Consulting Uncensored

AI as a Digital Worker: Moving Consulting from Personal Productivity to Organizational Impact with Ray Hsu

• Neal McNamara • Episode 7

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Every CEO is telling their teams to "do something with AI," so most firms hand out ChatGPT licenses, call it transformation, and move on. Then they ask it to forecast demand or reconcile five years of data, get a generic answer, and decide AI "isn't ready."

In this episode, Neal sits down with Ray Hsu, Vice President and General Manager at RapidCanvas, a native-AI company that pairs a secure, agentic platform with human experts in the loop. They explore the gap almost no one in professional services admits: the difference between AI that makes individuals a little faster and AI that changes how an organization actually operates.

They reveal the mindset shift Ray says most companies miss: stop treating AI as a tool, start treating it as a digital worker you hire, train, and trust over time. The conversation also turns to consulting pricing, where AI-driven headcount change will really land, and why leaving an "assistant" behind inside a client can matter more than the project itself.


What You’ll Learn:

  • Personal productivity vs. organizational impact: why most firms never escape the first.
  • What changes when you train AI like a digital worker and not a tool?
  • Why AI cuts offshore roles first, not domestic consulting jobs.
  • Why AI makes "outcome-based" pricing harder to design than it sounds.
  • Why an AI "assistant" left behind keeps you in the building longer.
  • What building real AI differentiation actually takes, and why we chose ‘build’ over ‘buy.’


Ideas Worth Sharing:

  • “Don't use AI as a tool. Treat it as a role or a digital worker in your company.” - Ray Hsu
  • “You have to really think about playing offense with AI. How do you reinvent yourself? How do you reinvent your consulting business?” - Ray Hsu
  • “Everybody's blaming the RIFs on AI, as opposed to they're just not running their businesses as well as they should be… Total lazy excuse.” - Neal McNamara


Resources:


Connect with Neal:

If you lead a consulting, finance, or professional services team and want to stay close to how investors and private equity are really thinking about growth and value creation, connect with Neal on LinkedIn to keep the conversation going and share your perspective.

To learn more about how Virtas Partners helps clients navigate major financial transitions from acquisitions and carve‑outs to IPOs, restructurings, and other complex changes, visit the Virtas Partners website.

SPEAKER_01

I think what most companies fail to realize is that don't use AI as a tool. Treat it as a a role or a digital worker in your company. If you change the mindset and you think about, you know, AI is really, I'll just say talk about large language models, are really mimicking sort of human reasoning. It's a probabilistic model.

SPEAKER_00

Welcome to Consulting Uncensored, the podcast that pulls back the curtain on the good, the bad, and the ugly of the consulting world. This is where real conversations happen about leadership, strategy, culture, and careers in consulting. Hosted by industry veteran Neil McDemari. Each episode features handed discussions with consultants, executives, and firm leaders for building, challenging and reshaping the industry from the inside. No filters, no floppy, just honest insight into what actually works and what needs to be changed. This is Consulting Uncensored. Here's Neil.

SPEAKER_02

Ray, welcome to Consulting Uncensored. As I mentioned, what I like to do in these interviews is instead of me going and trying to introduce you very imperfectly, I will uh give you the mic and uh you know please uh introduce yourself, tell us a bit about Rapid Canvas, and then we'll go from there.

SPEAKER_01

Yeah, thanks for having me, Neil. I am the vice president and general manager at Rapid Canvas. We are a native AI company that is helping companies and businesses really operationalize AI to go from individual productivity to organizational impact. And we do that in in two ways. One is we have an agentic technology platform that's secure, that is scalable, and that can host these these types of solutions. And then what's unique about us, we we also include experts in the loop because we feel like these experts, AI engineers, data scientists, are really key component in terms of allowing these solutions to be successful. And when was Rabbit Canvas founded? Rabbit Canvas was founded in 2022. The founders were formal Booble. They had a successful exit with another AI company that was successfully sold to PayPal. And then they moved to Austin where I was able to connect with them. And I came from a technology background, but I worked a lot in manufacturing, engineering, supply chain, oil and gas, and really helping those industries apply the previous trends, which was Dotwam, mobile, internet thing, and now AI. And so I I was connected with them in in 2023 and really helped to try to build out a practice around supply chain and manufacturing and logistics. Okay.

SPEAKER_02

So you said something in the beginning, which I think is really important because I think this is what is missing in a lot of the AI discussions. Correct me if I'm wrong, I think you said go from was it, you know, personal productivity to only the needle moving, but like organizational impact. Organizational impact. I I use move the needle when I when I'm when I'm talking about this as well, but I think that is really the the crux of where we are right now because I think I I hear every day about the individual productivity side of this. And you know, the all all the plug-ins and and all that that that can that can and are making individuals more efficient at certain at certain things. What I believe is is missing that I'm not seeing it demonstrate in the market outside of what I have been seeing with you guys, which is one of the reasons that I wanted to have you on, that organizational impact is something I'm not hearing many people talk about having you know talk about having seen. Right and demonstrate. Can you talk a little bit more about that? You know, where you're where you're seeing the organizational impact and where do you believe this is gonna go? In the relative near term.

