Proving the Business Value of AI With Equiteq

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[00:00:29] [SPEAKER_01] start trusting your agents to make business decisions. But now, back to today's guest. How can you tell whether AI is making services business more valuable or simply making its sales presentation look more convincing? Well, today I'm going to be joined by Robbie Riggs,

[00:00:52] [SPEAKER_01] Global Chief Transformation and Operations Officer and Head of Coverage at Equiteq. And Robbie brings a perspective as someone who has built and sold a consulting firm before moving into investment banking. So today, what I want to discuss is what buyers look for when they're assessing AI capability. Explore why faster delivery doesn't automatically mean lasting value. And what happens to the people

[00:01:20] [SPEAKER_01] whose time technology frees up. And there are quite a few useful lessons here for founders, managers, managers, and indeed anyone being asked to prove that AI is working. And thankfully, the test involves evidence rather than counting how many times AI appears in a slide deck. But enough from me. Let's hear Robbie's perspective right now. Can you tell everyone listening a little about who you are and what you do?

[00:01:49] [SPEAKER_00] Yeah, thanks for having me, Neil. My name is Robbie Riggs. I got my start in my career in consulting. So working with Fortune 500 companies to implement large-scale transformation. And that ultimately led me to start my own company. So I worked with a co-founder. We built a firm from just the two of us to more than 250 people globally. We had offices in the US, in Ecuador. We had people in Brazil and India really learned how to operate, run, and scale a professional services firm globally.

[00:02:20] [SPEAKER_00] And I, at the end of 2024, sold that company called The Bridge to North Highland, a private equity-backed strategic buyer in our space. And that led me to thinking, what do I want to do next? And the opportunity to learn something new, learn a new skill, learn a new industry is what led me to Equitech. So over the last year and change, I've been driving our team here at Equitech. We are a global

[00:02:47] [SPEAKER_00] boutique investment bank. Our focus is on organizations that are transforming the world through technology. So thanks, technology services, specialty consulting, and the like. And my role is to drive the engine of the bank, how we operate day-to-day, and then coming alongside founders as a former founder myself to provide that perspective and really bridge the gap between the bankers and the founders. So something that is a new adventure every day. I have learned a ton

[00:03:15] [SPEAKER_00] in the last year, taking what we learned, helping organizations transform to partner with operators to make sure that they are doing the right things to create value for their organizations.

[00:03:26] [SPEAKER_01] Well, I love what you're doing here. When you said they're transforming the world through tech, that's one of the reasons I was excited to get you on because every week on this podcast, we explore the world of technology. But most importantly, what is AI or how is AI impacting the workplace right now? We see it everywhere on our news feeds, but what does it mean inside an organization? Where does it move the needle? What kind of difference does it make? And of course,

[00:03:50] [SPEAKER_01] if we zoom into your area of expertise, AI is rapidly changing how consulting and services firms deliver their work. But what are you seeing here? What is actually changing in transactions today? And what is still being overstated or possibly guilty of slightly being hyped?

[00:04:09] [SPEAKER_00] You know, it's so interesting because we internally within the bank, we're doing everything we can to leverage technology and automation and AI to enable our bankers to be more effective and more efficient. Of course, we're wanting to take advantage of that technology. But we have a very interesting perspective when it comes to the transaction. So let's say, for example, you have Neil Consulting Inc. and you're looking to monetize that asset. You want to partner with a private equity

[00:04:34] [SPEAKER_00] company to take on investment and scale faster in this transaction that's upcoming. What's real is AI is now a standard diligence work stream across every deal. So the private equity company that's buying you is going to dig in and understand, is this real? Is it slideware? Is this methodology? Or is it completely dispersed throughout the organization that everyone is using? So that's real. It's also real

[00:05:02] [SPEAKER_00] that our delivery on what I would call narrow, more repeatable work is absolutely faster. So we can be more effective. Those two things are absolutely real. What's overstated is the idea of like AI native. The reality is there are very few AI native, AI first firms. Most of it is hype. And the idea that AI is being delivered at scale already ubiquitously is completely overhyped. I have some bias here that

[00:05:30] [SPEAKER_00] at this state, I spent the first part of my career, as I alluded to, implementing technology in Fortune 500 companies. And the pace at which new technology is adopted is incredibly slow. Inertia is a powerful headwind. So we're seeing that that is a bit overstated. But the reality is buyers right now are having this, they're walking on this tightrope. They're looking at AI as a genuine tailwind that's a

[00:05:57] [SPEAKER_00] driver upside and risk. It could deprecate the company that they're acquiring. So it is a fun time to be doing transactions in technology services. Love that. And when you see buyers assessing a

[00:06:12] [SPEAKER_01] services company, how are they distinguishing between that genuine AI capability, the measurable value, et cetera, from another polished sales story or shiny demo at a tech conference?

