in these mega deals here. Now, you look at all that on combination, you could say that deal counts are down. So whilst we have volume being up in terms of deal volume, historically, we've now seen it down in the second half of this year. And also average deal sizes on the other side are coming up. So there's a bit of a barbelling again of these very large pulling it up. And I think what's been interesting is also that we've seen Europe come to the table. So out of the 37 deals we see now for this prior cycle here, 11 now are from the MIA region, which is a significant stepper from what we saw in the past.

10:18Alex Liu: Many of them are actually in-market consolidations in areas such as banking or in telecom and such, which are arguably slower growing, perhaps slightly lower value type of sectors. So we're really seeing a bit of the rise of also in-market consolidation as well as of these cross-border mega deals that are really coming to play right now.

10:38Tobias Lundberg: And so now let's dig a little bit deeper into the industries that you're seeing these mega deals concentrate and evolve in. We always talk about the big tech deals, and you just mentioned banking as well. Are there any other industries maybe that are counterintuitive or that one might not have expected to see the sort of size and number of deals happening?

11:00Alex Liu: It is truly a combination. We see them for sure on the technology side. We also see in areas such as logistics, frankly, consumer retail. And then frankly, as I said, more, if I can call it, slightly more traditional utility-like sectors who are trying to consolidate. So I think it's very different in terms of whether you're accessing a foothold of technology or your land grab in terms of access to market capabilities versus trying to consolidate an in-market. So there are several trends at once at play here that is driving this trend right now.

11:31Tobias Lundberg: Thank you. And related to that, what are you seeing in terms of the pricing in these mega deals? Are buyers bidding up premiums?

11:40Alex Liu: no it would be our short answer so when we when we do longitudinal analysis to look at sort of average deal premiums and where they are those have remained you know remarkably consistent you know call it around 20 26 percent or so is bang on historical averages and that's what we also seen for the first half of this year if we look on the deal multiple side of those have come up over time you know whereas we were looked at in the peak here 21 as cam alluded to we were at 11.6 So we're back at those territory after a couple of years where we're effectively two turns down on those multiples. And you read these two facts together, and it says something quite specific.

12:16Alex Liu: Buyers are not paying more for the assets, and they're not bidding more aggressively over the underserved prices. So the re-rating is really a market re-rating driven by the mix effect of the sectors that are being exposed to this M &A. On the one hand, you take fast-growing industries, and we'll talk more about those arenas in a second. We'll talk more about those arenas in a second. And, you know, they will have valuation multiples in the high 20s, as opposed to those in the more established industries, which are far lower. And then I think the other thing which, you know, is worth considering as well is also how people are paying for these type of deals, where we see equity linked considerations rise up to a whopping 22 percent of the deals.

12:53Alex Liu: And that is, of course, a reflection of the fact that when you're paying the 11.5 times you're paying today and you pay it in stock, you're sharing some of that re-rating risk also with the seller side, not carrying it alone. So I think that's a little bit of the behavior we are seeing right now. But a remarkable consistency, frankly, in terms of the discipline that corporate buyers are showing in the market overall.

13:15Tobias Lundberg: And Tobias, what's your perspective on where you see the future growth coming from?

13:20Alex Liu: When we look at where are the future growth arenas, and there's many of these you can imagine, whether that be on the AI software side, the semiconductor side, some of the consumer electronics and e-commerce elements or other frontier technologies. We've seen a pretty staggering shift where AI software services and semiconductors are really seeing the uptick in terms of where they're seeing deal activity happening. And then, frankly, some of the other ones slightly more cyclically exposed, be that consumer internet, advertisements, video games, all frontier technologies have all come down, have come down sharply as we see money rotating within the technology to some of these new growth bets.

13:58Alex Liu: So we're definitely seeing different acquisition types now, both from the hyperscalers as well as then sort of the large corporates. Got it.

14:07Tobias Lundberg: And since we're talking now about fast growth in software and services, as we look beyond the tech sector, how are you seeing the more traditional industries being disrupted or affected by this wave of AI-driven deals? Are they actually driving AI software and services acquisitions as they look to buy perhaps enhanced AI capabilities?

