Chapters

 

Jason Mlicki (00:01.808)
So Jeff, I know we have a recording scheduled today, but you know, I’m kind of busy. So I think I’m just going to send my agents. I’m just going to send a digital version of me on my behalf. I mean, he’ll largely say most of what I would have said anyway. And he’s probably smarter than me anyway. So are you cool with that if I just leave and just drop a digital version of me into this recording?

Jeff McKay (00:26.71)
Is it a Buckeye fan?

Jason Mlicki (00:29.096)
Love, of course.

Jeff McKay (00:31.598)
okay. So it has your level of intelligence. I guess that’s fine.

Jason Mlicki (00:37.887)
Exceptional. Exceptional intelligence, all right, so you’re the impetus for this episode. So we’re going to talk a little bit about AI agents today, the AI agent era, I guess, maybe. You shared a report from CB Insights. I think it’s titled The Future of Professional Services.

and how to win in the AI agent era or something along those lines. And so we’re going to talk a little bit about this because it’s really interesting and really good and really important. So really important for firms to read. So.

Jeff McKay (01:24.482)
Yeah, and I would encourage everyone to go out and read this. I guess you could read it after this podcast or if you read it before, it may make the podcast more meaningful to you. We’ll put a link in the show notes so that you can download it.

Jason Mlicki (01:43.922)
Yeah, and it’s not a hard read. mean, it’s 30-some pages, but it’s not a super hard read. OK, but let’s start at the beginning. So one of the things I thought we should do before we kind of get into this is just let’s just talk a little bit about what an AI agent even is. Like, what is an AI agent? And how does it differ from, say, generative AI in general? I think that’s important because I think a lot of times when

We talk about AI or anybody talks about AI, what they’re really talking about is generative AI, agentic AI or AI agents are a little different. So I think it’s important that we sort of differentiate the two before we kind of jump into this a little bit further. So do you want to take a stab at that? Do you want to kind of give us a working definition or you want me to do it or how you want to do it? OK. Well, thanks for that. So that’s why I tried to send my agent to do this because.

Jeff McKay (02:29.356)
I want you to do it.

Jason Mlicki (02:38.63)
Actually, I did ask chat GPT for help on this to say, okay, well, give me a good working definition. And I thought theirs was pretty good. So I’ll use it. it just says software that can autonomously perform tasks, make decisions and interact with humans or other systems to achieve specific goals. And, it’s what I liked about its description. Also, as it said, it’s, it’s, it’s, it’s, it’s an agent is supposed to be able to reason, plan, learn, and take initiative.

with some set of defined boundaries. I think the easiest way to think about this, to me anyway, is sort of like, I think we’ve all experienced some type of call tree or chat based interaction with a customer service center. And it’s sort of like the next evolution of that, where you could maybe have a more intelligent chat or a more intelligent conversation with an AI agent that could actually be useful and helpful and not.

frustrating where you’re yelling into a phone the way that we’ve experienced it over the last decade or so. The definition. Yeah.

Jeff McKay (03:46.414)
I think an important distinction there, Jason, is that that agent can actually act on your behalf as well.

Jason Mlicki (03:57.512)
Yeah. Yeah, which I think is the part that’s a little bit hard to wrap your head around at times. Because I think when you think about, and I think that’s also a good distinguish, distinction characteristic from generative AI. Think about generative AI and how we use it, whether it’s chat GPT or even copilot or Claude or whatever you’re using. You’re very much, you’re interacting with it actively in a prompt type model. Most people are at least.

Not everybody, but that’s most of the interaction. And I think an agent can, to your point, based on boundaries, can do things on your behalf based on instructions you’ve given it. Or coding you’ve given it as an organization, let’s say. So the other thing it said in the Chat-Chip E.T. summary it gave me, I like this. It says it combines large language models with

other tools, APIs and memory. That’s how it gets to action. So basically it’s sort of almost like a layer on top of generative AI or a system that connects with generative AI and other tools to get, let that action actually happen. So it gave me some examples. And I think there’s a lot of these in the, in that CB insights report. And some of these we’ve talked about it throughout.

customer and support agents. There’s a couple of different products out there that are being used to automate first line service interactions. We’ve talked a lot about research, like Bridgetown research, that voice enabled AI interviewers. So an agent that’s going out based on a call script and having a voice conversation with humans and modifying the…

interview approach and guide based on the answers, it’s getting back in an intelligent manner. you know, other ones, obviously I think co-pilot is an example of a personal productivity agents. mean, people are definitely using it. I mean, if you think about your asking it to summarize a document or draft a proposal or managing a workflow, it can do that. You know, that could be an example of one, I think. So,

Jason Mlicki (06:21.15)
So that’s, I think the extent of the context I wanted to give, I mean, anything you want to add that you think I should have said that I didn’t say?