[00:06:23] [SPEAKER_00] It's such a good question. So it shows in the numbers, not in the deck, right? So any banker worth his or her salt is going to have AI all over what we call the confidential information on random, the SIM. It's going to be all over. It's going to be AI this, AI that on every page. But this shows up in the numbers, revenue per head, margin, speed of delivery. And then going deeper, it's going to show up in the actual statements of work with clients. Are we doing general staff log development

[00:06:48] [SPEAKER_00] work? Or are we delivering agentic AI? Are we building agents? Are we building automated workflows? So that's where we're going to see where it's real. Internally for the firm, when they're looking at is the firm AI enabled, the test is always very simple, in my opinion. If we removed AI, do the economics break, right? If yes, if all of a sudden our economics get turned upside down, we yank AI out, then it's real. If it has no impact, then it's a story. And I think that's really

[00:07:18] [SPEAKER_00] the two key areas that people are looking.

[00:07:21] [SPEAKER_01] And I think over the years, we've all started to think that larger enterprises often get caught up in red tape and old processes, et cetera, may move much slower than the younger, smaller companies that can be so much more agile and move so much quicker. But when you throw AI into the mix, do you think AI makes scale less valuable if smaller firms can deliver work with fewer people? Or does it strengthen the advantage held by larger firms with data distribution and customer access?

[00:07:51] [SPEAKER_01] How do you see that age-old balance going there when you throw AI into the mix?

[00:07:56] [SPEAKER_00] Well, you're going to love my answer here, Neil, because the answer is yes. It's both. So net, I would say it's the latter. It will favor kind of that larger scale data and distribution. I'll talk more about that in a moment. But in the short term, there's absolutely an impact and a real lift to the smaller firm because a 20-person firm can deliver like a 50-person firm, right? I can rip through analyses. I can rip through client data. I can rip through slide development so much faster

[00:08:24] [SPEAKER_00] than I could before. So there's obviously a quick lift there where smaller firms can punch up and execute like larger firms. However, in the long term, when we talk about value and value creation, the moat for any professional services firm, any technology services firm has always been about data distribution, client access, the relationships that are formed there. And AI makes that even more powerful because I can train my models on that proprietary data mode, on that

[00:08:53] [SPEAKER_00] proprietary access that I have to clients. So I would say net AI commoditizes the work, but it can't commoditize the relationship for the data.

[00:09:02] [SPEAKER_01] And I think when AI first arrived, or when I say first arrived, obviously this has been going on since the 60s and longer, but when we talk about mainstream AI that we're all talking about that appeared what, three and a half years ago, I think very often we look at that and there's almost like, they call it an AI gold rush, like the California gold rush. People rushing in and everyone was trying to get value out of it, but nobody had ROI. There was that infamous MIT study, I think it was 95%

[00:09:29] [SPEAKER_01] there. We're not showing ROI. So there's a big focus on that now. And the reason I bring this up is how will you say AI affecting the way that investors think about revenue, quality, margins, utilization, and the value of IP and services businesses? What are you seeing here? Because it feels like there's a much bigger focus on ROI now and for good reason too.

[00:09:51] [SPEAKER_00] Yeah, you know, it's a great question. I really think the heart of where investors are trying to parse and create an opinion. And, you know, I have the opportunity in my role at Equitech to engage with sponsors all over the world. And this is really the, I think the key question that everyone's grappling with. Everyone is creating, all the sponsors are creating their own perspective. And so I just parsing out the question, I start with revenue.

[00:10:14] [SPEAKER_00] It used to be, we don't just want StaffOg. StaffOg was devalued versus project-based work because we're creating outcomes, right? We like that. That was more sticky than just you could get replaced with if someone came in and could create the widget cheaper, we're going to go with them. Now it's more about recurring and outcome-based is way, way more valuable than bodies for hours, right? Hours for dollars. That is becoming more and more discounted. And we're looking at the

[00:10:44] [SPEAKER_00] model slightly differently. You know, I've said this in the past and I think it bears repeating. In a previous world, services and software, they were two separate things. They were distinct and the two shall never meet. And in this future world, leveraging AI, I believe we're moving to this new world where it's all solutions. So we have solutions companies. And I, as the buyer, I don't know where you, Neil, start and end, where your agent starts and end, your digital employee, your digital analyst, and where your platform, the software you're employing starts and end. So I'm just paying for