14:28Alex Liu: It's very mixed. And I think from what we're seeing from the data and from our client service day to day is that corporates across all sectors are looking to acquire some of their capabilities. It may become, in some cases, a bit of a side effect that they're looking to buy a new set of capabilities or so on. And especially if it's a slightly more of a fresher vintage of a company coming in, they will actually acquire the significant technologies know-how that they're using to reinvent their core business, frankly, from an integration and value creation perspective. But I would say that we're definitely seeing it across all of the elements here.

15:00Alex Liu: But that is clearly one that is highly skewed to the hyperscalers.

15:05Tobias Lundberg: And Tobias, earlier you commented on some of the trends in Europe and EMEA where you're based. Are you seeing any more openness to an increase in deal activity there, perhaps even from a regulatory perspective?

15:16Alex Liu: So I would mention a couple of things. So first of all, I think there's a realism if we now stay on Europe, which was your question, Sean. A realization, if you think about European versus global competitiveness and how the European firms compete in that stage and arenas there versus both American and also Chinese competition, that they need to up their gain in terms of driving productivity and driving benefits. I think that is clearly one compounding factor that is kind of opening up for them. Another one has been a slight shift towards some more leniency for in-market consolidation as well on the European side and the EU side more specifically.

15:51Alex Liu: And I referred earlier to telecom and banking as two examples where we're now seeing in-market deals coming through. So that would be a second one. But then fairly frankly is in Europe in particular, you have the combination of an extremely rich and deep private equity pool. I think the private equity pool stands above 30 % of all deals in Europe specifically. So it's a very active part. And as I said before, sitting on massive sets of inventory combined then with interest rates coming down. And these companies are also looking to sell. I mean, I think it's a relatively benign environment also for corporates to do deals, both on the acquisition side, but frankly, also on the divestment side, where we've seen number of spins and so on increase over the last couple of years.

16:33Tobias Lundberg: Tobias and Cam, thank you. Really appreciate this update on overall M &A activity and the trends you're seeing. Now, let's turn our attention to AI and M &A. Benjamin, maybe you could provide us with a quick overview on how AI is informing or changing M &A dealmaking and maybe how it's also affecting the M &A process as we traditionally know it.

16:54Kameron Kordestani: Very good. Thank you, Sean. And actually, when we want to investigate how AI is reshaping M &A, we typically cover that through, I would say, three dimensions. There is the first effect, which is actually AI being a driver of M &A directivity in the continuity of what we have just discussed, not only for AI companies, but I think broadly as well in the ecosystem and even for other corporate companies. The second driver is M &A and AI as a catalyst of value creation. As companies are working now to extract the benefit of AI, Gen AI, authentic AI integration can be actually used as a vehicle to accelerate this process for, let's say, selective integration that are transformative.

17:53Kameron Kordestani: And finally, and this unable to obviously accelerate and increase the level of synergies, by at least 50, we have seen some situation where we could double the amount of synergy by what we call rewriting the companies during the integration process. And the third dimension is how we can use AI as an M &A processes accelerator. So in the M &A process itself, in terms of how we can compress, I would say, the timeline and how we can use more insights to improve the M &A from the target scan to the integration.

18:35Tobias Lundberg: Thank you, Benjamin. And how exactly is AI driving deal activity? Is it concentrating in larger deals or is it particular sectors or geographies?

18:45Kameron Kordestani: So if we just look at the top 10 deals since the start of the year, and actually you see that 7 out of 10 are in some ways, let's say, related to AI, either directly or indirectly. A few messages. First, actually, AI is hitting the top of this list. The second message is around, I would say, energy. And we actually see a lot of consolidation in the utility sector that are driven by, I would say, AI. The rationale of these deals include the fact that data centers need power. This is driving activity in the energy space. So for the top 10 deals, we see that seven are in some ways linked to AI. When we look at, let's say, the broader M &A deal activity, we could observe that in about half of the deals, we hear about AI either in the rational or at least in the narrative.

19:58Kameron Kordestani: Now, if we zoom out to the Gruller ecosystem, we actually see four archetypes of M &A for AI. The first one is, let's say, the obvious one. That's the core AI players doing M &A. When OpenAI, I would say, does an acquisition, this is not to buy revenues. This is typically to buy 10-person teams that have already solved a very specific problem, being an on-all multiplayer collaboration or 3D world building, and then they will plug it in a question of risk. The second archetype is tech-adjacent transformers. These are typically the IT services or software players that want to reposition their portfolio and product to serve in the AI era.

