Name: The AI-Native Consulting Firm: Rethinking How You Scale Expertise, Prove Value, and Win Work
Uploaded: 2026-09-29T16:30:50.723Z
Duration: 47 min 20 s
Description: The AI-Native Consulting Firm: Rethinking How You Scale Expertise, Prove Value, and Win Work

Transcript for "The AI-Native Consulting Firm: Rethinking How You Scale Expertise, Prove Value, and Win Work": Hello, everyone. Thank you for joining us for today's webinar, the AI native consulting firm, rethinking how you scale expertise, prove value, and win. Today, learn more about how the firms best positioned to compete are the ones rethinking how they build expertise, how they turn client data into an asset, and how they prove that value to clients. I'm Jen Souza from Deltek. And before we get started, here are a few quick housekeeping notes to ensure you have the best experience today. For the best paying experience, please use Google Chrome or Firefox. Audio will stream through your computer, so make sure your volume is turned up. There is no dial in option. If you have a question, type it into the q and a box at any time during the presentation. We'll address as many as possible at the end. Any unanswered questions will be followed up on individually after the webinar. Resources, including today's presentation slides, are available in the document center at the top right hand corner of your screen. That's also where our poll questions will be throughout the event, so make sure to pay attention there. You'll receive an email with the on demand recording within twenty four hours after the webinar ends. And now I have the pleasure of introducing today's speaker, Jason Malicki, principal at Rattleback. Jason, take it away. Alright. Well, hi, everybody. Thank you, Jen, for having me back. Thank you to Deltek for hosting these, over the years. That's that's always great to be with you and be with, all of your all of your customers. And, so I'm just really happy to be here. So thanks for having me. Alright. So consulting is dead. Yeah. It's it's dead. So we can just stand on the show right now. We're we're done. So we'll we'll stop right here, and let's move on with our day. Right? This is what the market has been telling us. Or at least about a year ago, that's what the market was saying. It was saying that it was that AI was the end of consulting in Thailand. The AI boom was leaving consultants behind. It was a existential shift, an existential threat to even the the tier one firms were were were going to fail. Right? This is what we were being told. And that quite frankly, consultancies needed to become software companies if they wanted to survive. So this is twelve months ago, The market narrative was that services in general were gone, that somehow AI was going to miraculously get embedded at the at the enterprise level, instantly, like Thanos snapping his snapping his, his hand. Right? So, yeah, a year ago, we we were we were all done. We were all done. Well, then it kinda changed. Right? About nine months later, it was like, okay. Wait a minute. Consulting's not actually dead. It's just sort of worthless. It's yesterday's news. This is a chart from a 16 z. It's basically comparing the the price to earning ratio of IT services firms, in this case, relative to the broader S and P 500. You can look at see if you look back over the last, whatever it is, eight years. In general, IT services firms have been valued either comparably or more than the broader, S and P 500, the broader, you know, consensus of large companies. By the last nine months, it's kinda done a straight downward arrow. Right? It's kinda collapsed. This is another chart from this is HFS research also looking at IT services and here they're comparing IT services to AI native companies. In this case, AI native companies are the open data eyes and the anthropics and the SpaceX and the Palantir of the world. And traditionally, you know, services firms generally you know, they're they're considered to be worth about, you know, one time revenue. So, for every dollar of revenue that you get, that's the that's the transaction value on the firm. That that's not unusual, but but these AI native companies are are getting 45 times revenue on average. This was a few months ago. So, you know, six, nine months ago, the narrative changed and everyone said, oh, oh, consulting is not actually dead. It's just, it's kinda worthless. It's yesterday's news. AI is the future. Again, Daniel's snap is is is is hand and and all of this will will just kind of come to be. Now here's where we are now. Right? Oh, turns out management consultants are David after all that AI needs help. Oh, and actually, it turns out, consulting is actually growing. So search for consulting is forecasting 6% growth by the end of the year, which by my metric is faster than the broader US gross domestic product. So, actually, it looks like it's a pretty attractive market. So it's still there. So we're not dead. We're not dead, but we need to change. Right? I mean, I think that's the that's something that we all know is that, no. The market overreacted. The device of services is not imminent, but every services firm needs a change, structurally, operationally, strategically, delivery, marketing. I mean, pretty much every part of the firm needs a change in some way, shape, or form to meet this new reality. So we're not the donor bird yet. Right? Okay. So let's jump in here. So this is my agenda for today. You know, consulting isn't dead, but AI is changing a lot of things, and we'll talk about two things in particular. And then we're going to talk about how there are there is a subset of sort of what I'm calling AI native firms that are separating, that are definitely pulling away, that are definitely, pulling themselves out of the gravitational pull