[00:11:14] [SPEAKER_00] an outcome. And buyers are love that because especially in the short to midterm, there's going to be a great arbitrage there when it comes to margin that we're attacking. And so transitioning into margin, there is this AI driven expansion. I leverage AI to drive down my cost of goods, which drives up my profitability. It's truly that simple. And they want to see that being durable over time. If you do it in one quarter, that doesn't mean anything because anybody can cut their

[00:11:41] [SPEAKER_00] way to short-term profitability. I want to see that margin durability over time, because that shows me you're truly leveraging and have adopted AI at scale where you're not laying a bunch of people off. Those people can do more at higher value, which means we're being more effective. Obviously that's connected to utilization, which is the other thing you've asked about, right? Utilization is directly tied to that. And it's going to be interesting over time to see how buyers, investors look at

[00:12:09] [SPEAKER_00] utilization. It used to be if it was under 82%, that was a huge right flag. Now, the way that we leverage AI, are we going to peg utilization at a different number? And I think that's still being worked out amongst sponsors as where they want utilization at billable to employees versus working on internal models that will enable us to do more for our clients. So it's going to be interesting when it comes to utilization. And then IP is the absolute swing factor. I mean, when you have

[00:12:37] [SPEAKER_00] the proprietary data mode that's built, when you have the proprietary deep industry expertise that is in the form of IP, that again, to use that word durable, it's durable over time, that's what's driving premium. So we're really, I would say, still in the early innings of defining what the future state, like what exactly the scorecard is that we're looking for, but we're definitely seeing changes in real time as to what sponsors, investors are looking for.

[00:13:06] [SPEAKER_01] And we're recording this conversation today, just a few months away from 2027. I think when we look back at 2026, it will be remembered for being all about agents and agentic AI and some of the big question marks around identity and putting the correct guardrails in place, et cetera. So which parts of due diligence now require different questions because of AI, particularly around data rights,

[00:13:30] [SPEAKER_01] model dependent security, and especially with customer concentration, and maybe even that role of identity as well and how we define identity. I'd say those first three things you mentioned,

[00:13:41] [SPEAKER_00] models and security, all of those are interconnected, right? I mean, who owns it? Who has access to it? How do we put that strong wall around it? All of those are looking very differently as we do diligence now. I mean, before those were almost, dare I say, check the box activity. Okay. Do we have some security plan on paper? Yep. It's 30 pages. Nobody really looks at it, but it's stored. It has the right logo on it and we move on. Now that stuff really, really matters. And sponsors, investors are

[00:14:09] [SPEAKER_00] digging into that deeper. And there's this whole new, I guess it's not necessarily new, but growing robust AI diligence model that's coming forward where companies are hiring firms to come do AI diligence because the investor doesn't have that capability internally. And it's really on those three things. Now, concentration, client concentration has always been an issue. It's always been a red flag, depending on what investor you're talking to, that most of them have a hard line drawn between 22 and

[00:14:38] [SPEAKER_00] 35%. And they have their own place that they draw that line. Now I think it's only getting sharper. There's a real fear of what happens if our clients, those top clients, can they insource what AI is striving to create commodities? So if now that 30% client concentration, that could get scary fast, leveraging the AI capability. And could it quickly be in-sourced or could I demand a much lower price

[00:15:06] [SPEAKER_00] because I have leverage because I'm a better client? So concentration is sharper now than it's ever been.

[00:15:11] [SPEAKER_01] And if either of us were to take a look on our news feeds and they quickly reveal some firms are using AI to improve delivery. I was speaking with Barracuda last week. They've doubled their cyber security team, for example, while others, they use it mainly to reduce headcount, which I think is incredibly short-sighted. Many have run into problems with the cost of tokens. Some have even found out that the tokens cost even more than having human employees. So how can buyers tell the difference

[00:15:38] [SPEAKER_01] between those durable productivity gains and short-term cost cutting? Yeah, to me, it's simple.

[00:15:45] [SPEAKER_00] Like what was done with the freed up capacity? So if we're leveraging AI and we're seeing gains, we're reporting, hey, we're 30% faster, stronger, better. What are we doing? If we're cost cutting, which means our headcount is down, that's going to drive flat revenue. So at the bottom line, I'm going to say, hey, I'm being more profitable. Look at me. Let me go ahead and pat myself on the back for driving profitability. But we know over time, that's a real issue. Cutting the bench,

[00:16:08] [SPEAKER_00] to make quarter profitability targets or to make my quarter look better, I'm destroying my next one, three, five years of talent that needs to be developed internally. So to me, it's that simple. How are you redeploying your talent? And if you're cutting your way to profitability metrics, you are in the long term going to be a very bad investment or a very bad bet.