20:57Kameron Kordestani: These are expensive deals. We saw that Synopsys spent$35 million to acquire Ansys. We had some deals as well in Europe, like Capgemini acquiring CNET. So that's the second archetype of software IT services company moving to AI. The third archetype, and this is probably the one that is most relevant, is, let's say, the corporate or typical companies that are doing AI-related acquisition to build AI capabilities. And typically, they acquire in a very fast mode. Now we are seeing as well a fourth archetype that we call AI talent acquihire, which is not the typical, I would say, acquisition as we are used to.

21:55Kameron Kordestani: But we are seeing multiple players like Amazon, Meta or Google that are actually directly hiring some founders to get access to AI talent. That's the example of Amazon when actually they hire the funding team of Adept AI on the Monday. On the Tuesday, they sign a licenses agreement back to the startup. And on the Wednesday, the startup can give back, I would say, money to the investors. It's a way to get access to the talent much quicker. Obviously, that's a quite creative way of doing M &A, but that's a way to cut the time to closing. So that's a new type of archetype that we are seeing that is driving activity in the AI space.

22:52Tobias Lundberg: Interesting. So as you think about a non-tech, say industrial or healthcare company, is one of these archetypes the most common? Is it the tactical capability acquirer? Or which one is it that you're seeing the non-tech companies typically going for first?

23:08Kameron Kordestani: That's definitely the number three. That's where we see, actually, if we were going beyond the top 10, we would have seen a lot of pharma companies acquiring, I would say, biotech or specific AI capabilities. You have examples as well in the industrial space. What Schneider Electric did over the last years is to do a large number of AI-related acquisitions to build capabilities around AI in manufacturing, AI in supply chain, and so on. So this is one implication that actually we see for corporate M &A.

23:54Tobias Lundberg: That raises another question on that archetype. Are you also seeing typically a positive valuation impact when these deals are announced or when they actually go through? In other words, is this deal-making activity value accretive to the acquirer? Yes.

24:09Kameron Kordestani: When I was mentioning that for half of the deal, AI was mentioned somewhere in the press, the communication. We feel that for a bulk of these deals, this is more, let's say, to get excitement around AI and to give the feeling to the investor, to the customer, than actually the company is investing on the right thing. If you really look at, let's say, the pure AI plays, this would be much less than this 50%. So we do see indeed an inflation as well of the word AI as a rationale, but beyond then the four archetypes. But there are multiple examples of companies that are actually doing that to accelerate their, I would say, build of the AI capabilities still.

25:08Tobias Lundberg: And with these four archetypes and the new kinds of AI plays that you're seeing, how is this impacting deal making then? Whether that's the target scan or new approaches to the deal structure. What are some of the big strategic implications for M &A and corporate development teams?

25:25Kameron Kordestani: We see five of them. The first one is obviously to redefine the target universe. So stop looking at your usual suspects. The AI capability that you need is probably not in your industry. It might be a 30-person startup that you have never heard about in a sector that you have never screened. So you need to move from who is our market as an ME team to who has the specific algorithm that we need. And obviously, for an ME team, this means new muscles, new evaluation criteria, new networks, new speed of assessment. A second implication that we see is around, I would say, talent, especially over the last months where we have seen so many, I would say, deals and interest on AI.

26:26Kameron Kordestani: In AI deals, the most valuable asset is actually the team and the type of talent, let's say, are not responsive to, let's say, the same retention levers than before. So the traditional three-year financial earn-out might not work, I would say, anymore. They typically value autonomy. They want to have access to compute. And if an AI expert doesn't have access to the right GPUs, he might go. So tenant retention, speed. Obviously, you don't want a long process that will make obsolete what you are buying. So as opposed to traditional M &A, I would say optimizing for thoroughness, we see now. a strong focus on speed.

27:12Kameron Kordestani: You need to be careful in terms of how you integrate. Back to, as I was mentioning, you don't want to kill what you are buying with your corporate processes, timelines, governance. So you typically need to be more careful in terms of how far and how fast you integrate. And finally, you might think about new types of structure. Again, not necessarily buying the full company, but thinking about JV, partnership, licensing, I would say to best optimize the benefit-risk balances.