from their peers and are outperforming, the the broader market. And we're going to take a look at a little bit about what an AI native firm looks like, and I'll be upfront in saying that I'm sort of using this phrase AI native a little bit loosely, and I'll explain what I mean by that. And then we'll close with my thoughts on the things that I would be doing right now if I were in your shoes, as the managing partner or CEO of a of a consulting firm. So, and I'll have a Q and A. Feel free. If you have questions along the way, feel free to type them in at any time. And if I I've told Jen if something rises up that needs to grab my attention right away midstream, I will definitely do my best to answer it. But otherwise, I'll I'll take the most at the end. So okay. So consulting isn't dead, but AI is changing a couple things. And the first thing that I would posit that it's changing is how clients search for firms. So there's just been a lot of discussion about this. This is actually some research I'm gonna show from a company called Carbon, which is broader than services. This is actually a b to b buyers report they put together that looks at, a survey of about 200 buyers of business to business products and services, and it looks at how they're they're seeking, looking for firms. And the first thing that jumped out to me in this particular study was that, they are clients are twice as likely now to turn to AI assisted search than traditional search or social media. So if they're looking for, a consulting firm, they're looking for someone to render advice or help them solve a sticky, thorny problem, they are more likely to turn to ChatGPT or Claude or Google Gemini than they are to turn to LinkedIn or Google. And not far off from asking from asking a friend. Right? Like that the space between asking a peer and asking chat g p t is shrinking, and I think it's going to keep shrinking. In fact, I think we find a lot of people that are just just turning straight to chat g p t or straight to Claude and asking it for advice the same way they would speak to their friend, under the idea that that the AI is is providing sort of the collective wisdom on the crowd. What are they doing? Well, they're doing exactly what you think they're doing, exactly what you're doing. They're using it to vet service providers. They're using it to figure out how to solve a problem. They're using it to get a hypothesis on the best way to solve it and then usually get to compare the available partners that are out there to help them solve it. You know, early on in this journey with AI, we noticed that in our client base, I'm a marketing consultant. Right? And I noticed in our client base that that inbound traffic was kinda falling off a cliff. So firms were losing search traffic dramatically as a result of AI. And then all of a sudden, there was a bit of a return in not in traffic, but in lead gen. So leads were were disappearing as well, but then leads were coming back. But I would argue that the AI inbound leads look radically different than yesterday's inbound leads, And we'll talk about that more a little bit later. The second thing it's changing is really just how clients think about their relationship with firms. So how they think about what they're getting out of of of hiring you or not getting out of what they're of hiring you. This is some research. Again, this one's from HFS Research. It's specific about consulting and really my takeaway from this is a lot of data on the slide, but is that they're just increasingly seeing consulting as less effective. They're saying you look at everything in purple there, there that's over 50% of clients in a survey over over a thousand executives. This was done with IBM last year, said that their traditional human led consulting, as they're calling it, was either ineffective at meeting their needs or just sort of their neutral. And the main reason they said it's it's less effective than it has been in the past or their perception is that it is, is that it's just too slow and too expensive. It takes too long to get to outcomes and it's too costly to get there. This is also research I've found using from source for consulting. That's the I I call this the it's like a it's a gap. It's a gap between their per clients' perceptions of quality and value. You as consultants and consulting consulting firms are delivering higher quality work now than you were four years ago, but the perception of the impact of that work has gone down. So it's like you're doing better work, but the perception is it has it's of less value. That's the the the the issue here. And this last slide is back from HFS research again, and what this is pointing to is clients increasingly are expecting AI powered consulting is what they're calling. The idea that you as console as consultants in a consulting firm are not just showing up with human expertise, but you're showing up sort of AI enabled. And I think this is a and the expectation is that this is going to grow over the next few years. That's what clients are saying. And I I believe this is a a bit of a change. You know, if I go back twelve, eighteen months and I think about my own conversations with firms, often clients were looking for an AI use policy and what they were they were sort of actually asking us not to use AI in the work we were doing because they didn't trust it, because they were afraid it was hallucinating too much, or they were concerned about data security, data privacy. I think you're seeing a flip in that. I think you're seeing now clients saying, well, not only am I less concerned about data data privacy and hallucination, my expectation is you're using it. And if you're not, I I see that as weakness, and I'm less likely to work with you because I wanna go faster and I wanna