Jeff McKay (06:31.275)
No, I think you did a pretty good job there. I think to solidify this lesson in your mind, you should go out and create a rattle and petal agent that handles all the post-production of our show. So I think this would help you understand exactly how

Jason Mlicki (06:40.084)
This is gonna be good.

Jason Mlicki (06:54.184)
And you’d like me to build this.

Jeff McKay (07:01.097)
Agents work. Agent would go out to Riverside, grab the latest episode, you know, and summarize it, transcript, bring it back to WordPress, put it into a WordPress post, send us a note saying, hey, this is all set up, you know, including all the metadata and descriptions and everything. And all we’d have to do is review it and…

Hit publish. So could you take care of that this afternoon?

Jason Mlicki (07:39.156)
I I only need 25 minutes according to a video you sent me. 25 minutes. I can have this done just in 25 minutes. actually that sounds amazing. I, yeah, we should totally do that. I don’t know how difficult it would be to do, but I think we should totally do it. So all right, well, let’s step back and kind of think bigger picture here than just our podcast post-production.

Jason Mlicki (08:11.198)
There’s a lot of money flowing to this space. And I think that’s kind of the gist of the CB insights report. think that CB insights report really for people that aren’t familiar with CB insights, it’s, don’t know. Maybe you can kind of, maybe you know a little bit more about the organization than I do.

Jason Mlicki (08:30.994)
I know they do a ton of like really interesting research. Whenever I read their research, what I find interesting is they thread back to essentially where dollars are flowing is usually where it always starts for me. Is they look at not just like what a company is saying, but they’ll first look at where money is going. And then they’ll look at what a company is saying and they’ll do, you know, in depth research. think this research piece, they kind of were a little bit vague in terms of how they did it. They said,

They use predictive intelligence and insights from senior AI and data executives at top professional services firms. So it’s not super clear what they did, but you know, there’s sort of a, like a mega chart they did of, of partnerships and investments and acquisitions showing again, where the money is flowing. And there’s just a lot of money. Now I did some math and I came up with there’s, you know, at least $10 billion.

flowing at AI and agentic AI primarily from the big four, the large tech firms and the top strat firms, right? At least $10 billion going into, you know.

Jason Mlicki (09:49.852)
acquisitions, development of agentic AI tools, you name it for all different types of use cases. and CB Insights does a pretty good job of showing where that money is going, or a very good job of showing where that money is going and for what. So I thought we’d start there.

Jeff McKay (10:14.109)
I loved that image that they created. If you want to get your arms around this land grab and the strategies of the big four and the big three, because they had McKinsey, Bain, and BCG in the mix in that graphic.

It’s, a fascinating graphic. And then the report breaks down those specific investments and from a strategic perspective, how much is going in? What’s the reasoning behind those investments? But you know, one of the things that really struck me in that image was the mutual exclusivity of all those investments and partnerships.

there were a lot of one-to-one relationships with these emerging AI firms. I just, found that fascinating. It’s like the firms are saying, hey, I’m marrying you and you know, it’s you, it’s you. There wasn’t a lot of,

collaboration across firms. And I’m sure, you know, that’s partly from, you know, competitive advantage, focus. I kind of get that, but it just jumped out at me. I don’t know what struck you with the image.

Jason Mlicki (11:46.878)
Well, for reference for listeners, if you do download the report, this is on page two, I believe, and it’s basically sort of like a network node diagram with the firms as the nodes in the network and all their relationships with different software firms and AI native software companies. What jumps out to me as you’re saying that though is the way this thing is mapped, Accenture is sort of like the scale of Jupiter.

and it’s got tons of moons and McKinsey is like the scale of the earth and it’s got a handful of moons. So you kind of get the sense that like Accenture is their play is like, we’re going to invest in a lot of options and just see what works. They’re gonna just try a whole bunch of stuff and a whole bunch of different directions and sort of like give themselves a lot of different ways in on this.

And then, you know, whereas the large strat firms are making fewer bets, you know, maybe those are a little bit more substantive, or maybe they’re just being more selective in the bets they’re choosing. Hard to say. But that’s the one thing that just jumped out to me as you as you said that that I’ve seen when I look at that is that there’s just a wider volume of bets from Accenture than everybody else.