27:49Tobias Lundberg: Thank you, Benjamin. Now, Alex, I'd love your take on how AI is actually reshaping M &A and how companies are truly extracting value from it when many companies continue to struggle to see the value impact of AI.

28:06Benjamin Houssard: Wonderful. I would lead off by saying, you know, it's incredibly exciting to see how AI is really innovating, how we deliver value creation. That said, I would say that there's, frankly, a fair amount of experimentation that's happening. And so while there are a number of kind of point examples of companies doing exciting things, I would say that we're on the front end of really seeing, the standard being kind of hard dollar impact coming from a number of these. Got it.

28:41Tobias Lundberg: And maybe you could share a few examples with us.

28:43Benjamin Houssard: Let me start by talking about some of the more mature use cases. And I would start with customer service, as well as product and engineering in the technology sector. So when you think about the classic software development lifecycle, the AI models, of course, are now quite mature, quite advanced. And we're seeing companies take upwards of 45 % productivity gains and 70 % reduction in kind of the end-to-end lifecycle. So what took months and quarters is now taking days and weeks to develop end-to-end, out-of-the-box software development. And you can point to many examples in this space. And I would say that that is a quite direct tie to that creation.

29:43Benjamin Houssard: I think the other use case I would call out from a maturity standpoint is in the customer service realm. And frankly, all of us have likely experienced the discussion with virtual agents, troubleshooting with virtual agents. I think what might be less obvious is there are now productivity tools that are supporting real agents. So for example, after each customer agent does a customer service call, they oftentimes have to kind of record what are the notes, what are the follow-ups. Now that is largely driven by AI. And so you can imagine there is a significant value unlock from really freeing up that time and that capacity of the frontline.

30:32Benjamin Houssard: So I would say those are, I'd say, the most mature, the most tried and true, largely because, frankly, they were doing it prior to this AI revolution. In addition, they have a very high transaction volume. And so those are some of the patterns that sort of drive high adoption. The other one that I would call out is in the back office. So if you think about finance, once again, I would say an early adopter of kind of process-driven innovation, we're seeing them really automate with AI, invoice processing, closing the books, even financial forecasts, things that you can apply kind of a rule set to and have kind of a process orientation.

31:19Benjamin Houssard: And you can see a number of companies are doing that and are quite mature. So I think the simple point here is that lots of kind of proven examples, but also I would say a fair amount of experimentation that's happening when you think about specific use cases.

31:36Tobias Lundberg: Thanks, Alex. And you've previously written and spoken about the opportunity that a transaction can provide for transformation. In fact, we have an episode on it, which we'll reference in the show notes. Right now, many of the things that you're describing could also tie to the way one might think about transforming one's company. So are you seeing this integration of AI into the overall plan as part of a bigger story, perhaps, related to using AI to help transform these companies as a result of the deal?

32:08Benjamin Houssard: Yeah, that's a great question. So we like to say the merger or an integration is one of the most powerful change agents, right, when unlocking transformation. And to answer your question very directly, Sean, I would say we're starting to see it. And this is the point that I was making about experimentation, right? And I would say we're seeing that level of transformation or rewiring in a couple of specific disciplines. So one is, obviously, as you think about the tech and the data platform, and really creating kind of a integrated backbone, and all of this here requires kind of a very deep and integrated set of data.

32:54Benjamin Houssard: And so we're now seeing organizations really build that data and tech platform of the future, right? So that's kind of part one. Part two is you need that platform to really deliver all these specific use cases. So if you're going to integrate finance and develop kind of an integrated dashboard or performance management, you have to have good information. That's sort of the second area where we're seeing kind of this unlock is really transforming the performance management aspect. So one of our clients is developing a new kind of executive cockpit to really power the metrics they're looking at, deploying agents to really give recommendations to their various functions on direction.

33:43Benjamin Houssard: And so we're seeing that sort of performance unlock or kind of how management teams kind of newly operate. And then I would say, thirdly, we're seeing them in these specific use cases innovate the way that work is done. And so there are, I would say, I don't know, seven to 10 of these use cases where organizations are deploying AI to really kind of get these productivity and speed gains. And frankly, not just on the cost side, but also on the revenue side.

34:16Tobias Lundberg: And so, Alex, what areas are companies focusing on here then? Are you seeing any patterns or categories of effort?

