TBR Talks: Decoding Strategies and Ecosystems of the Globe's Top Tech Firms

Revisiting TBR’s 2025 Predictions: What We Got Right (and Wrong) About IT Infrastructure and Digital Transformation

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How accurate were TBR’s 2025 predictions for the IT infrastructure market and digital transformation efforts? In this episode of “TBR Talks,” TBR IT Infrastructure Principal Analyst Angela Lambert and TBR Digital Transformation Principal Analyst Boz Hristov share how they and their teams look at the future of their respective IT market segments.

A mix of retrospective and forward-looking thoughts about 2026 and beyond, this episode offers insights into what the team got right in their predictions for 2025 and what they anticipate will come next. AI servers, unified data, AI services, strategy consulting and how AI is impacting the services business model are all topics on the table.

Prediction checks:

• Did infrastructure vendors’ focus shift from cloud to AI?

• Did digital transformation come roaring back?

• Did infrastructure vendors gain relevance in the AI partner ecosystem?

• Did the companies that made the right bets on ecosystems outpace the competition?

Listen and learn with TBR Talks!

Submit your Key Intelligence Questions for Patrick and his guests

Connect with Patrick on LinkedIn

Learn more about TBR at ⁠⁠⁠⁠⁠https://tbri.com/⁠⁠⁠⁠

TBR Talks is produced by Technology Business Research, Inc.

Edited by Haley Demers

Music by Burty Sounds via Pixabay

Art by Amanda Hamilton Sy

Revisiting TBR’s 2025 Predictions: What We Got Right (and Wrong) About IT Infrastructure and Digital Transformation

TBR Talks Host Patrick Heffernan: Welcome to TBR Talks: Decoding Strategies and Ecosystems of the Globe’s Top Tech Firms. Where we talk business model disruption in the broad technology ecosystem from management consultancies to systems integrators, hyperscalers to independent software vendors, telecom operators to network and infrastructure vendors, and chip manufacturers to value-added resellers. We’ll be answering some of the key intelligence questions we’ve heard from executives and business unit leaders among the leading professional IT services and telecom vendors. 

I’m Patrick Heffernan, Principal Analyst, and today we’ll be revisiting 2025 Infrastructure, Ecosystems, and Digital Transformation predictions with Angela Lambert, Principal Analyst for TBR’s IT Infrastructure and Devices practice, and Boz Hristov, Principal Analyst for TBR’s Digital Transformation practice. 

Prediction check: did infrastructure vendors’ focus shift from cloud to AI?

Angela and Boz, thank you very much for coming back to TBR Talks. This is our- do you want to say that, you know, you’re happy to be here?

Angela Lambert, TBR Principal Analyst: I’m thrilled to be here.

Bozhidar Hristov, TBR Principal Analyst: Always excited.

Patrick: Excellent. Oh my God, the sarcasm in everybody’s voice this afternoon as we record. 

All: *laughs* 

Patrick: Lovely. So, well, welcome back. We’re doing something a little different this year. We’re going to talk about predictions early, and by that, I mean the predictions we made at this time last year as we prepare for predictions going into this year. We’re going to talk about what you said. We’re also going to talk about the process. How, as analysts that have decades plus under your belts, how your process of making predictions every year has changed, and then what you anticipate is going to change this year as you look at predictions. But what we’re going to do, we’re going to go through a couple of predictions that each of you made and talk about whether or not they panned out in 2025 and how we anticipate that’s going to change maybe for next year as well. 

So, let’s start with this one. Angela, you made the prediction that infrastructure vendors focus will shift from serving cloud companies to making a massive push in enterprise AI. Did that actually happen? Did we see the shift? And were any companies significantly leading now or any left behind?

Angela: I would say yes and no on the degree to which this happened. So obviously, no one’s leaving behind the CSPs and the GPU-as-a-Service farms here in terms of wanting to serve those client bases. I do think we saw a lot of movement on preparing the enterprise for more AI adoption. I think the degree to which the enterprises themselves moved on, it was maybe slower than we would have expected. However, you know, we saw motions like storage vendors, like Pure Storage and NetApp, you know, getting much more focused on data platforms that can help enable AI. We’ve seen a lot of storage systems fine-tune for AI, and we’ve seen a lot more just general, I think, focus and participation on how enterprises can prepare their data. So, the year before was all about, you know, just flashing kind of these impressive servers around, and it got a little bit more tactical in terms of how are we actually going to help enterprises achieve these goals.

Patrick: And when the infrastructure providers talk about data with enterprises, are they talking about the cleanliness, the orchestration, the storage of that data, or are they more just talking about sort of volume and the need to provide the capacity to handle data?

Angela: I think for them right now they’re still focused on a little bit on speeds and feeds, right? Like we can get this blazing fast and get it, you know, maximize your investment in your really expensive AI servers by having storage power that can match that. But there is also this idea of unifying data that is not unified today. So that’s certainly another theme there.

Patrick: And you mentioned Pure Storage and NetApp. Were there any other infrastructure providers that sort of stood out over the course of 2025?

Angela: You know, I think HP has had a very clear enterprise focus on their AI strategy. So, I would say certainly them and interested to see how that continues to change as they’ve acquired Juniper and have kind of a unique network forward approach compared to some of the others.

Patrick: It sounds like you’re preparing for your predictions for 2026 with that.

Angela: Maybe I am. 

Patrick: Maybe you are. 

Prediction check: did digital transformation come roaring back?

All right, Boz. One of your predictions was that transformation comes roaring back. You said that after declaring digital transformation dead a few years ago and witnessing the past 18 months of GenAI hype centered on cost takeout and efficiency enhancing use cases, that we anticipate enterprise IT buyers and their C-suite bosses will pivot in 2025 to large-scale digital transformations and business model reinventions supported by spending on strategy consulting. Did that happen? Did we see an uptick in strategy consulting, but more importantly, did we see that pivot away from, or less concentration on cost takeout and more concentration on business model reinvention and digital transformation?

Boz: I think all the flavors happened over 2025 and continue to happen. Now, strategy consulting in its pure form continues to face headwinds. And I think all the management consultancies that have as a core capability, aside from McKinsey and BCG and Bain and the Big Four, they have realized that some of them are further along in terms of diversifying and expanding their portfolio offerings and capabilities. So, they are rarely trying to sell strategy consulting for strategy consulting’s sake. They are trying to permeate the technology element in their discussions much sooner, much faster, either as an enabling tool, now with using agents or otherwise, or they’re trying to steer the conversation that will provide them as an entry point for maybe driving systems integration services or managed services for that matter. Maybe not McKinsey, but some of the Big Four are a little bit leaning that direction. 

So, while the strategy consultants- consulting revenue continue to face the headwind that I mentioned, I think the business, the digital transformation roaring back is roaring back in terms of, you know, again, depending on the client. We saw some clients that were- I would consider laggards, take the insurance industry or some of the financial services, maybe some public sector, public services clients. They were a little bit behind in terms of adopting and thinking about moving along the way from on-prem to a cloud infrastructure. They are starting to come moving a little bit faster. So, you can argue that maybe the transformation was happening more for them, for the more digitally mature enterprises, there was a little bit more of that reinvention business model, kind of a transformation, sort of like a little bit kind of different flavors, new words being used by consultancies to do exactly the same thing. 

We know there’s still a large opportunity around SAP S/4 migration. So, that’s still happening, which I think a lot of the companies are capitalizing on. The other part of the roaring back for digital transformation made us starting at this point is opportunities within the mid-market. So, kind of going beyond the large enterprises. And that obviously requires a different engagement model for consultancies and the services providers than they- kind of like a delivery models. So, net-net, maybe not the full extent, but looking at the overall market performance, company performance, we saw an uptick in performance of the IT services companies compared to 2024. We are trading up into more in the low to mid-single digits as a market. Everyone is trying to move up further along, you know, more in the upper mid-single or even aspiration in double-digit growth. That double-digit growth, it will be a while before it happens, if ever. But that’s maybe for another prediction to talk about. But that’s just the way we see the market. So certainly an improvement with companies taking different approaches that are trying to capture some of the rebound in certain pockets of the market.

Patrick: So, the overall idea that digital transformation is no longer dead, the companies are trying to make this business model reinvention that they are trying to use all the tools that are available now to do revenue growth, not just cost cutting. That’s all true, yeah?

Boz: For the enterprises, again, I’ll split those in two camps, the leaders and laggards. The leaders are more looking at the revenue growth. The laggards are trying to catch up. And I think it’s the vendors are kind of victims of their own success, so to speak, because the focus, especially with blending and balancing the messaging around what GenAI can do for the companies, for the buyers, and what it does for them, and so much more focus on improving productivity has left some of them kind of hanging and not making a shift towards let’s do something more with our productivity. How are we capturing the productivity improvements from terms of dollars and budgets and how are we reinvesting back for growth? So, I think this is the biggest opportunity that I think if 2025 was a learning experience, I think I want to see more of that conversation happen in 2026. So, kind of like I’m shifting the timeline, I guess, from a growth perspective, but that’s just the nature because I think services companies are, and some buyers are tired of proof of concepts. I think that kind of just got grinded to the ground and nobody wants to talk about POCs anymore. I mean, they still are, but I think enough is enough. Everybody knows about all the use cases around, you know, customer experience and software automation and supply chain and procurement. We all heard them, right? Now it’s what do you do with that? How do you drive the business to grow?

Patrick: Right.

Boz: And I think that’s going to come on both sides. So opportunity for the vendors on the vendor side is like, can they use and can they convince the buyers that those savings that they generate as a result of using some tools, AI, GenAI, whatever flavor of AI you want to say, can they reinvest and reinvest in what’s important with them? That’s the big question. Or are they going to look at their partners? Are they going to look at their shareholders? Or they’re just going to cut back on their budgets? So, we’re going to- we shall find out.

Patrick: So, you’re previewing one of your predictions for 2026 right there.

Boz: A little bit of that, yes.

Patrick: Should have known I was walking into this trap. 

Boz: *laughs*

Prediction check: did infrastructure vendors gain relevance in the AI partner ecosystem?

Patrick: All right, Angela, back to you here. Back to talking about infrastructure for a bit. One of the predictions you made was infrastructure vendors will gain relevance in AI partner ecosystems. So, you said having learned their lessons from being slow to adapt to hybrid cloud in years past, infrastructure vendors are working much more rapidly to build out partner ecosystems that will enable a wide range of AI use cases, including those leveraging public cloud. I think one of the challenges that we always have as analysts is we think that companies and vendors have learned their lessons, but maybe they haven’t. Are the infrastructure vendors still moving too slowly, or did they learn their lessons?

Angela: I think there’s certainly been lessons learned and everyone can always move more quickly. But to me, it’s really at like the DNA level of a mindset in previous times that was very focused on keeping the customer entirely in your ecosystem. And that I do think has really shifted to more of an openness, more of an acknowledgement and embracing that particularly with AI workloads, that will be an edge to data center to cloud type of arrangement. And I do think that OEMs have at least embraced, on some of those elements, deepening their public cloud partnerships, establishing new data-related partnerships that didn’t exist before. Boz and Patrick, you could probably tell me how things have changed on the services side, maybe a little less so there. I think more on the technology partnerships, yes, I do think that there’s been a whole host of new partnerships established this year, but maybe you two would have seen different perspectives depending on the partnerships you’re looking at.

Patrick: Boz, you go first on that, and then I’ll weigh in.

Boz: Different partners, different ecosystems. I think it’s, there’s two parts of it, the way we’ve seen it. It’s one is the expansion and grow, well, I guess there’s different kind of phases. One is growing the, kind of the, within the ecosystem that you currently have, can you do more with your existing partners, and now it’s looking at expanding your ecosystem with, you know, if you are services providers, who else can help me? I mean, you mentioned the data side, you know, the Snowflakes, the Databricks of the world; those are obviously partners that are becoming ever more important, but then you look at the next phase. So now we look at OpenAI and Palantir and Anthropic and all these companies are kind of becoming mainstream names and kind of like household names when it comes to AI and agentic AI. I think we’re going to see more of that. And we’ve seen some of the vendors being a little bit more aggressive in their relationship and trying to kind of build a beachhead in those, and investing in developing resources and skill and certifications and really trying to go to market together, either specific industries or just a kind of like a horizontal functional area. 

The other thing from a partner ecosystem is the expansion of the ecosystem from a two-dimensional to three- and multi-dimensional relationship. That’s the other part of the equation where we keep seeing and hearing about how there’s more opportunity for services companies to be positioned more as an orchestrator and bringing together, you know, if it’s EY bringing Dell and NVIDIA and Microsoft and SAP together in one mix, right, for the customer. So, I think  there’s an opportunity for that kind of a relationship. We have been discussing probably for the better part of the last two years at least, if not more than that, for that multi-party alliance construct. It’s challenging when you’re talking about at the enterprise white level, but it certainly has a strong use cases application when it comes to specific line of business, fewer disruption, very specific, deep knowledge and function and industry specialization that can be applied. Usually that’s where the budgets are, then the line of business, that’s where it starts. So, you got to position it the right way that you are the preferred partner with XYZ sub-partners and you kind of go kind of that GC approach and it both back down now. It’s easier said for us then down for the partners because you got to think about the commercials, the accountability, the execution and all these other things that come along with it. But those are the couple of areas that we’ve seen the ecosystem evolving.

Patrick: I think too to this specific point, how well do services companies and consultancies, IT services companies, consultancies partner with infrastructure providers? I think part of it is that we’ve seen the IT services companies and consultancies expand their view of what their ecosystem is. I mean, five, six, seven years ago, it used to be your ecosystem was the cloud vendors, your ISVs, the SAPs of the world, and then you were really out there if you included like a university.

Boz: Right.