deliver better outcomes. So that's what's changing. AI data firms are pulling away. So we're gonna look at some data in here, from multiple sources, but but but we are definitely seeing that that AI adoption, the consulting sector is accelerating, and the firms that are furthest along in their maturity path are, are are growing the fastest. So, Jen, I think we were gonna do a poll here. I was curious or or am I slide ahead? I think I think I think we're gonna pull here. Right? Okay. So there's a polls tab where you can enter an answer to a question. What I'm interesting in in understanding is where you are in your use of AI, And I've got four different options here, so you can answer any one of these and tell us sort of where you fall in this trajectory. And either you're at one end of the spectrum where you're you're costing your teams against any AI use or you feel like you're in the early stages of use. And at the other end of the spectrum would be your we built this firm from the ground up with AI central to our operations. So I'm curious to see where the audience is on this, and then I'm gonna show you the data, that we're getting from a a friend of mine. So this is actually data that we're actually very lucky to have. It's from Tercera, which is a venture capital private equity firm that invests in IT services firms, and this is based on research they did last summer. And this summer, looking at AI maturity and performance of of companies. So we can see that of those folks that took the time to answer, 70 ish percent right now are kinda saying they're leveraging AI across many, but not all teams and functions and sort of a minority of about 32 feel like they're at the front side of adoption or front side of the curve. So, let's look at our research and this is research that, again, this comes from Teixeira and we're really lucky to have this because this isn't even public yet. So this is actually the first time this has been released. It won't release for a few more weeks from Tercera as part of their Tercera authority release which is scheduled for mid October. And, what this is looking at is, again, AI maturity, And this is IT services firms last summer and this summer, and you can see exactly what's at the top of the slide is that there's this kind of growing volume of firms at the front side of this curve. So the collection of firms that were either built from the ground up or have AI fully embedded across all their their teams process systems and IP has basically doubled in the last, twelve months. And what's interesting about this is when we look at the data underlying this is going forward, when I say AI native, what I'm actually talking about is going to be these two clusters of data. So firms that either have AI fully embedded across the firm, that's what they're saying, or they've built it from the ground up with that in mind. That cluster of firms, those two firms, those of you who answered in that in that bucket are likely growing faster than your peers. When we look at the data on revenue growth, that's what we're seeing. We're seeing that the firms that are AI native, that are fully embedded across the organization or built from the ground up are much more likely to be achieving high growth rates, growth rates in excess of 15%. Now again, these are IT services firms. So you might fall into being a maybe you're an operations consultancy or an HR consultancy and that data might look different. But, the the fact of the matter is that there's there's a kind of a clear relationship between everything I just shared with you. Right? That clients expect more from the consulting relationship. They want AI enabled consulting, and the firms that are further along the AI maturity curve appear to be, generating better outcomes. Alright. Okay. What does it even look like? You know? So what we're gonna do here is I'm just going to share some more data, thanks from the folks at Tercera, about what AI native firms look like. And then I'm also going to share a few examples here and there of what I think that actually looks like in practice. It's one thing to say when we research it and we survey it and we ask firms what they're doing, they say this. It's not a thing to actually see that in in practice and in reality. So, first things first, you know, there's this notion about embedding across the entire firm. And one of the questions that Tercera asked, which I think is a really insightful one, is they looked at, the four functional areas of a firm and asked about how how well AI was adopted across those four areas. So there's sort of two questions in one here. There's sort of the the question set one that says, how mature are you at the highest level in your AI use? And then there's how mature are you in each of these four functional areas. And the reality is that across the board, firms that are highly mature in their AI use across at a high level are then more likely to be highly mature in each of these four function areas. So it just kinda reinforces this idea that if you really are mature from a AI adoption perspective, then you're mature across the organization. So what does that look like? This is an example of a firm. This is actually one of Telstra's portfolio companies, by the name of Zenify. So Zenify is a data AI and customer experience consultancy for financial services firms, and And they wrote a really nice public piece about their journey to AI. And so this is a firm that's going through a reinvention, and they and they just flat out said, hey. We we we rebuilt the entire firm from the ground up using AI. And the way they did it was they started out by looking at themselves as client zero and saying, we've heard a lot about this conversation, but the idea that, before we can advise a client on how to get more how to