34:23Benjamin Houssard: I would say there's a few point examples where we're starting to see companies really deploy and go after AI, right? And there's kind of three levels, right? Level one is, hey, let's just kind of use AI to make the process faster, right? That's sort of the first one. And, you know, I think the finance example of invoice processing is a good example of that. Like we have a process, let's just make sure we do it fastly and accurately. I think the level up from that is where can we deploy virtual agents to really do the work that kind of humans did before? And I think the customer service example was a good example of that.

35:06Benjamin Houssard: And then really the top end of the spectrum is where can AI plug into a much broader ecosystem, right? And so there's some exciting stuff happening in the operations planning arena where the models are kind of forecasting inventory stock levels. They're automatically doing order replenishment. And so you see that as kind of like the nirvana of where AI is taking on kind of full-on ecosystems of work.

35:39Tobias Lundberg: Thanks. And how about any critical factors that you're seeing that need to actually be in place to enable what we just discussed?

35:46Benjamin Houssard: Yeah, it's a great question, Sean. So, look, the first thing is setting the mindset and the expectation with leadership that we are going to leverage the transaction as a pivot to really kind of transforming how we work. I think that's step one. I would say that it is important, kind of the deal archetype that you are thinking about as Benjamin discussed. I think particularly for, we're seeing a lot of activity on the corporate side or corporate buyers. That is very important. Number one is kind of the leadership mindset and the expectation to swing for the fences. The second is talent. So there is, I mean, the market for AI talent in data and tech is super hot right now.

36:33Benjamin Houssard: But obviously, you have to have someone who kind of really understands what they are doing and the pace of innovation that is happening in this space. So I would say the second is you've got to get the right team in place. And then the third is really going after that kind of data and technology layer, right? That is the foundation, having clean data standards, having clean data governance, right? I mean, this is frankly not that exciting stuff, but you have to have really good data foundation and backbone to really kind of set, you know, kind of these more value creation components, you know, on top of this sort of data layer.

37:21Benjamin Houssard: And so it really takes, you know, all three of those foundational elements. And then obviously there's, you know, the use cases and the plan and, you know, where you want to go. Well, and that to me is the easier part, right? That's kind of classic, you know, sizing of opportunity. And, you know, companies usually know how to do that stuff. I would say the three things I described, leadership, talent, and the data layer, those are the most critical things.

37:49Tobias Lundberg: Thanks, Alex. And Benjamin, we touched on the importance of speed earlier versus the more traditional M &A timeframe. So how does AI help compress the process? us. Yes.

38:00Kameron Kordestani: So, indeed, we discuss about how AI is driving M &A activity, how you can use the excuse of an integration, let's say, to accelerate the value, but AI can indeed be applied to the M &A process independently from whether this is an AI company or not, obviously. So, on the upstream part, I would say that traditional M &A was quite periodic. You would like you would look at maybe a target scan on a quarterly basis you would come up with maybe 50 names that probably are often i would say the same ai i would actually shift that from uh what we say what we call always on deal sourcing you can do that i would say on the moon on a much more continuous manner and with much more data.

38:54Kameron Kordestani: So actually, instead of looking at the past, through AI, we can scan the patent, I don't know, in pharma, we can look at the web signals, we can look at the transcripts to actually expand the universe. So that's the main impact of AI on the upstream part, which is to go faster and to look at a broader, I would say, portfolio of potential acquisitions. On the midstream part, on due diligence, the shift is around completeness. In a due diligence of three, four weeks, it was difficult to look at thousands of documents. So you would typically only do sampling and focus on a few things. And at the end of the day, maybe only look at 15 % of all the data available in the data room.

39:44Kameron Kordestani: with AI and the solution that exists today. Actually, you can look at everything in a question of errors and then you can focus on all the risks that can pop up on looking at all the contracts, the footnotes, etc. So that's the main impact on due diligence. We could expect faster due diligence. What we actually see is deeper due diligence where we anticipate even more what might happen. And then on the downstream part, on integration per se, on separation, this is where we see the impact being much faster through the use of a library of agents. We have put after a library of example of agents across the multiple war streams.

40:38Kameron Kordestani: Here the question is for each step that used to take weeks, how you stream that, I would say, two days, being on the master planning, on the communication, on the cross-sell, on the delivery. So by using now, I would say agents, you can really compress the time. Now, if you look at the level of awareness and the level of adoption of AI in the M &A process, we are actually running yearly survey in terms of the level of awareness and adoption of the M &A community. What we see here is that now AI is seen as a key element to help M &A teams. You see the level of awareness for upstream now up to 88%, up 51 points from last year.