Patrick: Or if you thought about academics and NGOs in your ecosystem, well, you had an expansive view of the world. That is finally starting to change. And I think the IT services companies and the consultancies are recognizing that there is an opportunity to talk to someone different at their client by bringing in an infrastructure partner. The challenge still remains, Boz, exactly what you said around the commercials of it. And honestly, the how do you tell the difference between, I’m guessing you can’t tell the difference between the Big Four firms, Angela, and we cannot tell the difference between the infrastructure providers. 

Angela: *laughs*

Patrick: And that has to change at those companies themselves, not just here at TBR. 

Prediction check: did the companies that made the right bets on ecosystems outpace competition?

And Boz, that actually teed up perfectly the last prediction that we’ll talk about today. And that was, you said the most successful IT services companies and consultancies will be the ones that partner best. You said, further, those companies and firms needed to demonstrate differentiation to their enterprise clients and critically their technology ecosystem partners. Exactly what we were just saying. Some could, some couldn’t. In 2025, the IT services vendors and consultancies that make the right strategic bets on the best fit ecosystem partners will outpace peers. So, who did and who didn’t? And then maybe more importantly, other than just naming names, did the strategies that you thought would work best for those companies actually turn out to be the things that they needed to do?

Boz: I’d say companies should continue to test, they have some best practices, no doubt. I mean, we’ve seen, if you kinda- the three layer approach that we’ve seen the most consistent across the vendors is leadership alignment, kind of like seeing the vision and aligning with what the priorities are. The second one is around co-development in terms of portfolio investment and skills and just trying to really go as close as possible and make sure you have the right people, the right portfolio that supports that vision. And the kind of foundational layer, which without it, I think the first two are really not going to go much further, is around knowledge management. So that’s kind of the three-legged stool on the successful partner strategy. And that knowledge management is what’s separating some of the more successful vendors than others. But again, it’s really important, like how deep you go on the first two, because that will enable and force you to do a better knowledge management and how you educate your partners, how do you ensure you have the sales enablement to mean- and how they are equipped with and they can tell your story as good as you can tell yours. So, I think this is where rubber meets the road kind of thing and we’ve seen and we constantly get questions from our clients and a lot of them come from within the ecosystem about from technology side, from services vendors and vice versa. How can we go better together, right? What do we, what should we do about, you know, gaining so-and-so’s attention, right? So, how- that’s just the kind of a constant, how can we force, you know, how can we make sure that an SI sells more of our infrastructure and how can we maybe get on the infrastructure provider’s radar? So, if we are services provider maybe on the BPO side and try to go upstream and go into the IT side of it. So, it goes both ways. So, I think this is kind of like where we’ve seen some of the success. 

Probably some of the more successful ones that we’ve seen and we measure that are some of the top, the kind of the more larger SIs, I would say the, like I said, the Deloitte’s, the Accenture’s of the world, the Capgemini’s of the world. We’ve seen definitely a really strong progress from KPMG as well as one of the firms that has really done really good progress when it comes to how they manage the ecosystem. EY certainly has placed some strong bets on a select few vendors that is really investing deep along the way. Some changes for the better on the IBM side as well, because it’s trying to kind of pivot away from that big blue first kind of mentality. Still some work to do, but we’ve seen some good feedback. 

Overall, just to kind of fall back on our data and research for a moment, from our Voice of the Partner research when we survey partners, what they think of each other and kind of satisfaction, pretty much all the service providers have strong satisfaction scores from their cloud and software partners as well as the OEM partners. Some have more of a neutral view on each other, but overall positive sentiment. But we do see, like I said, some of those few names that have made some really good progress, both on the financial side, the performance side, as well as just the perception that it’s evolving, it’s actually making and compelling others to get attached to that two-dimensional ecosystem, right? So, I mentioned Deloitte, you know, really strong relationship with AWS, and now Snowflake is trying to go along that side as well. I mean, it’s just kind of going kind of three-way set up. EY I mentioned with Dell and NVIDIA, and then you know Microsoft, so there’s that. That’s what’s, these are kind of qualitative KPIs in a way that’s measuring success, but there’s a few examples that come to mind.

Patrick: Yeah, and I think just thinking about all the research that we’ve done over the last year around the ecosystem and not only the Voice of the Partner, but all the different ecosystem reports. And then I know our cloud team has a new report out now looking at the ecosystem very specifically from the hyperscaler angle. I think that’s where we’re able to now, because the prediction was the most successful IT services companies and consultancies will be the ones that partner best. And what the hell is best? 

Boz: Right.

Patrick: So, I think now we’ve actually got, to your point, a lot more quantitative analysis behind what exactly best means. 

Boz: Yep.

The predictions process and how AI changes and doesn’t change it

Patrick: So excellent. Let’s pivot here now to not giving predictions for 2026. We’ll do that later in another podcast, but instead looking at how you go about making predictions, the thought process, the research that you do before you sit down and say, okay, this is what I’m predicting for the coming year. And then importantly now to think about how artificial intelligence will or won’t change your process, influence your process, be incorporated into your process. With sort of the idea that artificial intelligence by its nature is, you know, GenAI is more backwards looking. It’s pulling from the past to make a prediction about the future. Whereas what, and you tell me in your process, you’re not just relying on the information that’s in a large language model in your head. You’re relying on more than that. And so, if you could maybe talk a little bit about how that process works and then how you anticipate a change, or maybe don’t anticipate a change this year. Who wants to go first?

Angela: I’ll give a crack at it. 

Patrick: Alright.

Angela: So, step one, you make a huge coffee. 

All: *laughs*

Angela: Well, I think to me, there’s a couple components to the time of year when, you know, it’s time for the TBR analysts to start making their predictions. First and foremost, you know of course, our teams, right? So, it’s getting together with the team, talking about where we’re at now with prevailing market trends like we would in any given quarter, but also looking at market signals. We look at the comparison of what we’ve learned throughout the year in attending vendor events, what they’ve been saying at all of their big customer events, reading between the lines on the quarterly transcripts, and financial performance. So, we’re looking at the messaging of vendors in the market, but we’re trying to compare that against what we see from customers and importantly, what we’ve seen from actual performance financially, where really the rubber meets the road. So, we love to discuss all those things as a team and bring out our most skeptical of opinions as we do that.

Patrick: And then do you think, do you anticipate incorporating any of our in-house AI tools into your effort this year? Or does it shape, or are you reluctant to, or how do you feel about that part of it?

Angela: I will really look forward to having tools now that can look back across everything we’ve written, published in the past year or longer and kind of query topics against that, you know. And what are the most common things that our team talked about this year? How did that compare to what we’ve seen? And going forward, what’s that going to look like? So, I think it’s going to help us a lot in terms of identifying maybe what trends have been talked about the most and what we should assess going forward. So, that’s definitely one way I’d do it. How about you, Boz?

Boz: 100%, I was just listening to you and thinking, yes, number one, internal knowledge management. You know, that’s the key. I kind of wrapped up the alliances part with it, but that’s the foundation for everything in the professional services, it’s not just professional service, but the process is a critical element. And so that’s the internal part. The external part is the signals, right? And the signals come from multiple sources that we go around and collect. Probably another external source could be just the geopolitical side of the house, understanding the macro trends as well. So, kind of including those into our perspectives and considering as we are thinking about, you know, what moves and what shakes the market, essentially, right? The skeptical view, I love it because you know me, I try to put my skeptical hat on as much as possible, as often as I can. You know, I may not be the most favorite opinion sometimes among some of the clients, but some do appreciate it. So just the way it goes. And that’s, I think, that’s what some clients do appreciate, coming that way. And it’s, because everyone can read the news these days. 

Patrick: Yeah.

Boz: And ChatGPT can read even faster than you can sometimes, and not sometimes, but all the time these days, right? It can kind of like scan it and give you the summary of what the news is. So, we really are trying to bring in- and really trying to elevate and fall back on our proprietary data models. I think that’s a key part that as we build the predictions, as we look into what we have in-house and thinking about all the qualitative, we want to make sure our quantitative database also supports those hypotheses. And kind of go back and forth, not just- you can start with a hypothesis and look at the data, or you can look at the data and then build an opinion on that. 

Patrick: Right.

Boz: So, you can go both ways, because you can- this is the beauty of the human brain, right? You can, you know, take multiple angles and interpretations versus to your point about the AI, I’m not sure- that may not do that, maybe a few years down the road, but that’s what you ask them to do, right? It’s a linear way of doing it versus the human brain can kind of react a little faster sometimes and take a different approach, a more creative- 

Patrick: Right.

Boz: Creativity is still a little bit stronger in my opinion.

Patrick: I think so too. And one thing I’ve done the last couple of years in preparing to do predictions and adding my two cents in is anytime I go to an event, and oftentimes when we get briefings, whether over the phone or live, I take notes by hand. And always at events, someone will say something and I’ll put a big star next to it, or they’ll say something that will make me think of a question, and I’ll mark that very clearly in my notebook. Honestly, 9 times out of 10, that doesn’t make it into print. It just, it doesn’t. 

Boz: Yeah.

Patrick: So, then I have to go back in the prediction time of the year and look, and it’s easy for me to flip through the notebook. And anytime I see that star, the big question, the big bold writing, that- all that stuff doesn’t exist anywhere else. There’s no way for it to be scraped. That’s where some of that creativity comes in.

Final thoughts

So, I want to wrap up with two predictions from each of you. I know this isn’t the predictions episode, but we’re going to do predictions anyway. The first one is easy and the second one is easy. The first one, and neither one of them do you need to give me a reason. Let me just say that. You need to give me one name for each one of them. And I don’t need a reason behind any of it. And I’m not going to give you a whole lot of time to answer. It’s got to be quick. So I’ll go, Angela, you’ll get the first one first, and then Boz, you’ll get it, and then Boz, and then Angela. So, in 2026, which company are you going to write the most special reports about? Angela.

Angela: Intel.

Patrick: Boz.

Boz: Palantir.

Patrick: Palantir. Wow, interesting choice. All right, in 2026, Boz, you go first, and then Angela. Who’s going to win the World Cup? Boz.

Boz: Spain.

Angela: My gosh, I have no idea what to say.

Patrick: Well throw a country out there. 

Angela: Ooh, Portugal?

Patrick: The US is hosting, and Mexico will be in it, Canada will be in it, Portugal will probably be in it.

Angela: Okay.

Patrick: You have colleagues in this building that love Greece, you know? Just saying.

Angela: All right. Seems like a great bet.

Patrick: So, who do you want to go with? Don’t say Greece, I don’t think they’re going to make it.

Angela: I’ll say US.

Patrick: All right, US, fantastic. Excellent. Thank you very much, both of you, for coming on. Really appreciate this, this is always a lot of fun. And we’ll do another one of these in a little while, we’ll talk probably early January, talk about your predictions for 2026. Thanks.

Angela: Thank you.

Boz: Thank you.

Patrick: Next week I’ll be speaking with Angela Lambert and Ben Carbonneau about Lenovo GIAC 2025. Don’t forget to send us your key intelligence questions on business strategy, ecosystems, and management consulting through the form in the show notes below. Visit tbri.com to learn how we help tech companies, large and small, answer these questions with the research, data, and analysis that my guests bring to this conversation every week. 

Once again, I’m your host, Patrick Heffernan, principal analyst at TBR. Thanks for joining us and see you next week.

T

TBR Talks: Decoding Strategies and Ecosystems of the Globe’s Top Tech Firms

Join TBR Principal Analyst Patrick Heffernan weekly for conversations on disruptions in the broader technology ecosystem and answers to key intelligence questions TBR analysts hear from executives and business unit leaders among top IT professional services firms, IT vendors, and telecom vendors and operators.

“TBR Talks” is available on all major podcast platforms. Subscribe today!

TBR Talks: Decoding Strategies and Ecosystems of the Globe's Top Tech Firms

Managing Strategic Alliances & Ecosystem Partners: How Top Alliance and Enabling Technology Practice Teams Use TBR Data

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In this episode of “TBR Talks,” TBR Senior Vice President, Sales & Marketing, Dan Demers interviews show host Patrick Heffernan on how the globe’s top global systems integrators, ISVs, hyperscalers and OEMs use TBR’s proprietary data and analysis to make validated and data-backed decisions.

From strategy planning based on partners’ annualized revenue or headcount growth to allocation of training budgets and schedules to align engineering resources, TBR’s unique data and analysis within the ecosystem give leaders a meaningful and independent set of data to make partnership investment decisions.

Episode highlights:

• Understanding TBR’s data view of the market

• Case studies: IT outsourcing and applications outsourcing, staffing and headcount, perception of partnership alignment

• Age of AI and agentic AI: Pricing and staffing changes

Listen and learn with TBR Talks!

Submit your Key Intelligence Questions for Patrick and his guests

Connect with Patrick on LinkedIn

Learn more about TBR at ⁠⁠⁠⁠⁠https://tbri.com/⁠⁠⁠⁠

TBR Talks is produced by Technology Business Research, Inc.

Edited by Haley Demers

Music by Burty Sounds via Pixabay

Art by Amanda Hamilton Sy

Managing Strategic Alliances & Ecosystem Partners: How Top Alliance and Enabling Technology Practice Teams Use TBR Data

TBR Talks Host Patrick Heffernan: Welcome to TBR Talks: Decoding Strategies and Ecosystems of the Globe’s Top Tech Firms. Where we talk business model disruption in the broad technology ecosystem from management consultancies to systems integrators, hyperscalers to independent software vendors, telecom operators to network and infrastructure vendors, and chip manufacturers to value-added resellers. We’ll be answering some of the key intelligence questions we’ve heard from executives and business unit leaders among the leading professional IT services and telecom vendors.

I’m Patrick Heffernan, Principal Analyst, and today we’ll be sharing the audio of a recent TBR Insights Live webinar session where Dan Demers, Senior Vice President, interviews me about a TBR case study in managing strategic alliances and ecosystem partnerships. If you’d like to view the visuals from this presentation as you listen along, you can do that through the link in the show notes.