SPEAKER_01

Yeah. Yeah. No, what obviously there's tons of investment from data centers to the hyperscalers, improving AI over time. And it's incredible how far it's come in just a couple of years, right? Yeah. I think we all use it. I think individual productivity, every CEO is asking their teams to to leverage AI. And what I'm seeing is very common is okay, just everybody gets ChatGPT copilot licenses and go be productive. Yeah. And they can be productive. I think what what happens is then you start trying to use it for real types of things like demand forecasting and inventory optimization, or trying to use AI to help plan and and schedule your production demand, or or even going out to get market insights to make better decisions. When you start doing that, then what happens is what the the large language models are getting back to you is fairly generic. And invariably when you will get bad answers, right? You'll just get very peanut butter answers. And there are ways that you can add context, and and some folks have done that to give give it more grounding and and more understanding. But I think what most companies fail to realize is that don't use AI as a tool, treat it as a role or a digital worker in your company. So if you if you change the mindset and you think about, you know, AI is really, I'll just say talk about large language models, are really mimicking sort of human reasoning. It's a probabilistic model. Right? So, and just like a new employee that you hire, they will come with a set of skills and experience that you hire them for, but they'll make mistakes, right? And so what most people do is they use AI for some bigger, more complicated thing to make a mistake, they say, well, it's not ready for my organization. But what they really need to do is treat it as something that you need to train over time and give it more context over time. Just like an employee that's been with you for a year versus some somebody with 20 years and will trust the person with 20 years of experience in your firm more so than somebody who just started, right? And so you have to really flip the mindset. The key is though, how do you train it? Right. In an organizational way. And it's been talked about now. Like I I attended the Gardner Supply Chain Symposium, and it's all about how to create context and how to create grounding, and that understanding that over time AI will understand your specific business and why you do what you do. Some of it's in documents, some of it's in your data and your ERP. Some of this, frankly, is just in people's heads, right? And so, how do you extract that out and and give it that context? So over time, it's giving you answers that you trust more and more. And the trick is how do we do that? There are tools that that you could use to do that, but really what Rapid Canvas, we believe, and I think the industry is starting to see this, is that you need expertise that is working with you, that is underst that understands your business, iterates with AI, and helps fine-tune it over time. And this idea of the enterprise context engine, which will be, I I think, a unique uh intellectual property for every company, where it it's this center of grounding and context about your organization that AI can leverage to help you make better decisions.

SPEAKER_02

You said you need to look at this as well, like as another resource, an employee, effectively. What does that look like? When you're saying, you know, yeah. Again, kind of so alright, if you're if you're pitching to somebody who's like, all right, well, I I don't want this just to be a tool. I want this to be able to do things that an employee does. How does one execute right then?

SPEAKER_01

Well, if you think of it as like most of us will use AI to help us write things and author things. So it I I would treat it not as a tool that does writing, but as an assistant that helps, right? So I think what I'm seeing is like the buzz around AI, get it these big roles, it'll just do things for you. I think that that is a uh grander vision we're not quite ready for. We need to you need to understand where humans are are still in the loop, and then you need to understand what role that AI is playing in that whole, whether it's customer journey or or planning process, right? And a lot of times the role comes down to some kind of assistant, some kind of assistance that's really good at taking all the context, all the data, and you asking it questions and it giving you recommendations and insights that were very difficult to get previously.

unknown

Okay.

SPEAKER_01

So think of it as so a good example is a sales and operational planning where you have to do some demand forecasting as well as some inventory optimization. We typically will look at that as a a planning assistant or planning agent that you can use to it, it can go out and give you what the forecasts are, and it's trained to do that and give you recommendations on what you need to buy from which which suppliers on a monthly basis. Now, it will also know that hey, my recommendations, I have high confidence in these recommendations, I have medium confidence in these, and I have low confidence in these. And so the the goal is to train it so it has higher and higher confidence in most of the recommendations. And so over time, one of our clients would just they started trusting the system. So anything that was high confidence, they would just submit it to the ERP, just go buy it. But it took six to eight months to trust it. And then the medium and low confidence, we would work with them. This is part of our value, is we would work with them and try to see why did it have low confidence and why, or why did it have medium confidence. And sometimes it's it's an outlier, or sometimes, hey, it was actually a some kind of change in the market or some kind of change in the business that we need to teach this assistant to to kind of look for that. And so the the accuracy and the recommendations become better and better over time.