use AI to improve their business, we have to do it all ourselves. And if we haven't done that, then we're, at best incompetent, at worst, the hypocrite. Right? So they started there. And they built an AI digital maturity model that they could deploy with clients and they put themselves through that model. And then in that journey, they identified, I think they said, 16 processes that they could automate using AI and they built agents to automate them. And they built guardrails around those agents, the types of guardrails that a financial services organization would require either in a very practical sense or quite frankly in a in a legal sense, by regulation. And then they built a, a six step pro a six step process for deploying agents for their clients that they can redeploy. So, essentially, they're productizing a piece of the service. Right? The net effect of all this, at least what they shared publicly, was that they've been able to compress the sales cycle. So they're moving new business through the pipeline faster from forty days to fourteen. And that prioritization piece, that six step process also has increased their ability to, generate fixed fee arrangements. So rather than selling time and materials expertise as a service, they're selling a fixed fee productized service engagement, more frequently than they have in the past. So really good example of what it means to, at least in my mind, to embed AI across an entire organization. Okay. I think Jen, do we have a poll here as well? I think we do. Okay. So here, what we're looking at is the primary focus of a firm's AI investments, and there's some interesting data here as well. But there's definitely a relationship between how you think about AI as a leader and, the outcome that you're getting as a business, and your AI maturity model. So, one of the things I've been saying for the better part of a couple couple years since AI showed up is that, I shouldn't say that since it showed up, but but but but since chat gbt burst on the scenes and AI grabbed everybody's attention, was that I felt like the entire business community was focused on how we can be more efficient using AI, how we can save money or do things faster or more efficiently. And my sense was that that was the wrong lens, that we were thinking about this wrong. And the example I've used lately, at least in the marketing arena, is this idea that, you know, if you're using AI to optimize your marketing efforts from the last 10, that's like running downhill with a with a rocket on your back. You're basically, like, just accelerating the race to the bottom when you have to rethink your entire marketing model for this new reality because as we saw earlier, client behaviors are changing. So we can see in this in this take here that the majority of of of us on the call are looking at AI as a tool to drive revenue growth. And, and then after that, it's to to gain efficiencies. Now let's look at what Tercera's data says. And that's very consistent with a broader sample of of people that were surveyed through Tercera's work. But where the separation is is at this bottom, as I just sort of kinda pointed out. The firms that have AI embedded across the organization are more likely to see it as a tool for innovation. So that if they're more likely to see it as a way to do something they've actually never done before, which allows them to solve problems maybe they couldn't solve before, which allows them to maybe grow revenue faster than their peers. So there's definitely a relationship between I'm not gonna explain there's a causation here, but there's a relationship, a correlation between how you as a leader, as a managing partner, think about your AI investments and then how you percolate that down the organization and the outcomes you're getting as a business. There's a there's a relationship there that you need to be very mindful of. I'm gonna point to a couple of examples here of different firms that I've not worked with these firms, so I can't say from the inside out whether or not the things they're claiming publicly are actually real. But these are their public claims, and they're pretty interesting firms that have had some accolades from a couple of different, researchers on on what AI native firms look like. This firm is actually, I think, a really interesting look at rethinking the business models. I said earlier, there's sort of this expectation from clients that we need to think about the consulting model differently, that the whole consulting model needs to change. This is like a firm called Ventura that's doing just that. So what they're doing is they are rather than trying to go into an enterprise client and say, what solved this really tricky problem as a project, they're going to enterprise clients and saying, well, what are, like, the sticky problems that you've just ignored or you've worked around for years or maybe decades? Things that you just to kind of let fester because you didn't really have a solution. And they said, let's create a joint venture around that. So they're creating joint venture operating models, that go after the sticky problem, and then the enterprise gets a piece of the upside of the solution. So the enterprise is essentially partially funding a joint venture in which when the problem is solved, that solution can then turn around and go to market as a separate operating company with its own p and l and its own money to be made. The founder gets access to enterprise grade data that they would have a hard time getting, and then the enterprise itself gets, a piece of the action on the upside. And and and if you go to their site, you can see they've got some proof proof of different things they've done with some pretty high profile companies like Porsche. So it's not like these are