Introducing the alliance and ecosystem use case

Dan Demers, Senior Vice President: Appreciate the chance to present some of the ways that we work with clients. This is a little bit of a different webinar, I know a lot of times Patrick, who’s sitting beside me today, Patrick and the team of analysts will present on topics, emerging, disruptive events. Today, we’re going to click into a case study. And this is a case study that we’ve seen evolve over the last seven, maybe ten years, and get more and more refined as each year has gone by. I’ve had the pleasure of sitting in a lot of these meetings. So, today we’re going to flip the script a little bit, I know, Patrick, you often will be leading these webinars with some of your colleagues. I seldom participate, so this is kind of fun for me.

Patrick: Yeah, these are always fun. So welcome. Welcome to the party.

Dan: I’m glad to be here. So, today’s agenda, as the title suggests, we’re going to be looking at how do global systems integrators and their enabling technology vendor partners, how do they go-to-market? How do they partner? How do they staff? How do they ultimately drive revenue? And hopefully, I’m sure for all of those parties concerned, continue to renew, a sticky relationship with digital transformations, AI integrations, modernizations, the whole panoply of the services that they provide. So, we’re looking at the- specifically in TBR’s research and our data, and how our clients over the years have come to use our validated and independent data, such as our IT outsourcing, applications outsourcing, consulting and systems integration revenue breakouts inside your team, the professional services team’s, research. Looking at critical data on headcount and credentialing and certification of that staff, and how are the SIs moving the pieces on the chessboard when it comes to people and how they’re training those people? And what does that then mean for their enabling technology partners? And lastly, as a part of this conversation to frame it out, we’ll be looking at objective data, how our clients have come to use that to guide critical decisions on how to staff, how to manage, how to enable, how to train, and how to fund these alliance groups. And then within those alliance groups, specific alliance teams as they pertain to different members of the Global Systems Integrator class.

So, speaking of clients, who uses our research? This is a slide that our marketing team has put together. Going into our user data and our subscription contract data, without getting into names, many of our customers prefer that we not mention them. But it’s safe to say that the vast majority of our customers are the very companies that we cover. Our historic use cases have always been in competitive and market intelligence, and again, starting ten years ago and moving through, really, the last four years, we’ve seen the incidence of usage, the conversations that we have, really start to shift towards those alliance and ecosystem leaders and the staff within those organizations as they strive to get a validated outside-in view on the ecosystem. So, 10 of the top 10 SIs, three of the top three big hyperscalers, virtually all of the major OEMs, the federal systems integrators, really the largest names, the most recognized partners and really the leaders in each of their core areas are represented by our customer base. So, the talk that we’re going to have today is really centered on whether it’s me sitting in listening to you and your team, Patrick, talk to clients, or our sales team receiving questions from our users, and we pass them on to you, or to Allan Krans and his team in the Cloud and Software group, Angela Lambert and her team in our Infrastructure group, really across the board, this use case has really organically grown from our users tapping into your expertise, your team’s data, and your colleagues’ analysis.

Patrick: Yeah, one thing I would add, Dan, is that when I started here over 12 years ago, my focus was entirely on those GSIs and those management consultancies, and that’s who I talked to all the time. Now I spend less than half my time talking to them because I’m instead talking to their alliance partners. So, it’s those hyperscalers, it’s the OEMs, it’s everybody else in the ecosystem that’s coming to us and saying, what’s really happening with the GSIs, what’s really happening with the management consultancies? And honestly, it’s a lot more fun for me that it’s now the ecosystem, not just one set of vendors.

83% of enterprise technology spend

Dan: So that’s us. I always like to look at this picture and think of the time that we spend on the road together. I often will refer to Patrick as my winsome travel companion. Together, we’ve traveled the world, we’ve met with leaders. And it’s interesting, as you were just talking about how half of the time you’re talking about other folks. One of our last trips to the UK, you shared that you were spending more time talking about microprocessors, silicon, and chips than you’d ever in your entire career.

Patrick: Yeah.

Dan: And we weren’t even really meeting with those folks. We were talking to your classic peer group, the systems integrators.

Patrick: Right. I was all fired up about liquid cooling at the time. So, it’s funny how that happens.

I do want to just frame out a little bit of this discussion today and from my perspective of where a lot of this is coming from. The most important number, perhaps in this whole entire session, but certainly on this slide, is that 83%. And that is that 83% of enterprise technology spend is going to multi-vendor engagements. What’s interesting about that is we also know that the win rates for IT services companies and their tech alliance partners are significantly higher when they partner with at least one partner, but even higher when they partner in a multi-party engagement. So, we know that this is exactly the thing that has changed so much and so dramatically over the last, say, five, six years within the ecosystem that we’re looking at is the reliance of the GSIs and the consultancies on their technology partners. And so, they have to have, in order to take advantage of that, in order to reach that 83% win rate, or in order to capture that 83% of the enterprise technology spend, they have to have really well-developed, constantly refined, leadership-driven alliance strategies. It’s an absolute imperative right now.

Dan: Again, it’s going to remind me of, I think, our first trip together, we went to Texas, visiting with some of the SIs and their experience centers. And they were avowed agnostic when it came to their technology partners. And I remember debriefing afterwards with you and members of your team and then progressively going across the world and visiting with other SIs and other hyperscalers. And that seems to have been a- there’s a change there. That vendor agnosticism is no longer something that they lead with.

Patrick: It’s totally dead. And I’m happy to see it go, because I think it was always kind of a bit of a fiction anyway. So, we can do a whole webinar on why that was a fiction, but all right.

Dan: So why are we talking about this? As you just pointed to, that 83% number has only grown in the time that I’ve been here since 2016/2017. More and more of the spend is flowing through this ecosystem. I think I’m going to quote you and tell me if I got it wrong, but, maybe 3 years ago, you finally said it is the end of end-to-end solutions.

Patrick: Amen.

Dan: There is no single entity that can deliver every aspect of a full modernization or digital transformation engagement, from the management consulting through the support and deploy of the hardware and managing the workloads on the cloud. It’s an entire ecosystem of partners. More and more of them are declaring their partnerships. They’re working deeper and more, engineering-wise, more intimately together, commercially, more intimately together. So, we look at our research, and we see clearly our clients using our strategy analysis for their strategy planning. We see their engineering headcount being driven by the revenue and the trailing 12-month trend lines that we see from our revenue in our services category. We see marketing staff, marketing budget, a lot of our research gets pulled into marketing enablement. Obviously, the sales and pre-sales staff and the credentialing, the vital critical time that gets spent. All of these core use cases are tied back to some of the data that we produce. And we’re seeing, it’s not that gone are the days of the Accenture lead at ISV-X telling us, “you can’t tell me anything about Accenture I don’t already know.” Sure, you talk to Accenture every day more than our Accenture expert, perhaps. But you don’t know what Atos is doing, or Wipro is doing, or CGI is doing or any of the other 20, 30+ SIs that you’re competing against. And ultimately, that gets down to their quarterly business reviews and how well they’re doing on a revenue basis. And we’ll show today how we’re going to connect some of our service line revenue that your team produces and how many clients are using that to literally benchmark team performance against specific SIs. So, it’s really very, very strategic and tactical all at the same time.

Understanding TBR’s data view of the market

Patrick: Yeah, so let’s get deep into the numbers here, at least just to show you the way that we look at the world, because I think it’s important if you’re not super familiar with TBR to understand.

You’re looking at our signature graphic. We take hard numbers, we put them into our taxonomy so we can compare companies in a meaningful way. The apples to apples is a cliche, I think about it more like it’s a fruit salad, you know, and you get a lot of different fruits, but you got to cut them up and put them all in the salad. And you only get to understand them as they are meaningful to each other. So then we show the most important metrics; revenue, revenue growth, and operating margin. Often we present directly to the GSI’s technology partners, again, like AWS, Nvidia, Microsoft, SAP. We typically stay right here. We just walk through all the analysis and all the insights that this singular graphic can provide. And I wanted to show two things to sort of reinforce this. First, we’re analyzing and presenting meaningful data, proprietary and meaningful. It’s a rigorous process. It’s our taxonomy. And second, this approach underpins all of our research. So, when we talk about ecosystem relationships and metrics, and performance in a little bit, we’re coming at that with the same kind of rigor. 

And I’ll share a quick example that just happened today. Our lead analyst who covers Deloitte, which is a privately held company, so they don’t produce quarterly earnings. They’ve recently- he recently published his estimates for the firm’s revenue and headcount. Again, Deloitte is privately held. He estimated global revenue, global revenue at $70.1 billion, and they’ve reported at $70.5 billion. He estimated global headcount at 474,000, and they reported at 470,000. So, being that close, which is for a Big Four firm, that’s essentially dead on accurate, that reassures us that our data is solid. So, that’s where we’re coming from.

Also want to show this, which is the ecosystem view that we take. And what you’re seeing here, speaking of proprietary data and contextual analysis, what you see here are the relationships between 3 GSIs, and yes, we’re considering Deloitte a GSI in this case, and one of their hyperscaler partners. We’re estimating the revenues, the growth, the staffing, and then critically, we think critically and we hear critically, what percentage of the GSI’s total revenue is tied to that hyperscaler partner? That’s the data and the context that helps understand the strategy behind it all, the go-to-market opportunities, the when, whether, how others in the ecosystem can or honestly should partner. So, this ecosystem research has become enormously important to us and to our clients.

Case study: IT outsourcing and applications outsourcing

So now we’ll sort of begin the case study part of this and we’ll dive into the agenda fully here. So, I’m going to show a couple slides real quickly. And these are the, again, bubble charts. This is the latest bubble chart on IT outsourcing. So here, take a quick look and a close look at where Infosys is on this chart. And then on this next chart, we’re looking at applications outsourcing. And here I would say take a look at HCLTech. A little hard to see, they’re to the right and up, but just barely, but they’re an important company. And I’ll explain exactly why in just a moment.

Here we have the trends that we’re seeing across these two areas, IT outsourcing and applications outsourcing. So, what do these trends mean? You can read them. What do they mean for the rest of the ecosystem? Well, you’ll see there’s a slight decline overall, at least in IT outsourcing. And that’s just not, that wasn’t true for Infosys. As I called out, and as we saw, Infosys grew over 5% in part because Infosys has been successful in integrating its AI platform and accelerating that time to value for clients. And that helps maintain client stickiness, which is necessary to secure their incumbent position in a market where there’s just constantly consolidation. And I want to say, Dan, at the very beginning, you mentioned the desire by GSIs and their technology partners for that client stickiness, true and not true at the same time. And a little bit later, I’ll explain why that’s not true. But it’s really important to understand. And when we look at IT outsourcing, how it’s client stickiness that really determines who is doing well and who isn’t. And again, I’ll come to why and how the hyperscalers and other technology players play in that.

Secondly, on applications outsourcing. So, HCLTech, as I mentioned, they use their AI platform, it’s called AI Force. We’ve done a couple of reports specifically on AI Force, because I think it’s something worth calling out and looking at. But they have used that to win more deals and like Infosys get stickier with their clients. And we’re, again, we’re cognizant that client retention is an IT services- it is the IT services company’s most important metric. And being embedded in a client ends up being a superpower for any one of these GSIs and these consultancies. So, it’s not surprising then to us that the companies that are succeeding in ITO and applications outsourcing are prioritizing this aspect of this engagement. And a caution on that, and this is what I mentioned before, client retention is the holy grail for IT services companies, but not for the technology ecosystem partners. Client retention doesn’t mean the same thing to a hyperscaler or to an ISV as it does to IT services vendors. And understanding that point is really critical. Understanding why those differences exist and how to bridge them is important too. Dan, I know you have some thoughts on this slide as well.

Dan: The slides that you’re showing with the bubble charts and the data, what I wanted to call out here was how I see members of your team when clients peel back the underlying data tables that our clients have access to through their subscription. They’re seeing vendor by vendor from this bubble chart and the others, vendor by vendor, revenue, operating margin, headcount, and in some of your reports, even nation state where headcount is located. And the key point here, I think, for the partners of the SIs, they’re able to look at that data and compare and contrast it against one vendor to the next, one country to the next, growth in headcount, growth in revenue, or decline in headcount. Because the question we get time and time again is: TBR, who should we partner with? And so, it’s finding the right match between the Tier II ISV and their widget, their value proposition. Does it align to which service line, which SI has the right engineering talent and is themselves focusing and investing in that? So, the data tells this incredible story with these visuals at the senior level when we’re sitting in a boardroom. But then there are the folks three layers deep in an organization who have to answer up their food chain. Who should we- tell me, give me the data, why we should partner with HCL versus TCS. All of those questions are very hard to answer from a data-driven sense because this data is not available anywhere else. And a lot of it is gut-driven, relationship-driven. “Well, our CEO plays golf with their CEO.” Okay, wonderful. But is it the right marriage? Is it the right combination of technology solution and SI skill set and staff?

So, all of these wonderful visuals have really deep, boring Excel spreadsheets underneath them. I don’t- I’m an English major, so I say boring. I apologize. I’m not a quant. Quants love our Excel files and our data files because you can go so deep and compare with such nuance that you’re able to tease out the exact right company to partner with. And you can always phone a friend. We often will have Boz Hristov, a member of your team, come in and talk a lot about the companies he covers, or Elitsa, or Kevin, or any one of our analysts to really help those technology partners who want to find the right SI.