[00:16:30] [SPEAKER_01] As someone working in this space, you've probably seen a lot of mistakes and a lot of things done brilliantly as well. But what kind of integration problems have you seen appear after a deal when two companies have very different AI tools, governance rules, data environments and working practices? You must have a few stories there too, right?

[00:16:48] [SPEAKER_00] One or two. One or two, Neil. I would say this. Our biggest challenge we're always going to have in integration is people. So I'm going to put that to the side because that was a challenge. It's still a challenge. I'm going to put that to the side over here and talk about technology. I think the biggest thing is just a nerdy word that we use in our business and that's sprawl. So when you have AI tool sprawl, you have two competing distinct tech stacks sense of ways that we do things and

[00:17:18] [SPEAKER_00] trying to integrate those becomes incredibly challenging. Let's say that one, let's talk to the extremes. One is highly governed, very intentional. And the other is the wild, wild west. We gave everybody Claude. We gave everybody access to Roco. We gave everybody access to, you know, we opened up Copilot and it's just all over the place. Trying to then maintain, the reason we bought this asset is they had tightly governed, they had a data mode that was proprietary, that they're leveraging, their models are trained on it. When we try to integrate those two,

[00:17:45] [SPEAKER_00] it's a disaster. And, you know, this new modern version of tech debt, you know, in the past, we always thought tech debt is, well, we haven't upgraded our, you know, mainframe systems or on a previous version of some cloud environment. Now you have these modern tools that are creating immense tech debt overnight because integrating that is really, really challenging. I mean, just the way in which we work, what are the ways that you and I work every day? Do we

[00:18:11] [SPEAKER_00] have something that we've integrated and redesigned our workflows, leveraging and integrated technology, or if we just bolt something on that kind of sits next to us and we swivel chair to leverage tech to make just one aspect of it, but it's not integrated. I mean, all of those are a real problem. And what we're seeing is investors, when they, especially in bolt-on environments where they're wanting to buy a company to bolster an existing asset, we find that they buy for that

[00:18:37] [SPEAKER_00] AI capability, but the integration can drastically drag the value of that investment. So doing that AI diligence, understanding what the plan is ahead of time, having members of your organization that are specifically tied to, and they're comped on the value of getting that integration right and driving the value that was in the thesis that we presented at the investment committee, that's incredibly important, more so than it's ever been with the understanding that it's always been important because the people integration is really hard.

[00:19:06] [SPEAKER_01] It really is. And I always try and give people listening a valuable takeaway. So for people listening, what should founders or leadership teams, what should they be doing right now if they want their businesses to be attractive to buyers without building the company around whichever AI claim is fashionable this month?

[00:19:24] [SPEAKER_00] Yeah, I'd say the biggest thing, Neil, is founders have to do their very best to be disciplined and not chase the flavor of the month. Yeah, yeah. You want to have conviction around what you're doing and get the entirety of your team on board with whatever that conviction is to create a durable, fully integrated solution that is truly like

[00:19:50] [SPEAKER_00] proliferates throughout your organization. So when a buyer comes in to do diligence, they say, oh, this isn't a team of four people in a center of excellence doing AI like that, that is very quickly going to get discounted. And the value of the organization is going to go down in the eyes of that buyer. But being really, really intentional about, you know, have a thesis and run after it aggressively really matters and prove that in real metrics, you know, not things that pop in a quarter,

[00:20:18] [SPEAKER_00] but over time, here's what we're doing. That's what we want to see. I would say related to that, you have incredible knowledge in your organization. You know, in the past, it lived on SharePoints in the form of case studies or templates in Excel or PowerPoint, turning that knowledge into IP that then your models are trained on. I mean, that's huge. And that's how you transform methodology into reusable assets that has value. I think that's incredibly, incredibly important. And at the end of

[00:20:48] [SPEAKER_00] the day, you have to ensure that you, the, whatever thesis you're chasing, whatever that North star that you're going after, that it isn't something that's a flavor of the week that an investor in three hours is going to cut through and say, this is all lipstick on a pig. This is all slide wear. None of this is real. So don't chase that short-term pop because it feels good. Or you listen to a podcast or you read

[00:21:13] [SPEAKER_00] a Wall Street Journal article, but think long-term about what, what is my quarter over quarter plan to the, the, when the time I get to the end of the year or the middle of next year, I can show that, that, that, that game that has true staying powder. You know, we talk a lot about the extensibility of tools, their, their ability to flex up and down over time. That's what we're looking for. We're not looking for that short-term game so we can fire three people, so we can have a more profitable