flatbed in operations. So it's definitely a real thing. How well it's performing, I I can't say. This is another firm I found that I thought was really interesting in terms of rethinking the business model and what this is. It's a firm called Telon. And what they're recognizing is that driving AI adoption in the in the legal industry isn't a technology problem, it's a it's an adoption problem, which is probably true in most companies in general. And what they're doing is saying, well, it's not about getting four deployed engineers. It's about getting four deployed lawyers. And so they've sort of done what other consulting firms have done through through the years where they're taking lawyers, ex lawyers, and turning them into consultants that are AI enabled AI native lawyers is the phrase they use. They they embed themselves in the organization. They build the agents. They engineer the prompts. They encode the judgment. They do all the things that, folks would do as engineers, but they're doing it as lawyers. Right? Folks that understand the law and understand its practice, and they've got different avenues into relationships from, which is not particularly new or innovative, but just this idea that you can buy your own technology. We can help you activate it. You can buy hire our people as sort of a staffing type model, or you can buy the outcome, which I think is a new thing where there's definitely, more and more firms that are recognizing that clients don't just want to buy time, they want to buy outcomes and then trying to get to a place where they can price around the outcomes, not price around the time. And this firm probably will be doing. So alright. AI native firms create more value and reap the rewards. So what I think is really interesting about this moment in time is that we're seeing real time the idea that, the more value you can rate can you can create for the client, the more rewards are returned to the firm and to the client as well. So, this is, again, looking at some of Tercera's data and what we're seeing is, again, the more mature AI firms are growing revenue per customer, they're growing gross margin, they're growing net profit more than their peers. And it's sort of stands to reason. Right? Like, if we go back to some of the things that we've just looked at in this date in this data historically is that if clients feel like it's only too expensive and too slow, and you can use AI to make it go faster and maybe be more effective or more efficient, that's gonna be more valuable to them. So assuming you can divorce yourself from the time materials pricing model, you can find a different way to price your services either through fixed fee arrangements or outcomes based engagements. You have the chance to drive, you know, more revenue per customer, more revenue per employee. I would argue that one of the key things that needs to change in the sector in this window is going to be focusing less on utilization and more on revenue per employee because that's really what's going to matter. This is actually a partner of ours, a friend of mine. And and the reason I'm sharing this as an example is because I just think it's a really interesting migration up the value chain. So to me, creating more value looks like moving up the value chain. This is a partner I've I've worked with for over fifteen years. We started working with them. It was a web development shop. So when we were building client websites, they would do they would do the back end development work. My team did the front end creative. They did the back end development work. Over time, they recognized that that business was getting commoditized and much easier done through WordPress and other kind of low cost platforms or no code platforms, and they migrated into becoming a content partner. So then all of a sudden, they were more like a content agency, and they were providing, you know, white label content to agency partners. With the AI, you know, with the rise of AI, they recognize that, well, you know, increasingly, a lot of the content work that used to be done by people is being done by AI, and now they've pivoted into, more of an organizational consultant helping, in this case, market agencies, you know, embed AI fully across the organization. So you you think about this, they're just migrating up the value chain. We're going from, you know, a, a line item on a project, a cost line on a project to tackling the most thorny issue that their their clients face. So they're migrating up the value chain using AI across every aspect of the client's business, and they're creating AI enabled products and services. So to me, that's what that looks like. It's this, you know, whether you're you may not be an AI a firm, but you're using this moment to say, well, how do we go up the value chain to solve bigger problems that create more value for the client and in turn can create a higher exchange of value to us. Ultimately, what it comes down to. Okay. So what do we do now? Right? Yeah. So, I mean, where do we go from here? I'm gonna close with just my thoughts of the five or six things that if I were a managing partner of a firm that would be on my mind. And the first thing really is just talk to your people and your clients about how they want it out to change the relationship. I didn't share this data in here, but in our in the the Tercera research, one of the stuff that was interesting in there is and another research that I'm seeing in the marketplace, I'm seeing a gap between what managing partners and CEOs think clients want from AI, what their people think clients want from AI, and what clients actually want from AI within their consulting and advisory relationships. So the first thing I would suggest is to start there and get out of your own office and make