Patrick: I’ll add one other thing, because you throw up a bubble chart and it’s hard for us not to keep talking. But if you’ve got the right eyes and you’re not old like me, you can see that this actually says 2Q25. There’s two things that are really important about that as we’re sitting here in the beginning of 4Q. One, this is data that comes from the companies that we then put in our own taxonomy, like I said before, in order to compare apples to apples. So, this data is the most recent data because it’s the most recent data that’s been released that we’ve been able to transform. But really importantly, we do it every single quarter. So, Dan, to your point about how this is used three levels down below the C-suite, it’s because those people every single quarter need to have a reliable, relentless source of data coming to them.

Dan: Yup.

Patrick: So, I think that is super important. And the other thing is, yes, we just published this. The report itself, the benchmark itself, has projections going into this quarter, into next year, into two years, and in some cases into five years. So, we’re not just presenting a backwards-looking view, we’re using the backwards-looking view and the hard data and the hard estimates to go ahead and look at- seeing what’s coming next.

Case study: Staffing and headcount

All right, with that, we got a little bit sidetracked here because I had to talk about that. But now we’re going to talk about another aspect of this, like looking at what we can see from the peers in terms of strengths and weaknesses. So here, this comes from our Global Delivery Benchmark, and the lesson here is- so just by way of explanation, our Global Delivery Benchmark comes out twice a year. It’s all about where the people are. Dan mentioned the country by country look at headcount, that’s exactly where you’ll find this data. But we do it for a smaller subset of companies than the larger IT Services Benchmark, and that’s for a lot of different reasons, but what we’re trying to do is really understand, since services is a people business, you can understand how the business is doing by looking at where the bodies are, how much change is happening in terms of the way that IT services companies staff. And the lesson here on this chart is really clear. When revenue growth disconnects from headcount growth, the labor arbitrage model that is the backbone of outsourcing and IT services broadly is, if it’s not broken, at least it’s under some threat. And I realize that you can see on the far right, things seem to be coming back together. I don’t think we’re predicting that that’s going to last. And so only the deep pocketed and the well-managed and well-led IT services companies will continue to thrive.

So, if you think back to the very first bubble chart that I showed, the average, average growth was 2.5%. And that’s just not sustainable for IT services companies. It’s not sustainable for the industry, period. So, we’re looking to see what will accelerate revenue growth. And what we can see from this chart right here is it’s not going to be from adding bodies. And this is looking at Deloitte from the perspective of their hyperscaler relationships. The number that gets the most amount of attention here, of course, is $2.4 billion with Microsoft, which is a company that Deloitte, in fact, audits. So, we get the question a lot, how is it possible that Deloitte actually does that kind of business with a company that they audit? And if you’re familiar with why that’s complicated, great. If you don’t, it’s really simple. It goes back to Enron, to be honest, is where it all comes from. The bottom line is this; Deloitte is exceptionally good at managing their partners. They’re exceptionally good at finding ways to go to- sorry, I was going to say go to market, they didn’t go to market with Microsoft. They’re exceptionally good at finding ways to align their sales interests and their hyperscaler sales interests. They’re very good at aligning leadership. They’re very- they’re probably the best at, the most exceptional at ensuring that each partner knows what the other is bringing to the table. So, Microsoft actually pays for training for Deloitte professionals. So, if you’re in the consulting business, the only time you’re making money is when you’re at a client site, but you’re not always at a client site. And for that downtime, you need to find something to do. And Microsoft has stepped up and said, if you have a deloitte.com e-mail address, you can get training from Microsoft. So how do they do $2.4 billion a year and growing in Microsoft related revenue? It’s because they’re partnering in a different way, I would argue, in a much smarter way than many of their peers and the other IT services companies.

But all of that said, look at the other number that’s on there under Microsoft, and that’s 18.8% of Deloitte’s total trailing 12-month cloud revenue. So, despite this $2.4 billion number being as large as it is compared to where you think it should be, which some would say maybe 0, it’s only actually, it’s actually less than 20% of the total cloud revenue that Deloitte is doing. So, this is an example. All of this is a way of me showing that we dive into these numbers. All of this data on here is all proprietary, this is not reported. We have our own taxonomy and we have our own way of coming up with what these numbers mean. And we show these numbers to Microsoft, AWS, Google, and we show these numbers to Deloitte all the time to get that kind of feedback that we’re going in the right direction.

Dan: If I can just piggyback here as we transition to the headcount slide. So, this is a glimpse of our Cloud Hyperscaler Ecosystem report, which is just one ecosystem report among a portfolio that includes coverage of the technology partners in the cloud space, so the big three that you see here. Then we’re looking at the front office solutions, your typical standard Adobes and Salesforces. And we’re looking at the back office, we’re looking at Workday, we’re looking at SAP, ServiceNow, that cohort. In some reports, we’re even looking at Oracle. And we’re really diving into this exact same kind of framework.

Question that’s coming in, I can see this one comes up all the time, is it’s echoing on the methodology question, right? So broadly speaking, this, if you think back to all of those bubble charts that you were showing a moment ago, all of that underlying revenue and headcount data, that same kind of data is being tracked among our hyperscaler and ISV analysts, looking at all of those companies from their point of view. It’s the combination, it’s the, as I like to say, it’s the getting the chocolate on my peanut butter versus peanut butter on your chocolate, plus a bunch of primary research interviews. And the conversations that I’ve had the fortune of sitting in on, whether it’s the boardroom in Toronto of one of the Big Four eight years ago.

Patrick: Eight years ago, yeah.

Dan: To last month in San Francisco. These are the questions that we get asked all the time. How do you get this information? Can I trust this information? And then how often do you publish this data? So, the ecosystem reports are annual reports. The underlying revenue and margin and headcount data is typically coming out quarterly.

What makes partnerships work

Patrick: And I do want to just dive a little bit deeper for a second while we’re on the slide, because I think it’s a really important one. And I’m glad you brought up the SAP Ecosystem report, Oracle, Adobe, Salesforce, Workday, ServiceNow…

Dan: SAP, it’s the big ones.

Patrick: SAP, it’s all the big ones.

Dan: The money makers for the SIs.

Patrick: Right. And the question, Dan, like you said, the question that we get, that we got eight years ago, we’re still answering now is like, what makes these things work? And so, I want to touch on that real quickly here.

When I talked about what Deloitte does with Microsoft and alignment, alignment of sales organizations, alignment at a leadership level is a given. You’re not going to have a successful alliance relationship and you’re not going to do well unless you have that, so, that’s a given. It’s alignment at the sales level and alignment is never going to be, and I even hate using the word alignment, it’s probably more complimentary because take a McKinsey or a BCG or an EY, they do not have salespeople, but Microsoft does. So, organizationally they’re structured very differently. So, you’re not going to align, but you need to know what each other’s incentives are. You need to understand how each organization is set up. You also need knowledge management. I got to this with speaking about Deloitte and what they do with Microsoft. Again, you have to make sure that not only do you know what you do, but you know what your partners do, that you can articulate what the value is that your partners bring to the table. And that’s the most important part there. And that’s, do your partners actually sell you? When you are not in the room, is your partner saying, I think you should be going with you. If your partner isn’t advocating for you when you’re not in the room, you don’t have the kind of alliance, the relationship that you need. How do you get there? You got to invest, you got to measure, you got to analyze, you got to repeat, and then sometimes you actually need to stop doing what you’re doing and find another partner. And on that cheerful note, Dan.

Dan: Well, this is, I think this is just a specific example. So, we were working with a client and inside the Insight Center portal, which is our client user interface, we’re launching a data visualization tool. So, clients can actually go in on their own. They can either pull the data file and drop it into Tableau or Excel or whatever they want to use. But in our portal, you can actually dive in. So, this is looking at AWS practices among Infosys, TCS, and Wipro in the Americas and their headcount in the Americas. So, this is available across all of the hyperscaler research. You’re able to look at headcount across all of our ecosystem research. And this is that critical piece that when the technology enabling partners downstream, you know, they don’t want to be considered downstream of the SI, but that’s how the SI views it, right?

And we also look at the ecosystem from the hyperscaler marketplace. We can do a webinar on that next month. It’s a completely different ecosystem and a totally different set of dynamics. But in the SI ecosystem, it’s headcount, it’s people, and where those people are, especially now in this age of data and AI sovereignty, getting this data for Europe is absolutely critical, and we have it.

Patrick: Yeah. And we’re going to, at the very end, we’re going to talk about artificial intelligence, because you could be sitting there thinking like, talking about where the people are doesn’t matter in an agentic AI age. I mean, we’re all going to be replaced by robots, but we’ll get to that at the very end of this. I promise we will talk about agentic AI. We have to.

Case study: Perception of partnership alignment

All right, so this last part here, talking about the staffing, the marketing budgets and all that. What you’re looking at here on the right is a survey from our Voice of the Partner, and that is Voice of the Partner, the annual report. It gets back to what I was saying earlier about how alliances actually work. And maybe I’ll give you a good example of that while we’re in here. And I think Fujitsu is on this chart here. We heard an example once of Fujitsu partnering very closely with ServiceNow at a particular client. And to their credit, both ServiceNow and Fujitsu were very direct about what they were doing and what was working so well. And part of it was that ServiceNow was measuring their success at this client the way they always measure success, which was based on net new contract value. And they were looking at it quarterly. They even admitted at times they were looking at that monthly. How many people are they adding to the ServiceNow platform? How many people are they monetizing? And they were compensating their salespeople 100% based on net-new contract value.

Fujitsu on the other side is looking at the relationship with the client as a whole. What more can we bring this client? How do we retain this client to get back to that idea? They were not looking necessarily year to year, yes, they were looking year to year, but they were definitely 100% not looking at it quarter to quarter or either monthly. So how is it that you can get two sales organizations and two completely different companies aligned and working together and showing the client such a strong partnership, it was because they actually understood where they’re coming from. So, the Fujitsu people understood why the ServiceNow people were looking at quarterly or monthly metrics and the ServiceNow people understood, okay, this is about a relationship for them. So that’s the kind of thing we just wanted to pull out on this particular slide and just understand that that’s how those alliance partnerships can evolve. And having that alignment is just enormously important. Dan.

Dan: The broader picture, though, because it’s the commercial alignment, but then this report on the perception between and among how are the SIs viewing the OEMs, how are the ISVs viewing the SIs, how are the hyperscalers viewing all of- it’s a four-dimensional look from the Big Four partners in that transformation and modernization alliance, what do they need from each other? What do they want from each other? We’re going in and actually asking them what they think of some of these partners. And I’ve been in conversations where the SVP of global alliances saw how well she was doing, and they wanted to push that out to the world because they had tried so hard for so long to change how they were seen, and it was finally showing up. So, having this annualized benchmark on perception between and among peers and partners really does tie back to, how well are we aligned? How do we monetize? How are we commercializing? How are we supporting with engineering talent? All of those questions, this series of questions in this report is 80 pages long, just chock full of all of these benchmark standards and metrics on how they’re partnering.

It really is, for me, it brings it back again to that boardroom in Toronto, because I was always amazed at how partners at these Big Four firms would come to us and say, “well, what do our partners say about us when you guys are talking to them? Because I’m sure you’re talking to them, aren’t you, Patrick?” And vice versa. It really is, they want to work well together. There are many cases fundamentally built differently, but they still have to collaborate, build, and monetize and hopefully retain. I bet the ServiceNow sales guy really would like that contract to get renewed next year too.

Patrick: That’s absolutely true. Yep. And the other thing about this report is that this Voice of the Partner is we complement this survey that you see one of the results up here with in-depth interviews with alliance directors and above at a range of companies in the GSIs and consultancies. So, the Accenture’s and the McKinsey’s of the world and the Infosys’s and the Cognizant’s. And then we talked to alliance directors at hyperscalers and ISVs. And then we talked to alliance directors at OEMs. And I think one thing that we’ve learned in this is that when we have those in-depth conversations, to then be able to go to our clients and say, you know, this is what we heard from an OEM. I’ll take an OEM as a really good example. This is what we heard from an OEM. They’re trying to understand how can we get PwC to sell more boxes. And the answer is you can’t. You can’t get PwC to sell more boxes. But that is the opening for how they actually do build a better alliance relationship. How do they actually find the right people within each organization. So, this research has been enormously fun to do. I do see there’s a question in here that no one was very dissatisfied. Well, I mean, it was a survey, you take what you get. I mean, I imagine everyone has their sort of horror story out there of something that went very, very wrong with a particular partner. That’s how you fail at client retention, is having something go very wrong.

Age of AI and agentic AI: Pricing and staffing changes

All right, one more thing I want to share here before we wrap up. And that is, this is agentic AI, AI in general. We can’t talk about- we can’t talk at all these days without talking about this, in part because of the fundamental change that AI and agentic AI is going to have in the ecosystem that we look at. And again, I’m coming from a very consulting and IT services perspective on this. So, and yes, I’m borrowing this from something that I saw this summer. So, it’s, what is it, imitation is the sincerest form of flattery. This isn’t even imitation, it’s outright theft. Anyway, so, what you see on the left, that is Fifth Avenue, New York City, 1900 Easter Sunday. There are no cars. 13 years later, it’s all cars. Same exact spot, Fifth Avenue, New York City in 1913 Easter Sunday. And that is what AI feels like right now. It’s everywhere. But when you zoom out, and I don’t have the other half to this slide, which is the data on the number of cars sold in the US, but in 1913, it was 1,190. Twenty-seven years later, it was only 23,000. Twenty years after that, by 1950, it hadn’t even doubled by then. And then 30 years after that, it shot from 40,000 to 122,000. So, the adoption curve took a long time for all kinds of reasons that we all can get into in terms of the history. But if you were on Fifth Avenue in 1913 in New York City on Easter Sunday, you would think the world had changed completely. And it had for New York City, but not for the rest of the world certainly, not even for the rest of America. That’s where we are right now with AI. In some places, AI has changed the world, but in most of the rest of the world, we are barely entering the AI era.