Jeff McKay (13:12.247)
Yet the, you know, the other thing that jumped out at me in the entire report, not that I would say I had my arms around this. I’m not sure that anybody does. always kind of assumed that this was complex, but it’s even more complex than I thought. When you look at, and this was one of the major findings of the report.

is there’s this land grab for the AI tech stack. And I didn’t realize that the AI tech stack was that complex and that specialized. That really surprised me. And I didn’t realize that there were so many enterprise pieces that had to come together for this.

Jason Mlicki (13:46.279)
Yeah.

Jeff McKay (14:09.875)
It shows the complexity. I just think there’s so much opportunity here for these firms as a result of that complexity.

Jason Mlicki (14:23.41)
Well, it’s funny you say that because one of the…

Jason Mlicki (14:30.27)
Well, pause. Actually, I don’t want to say that. I was about to cite something from the TerraSara 30, but I don’t know for sure it’s going to be live when we do this. I don’t want to put us in a weird situation. So we’re at about 14 minutes.

The other thing that jumped out to me, and this was a little bit from side research I did more so than from the CB Insights piece itself was at least based on the announcements of investments that firms are making, that certain firms are sort of looking at this differently than others. There’s a propensity from the big four to try to focus on.

the internal employee experience and client service delivery and using agents to support that, sort of to support and lift up the people. At Accenture, you feel like it’s 100 % the land grab. It’s they want to be essentially helping their enterprise clients deploy and make sure they’re the ones that are sort of owning, to your point, the AI stack or the lead.

integrator of that AI stack. At McKinsey and Bain and BCG, I sort of took it as it’s almost like it’s more focused on the consulting process more, making sense of all the IP that exists in the firm and making it more accessible and streamlining it in terms of delivery. So it was really fascinating to me how…

There’s a couple of different ways to think about this. And you kind of see, at least based on a little bit of research I did and a lot of what’s in there. I mean, think all firms are deployed, are looking at all parts of it, but there was definitely more focus from certain firms in certain areas.

Jeff McKay (16:26.093)
That’s one of the things I love about being a consultant, versus being a corporate CMO, is you get exposed to these many different ways of thinking and how to tackle the problem. Because several of the firms had this concept of client zero, where their attitude was, if we can’t do it in-house, how can we take it?

out to our clients. So we need to experiment on ourselves. And I think you see quite a bit of that going on as well, where Accenture says, let’s just get out and do it. But Accenture is building some of those in-house tools as well. But they’re definitely doing the land grab for sure.

Jeff McKay (17:20.875)
Let’s talk about the four findings and then we can talk about what does this mean to our listeners.

Jason Mlicki (17:26.984)
Yeah, I think the four findings are sort of, I think they call them priorities. It’s sort of like, you know, what professional services firms, mean, even CB insights does a good job of pointing out that AI is both risk and opportunity here for firms. And we’ve said that a lot over the last 12 to 18 months, that it’s definitely, you know, eating away portions of things that consultants traditionally did, yet it’s also enabling them to do things they’ve never done before or do that.

much more efficiently than ever. I think agent-based AI has no difference. So yeah, they grouped them into four priorities. One, we just sort of alluded to. It’s sort of like, I’m just going to read it. It’s orchestrating the AI agent tech stack. to your point, it’s sort of opportunity number one is helping, I guess, clients navigate the complexity of all this. Figure out how to get all these systems connected and talking to each other.

figuring out how to get the data clouds and the data layer set up such that all the data can be accessible because I mean, any company of any reasonable size data is siloed in a million different systems, right? So, figuring out how to make those AI agents reliable, all that kind of stuff. that to me is very much the most client.

It’s client facing very much. It’s helping the clients navigate this reality and make sense of it and create value from it.

Jason Mlicki (19:04.946)
You want to talk about the second one?

Jeff McKay (19:07.533)
Sure. And this was the one that made me go, wow, I knew there was complexity here, but I had no idea how much complexity. And that is activating proprietary data. And connecting it is one thing, but preparing it so it’s actually usable.

but also governing it so that the inputs and the outputs are quality and not risky. And risk comes in many different ways. But one of the things, and this makes perfect sense, is one of the major issues for firms is how do you make use of

proprietary information that is client information, right? And you have confidentiality agreements and, you know, it’s, it’s almost like HIPAA, right? Hey, this is my healthcare data. can’t, you can’t use it, you know, for your gain or to, you know, market to me. but the, the getting to the data is to me, the first layer of all this.

is if because if you don’t have access to the data the rest really doesn’t matter and the research is playing that out and people are really struggling with this issue but if this report is any indication they’re going to figure it out pretty quickly.