SPEAKER_02

And and and you would probably be good on the in this this podcast is to take some of these terms and expand on them a little bit too, right? So there's a lot of accurate LLM. Yeah, right, right. So that is this an example of an LLM on on that that that's learned along the way.

SPEAKER_01

That's well, so LLM is a large language model. This is the this is kind of the pivotal moment in technology. Me being a software guy and having studied AI back in the 90s, this is like like the theory come to life, right? And but that's that's kind of chat GPT, that's what it all the chat interfaces are built on large language models. Those are the ones where you hear the term hallucination. I asked the question gave me a hallucination. Although like humans hallucinate too. We just say the wrong thing, but we don't call it hallucination. But it's funny because we do leverage large language models, but a lot of times we're just leveraging around AI, there's also something called machine learning, which has been around for a long time, which is looking at historical data and extrapolating patterns or grouping things. So we will we will use both. Okay, and they're both under the AI umbrella. A lot of times we use large language models to kind of match, do fuzzy matching of different things. A lot of examples of what you guys are doing with us.

SPEAKER_02

Yeah, we have used the fuzzy matching. That that term came up on a call today. So yeah, exactly.

SPEAKER_01

It's just better at it. So you there's less work in like the the the being, you know, for the last 10 years we've been talking about digital transformation. Well, that's becoming easier with with large language model. I mean, still still a lot of work, but it becomes easier. And then the other part is to generate narratives about what you're seeing in your business and say, hey, I want to I I have all this data, I want to generate a narrative for my CEO. I want to generate a narrative for my CFO. And that's what like a role in your company would do is like be able to generate something that is that will resonate with the CEO or whoever in your company that that needs to make a decision.

SPEAKER_02

Are there specific industries that you think are either ahead or behind in implementing and leveraging these again kind of the organizational impact?

SPEAKER_01

I mean, I think still you you look at the the fan companies, they've been leveraging AI, not large language models, but for a long time. But part of why they were able to do that, they were able to recruit a lot of the talent to do that were really do that. Right. Yeah. I would say in general, like in mid-market and and also some Fortune 500, I would say like nobody's really, in my assessment, nobody's really that far ahead or that far behind. I think what's happening is with the, you know, with what I've seen that the different now is because of the explosion of AI and the, hey, I've got to, I gotta do something with AI, that's it's a critical part. And it is. It's just like it's like dot-com, but it's moving much faster. I think it's opened up people to have conversations with us because they're either curious about AI or or that their CEO says do something with AI. But the end solutions we do, like step one, may not include any AI. It's just helping automate a spreadsheet or automate some things, and then step two, start implementing more predictive algorithms or more more insights around and leveraging large language models.

SPEAKER_02

So I I will give an anecdote on that, right? You guys are doing work with us. And this is probably the first time in my career that I've seen something where I have almost a hundred percent hit rate and response rate on outreach to contacts, clients, prospective clients on this topic and say, hey, we are doing this. Like we again, we're we're really trying to move towards organizational impact. This is how we we've successfully done this at other middle market companies. This is the the approach we've taken is a little different. Would you like to hear more? And I will tell you, we're at like close to a hundred percent hit rate of one getting a hit rate of just a response to all emails, like just just a response. Yeah, right. But not only are we getting almost a hundred percent response to the outreach, it's almost it's also pretty much a hundred percent, yes, I would like to hear more. I've never seen anything like this. It's the e this has been the easiest time to schedule meetings with clients and prospective clients in my career. Yeah. There's been there's been nothing like this where it was like, what like you said, they're all the these mandates are coming down. You must leverage, you must learn more. And nobody is seeing some anything that's truly like organizational impact. Yeah. Here.

SPEAKER_01

So so you're clearly onto something on taking this approach. Definitely a door opener. I meet a lot of people that just ask, what are you doing with AI? And that that gets the ball rolling. But there's also a lot of fear of AI. You know, I think there's definitely an undertone from the folks that are hearing from their CEOs, they believe that this is a this is about, you know, trying to trim the workforce, right? Which is unfortunate because I, you know, I actually think certainly AI can help you be more efficient, but that's just, you know, efficiency is not not the only play. You have to really think about playing offense with AI. How do you reinvent yourself, right? How do you reinvent your consulting business to think about that?

SPEAKER_02

It certainly doesn't help that all these consulting firms are having all these rifts and they're using AI as a and it's not just consulting firms, but in in our industry. Yeah. Everybody's blaming the rifts on AI. As opposed to they're just not running their businesses as well as they should be. And there are rifts all the time in consulting. And so they're I truly believe, and I you're seeing others talking about this now too. Lazy excuse. Total lazy excuse saying that the the user. Are there some? Maybe, but I don't I don't think it it well, I firmly believe it's not because of the impact of AI on efficiency today, it's uncertainty. And uncertainty causes fear, and you know, it's easier to pull the trigger on executing a rift and you're concerned and not you've got that that uncertainty. And again, blame it, yeah, you know, on the impact of AI and I and the SBS.