We were just out in San Francisco, and every billboard, literally billboard, which kind of stunned me that the physical hard- it cannot be more hard copy than a billboard, was all about AI. Every single billboard was about AI, the Waymo’s were everywhere. There was the sense there that AI had taken over the world, and yet you step out of that bubble and you realize a lot of us are still back in 1900 on Fifth Avenue with the horses and buggies, not the cars.

Dan: It was absolutely shocking. And you step back into the real world or here in the comfy environs of New England, and people are still getting soft-serve ice cream and playing putt-putt golf. They’re tucking their kids in at night, and the robots haven’t quite arrived.

Patrick: Not yet.

Dan: Not yet.

Patrick: They’re very, very, very much coming for all of us. And I think it’s going to mean, we can open it up to some more questions, but I think it’s going to mean for the IT services companies and the consultancies, and their broader ecosystem, there’s, I think, two things, Dan, that I think just to wrap it up from my perspective. As we look ahead for the next five years, let me back up, as we look ahead for the next three years, I think there’s going to be two really profound changes at the IT services companies and the consultancies that will have an impact, an effect on their relationship with the hyperscalers and the ISVs and the OEMs. And that is, first of all, pricing is going to change. We’ve been talking about it since AI, since ChatGPT got popular. AI forces transparency, and transparency means there’s going to be a change in the way that the pricing is done. We’re going to see the traditional times and material model fade, not fade away completely, and we’ve got different bets within this office, you know, what the percentage is going to be over time. But basically the way that IT services and consulting engagements are priced is going to change. That’s number one. And so, all right, and I’ll come back to what that means in a second.

Number two is staffing is going to change. You’re going to have full-time digital employees, digital full-time employees, whatever you want to call them. You’re going to have agentic agents doing a lot of the work of an IT services company, less so a consultancy, so there will be probably fewer people doing more work, or at least fewer people delivering more value to the enterprise customer. So, what does that mean for a hyperscaler or an ISV or an OEM? It means that their go-to-market, their sales alignment, even their leadership alignment, is going to have to recognize that the companies that they’ve been working with, the Accenture’s of the world, are changing and are going to change dramatically over the next three years. So, if they are aligned and understand where they’re going, and they can say strategically, these are the bets that we’re placing, then they’re going to be able to walk side by side with them and continue to grow. If they don’t understand, if an SAP doesn’t understand what’s happening, at an Accenture, at a Deloitte or an EY, if they don’t understand the strategic bets that those companies are making right now, then an SAP is going to be lost. They’re going to miss opportunities. They’re not going to be able to change alongside the IT services companies and the consultancies as they change. That is my soapbox that I just built and I’m very happy to be standing on top of.

Dan:  Well, it reminds me again, to go back to some of the meetings that we’ve had and clients that we’ve been able to serve, as AI came out hard and really began to disrupt the services model, we immediately got questions and it looks like we can get to that question next. The core questions around pricing, if enterprise is now seeing fewer people in the engagement and the bill continues to climb year after year after year, we’ve been able to go out and look at the market and interview ITDMs and ask them, what is the perception of delivery of value? What is it that they’re willing to spend and pay? I mean, these are the core questions that we’ve been able to answer using the research, a lot of which we’ve shown today. And a lot of it is getting commission and going out and doing that kind of work.

Final thoughts

But one of the questions was, how do we see more of this? So, I believe there’s the link in the bottom of the portal here for the webinar. We’re happy to extend trial access to the entire array of data and analysis on our Insight Center portal. So, go ahead and pop in that request through the portal. One of the folks in my sales organization will be happy to reach out and set up a seat or two for your organization.

I think that about sums it up. Patrick, thank you. I appreciate the chance to come in and kind of be the host. It’s a little bit of an inversion for you, but it’s been fun. I love having the chance to chat. Look for us, we’re going to be hitting the road, probably going to London in a little bit, maybe going to Seattle, going down to Texas, we’ve got a trip to Chicago. Where are we not going?

Patrick: I think we need to go back to Toronto because in a lot of ways those meetings eight years ago sort of got the ball rolling on how the ecosystem was changing for all these guys. And most importantly, like they didn’t know, like they didn’t understand. They were sitting there, and by they, I mean the consultancies and the IT services companies, were looking out at their tech partners and saying, we know what they do. Like we see the technology, we can implement the technology, but what are they actually doing? What’s their business model? What’s their strategy? Which ones of these do we bet on?

Dan: Well, thank you, Patrick. This has been fun.

Patrick: Awesome.

Dan: So, thanks folks for joining us. Again, this has been Dan Demers on behalf of Patrick Heffernan, we appreciate you spending 45 minutes with us. Look forward to helping you. Feel free to reach out. Have a great day.

Patrick: Next week, I’ll be speaking with Chris Antlitz and Allan Krans for a retrospective on their 2025 predictions.

Don’t forget to send us your key intelligence questions on business strategy, ecosystems, and management consulting through the form in the show notes below. Visit tbri.com to learn how we help tech companies, large and small, answer these questions with the research, data, and analysis that my guests bring to this conversation every week.

Once again, I’m your host, Patrick Heffernan, Principal Analyst at TBR. Thanks for joining us and see you next week.

TBR Talks: Decoding Strategies and Ecosystems of the Globe’s Top Tech Firms

Join TBR Principal Analyst Patrick Heffernan weekly for conversations on disruptions in the broader technology ecosystem and answers to key intelligence questions TBR analysts hear from executives and business unit leaders among top IT professional services firms, IT vendors, and telecom vendors and operators.

“TBR Talks” is available on all major podcast platforms. Subscribe today!

TBR Talks: Decoding Strategies and Ecosystems of the Globe's Top Tech Firms

AI Tools for Knowledge Management, Featuring Kelly See, Knowledge Analyst for BI/CI at Ericsson

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Kelly See, knowledge analyst for BI/CI at Ericsson, joins “TBR Talks” host Patrick Heffernan for a discussion on the state of AI tools for knowledge management inside one of the world’s leading telecom vendors. See also shares how the demands of global knowledge management are being served with artificial intelligence tools across a diverse global workforce.

Episode highlights:

• Measuring knowledge management success

• How changes in technology and AI have evolved the day-to-day role

• Working with internal AI for the best results

Listen and learn with TBR Talks!

Submit your Key Intelligence Questions for Patrick and his guests

Connect with Patrick on LinkedIn

Learn more about TBR at ⁠⁠⁠⁠⁠https://tbri.com/⁠⁠⁠⁠

TBR Talks is produced by Technology Business Research, Inc.

Edited by Haley Demers

Music by Burty Sounds via Pixabay

Art by Amanda Hamilton Sy

AI Tools for Knowledge Management, Featuring Kelly See, Knowledge Analyst for BI/CI at Ericsson

TBR Talks Host Patrick Heffernan: Welcome to TBR Talks: Decoding Strategies and Ecosystems of the Globe’s Top Tech Firms, where we talk business model disruption in the broad technology ecosystem, from management consultancies to systems integrators, hyperscalers to independent software vendors, telecom operators to network and infrastructure vendors, and chip manufacturers to value-added resellers. We’ll be answering some of the key intelligence questions we’ve heard from executives and business unit leaders among the leading professional IT services and telecom vendors. 

I’m Patrick Heffernan, Principal Analyst, and today we’ll be talking about adopting AI tools and how non-traditional skills are applied in a corporate setting with Kelly See, Knowledge Analyst for BI/CI at Ericsson. When the Ericsson team released their tool to the full organization, the name was established as “Ask BIC” to keep the team branding consistent, but in this conversation, it was referred to as Erica. Please enjoy my chat with Kelly.

Corporate libraries

Excellent. Kelly, thank you so much for joining the podcast. I really appreciate it. I know when we met in Texas a couple of months ago, it was great to see you in person, and I know I sort of threw this out there as an idea, and I’m so glad you jumped on the opportunity.

Kelly See, Knowledge Analyst for BIC at Ericsson: Thanks for having me. I’m looking forward to our discussion.

Patrick: Yeah, and maybe we could start off with just sort of your roles and responsibilities at Ericsson, maybe how it’s changed and like sort of what is most of your job today and maybe a little bit of, you know, how it’s changed from when you first began at Ericsson.

Kelly: Yeah, so I started at Ericsson almost 20 years ago. We had a library at our North American headquarters in Texas, and I was getting my master’s in library science. So, I was an intern and then got hired to work in the library. And so, we did all the traditional library things. We actually had books that we checked out. We had some digital material, and then we did research. And eventually that library went away and I went to work in the Business Intelligence Center, which is similar in that we do research, and we support people that are trying to find information. But we solely have market research as our purview. So, we put market research into a portal that we have online, which we call BIC, or our Business Intelligence Center. And then I specifically support internal knowledge management. So, we have all the external market research that my colleague Elizabeth Roberts is responsible for. And then I work with internal teams to help get internal sources of intelligence, so reports or presentations or any material that they’re generating in their daily work and getting that into our portal so that when our users go out and search for information, they can find both that external and internal material. 

Patrick: Yeah. So, you said a couple things here that really have sparked a lot of interest for me. First, getting a master’s in library science. You- when you started, when you started your sort of academic pursuit in that, you probably weren’t thinking I’m going to work for a great big telecom company, or was Ericsson a company you had targeted that you wanted to work for? I’m just curious.

Kelly: No, not at all. I figured I would probably either work in a public library or an academic library. And I did not have any previous library experience when I started grad school. And I went to a networking session where they brought in librarians from all different aspects. They had academic and public, and then they had several corporate librarians there. And that’s how I met someone who had worked at Ericsson, and she connected me with Elizabeth, who was working in the library at Ericsson, and that’s how I ended up where I am.

Patrick: That’s fantastic. I mean, so I was with Deloitte for a while doing competitive intelligence and the same kind of experience where I didn’t even know that competitive intelligence within enterprises and companies existed. Sounds like you probably didn’t know that there were such things as, you know, these corporate libraries that you could go join.

Kelly: Yeah, exactly. And the great thing was that the aspect of it that I really loved was doing research. And I got the opportunity to do that in addition to the traditional library things. So, it ended up being a perfect fit. And now so even more with working in BIC, getting to support intelligence research and learn more about business and competitive intelligence has been really good.

Measuring knowledge management success

Patrick: And knowledge management, which we talk to companies across the entire technology spectrum, I mean, so, from IT services and consulting and telecom and cloud and software. One of the consistent, so I’ve been here a dozen years, one of the consistent themes is that knowledge management is really hard, often underfunded, never quite measured well, and always something that people sort of fall back on is, oh, we need to do better at it. So how do you, let’s take a couple of those, like how do you measure your own success when it comes to knowledge management? What’s the way that you say, okay, my mission here at Ericsson has been better served this year because we accomplished this with respect to knowledge management.

Kelly: That’s a really tough one because it is something that everybody knows they need to do and that they need to do better, but it’s a challenge to make the time and to change people’s habits and to get people to share, which can be really challenging. So, one of the ways that we have measured it is just counting the number of things that people are sharing. So, just in a really simple way, how many knowledge assets, we call them, are people sharing into the BIC platform. And then we’ve also worked with teams who have found other ways to share not just knowledge assets, but other types of insights. We also do special pages on our platform for different teams so that they can come into the platform on their own dedicated page that has information that’s specific to their business area or their market area. So the more interaction that we have with teams, the number of teams that we’re supporting, the number of questions or projects that we work on with those teams, those are just kind of the basic ways that we measure it. Also, we work a lot to just make people aware of what we’re doing, not just knowledge management, but also just BIC in general and the market research that’s available to the organization. So we do newsletters, we do training, we participate in team meetings and things. So, we keep track of all of our interactions as well.

Who is a good internal knowledge management client

Patrick: Yeah, and so that, I mean, that’s a- you have to start with, sort of, the most fundamental thing, like what are people actually sharing, that makes sense. And keeping track of that’s got to be a challenge. But we’ve had on the podcast a number of analyst relations professionals. And the question I come back to them a lot is, what does a good internal client look like? Like who do you like to work with within your own company because they understand what you do and what value you bring? How about for knowledge management? What’s a good knowledge management client, internal client? What are they like?

Kelly: Just somebody who is eager to share, I would say is probably the best internal client. Somebody who really gets behind the idea that what we’re doing is benefiting other people in the company, and they’re willing to work with us and help us as well as we help them. So, they become actually our biggest cheerleaders within the organization as well. So, they’re sharing in our portal, and then they go out and tell people, hey, we have this great tool. You should be using this as well.

Patrick: Yeah, that’s something that you share in common with the analyst relations professionals that we talk to, is that when they find somebody who’s an advocate for what they’re doing. It’s sort of- it’s great for you to go out and tell everybody about what you’re doing, but it’s even better when somebody internally is like, hey, this is this incredible resource, go use them. So, yeah. 

Kelly: Exactly.

How changes in technology and AI have evolved the day-to-day role

Patrick: I’m curious, so the other thing I’d love to talk about is sort of how much- so of course, technology has changed everybody’s lives, and especially in the last few years the way AI has sort of upended so much. But I’m curious, when you think back to what’s happened over the last five years, has it been that AI and technology has sort of changed your day-to-day work so much that it’s very different, or has it just accelerated what you typically did and just made it easier?

Kelly: I would say it’s accelerated it and made it easier. We’re still working to incorporate a lot of that AI into the work that we do. We have tried to be very careful about the way that we do that because we want to make sure that the AI is helping and not providing the wrong answers or bad sources of information. That’s something that we find to be really important, obviously, in intelligence work is that we want to make sure that we’re providing right answers, the best answers, accurate information. So, we have wanted to embrace AI, but we’ve taken it really slowly to make sure that the ways that we’re using AI are valuable to us.

Patrick: And you’ve hired an intern named Erica to help you do that, right?

Kelly: We have, exactly, yeah. So, Erica is our newest team member in BIC. She’s our AI research assistant. And we launched a little over a month ago with having that service available in our portal. And we’ve gotten some really good feedback about it, I think people really like it, so.