sure that the opinions you have about what your clients want from you as a result of AI are in lockstep with what clients really want and what your people are hearing from your clients. And also recognize that there are as you know, I'm not telling you anything you don't know, but there are different levels in the organization. And oftentimes, as the managing partner, you're engaging with the top of your client's organizations and your people are engaging with the middle. And expectations of what the top wants and what the middle wants is radically different. And you may actually need to be doing both, creating value up, at both levels of the organization. So start there. Make sure you really know what your clients want your relationship to look like as a result of AI before you jump in to reinventing yourself. The second thing is just become client zero. I think you go back to that that example I have at the opening of this deck. I think the most important thing, and I've talked about this a lot in our business over the years, is that we should not be going to clients with, a solution to a problem that we've not at least tried to solve on our own. So if we've not seen this work for ourselves, then we don't really have the business trying to get it to work for other clients. And there's obviously some nuance there. I mean, if you're a consultancy and you're serving realtor organizations, you're not a retailer. So you can't necessarily deploy the things you're gonna deploy for your clients in your own organization, but you're gonna deploy things like that, and you can see how they work. Right? So be be client zero whenever you can. Oops. Sorry. I can't express this enough. Get clear on the one business issue you solve. This is a positioning conundrum for to me. But one of the things I've joked about over the years as a marketing adviser to this space is that most firms are a solution looking for a problem. So firms kinda show up as a collection of expertise and they go out into the marketplace looking for clients that need that expertise. It's sort of we have a skill set and we can solve a whole wide variety of problems using that skill set. Who needs them? Who needs that skill set? I think you need to flip that script. We need to focus on what are what is the the what is the real business issue that you solve for clients at a macro level, and what's your point of view on how you solve that? And you've got to get crystal clear on that right now because clients just are not willing to buy expertise the way they used to with the fuzzy idea that that expertise is going to come in and solve a largely undefined problem. They're showing up with a very clear problem statement, a very clear opinion of how that problem should be solved, a very clear reason as to why they think you are one of the solution partners they might wanna work with. And the moment you walk in the door, you gotta show up with the point of view on how to solve. And you better have that figured out. Fourth thing is then use that you know, so when when you're clear on that business issue that you solve, identify all the ways you could use AI to solve that issue better, faster, more effectively, more efficiently, safer, cheaper, all the dimensions that you can apply AI to that problem to solve it better. I've said for years, one of the most important things you can do as a as a firm is fall in love with the problem you solve, not the solutions you have. If you fall in love with the problem, the new ways to solve it are a wonderful gift to you and your clients, and you're leaning into that. But if you fall in love with your solution, then essentially, AI and anything like it is a threat, and you wanna change your lens, your your way of thinking about it. And then ultimately, ensure you have the right AI tools and training to get where you want to go. Now we saw this in that one example, but this is sort of across the board. You see a lot of firms that they're putting AI tools in place, but people don't know what to do with them. Well, they're just toying with them on the edges. So once you're clear on how you want to use AI in your relationships, you're you're clear on the problems you solve, and you have identified different ways to apply AI to solve those problems better, make sure people know how to do it. Make sure they've got the tools they need to do it well and have the training they need to understand what they're doing. And that's a step that just gets passed over literally all the time. And then finally, I would encourage you to actually, Tercera again, and and and there was was kind enough to to to let us, you know, share all this research before you get the first look at it really. They have an AI maturity model. They have an AI maturity assessment you can take that's custom fit for consulting firms. So I would highly recommend if you are kind of questioning where you are on this on this AI maturity landscape, just search for the Tercera advisory AI assessment tool and you'll find it pretty easily. And you can go through it. It's a series of of a few questions and at the end, you'll you'll get a you'll get a gauge on where you are relative to your peers as it relates to your AI maturity. So alright. I hope I didn't go too fast. Thank you for having me, Jen, and thank you to Deltek for hosting these. And I'm gonna flip it back to you to talk a little bit about Deltek and then take us into questions and answer. Great. Thank you so much, Jason. We really appreciate you spending the time with us today, and we'll be right back with some q and a for you. Well, we're we're gonna give everyone a quick minute to locate that q and a window. It's on the top right hand side of your console, the tab that says q and a next to docs. While you find that, I'd like to thank you