SPEAKER_01

It is largely yeah, it's kind of the story, but you know, you hear things like, well, a lot of overhiring are VOVID, and so it's a morbid person. It was a long time ago.

SPEAKER_02

If you have if you overhired five years ago and you're just now fixing it again, I'm called bullshit on that. Yeah, yeah. I'm here I hear the bullshit. You don't you don't wait five years to fix an overhiring. And it's not like, yeah, yeah. Yeah. I think it's just an I think that's just another excuse for we're just not running our business that well, and therefore we have to execute a riff. That's right.

SPEAKER_01

That's right.

SPEAKER_02

Or or how we run our business, part of our again, like how many years do you go without a lot of these firms executing riffs? At some point, you have to look at it as like that's just simply how they run their business. They overhire, they slow, you know, they they at times and when when things don't recover, you know, they again, that's just how they're in their business. Rifts are just simply part, it's not a one-time item, it's not a anomalistic thing. It happened every year or two. It's something LT and I were talking about off-camera, and I'd be interested in your perspective on this, where in when I look at the consulting industry broadly, and I think about that organizational impact when it comes to headcount, I've been saying that I in the near term, I don't believe that this is going to be an organizational impact from an FTE perspective domestically, anytime soon. I believe that the first wave of uh headcount changes in the consulting industry impacted by AI will be offshore. And I guess you can apply this to other uh industries as well, that offshore sort of things, but I I I think that that where we're going to see uh headcount reductions, it's going to be offshore. That's I I I believe in our industry, but there will be things if you would have uh we're doing it now. There are things we would have had an offshore team do in some of these brute force projects that we built some technology to to do some of it for us faster that removed hours that I would have had somebody offshore execute on. And I think that's that the industry broadly, there are things that are sent overseas to offshore teams that will be replaced with the technology.

SPEAKER_01

What do you think? I I think that makes a ton of sense because just like I was saying before, if you look at AI as a role, today it's usually some kind of assistant or some kind of analyst. And those are the types of jobs and roles that that let's say you typically might find cost effectiveness science.

SPEAKER_02

All of our analysts are overseas, actually. We have no analysts with you, best, but we have a different business model.

SPEAKER_01

So so yeah, for sure. I think, like I said, but most of the agents are they play a role of an analyst or an assistant. You rarely find a role that is not the director of engineering agent, right? And we're just not there yet.

SPEAKER_02

Yeah.

SPEAKER_01

Where we might not ever get there. That's the thing.

SPEAKER_02

And then we we were talking about this as well, and I I've had this conversation with others. It is again in really thinking about that organizational impact, what is the organizational impact going to be? And you start thinking about the bottom line. So the impact to the financials of businesses that are reducing heads overseas or you know, offshore with this technology I think again, a very interesting uh thing to track is going to be is that going to be a significant impact to the bottom line? Is the the cost of the technology going to be a lot less than the cost of the labor force that you had over there? Is it gonna be the same? Is it gonna be more? Right. You don't think anybody knows?

SPEAKER_01

No. I I think if you read the news, everyone's trying to figure that out. Yeah. But that is the right place to start, you know, versus thinking about how do I implement AI is really start with your PL. You know, what's gonna move the needle? Where's the value? Like, forget about technology. Like, where is the value here? And then layer in technology like AI to say, okay, I can help move this cost lever, or I can help drive this growth lever. But that's just running a business. Right? Right. What you really want to do is think about what AI is going to empower you to do that you weren't able to do before. Like one-person product teams. Really? You know, and how do you how do you use it to do more and disrupt the market? So going back, you you have to think of this technology as playing offense and not playing defense, which is like getting more divided out and all of that. That's just running the business. And AI will help. But AI is going to the the companies that'll it'll be less of a differentiation over time because everybody will be able to have access to it. Everybody race to the floor, right? But but yeah, the companies that can figure out how to reinvent themselves or create some kind of disruptive model based on AI is going to uh long term gain market share. And we'll see in five years. I think those are the companies that'll uh that'll win.

SPEAKER_02

And where are you seeing any of that now? Or do you think it's too early to really assess where people are really playing offense?

SPEAKER_01

It's still too early, I think. I am trying to think. I do have some companies who are heavily investing in in AI technology with us to help them find new business, new logos, new business that they never have been able to find before. Think of a sales prospecting or BD type agent. And they're really leaning into that. We're helping them train again to give context to their multiple product lines and multiple verticals. So they're not a simple company that's selling, you know, one or two products, but products that go into multiple verticals. So really kind of helping use AI to find not only fit for new customers, but also intent, looking for those signals to say this is the right time to reach out and this is how you should reach out. And they're really leaning into that to create growth and gain market shape. That's okay.