[00:21:37] [SPEAKER_00] quarter so that we can truly take three steps back when it comes to what our firm can do over the next

[00:21:43] [SPEAKER_01] three years. Fantastic advice. And as I said, a few moments ago, we are heading directly into 2027 from all the conversations you're having with customers and clients and everything you're seeing and hearing. What excites you about the future and where we're heading and what you're going to be focusing on? What makes you want to jump out of bed in the morning? Because I can tell you're really passionate about this space. So what excites you at the moment? Well, I'll tell you just the, the,

[00:22:07] [SPEAKER_00] the realization of our thesis, seeing it come true, you know, at the end of 2025, it was the world is ending. All white collar is going away. AI is going to take every job. And by the, by the start of 2027, it's done like we're new world order. And the, the individuals that were writing that very, very smart, learned academics hadn't been in fortune 500 companies implementing these technologies,

[00:22:32] [SPEAKER_00] you know, inside organizations, seeing the, how it's actually being used. And we went from investors going, Oh my word, the sky is falling. We can't make any investments. And Oh, by the way, let's layer in all the geopolitical frustrations and dramas. And it's always like, nobody was spending a dollar white collar was over. So now everyone went, hold on. AI is wind. We can adjust the sales

[00:22:54] [SPEAKER_00] and make this a tailwind. Hold on geopolitical uncertainty and drama is the new world order. So we can still in make investments in this environment and seeing those two things come together. We have seen over the summer and now as we're moving into fall and aggressively into Q4 and into next year, this is a great deal-making environment and entrepreneurs that are bullish and

[00:23:21] [SPEAKER_00] have enough courage to go in and build these companies and embrace AI are going to have incredible outcomes. And investors that are willing to get behind this and see this as a tailwind are going to make incredible gains. This is not a six month wave. This is a 36 to 48 month wave. And I believe that there's incredible wealth that will be generated and created for those that are brave enough to jump into it. So that's what I'm excited about. I'm excited to continue to see that happen.

[00:23:48] [SPEAKER_00] And there's so much energy in the space, which I absolutely feed off of. So I'm really excited to be part of this and to be able to work with founders and investors on a daily basis.

[00:23:59] [SPEAKER_01] And I think that is a beautiful moment to finish on today. And I love that line you use there. AI is wind. We just adjust our sails. And it's so important to think that way. I think mindset is a massive part of the change that we're seeing right now. And for anybody listening just wants to continue this conversation we've had today, maybe explore some of that energy that we're all seeing. Where can they find you and your team online or find out more information about your work and how you can help?

[00:24:25] [SPEAKER_00] Where should they go? Let's take it all the way back to 2002. Go to our website, equitech.com. That's for those of you listening, E-Q-U-I-T-E-Q.com. We joke all the time that every transaction starts and ends with EQ, which is where that comes from in our name. Go find us at equitech.com. If you have a specific question you want to connect, we have a connect form on there, but you can always find me on LinkedIn. Connect with me on LinkedIn, send me a DM, and I'd love to chat.

[00:24:51] [SPEAKER_01] Yeah. Well, although we've talked around technology and AI and the difference it can make today, what I've loved about chatting with you is your passion, your excitement for this space really shines through. And also in the work that you're doing at the heart of what you're doing here, I had a quick look on your website before you joined me, and it's emotional intelligence is at the heart of everything that you do. And I think in a world of AI agents and robots and stuff, it's so refreshing to hear that. So thank you for sharing your story today.

[00:25:18] [SPEAKER_01] Neil, thanks so much for having me. I think Robbie's question about free capacity is one I'd take into any conversation about AI at work. When a team can deliver faster, what does the business actually do with all this time it gets back? The answer could tell you something about its priorities, its people, and the kind of value that it wants to build. I also appreciated the reminder that

[00:25:47] [SPEAKER_01] buying AI capability and putting it to work across a combined business are all different challenges. Data rights, working practices, and tool choices need attention before the deal becomes a celebration. So a big thank you to Robbie for sharing his perspective today. I'll include links to everywhere you can find him and explore everything we talked about in a little bit more detail. But

[00:26:14] [SPEAKER_01] please share your thoughts with me as well. What evidence would convince you that AI is improving a business in a way that truly lasts? Network.com, you'll find all the episodes of AI at work, plus eight different podcasts as well. Whatever niche you're looking for in enterprise technology, we got you covered. But that's it for today. So thanks for listening as always. Bye for now.