again, Jason, for that insightful presentation. And if anyone on the line today would like to learn more about how rep Replicon can help you build an AI native consultancy, please select the ready to strategize button on your screen or say yes in the poll question that will pop up as well, Oh, and. At least I I think I lost you, Jen. Oh my god. us know. Oops. Sorry about that. If you if anyone wants to learn more, please select yes in the poll, and we'll be in touch with you soon. Alright, Jason. We had a couple of questions come in from the audience. So I'm going to ask get a go move ahead and start asking you this. Does that work for you? Alright. Now let's do it. Let's see let's see how I do. Alright. So our first one is how does an inbound lead from AI research differentiate from a traditional lead? Yeah. I kind of alluded to this, and I in full disclosure, I asked you to ask me just because I wanted to cover it, but I didn't wanna cover it in the in the in the talk. And so I many of you maybe are in this seat as well, but I'm in the unique seat in that. I am both the marketing adviser and the marketing lead for our clients, and then I'm also the the the first point of contact for anybody wanting to work with our firm. What I see in a lot of firms is that that's not the case. Right? The marketing leaders or the business leaders are not in the day to day of the sales interactions, and they're just seeing it through either recordings or notes or feedback from sales folks. And what I've noticed is that having done this for over twenty five years is that there is a radically different experience when a lead comes in the door from AI assisted research versus one that came in the door from traditional search five or ten years ago. And the huge difference is the level of due diligence that's being done. So ten years ago, the buyer showed up with massive due diligence. They've read everything that our agency had published. They understood our perspective on virtually everything, and they were coming in the door with this perception of, well, Rollback really knows how to solve this problem, and I really wanna work with them. Today's lead shows up as they maybe did thirty seconds of due diligence. They did some they put some prompts into AI, and AI said, oh, Radovac is how to solve this problem, and here's how they would suggest solving it, and it gets it kinda right. The conversation looks radically different. Right? So there's a a their perspective of you as an advisor and as an expert is radically different than it was a few years ago. And so there's a lot of retooling that needs to happen in the sales cycle to deal with this because your your your sales folks are not used to this type of lead. They're not used to this type of conversation. It's a new one that they haven't seen in a little while, particularly if you bought a big inbound model. So, it's really interesting. So keep on going, which is where there's a bunch here. I'll let you I'll let you choose which ones to go after first. Alright. Can you talk more about focusing less on utilization and putting more focus and emphasis on revenue by employee? Yeah. I think all of this comes down to, value creation and understanding why clients are really hiring you. One of the things that we talk about is value based selling. And the idea here is in early stage of the sale, what you're trying to get underneath is why is the client ultimately hiring you, and what is the value that they're looking to unlock in their organization. And recognize that you as a consultant, whether you're implementing software or you're rendering advice, you're a lever to unlock that value creation. And the more you can do to understand what that value is they're trying to unlock, the more you are able as a consultant or a consulting firm to basically be rewarded for a fair share of that value creation, if that makes any sense. And so your goal, let me is more on how do you cocreate value with clients? How can you help a client maybe create more value than they even recognize is that is there to to be to be found? And when you focus on that, all of a sudden, in your mind, you go, wait a minute. Like, we're measuring our performance based on a flat day rate that we made up and a u l a utilization target that we made up when we need to be thinking about, well, what's the value we're creating for clients, and then how does that translate itself into revenue for us? And when you change that lens, all of a sudden, the things you care about change. And so, and that revenue but for employees, I think, what where that's ending ending up is going to end up ultimately, particularly as you're kind of deploying whatever you wanna call them, digital employees that are AI agents that are supported by humans. I don't know. And all of a sudden, you're you're using things that aren't people, and so they're not they're they're they're they're they're at whatever utilization you want. Right? So hopefully that made sense. Yes. It did. Great job. Another question that just came in is, in regards to your insight about clients' buying outcomes versus buying time. They're seeing increasing talk about consultants overvaluing the personal touch versus client expectations across professional services. Do you have any evidence or insights to share around this? So the question is basically they're over evaluate so so so if I hear it right, the the clients are saying they're they're less concerned about the personal touch than consultants believe they are. Consultants are overemphasizing that personal touch. Correct. Is that. a takeaway? Yep. I don't have any, like, any specific data or insights about that that would change your perception of that. I do think one of the things that I've this is a different topic and a different conversation. One