SPEAKER_02

That that's interesting because I wouldn't I wouldn't have thought that sales would be the first place to go to make a meaningful impact in playing offense with that's a that's a trick.

SPEAKER_01

And we do that ourselves. We use the same type of technique ourselves internally. So we don't have a SDR EDR team. Okay. Right? And we leverage this agent to help us. And we train it on our ideal customer profile, look for intent signals, and we continue to modify it, but it it's serving that role for us. Now it's not doing the automatic reach outreach because we actually have found over time like cold outreach not as effective as it was 10 years ago. I think everybody knows that. So but you know, to to to to kind of see where to get insights on timing and fit and how to reach out to the right people, I think that's that's a competitive differentiation, I think.

SPEAKER_02

I don't think that's gonna work in the register, but but you know we're we're in such a heavy relationship-based sales, it's not trigger-based there. So I you know we've been pitched all the different kind of at scale, more cold outrage and whatnot. It's just it just it just doesn't work. I I was actually interviewing a podcast yesterday, uh, we we dug into this quite a bit, where it's just like scaling B D in professional services is really hard. Right. It's really hard. And I don't I don't I I would challenge that that AI will be able to do much do much with us on the sales side. Right. On the sales side. You were talking earlier on where you think our industry consulting is is gonna go with this. What are some of your thoughts on you know, specific to the consulting industry, uh, where do you think there's opportunity to play offense? What what changes would you guess are gonna take place over the next few years?

SPEAKER_01

If I had to if I had to think through this and talking to a variety of people, I think this idea of like a billable hour type of model, climate materials, is going to be less attractive. I think you're gonna look at outcome-based approaches, right? And you're gonna have to demonstrate that human expertise to to look around corners to leverage your experience to give unique value. And I think as consultants, even in the industry, has to have some s some level of AI fluency to carry through some of these, some of these, not just stick with some strategic, but also the execution and the continued execution of their of their books or their finances.

SPEAKER_02

Yeah, I would agree with you. I think that like any new technology, right? There's gonna be a a whole nother layer of services that we as consultants will be able to provide in implementing set of technology. So you definitely have that. And I think there's going to be a lot of consulting around. Oh, we're even seeing it with ourselves. We're getting opportunities to sit down with clients and and walk through and help them fake through where are the opportunities for them, maybe within the office of CFO, maybe broader there. So I think that's right. I also agree that this is gonna drive more and more towards outcome-based results on fees. Uh, but I don't think it's gonna get there immediately. Outcome-based depends how you define it, right? It's like success fees or fees at risk. Super hard to control and design. And there is there is still, I think there is still a simplicity and a comfort with a time materials or a fixed fee type of arrangement. And I I I don't, those aren't gonna go away, but I do think there's going to be what I suspect over the coming years is that you're gonna see a variety of models that all will work in their own in specific scenarios. I think I think there's gonna be there are gonna be specific types of consulting mandates that will still lend themselves to time materials. I think there are gonna be specific consulting mandates that will be very heavily outcome driven. And I think there's gonna be a lot of play in between. And I think that's where we haven't seen a lot of play in between, other than just straight fixed fee stuff, which in our business has really been the result of commoditization of the surface and turning it into a product and and having people just compete on price, which sucks. I think you know it's it's lazy in our industry to get that way, but it happens. So I do think you're gonna have this new place where we're going to have in that the middle, you're going to have non-commoditized solutions and projects that are going to be this you know, they're going to be this blend of kind of time materials and an outcome base, and what's effectively gonna be, okay, we're gonna we're going to accomplish this in X number of weeks, and we're we're gonna charge you this. So you're you've defined you've defined what the outcome is gonna be with kind of like the time and the result, and you're just gonna charge an A fee for it. And the consulting firms are gonna back into that and be like, okay, this is a it's a hybrid of my cost base is kind of like time materials. I've got a you know, I've got a technology cost here, and I'm okay with that, that margin on this engagement. And and we've already thought through that, where I think that we've we've figured out that again, through leveraging some of the tools you guys have built for us, there are examples of these projects where they would have been a brute force four-week, you know, 20 hours a day, multiple people onshore or onshore, just grind through this stuff very manually and very expensively. Right. And it's just a lot of labor. And whereas now leveraging some of the technology that you've built for us, what was four weeks, we could probably do it a little over two. Yeah, right. So you cut down the hours, you cut down the time to solution, and what some firms would could just go and say, oh, well, let's just it's just gonna be half the somebody's gonna come in and do that, and they just need to do half the cost. It's like okay, all we did was, you know, all we did is just reduce hours or reduce value, we'll reduce our own value. So ideally, where where we will probably fall out on an engagement like that is say, all right, well, it it would have been a $400,000 project under a pure time materials or savings through the technology that we've invested in, right? Wasn't free to develop it. If if you if you don't consider the technology cost, just the people cost would make it a $200,000 project. Now, time materials price it as a three fixed fee. Right. You have risk on the time materials because it might not, it might take people a lot longer to do it, but you you're getting some extra margin, which again is it's part of recovery, the cost of already incurred with technology. So I think that that will be that bridge. That next step is I think you're going to migrate on things that you wouldn't necessarily have ever done in a fixed fee manner. Now you're gonna do a lot more fixed fee work for clients as we evolve to figure out how this industry does more outcomes-based pricing because it's not something it's only very narrow niches of consulting have really tied fees directly to outcomes. Outcomes because it's again, there are a lot of really good reasons why, because a lot of times, you know, there's so much of the outcomes that are controlled by the client, not by the consultant. So that's the thing. We we've we've had these conversations on okay, okay, yeah, sure, I'm I'm happy to put fees at risk, but I have to you can't have the ability to just not do something and all of a sudden us not get paid for it because you didn't do it the right way or what we told you to do, or purposefully, and sadly, human nature people will do that purposefully not do what you should just so you don't have to pay us.