41:28Kameron Kordestani: Even if the level of adoption is lower, this level of awareness and adoption drop a little bit when we go to diligence and integration. This is often when we ask people a question of being aware of what exists. But actually, this is moving super fast. Actually, the typical LLM that you might have access to, ChatGPT and Cloud, can be the first level, let's say, to answer some of that. But actually, the players that we have seen that can really compress the time are actually players that could use a solution that could build on integration playbook and so on to really be specific agents for the specific integration capabilities.

42:23Tobias Lundberg: Thanks, Benjamin. That is a lot to think about. So, Cam, as we come to the end of our episode, I was hoping maybe you could share your key takeaways for our listeners today. Thanks, Sean. First is we're seeing activity pick up, And this is across the full set of M &A activities, whether this is acquisitions or divestments, JVs and alliances. And as several of my colleagues mentioned, this is, while going up, it is being marked by several very significant, large situations. We're seeing corporates leading this cycle with private equity still a bit on the sidelines. but the topic du jour and the topic of the year, we'd say this is the year of AI and this is the year of AI.

43:10Tobias Lundberg: How do you take the leap as you think about how to activate and engage with AI wherever you are in the M &A cycle? If you think you're upstream evaluating opportunities and targets, how might you shift, as Benjamin said, to an always-on model as you think about scanning the broader horizon for what might make sense from a strategic perspective. If you find yourself in the midst of diligences, how might you use AI today to broaden and connect the different pieces of the diligence exercise in a comprehensive and coherent way? And finally, if you're in the midst of an M &A activity itself, an acquisition or a divestiture, how might you automate and think about the end state as as alex alluded to in several examples in a way that begins to transform or drive greater efficiencies in how you are activating against those opportunities bottom line we're seeing a gap between those companies that are experimenting and adopting which are now leading the pack and those that are waiting on the sidelines.

44:27Tobias Lundberg: Again, wherever you are, begin to take that opportunity to explore what AI might mean for your organization in the M &A context. Wonderful. And before we close out, I'd like to give you an opportunity to share what you and Tobias are most excited about in terms of the AI opportunity in M &A. Yeah, we haven't really talked about this topic as directly. I'm excited about the implication of how you can use AI to better understand a culture as you come together and how you can experiment with and seek understanding and identify potential similarities and differences in how work is done in each organization to ensure that that does not become a friction point in the long run.

45:16Tobias Lundberg: That sounds great. And we also have another episode that we've done on the importance of culture in M &A, and we'll refer to that as well. Thank you, Kim. And Tobias, we'll give you the last word.

45:26Alex Liu: Yeah. So I'm most excited about how AI can be applied to improve the capabilities of corporate executives in the deal process. We've surveyed corporates over time, and the bar has risen, and the U.S. corporates have got better and better at most there. But the one area which has been a bit more flat has frankly been capabilities around really extracting the most the value and integration capabilities out of deals. And I think with the ability to accelerate, you know, access to information and connectivity and so on, as we heard out here from some of my colleagues, I'm really looking forward to also see how corporates can embrace that and move the bar up also in that area.

46:01Tobias Lundberg: Benjamin, Alex, Tobias, Cam, thanks so much for this wonderful conversation. Really appreciate you taking the time today. Thank you. And thank you to all of our listeners for joining us today. We hope you enjoyed the conversation and we welcome your feedback and ideas for future episodes. Just email us at ITSR at McKinsey.com, which stands for Inside the Strategy Room. You can also share your ratings and reviews on any podcast player with many thanks to all who've already done so. We really appreciate the comments and feedback we receive each week and encourage you to keep them coming. If you enjoyed this episode and you'd like to subscribe, you can easily follow our weekly series on any podcast player, where you can also access our entire library of more than 320 episodes.

46:42Tobias Lundberg: Finally, if you'd like to automatically receive our latest publications and insights, we encourage you to visit our M &A practice at mckinsey.com slash M &A. And you can also connect with us on LinkedIn. And we've included links for all of these for you in the show notes today. Thanks again for listening. We look forward to having you join us again next week inside the strategy room.

47:11Thank you.