Patrick: Do you think that Erica is going to be most helpful, because it’s not just use cases, I’m anthropomorphizing the AI, but still, we’re all going to do that, so I might as well do it. So, is she going to be most helpful with competitive intelligence, market intelligence, you know, generating sales enablement kind of stuff? Like where do you see five years from now, you’ll say, okay, Erica’s no longer an intern, she’s a full-time digital employee that is super helpful in what?

Kelly: I think that she is most useful for market intelligence right now. I’m not really sure what to say about where she’s going to go. It’s going to be interesting to see. I think that right now, her strong suit is being able to take all of the information that she has available and kind of synthesize that, speed up the process for our researchers and give an answer that kind of synthesizes all that information. She’s not doing a lot of insight work. The technology behind Erica is that she uses RAG. So, she takes the information that we have, the market research, looks into it and brings back an answer. So, she’s not reading it and necessarily creating insights out of that. She’s just pulling out information that the analyst firms have provided us. So, in that sense, she’s providing insights, but they’re not her insights. So, we’ll see what happens if she learns and is able to create her own insights. That sounds a little scary to me, actually.

Patrick: It does. It does. It sounds a little scary to me as well.

Kelly: Yeah, I think it’s really important that our analysts still do their own reading and their own analysis. So, this tool can speed that up for sure, narrow down where they need to look for the insights that they’re gathering. But I think they still need to focus and make sure that they’re doing their own reading and analysis. I think that’s such a valuable resource that we have are the people inside our organization. And I don’t want AI to be seen as a magic tool that will take the place of all of these important minds that we have.

Patrick: Right.

Kelly: Yeah.

Patrick: Right. Yeah. And it’s, I mean, you need the- you need the trusted opinion, you need the contextual analysis. And if Erica can simply find it faster and bring it to the sort of end user quicker, that’s the skill set.

Kelly: Exactly, yeah.

Working with internal AI for the best results

Patrick: I’m curious, and this is going to get a little bit into the weeds on this, and if it’s too much, let me know. But knowing that Erica’s the set of knowledge that she can tap into, the contents of the large language model or small language model, however you want to phrase it, that she’s tapping into is a diverse set of opinions and analysis from a diverse set of analysts and analyst firms. Is there a way over time, I know you just launched it, so man, this is again, maybe too in the weeds and too early to ask, but is there going to be a way over time for you to say, okay, she typically, she’s relying more on these three or four analysts or these three or four firms and relying less, like sort of tier out and say, these are the top, these are the middle, these are the bottom. And if that happens, would there be a way to sort of say, to evaluate that? Is that good or bad? Is she tending to lean toward a particular set of firms because of X, or is it just, we’ll take whatever she- however she evolves in that way?

Kelly: I think that because we have such a vast variety of content. So not all of the firms that she’s looking at provide information on the same things, that she will continue to look at all of the different resources. I think that is an interesting question to look at to see is she depending too much on one source or another or a topic that maybe two firms cover. So, that would be an interesting thing to track. It’s not something that I’ve actually thought too much about, but I do think that just because we have a variety of information and we have people asking a broad range of questions on different technologies or different trends and things that are happening in the industry, that hopefully that won’t happen, but something to watch for.

Patrick: Absolutely. And maybe we can gather again in six months or so, have Elizabeth on with us and talk about where Erica is now. Has she- she’s no longer an intern, she’s now a full-time digital employee, and these are the things that she’s doing really well.

Kelly: Exactly. And that’s something too that we’ve asked our users to provide feedback for us on the tool, because they’re the ones that can point out to us, is there an error. She doesn’t hallucinate very much. Just, there have been a couple of things where she’ll give an error in her answer, as I think all AI LLMs have been shown to do. And so, we have to make sure that we’re finding out about those errors. And so, we have encouraged our users, hey, if there are errors or there’s an answer that’s not quite right, please share that with us. We want that feedback. Because Elizabeth and I use the system but not in the same way that somebody who’s doing research on a topic that maybe we’re not looking at is.

Patrick: Right. Yeah, it’s fascinating. And I think, from your own sort of career trajectory to go from coming in as a trained librarian to being an expert in how to wrangle knowledge management and make knowledge management an asset for the company to now how to make AI even more of an asset internally, it’s just fascinating.

Kelly: It’s a very interesting change for sure. But I think that the knowledge that I have from library science and that you learn all of the search techniques and Boolean logic and all of that, I think that will translate to prompt engineering and figuring out how do we ask the generative AI systems questions so that we get the best possible responses. And that’s something we’re also focusing on is training our users to ask questions in the best way. Because search is not necessarily a natural skill that everyone has. You know, they are used to going out to Google and just asking a question, but with AI, you have to be very specific. You may have to include dates and sources and things like that. So that’s another, hopefully, skill that I can bring to helping our users get the most out of our new AI assistant.

Patrick: Yeah, that’s, and that reminds me of like when GenAI first, when ChatGPT first like, sort of exploded a year and a half, two years ago now, one of the, sort of the ways I thought about it a lot was that we have an Alexa in our kitchen and there are still times when we ask Alexa a question and we get an answer that makes absolutely no sense at all. It’s like, yeah, there’s still a ways to go here with the AI. There’s still a lot of work to be done. And not just in the AI and the technology itself, but in the human component of asking the right question, understanding how to ask the right question.

Kelly: Exactly. Yeah, there’s challenges on both sides.

Final thoughts 

Patrick: Yeah, well good, as long as there’s challenges on both sides then neither of us are going away. So that’s all a good thing. Kelly, this was fantastic. Thank you so much. And I promise we are going to do this again in six/nine months and talk about everything that you all have learned over the last six/nine months with your new intern.

Kelly: That would be fantastic. Thanks so much for having me.

Patrick: Excellent. Thank you, Kelly. 

Tune in next week for another episode of TBR Talks. Don’t forget to send us your key intelligence questions on business strategy, ecosystems, and management consulting through the form in the show notes below. Visit TBRI.com to learn how we help tech companies large and small answer these questions with the research, data, and analysis my guests bring to this conversation every week. 

Once again, I’m your host, Patrick Heffernan, Principal Analyst at TBR. Thanks for joining us and see you next week.

TBR Talks: Decoding Strategies and Ecosystems of the Globe’s Top Tech Firms

Join TBR Principal Analyst Patrick Heffernan weekly for conversations on disruptions in the broader technology ecosystem and answers to key intelligence questions TBR analysts hear from executives and business unit leaders among top IT professional services firms, IT vendors, and telecom vendors and operators.

“TBR Talks” is available on all major podcast platforms. Subscribe today!

TBR Talks: Decoding Strategies and Ecosystems of the Globe's Top Tech Firms

AI in Strategy and Geopolitics at BCG Henderson Institute

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In this episode of “TBR Talks,” Senior Director David Martinez shares his point of view on key topics covered by his BCG Henderson Institute team, particularly regarding geopolitics and artificial intelligence. The BCG Henderson Institute is an internal think tank at Boston Consulting Group.

David Zuluaga Martínez is a Senior Director at the Geopolitics & Society Lab, based in BCG’s Brooklyn office. Prior to his current role, David was a partner affiliated with BCG’s Public Sector practice. Previously, as an Alum Ambassador at the Tech & Biz Lab (2023-2024), he co-authored research on generative AI and, as an Alum Ambassador at the Strategy Lab (2021), on business resilience amid the COVID-19 pandemic and collective business action to address climate change. Since joining BCG in 2018, David has worked on strategy, operations and technology projects primarily for social impact and public sector organizations.

Episode highlights:

• Designing a research agenda

• The importance of feedback in the research process

• Go-to daily sources

Listen and learn with TBR Talks!

Submit your Key Intelligence Questions for Patrick and his guests

Connect with Patrick on LinkedIn

Learn more about TBR at ⁠⁠⁠⁠⁠https://tbri.com/⁠⁠⁠⁠

TBR Talks is produced by Technology Business Research, Inc.

Edited by Haley Demers

Music by Burty Sounds via Pixabay

Art by Amanda Hamilton Sy

AI in Strategy and Geopolitics at BCG Henderson Institute

TBR Talks Host Patrick Heffernan: Welcome to TBR Talks: Decoding Strategies and Ecosystems of the Globe’s Top Tech Firms, where we talk business model disruption in the broad technology ecosystem, from management consultancies to systems integrators, hyperscalers to independent software vendors, telecom operators to network and infrastructure vendors, and chip manufacturers to value-added resellers. We’ll be answering some of the key intelligence questions we’ve heard from executives and business unit leaders among the leading professional services, IT and telecom vendors.

I’m Patrick Heffernan, Principal Analyst, and today we’ll be talking about artificial intelligence, the research process, and philosophy and consulting with David Martinez, Senior Director at the BCG Henderson Institute’s Geopolitics and Society Lab.

From philosophy to BCG

David, thank you so much for coming on TBR Talks. I really appreciate it, and we’re kicking off season four, this is pretty exciting. We’ve been doing this for a while now. So, we’re so happy to have people from outside of TBR come in and give us their insights. And so, I’d love to, if you could just tell us a little bit about yourself and about what you’re doing right now. We know you’re with BCG and you’re in the think tank part of BCG, which is fascinating to me. But just give us a little bit of your background and what you’re up to right now.

David Martinez, Senior Director at the BCG Henderson Institute’s Geopolitics and Society Lab: Of course, and Patrick, thank you for inviting me to the podcast. Very, very excited to be joining you today for this conversation. So, my background is in philosophy, so I have a bit of a heterodox non-business background in terms of my academic training. I have a PhD in political philosophy and joined BCG as a consultant once I left academia. I was until recently a partner at BCG’s public sector practice, working primarily with state and local clients in the US and have for a couple of years now been in a different role as a senior director at the BCG Henderson Institute. That is, as you mentioned, BCG’s think tank.

It’s a very different job compared to regular consulting work. It is not client facing in the same way. So, we don’t do projects for specific clients, but rather we spend our time thinking about and researching the topics that we think are decisive in shaping long-term strategic outlooks for companies. And in all fairness, for policymakers as well, for leaders in all walks of life. So, we do research on, you know, AI of course, technology, we do research on geopolitics, on, kind of, traditional strategy topics from a business perspective, uncertainty, resilience, optionality. Now we’re doing more work on demographics, for example, and the impact of demographic change in many, especially affluent societies. So, these are all topics that might feel a tad removed from the immediate exigencies of running a business, but precisely because they are slightly removed and nevertheless vital when you take on a sufficiently long-term perspective, someone’s going to think about them. And we think as a company that somebody within BCG has to think about them. That’s the role of the BCG Henderson Institute. That’s what I do specifically in the technology and geopolitics space.

Designing a research agenda

Patrick: That’s really fascinating. And I want to get back to the technology and geopolitics in a second, but one thing that you said at the beginning was how it’s topics and trends and issues that you think are most important. And so, we’re in market research here at TBR, so, we have the things that drive our research and a lot of it is tied to the earnings cycle. So, companies release their earnings, we’re all over it. If you’d like to release your earnings as BCG, I would certainly appreciate it, I know you can’t today, but maybe you will someday.

David: *laughs* Above my pay grade.

Patrick: *laughs* But that’s where we’re getting those- we look at the company’s activities, what they’re doing. And that drives how we think about, and what we go after in terms of our research. So, do you get any feedback from or any insights from companies themselves who are coming to you and saying, hey, can you take a look at this? Or maybe it’s BCG partners that are saying, this topic keeps coming up with my clients, what do you guys know about it? Are there other sources of inspiration for what you want to go after? Or is it more you guys sitting around and thinking about what are the most important topics today?

David: Yes, to all of those.

Patrick: Okay.

David: So we source our topics and frankly the questions, rather, that we want to explore from yes, clients. Yes, also partners, folks at BCG who talk to numerous companies and business leaders and start noticing patterns around, not necessarily what people might be thinking about, but also what perhaps they’re not thinking about, which is just as important, and that I think ties to the third source of guidance, if you will, in designing a research agenda, which I would describe as sort of the intuition around what people aren’t thinking about and either should or will soon have to.

So, the challenge that we’ve set for ourselves is to be simultaneously responsive to the concerns that are already there in the business community amongst business leaders, but also to be able to anticipate some others. And I’ll give you an example. The topic of resilience is now everywhere, right? Everyone thinks about it. Everyone’s very mindful of it, very aware of it. I surely don’t need to mention COVID as a particular catalyst of interest, but we were doing work on that for a few years before COVID happened. Already thinking about, and this is particularly the work, for example, out of our strategy lab, thinking about how environmental systems or ecosystems rather in biology are resilient. What are the structural features of resilient ecosystems and through biological analogies, trying to understand what makes for a resilient enterprise and analyzing the value creation potential. So that’s just an example, but it goes to show that it’s a combination. It’s sourcing what people are already interested in and thinking about and in need of answers to, but also what might lie ahead.

The importance of feedback in the research process

Patrick: Okay. That’s fascinating. And I was going to go to geopolitics, but you’ve sort of teed up another question that I had, and that’s around feedback. So, I’m sure you got feedback from folks within BCG and outside of BCG, BCG’s clients, about the way that you were approaching resilience when it went from something you were thinking about to something that suddenly everybody was thinking about. But within the- and so I think of us, TBR, as an intelligence firm more than anything else, and as intelligence advisors, and part of the intelligence cycle is that feedback. You have to know what people are saying and thinking about the research you put in front of them in order to get better at your research. So has there been, maybe it was with resilience, maybe it’s with something else, where there’s been a sort of piece of feedback that you’ve gotten that has sort of changed the way you think about the way you do your work, or was just so fantastic that you said, hey, I’m the best at this, or made you question whether or not you should be even doing it at all? I mean, have you had that experience where the feedback is sort of that exceptional?