SPEAKER_01

So no, if that makes sense. Like I that's pure outcome-based model. Yeah. So I I was actually thinking more like what you're saying, like a fixed fee. But the fixed fee is that she achieves some outcome. Yes. So we're that the customer and you here's like the delay.

SPEAKER_02

It's like, yeah, the rumble of of some sort, you know, the rule, you know, get I think more loosely defined, not like a report necessarily, but it's like we're going to accomplish this in this period of time, and we're gonna caught and we're gonna bill you exactly this for solving this problem for you. Yeah, that's outcome-based, right? Right. I mean, again, we'll use my my favorite example with one of the tools that we built with you is intercompany reconciliation, right? You got five years of intercompany data that that's unreconciled, there's 300,000 transactions, and we're going to fix that in X weeks. It's gonna cost you X. And it's outcome-based. And then, right, what we what we hope that we're able to do is that you go, okay, now that we've solved the history, let us let us modify the the the technology to be something you can leverage going forward to as a tool that you know you take a tool that fixed history, and now you've you now it's an ongoing tool that you can leverage to not let it get out of mouth. Not a tool, Neil. An assistant. Okay, this is good. Reconciliation, a reconciliation assist. I you this is good. If you're gonna modify my vernacular here, I'm gonna have to have to have like a punch list of of vernacular changes now as I'm because I've got a you know, I'm talking to clients every day about this too, but the assistant. Yeah, but because yeah, no, I mean you yeah, that that yeah, that makes sense.

SPEAKER_01

At the first run of the reconciliation, it made a lot of mistakes. Yeah. And so working with your team, we were able to teach it, right? Teach it so that it goes from 80% to 90% to the humans just need to reconcile the last five percent, right? So it's my reconciliation assistant.

SPEAKER_02

Correct. And so you're licensing an assistant, you're not licensing a technology going forward.

SPEAKER_01

Is that yes, is that how we're gonna treat it like somebody you would pay, right?

SPEAKER_02

Like a it doesn't need benefits. That's you know, it's it's interesting though, because because there there are so many analogs to offshoring here, right? Because 15 years ago, right, it was very uncomfortable having this team working, you know, in another part of the world for you. And one of the things that we that I kept saying with my teams, like, listen, this is just this is just an employee that lives somewhere else. Now, granted, it's a complete time zone, yes, a different culture, and yes, they got a funny accent. But really, but it is you've got you've got to change the mindset. This is this is not like just my offshore team, it's my employee that sits over there and is from a different culture, just like you have people in different cultures that live over here with us, and they might work in California versus New York, and that's a time zone difference. But yeah, that took a while for people to get people still don't do it very well, right, right? And I think that that that's interesting though, that if you really if you enter in with that mindset is that this is this is like another resource employee that I'm teaching and working with that I need to learn to work with. I need to teach how to do these things better. And if I continue to work with it, it's gonna become more efficient. I'm gonna become more efficient, we're going to accomplish more. Have I missed it? I I haven't heard anybody describing like that.

SPEAKER_01

They're the folks talking about agents as being employees and how the IT team is the HR of these agents, right? But yeah, I think this idea of hybrid workforce is something that's gonna become a reality the next two, three, four years.

SPEAKER_03

Huh?