of the things I've I've I've thought about over the years is in a macro sense how business got done. You know, I think about twenty, thirty years ago, a lot of times, consultants and clients built personal relationships. They got to know each other. They served on a board together. They met through a nonprofit. They they maybe met on, like, the old fashioned way of meeting at the golf course. Like, that type of business, that's how business relationships started. So you started with a personal relationship and that led to a business relationship. I feel like in the last five or ten years, it's a 100% flipped. Right? It's it's you start with a business relationship and if that business relationship creates value for both parties, maybe it will become a personal relationship at some point in the future. And so my point in saying that is I think that if you're emphasizing that that kind of trying to build a personal relationship with a client before you've created business value for them, I think that's a very hard thing to do these days. I think it's much easier, quite frankly, to come in the door and prove to a client that there's a very specific problem you wanna solve. I think we can help you solve. We're gonna create value for you. And as a result of that, you sort of become friends. So, I think that that the way we we do the way we sell and win work, has changed over the last thirty years, and that would be my description of that. And so if you're I guess what what I'm trying to say is if you're trying to emphasize that personal touch as a differentiator, I think that's a mistake. I think you want to let that personal relationship unfold as a result of the business value you're creating. I think that's great advice, Jason, and what we're seeing as well. One last question that we have from the audience, and then I think we can wrap for the day. Do you think that AI is making more work as much as it is making work more efficient for organizations that have embraced it? That is definitely an opinion question. Right? You know? And I one to end on. Right? yeah, I I I I go back and forth on this because there are some days where I kinda just scratch my head. I laugh. I'll get, you know, just open my lens of what I do for a living, which is that at the end of the day, I I display two things I do. One is I give consulting firms advice on where to grow and how to grow. And two is we've been their solution partner for the last twenty years. So we've helped them build a point of view on the sticky problems their clients face and turn it into outward facing content. That second piece, AI has do do do them hard. Right? And one of the things that I kinda laugh about at times is is a client will in the past, we would identify a problem we wanna go after together, and we would get people in the room. We get the consultants in the room. We get our team in the room, and we would tackle that problem from multiple directions, positive point of view, build an outline, produce a piece, whether it's an article, whatever it is. Now what happens is a lot of times is a conversation that's had in the virtual hallway somewhere, it's recorded, the recording gets tossed over to us with an AI generated outline, and they want us to produce something out of that. And I kinda laugh because oftentimes, it's like it's less efficient. Like, that this new process feels more efficient because you're using less time of the consultant, let's say, but it's less efficient on the whole because now we're having to debunk all of the noise that AI kinda threw in there that may not be right. It could be a hallucination. Or it could just be I I always talk about, like, a good point of view is a contrarian point of view usually. Right? It's it's it's saying conventional wisdom says this, but the reality isn't over here. And so when you put AI in that process too soon, it actually bleeds you down the path of conventional wisdom and kinda does the exact opposite of what you're trying to do in marketing or thought leadership. So long way to way of answering the question, but I there are times I do think that we are, we're not necessarily getting ourselves more efficient. We're just changing the way work is done and and is the outcome that much better. But that's not across the board though, clearly. I I I saw a piece recently about how the Cleveland Clinic has deployed AI to, identify sepsis, which is a very hard disease to identify by by its surface symptoms for doctors, and they're finding that AI can do it way better than any doctor could before. So you're absolutely unlocking, like, whole levels of value that that they could say thousands of lives, tens of thousands of lives. So there are instances where clearly AI is creating tons of value, but I agree with you. There are times when I'm like, are we getting is this making us better or are we just shifting work from bucket a to bucket b and we're getting nowhere? And so I would I would end with the idea that as consultants, that's actually really where your value comes in. As you've got the domain expertise and the experience working in a sector or working in a functional area to have that levity to tell the client, this is a waste of resources and time. You're trying to, you know, automate something that doesn't need to be automated. We should be putting our energy over here. That makes sense. So That's a great way to end it, Jason. Thank you so much. I wanna thank you again for joining us today, and we hope everybody to see everybody again at another Deltek event. For more information on upcoming webinars and events, please visit deltech.com or complete the brief survey following this session. Thank you again, Jason. Uh-huh. Thanks, Jim. Thanks, everybody. You're welcome. a good day. Have a wonderful day, everyone.