David: Of all sorts. Yes, of all sorts, actually. And it makes for a very fruitful dialectical process. I would add that it’s very important for us to also go beyond the business world in pursuit of that kind of feedback. So, one thing we’ve been doing for a number of years, for example, is this convening we call the Meeting of Minds, where we invite numerous leading scholars, but also senior policy makers and maybe journalists, and also business leaders to talk about a big societal topic. And part of the point or part of the purpose is to ensure we’re not too wedded or too anchored to narratives or concerns that might be idiosyncratic to the business world, and that would benefit from that dialogue and that exchange beyond the business world. So, I would just add that those other layers, those other spaces for conversation, are very important to the work we do as well.

Patrick: That’s phenomenal. So, you’ve got a really sort of structured way to keep yourself grounded so that you’re not wandering off into, you know, woods that don’t matter to people in the business space.

David: Yes. And the way we do this very tactically is when we start pursuing a research project, we always do an academic literature review and also a business thought leadership literature review. We need to know what’s being said, what has been said, what hasn’t, to really understand what are the prevailing narratives or beliefs or conceptions, what are the competing perspectives on a given topic. And I think we also benefit, this is true of consulting generally, but it is particularly true of the research environment at the Henderson Institute. We benefit from the combination of deep expertise and potent analytical abilities of our generalist consultants, who may not be subject matter experts, but precisely because they’re not, they can sometimes help us ask what seem to be the simplest questions. And perhaps at first, they might come across as, you know, silly questions to raise, but they get at fundamental issue. So that combination of deep expertise, business world inside, perspectives from outside the business world, and analytical horsepower that is not sort of encumbered by the baggage that sometimes come along with expertise, the combination of all of those, I think, makes for a very rich research working style for the group.

Patrick: Yeah, that’s fantastic. And the baggage that sometimes comes along with expertise, I think is a beautiful diplomatic way to say what you’re really trying to say is which sometimes people think too much.

Tapping into boots on the ground for geopolitical questions

I want to get to geopolitics, but I want to come at it in an angle, a very specific angle. You, your firm, BCG, has people all over the world. You’ve got incredibly brilliant consultants who are day-to-day working in different countries with different kinds of clients. When it comes to tackling geopolitical issues, how often do you sort of tap into or directly tap into the people that you have, that have their feet on the ground that are living in a particular country and in a particular environment? Let me give you a very specific use case of what I’m thinking about, sort of framing this up. So, if one of your questions or one of the topics you’re looking at is sort of the economic implications of political turmoil in France, you’ve got, I don’t know, 15,000 people or so working in France. You know, you got 15,000 French people that you can directly tap into and say, hey, what’s it feel like right now? What do you think is going on? Do you ever use BCG itself as a source of primary intelligence for geopolitical questions?

David: Absolutely, we’ll be remiss not to. I think part of what we are very mindful of is that the credibility that the Henderson Institute has in offering a perspective is in large measure a function of its proximity to the front lines of business activity and strategic decision making. And that we know through our staff, through our colleagues who are doing work on the ground with clients. So, we do it. I think we have to do it. We always do it. And it helps us sort of navigate sensitive topics also in a way that is very strictly grounded in facts and analysis. Because for any firm, there are questions that are challenging in terms of developing a perspective and putting it out there. Geopolitics, of course, is particularly sensitive in many cases, but what we do is always fact-based and we endeavor to develop points of view that are analytically robust. We can do that because we can rely on the distributed knowledge of BCG as an organization and because we have very clear principles for the kind of quality in the research output that we commit to.

Patrick: That’s fascinating. A lot of your peers do not do that. I’ve spent time speaking with folks that are in a similar position to you and in a similar kind of firm that have that global capability. They have those boots on the ground in many countries, and they don’t really tap into that as well as you guys do. So, it’s fascinating to me.

Research questions we want to answer

I want to ask a little bit about the challenge that we always have when it comes to research, and that’s you sort of, you can’t please everybody. You put out a piece of research and somebody tells you, “you didn’t go deep enough.” And then this, you know, the same piece of research generates the, “you missed the bigger picture here.” So I want you to sort of take, I was literally, I’m not- don’t literally take your headphones off, but take your mind back, just step back for a second and think to yourself, okay, give me six months to just research anything I want to research in the world. What’s that? What’s David’s six months, I’m looking at anything I want to kind of project? What would you go do?

David: Well, I think right now, a very important question in our minds is how the roles of the corporations and governments are changing in the economy and how some of the traditional boundaries of strategy, as in, well, you think about your strategy in a competitive environment is primarily responsive to business factors, how that is changing. Because what is a business factor that you ought to take into account, is actually an expanding set. I think that’s an important, kind of a foundational question for how companies think of a strategy for the foreseeable future, given the current geopolitical trajectory of the world, which I recognize is a hopelessly vague statement, but I think you know what I mean.

AI research questions

Patrick: I understand exactly what you mean. Yeah. And then I will say we can’t have this conversation without talking about AI at some point. So is there an AI sort of trend or issue that you look at and think, okay, if I had, six months is probably too long with AI because it’ll change. But if there’s some, is there a top of mind issue for you right now that’s sort of gnawing at you that you really wish you could spend more time diving into with respect to AI?

David: Yes. And I think I’m not alone in suspecting that one of the big unanswered questions is how should we think about adoption for generative AI technologies in particular? There’s a lot of noise and a lot of uncertainty around this, and it matters because it shapes how we form expectations for, say, productivity effects or cost reduction or revenue enhancing effects for businesses. And at what point should you expect to see some macroeconomic indicators of AI making a difference? All of this has to do fundamentally with the extent of adoption of this technology by businesses on the ground. We know those processes too historically have been slow, much slower than people usually expect. How much faster the process might be with GenAI, which builds, of course, on top of the internet, which makes the distribution of new technologies, new digital technologies much faster. Nobody really knows. But I think the specific question that really fascinates me is how could we better understand the extensive versus the intensive margins of adoption? If you ask companies in binary fashion, do you use GenAI or do you not? You’re going to get the overwhelming majority saying yes. But what does that mean?

Patrick: Right.

David: If you pay for a Copilot subscription that nobody uses, does that count as adoption? Really, in the interesting sense, how do we even get our heads around that intensive margin and its structure, I think is a very, very important and puzzling question that many big economists are thinking about that I am not comfortably qualified to explore, but that I wish I could devote more time to, because I think it’s very important.

Patrick: It’s fascinating. And it’s super important for the companies that we look at, because that adoption and that expansive adoption and deep adoption is what’s going to drive their business. They are dependent on their enterprise customers actually adopting and then using AI. So, the answers that you’ve discovered are going to be important to businesses going forward.

Philosophical technology questions

I do have a question now that you’ve raised in my head that I know that you’re qualified to answer because you’re a philosopher. And the reason I need a philosopher to answer, I’ve never asked a philosopher this question before, but we talk about it all the time. So, we look at at businesses and technology and a sort of saying that we have around here is that the technology always works, the people are always the problem. So, from your perspective, that’s kind of a philosophical thing to say, you know what, it’s the people that are always the problem. When you think about AI and adoption, when you think about the changes that technology is bringing geopolitically, but also then at the enterprise level, are people always going to be the problem? Is this just going to persist?

David: Probably. And I might, I think in the same spirit, I might restate the view a little bit differently. Whether the technology has a problem or not is a function of the interests that human users have. Pieces of technology do not per se themselves carry their purpose with them, as it were. They’re instruments. And that for which they are an instrument is not set by the technology itself. It’s set by the people who use the technology. So, whether the technology fails or doesn’t fail is logically downstream from the interests of human users that that technology is intended to serve. So, I might, if you will, I would put it even further up the intellectual change ahead of the tech.

Patrick: I was putting them side by side, but you’re right. They need to be a little higher up. One more philosophy question, I promise, and then we’ll move on. But I have to know, because you mentioned this in the introduction and explaining your background, and then you said you worked with a lot of public sector, state and local clients. Having been in public sector myself, I was federal government, US federal government, for a long time, and surprising as this may be to some out there, I’ve actually been elected to local town government. So, I’m actually back in government at the very local level. I have never run across a philosopher consultant in my entire time in government. Were you the only one? Are you BCG’s only philosopher consultant?

David: No, no, no, no. There are a few more. And a friend who has since left BCG was actually a theologian. So that might have been even more interesting. It’s funny because I think the place that AI now has in so many conversations has sparked a certain interest in what are one way or another profoundly philosophical questions. So, it’s been a fun time to be a philosopher in consulting, thinking about technology topics, because even when people say, well, I’m only interested in the pragmatic business side of things, you know, have a chat with them. You’re always a few questions away from “are they conscious or not” and stuff like that. So, it’s been fun to be in this type of role with that sort of background. So, not too many of us, but also maybe more than you suspect.

Patrick: So, the WhatsApp group for philosopher consultants is bigger than I thought it might be.

David: *laughs* Yes.

Patrick: Fair enough.

Go-to daily sources

I do want to ask one question that came to mind when I was sort of thinking about this discussion we’re going to have. Because you’re in research and because of your role now with BCG, when I started with Deloitte, one of the pieces of advice I got, and it was in intelligence, and it was, look, you need to know what your boss’s boss’s boss is reading every day. You don’t want to bring to them something they already read in the paper. And so, I think about that all the time. Like for our readers, for the people that are looking at my analysis, I want to make sure I’m bringing them something- I want to know what they get every day. So, in order to do that, I need to ask people all the time, so what do you read every day? So, what are your go-to sources, both for maybe news and sort of current stuff, but then also your maybe longer-term analytical thought pieces, kind of sources, other than, of course, the stuff you and your colleagues are already writing yourselves.

David: Yes, yes, yes. I mean, you make an excellent point. I don’t think the role of a think tank like ours is to be a news aggregator. There are enough good ones out there. I think the role is to help distill the narratives that make sense of the relentless succession of news with which business leaders and leaders in other spaces too are bombarded on a daily basis. So, I think that’s right. It’s very sound advice that you got. And for me, I try to make sure because so much happens every day. I try to make sure that yes, I read the FT and I read the Wall Street Journal and look at the Times. I have a handful of newsletters, some that are more politics oriented, some that are more technology oriented. I try to balance perspectives. So, there are certain temperaments that come with these newsletters and aggregators and kind of light touch commentators. And it’s good to balance them out a little bit and have some optimists, some skeptics on a variety of questions.

But for me, what’s most important is to always make time to read deep research. I have tremendous respect for academics who do very serious, very rigorous, slow work that seldom hits the CEO’s desk but that can be profoundly illuminating. And I think oftentimes the role for think tanks like the Henderson Institute is to help mediate between those two universes. You’ve got lots of noise when all you’re doing is reading the news. You have lots of depth, but a little bit of disconnect from the urgencies of the day when you’re only reading academic literature, someone has to help see how those tie together and what might be the narratives that unify them or the questions that shine a light in both directions. So, it’s very important for me to always make time to read papers. So, I mean, I’ll give you a very concrete example. I read everything David Autor writes. He’s one of the great labor economists at MIT. He’s done amazing stuff on AI. And a lot of my thinking on labor economics of AI has to do with what I’ve learned through his work under long brilliant papers. And so, it’s just important to make sure, as we all know, that there’s time for what’s important, not only what’s urgent, and I think of huge chunks of academic research out there as falling in precisely the category of the important.

The impact of the Henderson Institute’s work

Patrick: I love the way you framed it, because you didn’t say that you read academic papers. You said that you make time for that deep reading. And I think that’s the thing that I think I know I’m guilty of, and I think a lot of us are, is that you just don’t make time for that. I do make time to read the hard copy of the New York Times every day. I think I’m the last print edition subscriber of the New York Times in America, but I do get it on my doorstep every day. So, I know that I have to have it or else my day isn’t complete. I want to bring the conversation back to something that you said at the very, very beginning, which is that you’re not client facing. And yet it seems like throughout this conversation, there have been multiple times when you’ve talked about the way that your research is directly presented to or absorbed by and influenced by BCG’s clients. So, do you think there’s- do you feel like you have a solid measurable, maybe not measurable, but an important impact on the way that your clients actually think about the world?

David: I certainly hope so. *laughs* So, when I say my role is not client facing is perhaps in the insider sense that I’m not part of a project that is executed on behalf of a specific client. Doesn’t mean that I don’t talk to clients, on the contrary, because I’m not in any one project that is committed to a specific client. I get to talk to lots of them at the same time about questions that are of common interest and concern. But yes, the work we do goes straight to clients, just as to your earlier question, clients themselves are a critical north star in designing a research agenda. They’re also, in a certain sense, the terminus ad quem of what we do. The whole point is that we do develop and help shape the way senior executives think about their broader context and their business and the questions and strategy that they’re grappling with, for sure.

Patrick: Fantastic. You are, by the way, the first guest that we’ve had in our four seasons to use the word dialectical and also to drop a Latin phrase into our discussion. So, I didn’t miss it.

David: *laughs* That makes me a professional snob, I suppose.

Patrick: *laughs*

Human skills in the age of AI

All right, so I have one last question before we wrap up. And this has been a fantastic conversation. I really appreciate the time that we’ve spent together. I’ve been thinking about this a lot because AI, when we talk about AI, the first question that comes up outside of the confines of TBR and outside of the confines of the technology space, but when I talk about it with my friends, when I talk about with people outside of this little insulated world, it’s all about what jobs are going to get taken away by AI. And you mentioned the labor economists at MIT and all that. So, I think about how to counter that sort of narrative. And part of it is, well, there are some skills that will never be replaced by AI. So, when you think about that, you think, all right, well, what would be a skill that I would want to master? And maybe it’s playing the bass guitar, maybe it’s speaking 4 languages, maybe it’s the ability to turn yourself invisible. I mean, what is, and if you could think, you know, David, what’s the skill? Give yourself time to master a skill that’s sort of, maybe AI proof is part of it, but more importantly, it’s like something you would really want to have. What’s that skill?