SPEAKER_02

So it's my okay, we're deployed assistants. We have new assistants and analysts. It's good. I've got now now I can say I have onshore analysts because I've got uh you know, we're we're using the technology to be my onshore analysts. But yeah, that's okay. I that's that's something I I like that you know what else I like about that is I think that so many people are really well you got you're seeing this like even socially, right? You get a lot of people that are put off and having fear, concern, and whatnot. And part of that is just the unknown, but also not mean maybe technically, I'm not technically claiming to understand how the technology really works, but when you can put it in these terms of framing it with, okay, well, this is again, this is this is something that can learn and you can yeah, you you can treat as as an assistant here. And yeah, that that's uh something you can write, I think it's something you can kind of wrap your head head around operationally, at least. Yeah, and it changes and understand how it actually works in the background. That's fine. You know, understand how a computer works either, but you know, you use it, right?

SPEAKER_01

But so yeah, it changes the mindset for a lot of our clients in terms of now. How do I organize around this this role instead of having the same team that use the uses a tool like a traditional software tool? But now how do I reorganize to make my processes and my my business more efficient? I think just the a slight shift in thinking.

SPEAKER_03

Huh.

SPEAKER_02

All right, so we're building out assistance. So we've got the intercompany reconciliation assistant, we've got the the cash application assistance, quality of earnings, quality of earnings assistant. Well, yeah, that that one's an easier one to wrap your head around on because that that's a little bit more quality of earnings, and it's a little more product, productized, yeah, and commoditized. It's well, it's like joke around, it's the most commoditized thing we do, and it's unfortunate because there's there's more there's a lot more value in it than it's really appreciated, but it's just become a a product and then to you know and race drives the price of said product down and competitions is very difficult to differentiate. So it's like okay, I'll just do it for less money. Yeah, it highly standardized the process and whatnot, so which does allow, you know, with a standardized process does allow for agents to those assistants to be able to build out data books.

SPEAKER_01

Yep. That one should be more common, yeah. But but yeah, the the partnership between us, I think, is I'd be interesting to see how it evolved because I think in the industry it's fairly unique, but it's starting to catch on. Right. I don't know if you yeah, so let's talk about that.

SPEAKER_02

And as it, you know, so I think we clearly did something novel in a couple of years ago at this point, right? And I didn't realize that it was, I didn't know what the rest of the industry was doing. And so just to to go back again, I'll I'll take my as owner mindset of why we did this two years ago or why we started going down this journey. The first was simple, just protectionist. So I was concerned that somebody else would do this and then do the stupid thing, which is oh, okay, I can build agents to do this work faster, and I can just go and undercut Virtus' fees, you know, by half, because I've had an agent that can do it many at half time, and I'm just gonna build, I mean, I'm gonna still say the time materials model, and I'm just gonna undercut, but I'm gonna get all the work and we're gonna, you know, so I was like, okay, I can't let that happen. So you can't get caught out in the market with somebody all of a sudden doing work at you know 40-50 percent of you know for the for the same thing, which we are seeing in other in other things that we do. We are seeing some people really doing that, just doing it for being super low, which again is like okay, but cleaning money as a organization do that. So that was that was the first, like, okay, I've got to do this simply so we don't get caught by somebody else that that is getting ahead of us. And then secondly, so that was like priority one. Secondly, all right acknowledging as well that well, there is opportunity if we can develop some solutions, some assistance that can do things differently than our competition, we could get an advantage it in some manner and subsolution, not you know, not like holistically and and and really going crazy, but just like, all right, well, maybe maybe there's there's something that we do that we can do that we can show true differentiation from competition because we've tech we've got a technology enabled. And oh, by the way, I also know that that advantage will last like six to twelve months because as soon as anybody in your competition figures it out, they're gonna copy it and figure out really fast. That's the other thing is okay. All right, but let's all take the six to 12 month advantage, right? The real panacea for me on on doing this was that if we could do those first two things, but then we could also figure out a way to be a more strategic partner with our clients by leaving the assistant. See, I'm changing my vanactiver, leaving the assistant behind and you know staying in the building, right? Because that's one of that that one of the things that I've always said in this business that a real a real key premise is don't ever leave the building. Like get in with your clients and it's figure out a way to stay, right? And you want to you always want to be there, be relevant to them. It's not like you're always building them, but you want to be you want to be consistent and present so that when something really important happens, that you're the first call or you're just there. They just look at you and go, Oh, hey, can you help with this now? So so that to me was like, okay, that that one I would not have bet that we would be able to. Yeah, we're we're getting there, right? We've we've we have done it. We want to do more, right? So so I I think that's and so while we were doing that the last two years, I wasn't really paying attention to what the compet competition was doing. Because again, you'd have to like to actually kind of try to get under the covers because they're all talking about it. And so I just assumed that we were just at best key deal. And that was okay, right? Because we didn't want to drop millions of dollars of investment on something that we weren't sure how how we leverage it and what the market was gonna do. But what's been really, really crazy is that because of the approach we took by partnering with you guys versus some of our other competitors, they just had in-house technologists try to start doing this themselves. And then some that even didn't even do that. Now they're trying to buy like a rapid canvas or other either. They're they're out trying to to to buy native A AI native companies to do this for them. We're actually ahead. Yeah, which is freaking awesome. And uh it was great because I met with uh Another an investor in our industry, an investor in one of somebody we compete against. And he's like, oh man, no, you guys like you are deploying this. And again, I think it's because we we we've taken a distinct approach at bike-sized chunks, distinct solutions or distinct, I guess I should be certain. Right? We're like, let's just let's build this one thing to do this, do it really well. And it doesn't cost crap tons of money to build it. And it doesn't you don't have to you don't have to sell it for a lot of money, but it's but it's also sold. It's very effective, and it is making an organizational impact for this thing that it needs to do. And and you can do that, you do it fast. I think the fast is really helpful, right? Is that and then we can build, you know, we we keep, I guess you're and try to you can keep usual like assistant analogy. It's like we just keep hiring new assistants. Let's try the pick. So do this, do that. We got this analyst. Do they develop into senior associates over time? I mean, I guess that's the that's kind of the question. Right, yeah. So so I I'm excited that that we've got something differentiated. That is, I mean, that is a rare uh it's it's rare in our industry to have something that is actually truly different versus you're bullshit. Right. And acting like you're different or you're using consulting speak to yeah, to to make it sound like you're different, but it just comes a bit down to yeah, I've got different people that do different things, and my people are really good. And that's true. We have great people, and we have people that can do things, we have some people that can do things better than the competition, but the competition also has people that do things better than us, right? So it's to have something meaningful, it's like, no, no, like nobody has in our company assistant, right, that can be deployed today. Right. Maybe it's three months to do it, but fine. But right now, we've got that. And right now, our the market, going back to my point on every single private equity fund that I reach out to and say we are deploying to deploy these assistants in the market and make the organizational impact, not just driving personal efficiency, but we're actually moving the needle here on either our own engagements or moving the needle directly with outcomes for our clients. They are like, can you talk next week? That's great on this. Here are here are my time slots next week. We're at easily, we're six to ten meetings a week right now, only with private equity funds that want to hear how we're deploying this within organizations. And it's in a bolt, yeah. It's absolutely bold. It's gonna yeah, it's gonna be great to see where that goes, you know, from uh education about what's out there and how we're doing it to hopefully really engaging. We had a discussion today though, again, where the the the fund was very much interested in engaging us to help them and or help their portfolio companies assess where they are on on this journey and identify where those opportunities are and start figuring out where they can make some organizational impact through the leverage, you know, whether it again be a lot of it with us is within the the office of CFO, but it can be broader as well. You're doing things in other issues as well.

SPEAKER_01

No, that's fantastic. And it's and from uh from our perspective, two years ago, we have experts in AI, but we're not experts in you know financial analysis and business strategy and financial use cases. And so I think this kind of partnership really helps amplify the AI technology. And what what I've seen, I don't know if you saw the recent news, like Anthropic, the creators of Claude, are creating a consulting firm in conjunction with BlackRock and uh Goldman. Yeah, open AI is doing the same thing because they realize like go from personal productivity to organizational impact. You need consultants, yeah, who know how to train them train the model to give that contact that we talked about.

SPEAKER_02

Yes, they have a real opportunity. You know, it's fine. Is that I I saw as well some that you know the KKMG is looking at go going to Silicon Valley looking to buy to buy native. I mean, the big consultant firms are horrible at acquiring other business and integrating them. There's there's just no way you the the what you know that I have much more I have much more confident. It is a paradox. I have much more confidence in the AI companies becoming strong consulting firms than these large accounting consulting firms going and buying AI native topics. That is just that good luck. Good luck. Like I said, I you could point to a handful of inorganic growth strategies at large consulting firms that have actually created value in those firms. Yeah. So but I I I agree that's gonna be fascinating to see that that consulting market within this and and how that changes from firms creating new service lines to do this, or again, technology firms getting into getting consulting.

SPEAKER_01

I think it's a it's a validation of what we were doing two years ago. So really excellent.

SPEAKER_02

Well, this has been great. Thank you for joining me on consulting uncensored. I look forward to continue the conversation, continue the partnership. Thank you, Neil.

SPEAKER_00

And that's it for this episode of Consulting Uncensored with Neil McNamara. Want to join the conversation? Connect with Neil on LinkedIn to share your thoughts on today's episode and join a community of consulting professionals who want to cut through the video. Thanks for listening. There's a new episode every other Wednesday. We'll see you then.