David: This is going to sound very abstract to you, but I think sense-making is something we won’t, for the foreseeable future, be able to or want to delegate. And this relates to your earlier question as well, you know, is it the technology’s fault or is it the human’s fault? And when I was saying that humans set the ends for which they use technologies as instruments. The reason why I think that’s a very important fact to keep in mind is that technology helps us solve problems. It doesn’t actually define the problems. What counts as a problem worth solving is on us. And I don’t mean that as a burden. I mean that as, you know, it’s a wonderful thing and it’s as it should be. And so, when I say sense-making, I mean defining that for which the technology is useful, that for which it is not, that for we want to use it, that for which we won’t want to use it. Now, there’s a side of the response that, you know, just could turn to, you know, almost cause disease and phenomena of that sort. Whereas, you know, whereby we know that whichever distinctively human skills are not mastered by AI will thereby become more valuable, more economic bottlenecks command a greater share of spend in the economy. That’s all true, but I think the more fundamental question is, does it make sense to think of AI as a technology that sets its own ends in terms of problems to be solved in the economy? I don’t think so, because I don’t think degrees of autonomy for the execution of tasks really get to the point of saying, well, this is a task worth executing in the first place. I think that will remain strictly and a profoundly important human activity for as long as I can project out my sketchy vision of the future.

Patrick: That’s fantastic. We were just today, I was talking with one of my colleagues about exactly what you just described, which is the way we were coming at it was, why is AI being applied to solve some problems and not other problems? And we thought about many of the use cases that AI is being put to now that are such low stakes. And maybe it’s because they are low stakes that more are being applied there. When there are other use cases that are much more higher stakes that AI seems to be ignoring, or the people who are developing AI solutions seem to be ignoring.

David: Yeah, absolutely. I think that’s right. And add a layer that it’s not just about what’s technologically feasible or possible. I think it’s easy to mistake that which is technologically possible for that which will happen or should happen. And technology may be able to do many things. And for a whole host of reasons in specific contexts, you might decide, again, with good sense, that it shouldn’t be used for that purpose. Right? A piece of technology for example, may not have the requisite type of accountability that a certain type of service ought to have in a certain conception of your value proposition. And so that means that whether a GPT could do what person A or B is doing is kind of not the real question in that kind of case, it’s, well, GPT is not the sort of entity that can be held to account. And that possibility of accountability is essential to the valuable proposition in this instance. And so, the person being there serves a valuable purpose, an important one, independently of whether kind of a neutral description of the task would lend itself to automation. I just think that that sometimes obscures more than it illuminates when you think about the application of technology in real life cases in all sorts of contexts.

Patrick: And as soon as you bring up accountability, accountability by definition includes some sort of legal structure that can hold someone accountable. And right now, you cannot sue a robot. You cannot sue a bot. You need to have a person. So, until that, until we flip that switch, which maybe we- maybe we shouldn’t, you know.

David: *laughs* But it’s not just legal. It’s not just legal, Patrick. Think about just interpersonal dynamics in, I’ll speak, but what I know, the professional services environment. When you’re working with a client, the role of trust, the role of conversation, the importance of being able to persuade someone and being persuaded in turn, these are all, they might seem soft and fluffy components of the value proposition. Sure, that’s because we often don’t have to spell them out because there has been no alternative to the human delivery of, you know, the insight, the strategy and whatnot. But once you have a non-human alternative for the delivery of exactly that content, you start realizing that there were these other features that are just as important to the full package, to the whole value proposition, that are not nearly as easily replaceable, and that’s not a function of technological capabilities. It’s a function of the kind of entity that a piece of technology is, namely, not a human. And that alone becomes significant.

Patrick: Right.

David: So even before you get to the law, it’s already, I think, a very relevant factor in many contexts, certainly in the services space of the economy.

Patrick: 100% agree, and I think part of why we both agree is because we are in the services sector of the economy, so we need that to be true.

David: *laughs*

Patrick: Sometimes what you think is true is what you need to be true, so.

David: Hopefully we’re both true and beneficiaries of the truth, but not because there’s a causal link between those two.

Final thoughts

Patrick: Right, And I’m not going to ask whether or not philosophy is pursuit of the truth, but I will ask you, just last thing, is there anything that you want to let people know they should go check out and read, anything you want to call out, stuff that you published recently? Like where can someone go after they listen to this to get more of your insights?

David: Yes, of course. I mean, anyone who’s interested in the type of work I’ve been describing across a variety of topics, it would be great for you to check out bcghendersoninstitute.com or bcg.com, either of those, and you’ll find lots of the research we produce. A lot of my work over the last few months has been about the geopolitics of technology and AI in particular, and thinking about how AI changes the way we think about power relations in the global stage and what can we expect. And it’s a very, very relevant topic, of course, at the moment, and one where, if anyone cares to share their feedback, I’d very much welcome it.

Patrick: Well, as a former diplomat who now, for some reason, spends all this time talking about technology, I’ll read it and I’ll give you some feedback because believe me, I’ve got thoughts when it comes to geopolitics. I’ve got thoughts.

David: I look forward- I look forward to that, Patrick.

Patrick: David, thank you so much for coming on this podcast. This has absolutely been fantastic, and I really appreciate your time.

David: It’s my pleasure. Thank you for inviting me.

Patrick: Tune in next week for another episode of TBR Talks. 

Don’t forget to send us your key intelligence questions on business strategy, ecosystems, and management consulting through the form in the show notes below. Visit tbri.com to learn how we help tech companies, large and small, answer these questions with the research, data, and analysis my guests bring to this conversation every week. 

Once again, I’m your host, Patrick Heffernan, Principal Analyst at TBR. Thanks for joining us and see you next week.

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TBR Talks: Decoding Strategies and Ecosystems of the Globe's Top Tech Firms

Hitachi Digital Services: IT/OT Convergence Across the Ecosystem

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Principal Analyst Bozhidar Hristov joins “TBR Talks” host Patrick Heffernan for a discussion on Hitachi Digital Services’ view into Industry 5.0. Looking beyond the marketing spin of Industry 5.0, the pair discuss how Hitachi Digital Services leverages its engineering expertise, industrial know-how and IT capabilities to bring solutions to the market with its partners.

“I think just the way that Hitachi framed its value proposition — I think they coined it as Industry 5.0 and it’s IT plus OT plus AI — is a good way to start thinking about bringing the parties together, and obviously, that’s the part of the messaging, part of the marketing approach. I get that part, but kind of peeling back behind what’s actually — what’s the meaning behind the Industry 5.0, what are Hitachi’s capabilities — it’s really falling back on its legacy expertise and really being part of that engineering cycle,” said Hristov.

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Edited by Haley Demers

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Art by Amanda Hamilton Sy

Hitachi Digital Services: IT/OT Convergence Across the Ecosystem

TBR Talks Host Patrick Heffernan: Hi everyone, I’m Patrick Heffernan from Technology Business Research and I’m here with my colleague Boz Hristov for this very special, quick episode because we recently spent time with Hitachi Digital Services, a company that we don’t traditionally cover and we haven’t spent a lot of time with, but we were both intrigued by everything that we heard over a couple of days out in Dallas, I had to remember where we were Boz, Dallas. And so, we’re going to publish a special report on the event, what we call at TBR an Event Perspective, but I wanted to think ahead a little bit to, who ought to be reading this report. Because again, we haven’t spent a lot of time with them, this is new for us and possibly new for our clients and folks who typically read our research. 

So, three things came to mind for me Boz. One, any company that’s working in the IT/OT convergence, any company that’s doing that should be reading this report. Second, the management consultancies that we talk about and talk with very frequently. And then third, the technology partners, particularly the hyperscalers and the ISV’s, again the big global ones that we talk to all the time. So, knowing what you know from the time we spent with Hitachi and thinking about those three different groups, what are some of the reasons why? Let’s start with IT/OT convergence, like, why is that going to be- why is this report going to be helpful for them?

Bozhidar Hristov, TBR Principal Analyst: Yeah, absolutely. I think just the way that Hitachi framed its value proposition, I think they coined it as Industry 5.0 and it’s IT plus OT plus AI, is a good way to start thinking about bringing the parties together and obviously that’s the part of the messaging, part of the marketing approach. I get that part, but kind of peeling back behind what’s actually- what’s the meaning behind the Industry 5.0, what are Hitachi’s capabilities, it’s really falling back on its legacy expertise and really being part of that engineering cycle. Hitachi as a company, as a conglomerate, you know, as a massive conglomerate that has brands in pretty much every facet of the economy, investing in a lot of the physical products and investing understanding into what does it take to be a product engineering company, makes it an easy, you know, easier transition as you’re trying to bring in the OT and speaking the OT language. Now, the IT part becomes, you know, the important element here, as Hitachi Digital Services outside the bigger broader Hitachi has start investing in its IP capabilities and skills training, investing in partner technologies, understanding the implementation side, the services side and so forth, so then obviously comes the AI component that everyone is investing in, and they certainly are not shy of investing as well as having the know how of again the bigger brother Hitachi. So, it’s- I would say the IT/OT is buyer and reader probably OT have more familiarity with Hitachi but bringing the Hitachi Digital Services element to the mix wrapped in AI offerings, you know, certainly will elevate those discussions. So having the DNA, having the background of engineering, knowing the OT side of the house and now bringing in the IT capabilities that they have been expanding and enhancing through experience through the client use cases because it will be of use to understand what else can Hitachi Digital Services do for traditional OT buyer and how they can actually help them to connect better with IT buyers.

Patrick: Yeah, and I I totally agree that the IT plus OT plus AI is just a really smart way to frame what’s happening in the IT/OT conversion space. And then the last thing you said I think is really important when we think about the management consultancies and why should they care? Hitachi Digital Services is not large, so they’re not going to be stealing revenue from anybody, but they are going to win, and they have been winning, consulting engagements with known clients, with existing clients because they’re on the ground, because they have that expertise, because they provide something that a lot of management consultancies can provide, which is the ability to execute, the ability to actually provide the services all the way through, particularly again in the heavy manufacturing or in the spaces where they play, and I guess that’s the other reason why I think it’s important for the management consultancies to consider Hitachi Digital Services because they were very clear that there are certain industries where they have strengths, they have experience, they have the permission to play. And so, for the management consultancies looking to perhaps expand their footprint in automotive, in rail, in transportation, in utilities and energy, in all those areas, they are- they could be a really solid partner for a consultancy to say we can do a lot of this work, but we also can bring in our friends from Hitachi Digital Services.

Boz: Yeah, absolutely. I think- we know some of the major consultancies and IT services peers have already- product engineering has been double bonded to them, looking at the OT as a new buyer persona that can pursue, you know, discussions with certainly many have not shied away. Some of the IT services companies like Accenture and Capgemini and the HCLs of the world certainly have done a little more aggressively, so maybe perceived as more of a competitor to Hitachi in that sense. But then the likes of PwC and Deloitte, they do have, you know, that C-suite relationship that in an attached-with Hitachi can be a little bit more little, with Hitachi Digital Services, can be a bit more partner-like or co-opetitive-like set up than just pure competition.

Patrick: Yeah. And, they speak to the OT buyer in a way that that the management consultancies don’t. So, then the last group is the hyperscalers and the huge ISVs, the Salesforces and ServiceNows of the world and I think there, Hitachi Digital Services is not among the top ten partners for those, you know, for AWS and Microsoft and SAP and the rest. But they’re growing, and they’re growing in a way that I think should be something that those companies keep an eye on and maybe look to say, as we reevaluate our different relationships, as we evaluate our ecosystems, we look to consulting and IT services partners, is this somebody we should be partnering with because of the capabilities they’re bringing, particularly again around IT and the OT buyer and particularly around that convergence, that blending of AI into it. Yes, that they have companies and partners that can do that with them. But this is one that maybe has a unique set of- unique combination of skills and capabilities and current clients, to be honest.

Boz: Yeah, you made an important point. They may not be the number one partner. You may hear a little bit of pushback from Hitachi on that I guess.

Patrick: Maybe.

Boz: But I can put that big Asterix there, that’s in the TBR view of the world. 

Patrick: Yeah. 

Boz: And the way we scale the practices of the large GSIs and looking to the- when we do our data modeling and understanding how- what’s the size of those practices, and how are they changing, but they do have some strong relationships and they’ve been recognized by some of those partners as top partners for a particular domain area and whatnot. But beyond the marketing that Hitachi is looking for why the likes of Amazon or SAP or Oracle should be caring about Hitachi, I mean again they bring in that technology know how, the stack, an understanding of how it all fits together, how it all you know, essentially stitches together. Especially as the worlds, the macro trend, I should say, not the world, but the macro trend in the IT space is moving towards the physical AI.

Patrick: Right.

Boz: So, Hitachi provides a really strong conduit into the physical AI discussion in terms of how they can actually connect, you know, the hyperscalers, they provide the backbone infrastructure, the ISV partners can certainly provide those layers of application modernization and optimization everyone is talking about. But Hitachi actually makes that better connection into that physical AI world that, you know, the OT buyer can actually be able to have a better position with. So, again it’s the physical AI, is kind of the North Star at the moment for most of the vendors that we track, and I think when it comes to the relationship between Hitachi Digital Services and the hyperscalers and ISVs, they can be that accelerating lane essentially, their conduit to get quicker, faster.

Patrick: Right.

Boz: And provide more opportunities to them.

Boz: Oh yeah.

Final thoughts

Patrick: Excellent Boz. Thank you very much, and thanks everybody. I know, a quick sort of quick little in-between seasons episode, but really wanted to get this out there to complement the Special Report we’re putting out. Thank you.

Boz: Thank you.

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