Jason Mlicki (20:54.962)
Yeah. Well, you raise a really interesting point. You think about the multiple layers of this, right? The client has their own data that they’re sitting on top of. Most of generative AI is built on public data. And so if you’re using large language models on the open market, let’s say, you’re getting content based on public data, but all that proprietary data sitting inside of the client organization need to make that accessible inside of the firewalls of the

of the company, right? And then to your point, the firms themselves have access and privilege to all the data for all their clients that they’re working with. So then how do they determine what data is accessible and what’s not? In the report, they call it building out a data fabric layer was their quote, quote, they used, which was a nice way to talk about it. It’s like thinking about how all this data fits together and then even bringing in external data.

because it’s like, talked about that too, just third party data that might augment existing data that a client has or the firm has. And so there’s just multiple layers of all this. So I’ll do the third, you the fourth. The third they talked about was turning services into scalable products. And you actually ended up writing a really nice blog about this, about how to think about this. And I think you covered this really well on there.

But it’s just sort of this shift. I call it a shift from bespoke services for each client, AI agent platforms that kind of serve as delivery foundations. So it’s sort of this. And we’ve talked a little bit about this with Chris and Michelle, this idea of evolving from pure services to services as software. So how do you automate pieces of the service delivery?

Or maybe automate the entire thing. kind of had this mental model in my head that it’s like there are instances where it might be feasible for firms and they’re probably already doing it to sort of roll out.

Jason Mlicki (23:02.772)
AI agent brands underneath their own umbrella that are sort of DIY self-service type relationships that a client might have with a product of McKinsey or Accenture or whatever. They may already be doing that. don’t know. And they gave some examples in there of different things that KPMG is doing, Bain’s doing, and it’s pretty interesting.

Jeff McKay (23:31.704)
This one didn’t really surprise me so much. We actually did a podcast on this. And I’ll put a link to it in the show notes. But I’ve seen this coming for the last 15 to 20 years. And it was a lesson I learned when I was the marketing leader at Hewitt. And we were doing so much of

Jason Mlicki (23:36.404)
Yeah.

Jeff McKay (23:59.37)
you know, benefits outsourcing and moved into the HR outsourcing space. And it was interesting seeing the play between the outsourcing and the consulting. But the thing that was really clear is that buyers of those services expected the best thinking of the consulting, the best practices baked into the software. And I was like, well, that’s, that’s a telltale sign.

right there where the industry is going. And I’ve been saying for over a decade that SaaS firms will be the new professional services firms. And this is exactly what we’re talking about now. So I wasn’t surprised about that, but I encourage people to go back and listen to that episode because it was a good one.

Jason Mlicki (24:48.946)
Yeah. Well, I’ve always thought, too, it’s like you have this foundational IP, whatever that IP is, and consulting, outsourcing, software training is all just a delivery mechanism. It’s just a different way to deliver that IP into the marketplace. So it’s a logical thing to do to say, well, OK, we’ve been doing this through one-on-one consulting assignments. Now what if we did it through some combination of software and service? That’s not a huge mental leap.

Let’s get to the fourth one, because I want to get to what does this all this mean? So the fourth priority according to CB Insights is.

Jeff McKay (25:26.645)
found this one fascinating. It’s building the human AI workforce. And we just talked about this on an episode with our friends at Tercera. And they call this the carbon-silicon continuum, which is an interesting, huh? It’s an interesting way of looking at it, for sure. But what fascinated me with this,

Jason Mlicki (25:42.302)
Yeah. You love. You what you love.

Jeff McKay (25:57.238)
One is, of course, as you’re doing workforce planning, you need to be thinking about the skills required to operate collaboratively with these AI agents. What are the types of peoples and attributes they have that are really going to flourish working in collaboration with an agent? But the second part, and maybe I misinterpreted this.

but was the technology to manage the agent workforce and its performance in the way they talked about it. What’s the word? Anthropomorphize? Anthropomorphize? Were you given in management object human characteristics? It was really interesting to see and it really expanded my thinking about what

this carbon and silicon union looks like in how you actually manage performance. Because we looked at some of the pricing models for some of these products, and I get that, that’s kind of relatively straightforward, but performance of the product itself, I thought was just really fascinating.

Jason Mlicki (27:23.22)
Say more, what do mean?

Jeff McKay (27:26.507)
It’s just a new paradigm of treating these agents as if they’re people.

Jason Mlicki (27:34.724)
Yeah. Yeah, you know, to your point, I was thinking, I’ve talked a lot about the Bridgetown research guys on this show, I think, and I’ve written about them a little bit, and just this idea of, you know, using an AI agent, a voice enabled AI agent to do qualitative research at scale. And to your point, as I was reading this, one of the kind of mental leaps I made, it’s a fairly obvious one, is that you sort of think about an as an entity.

is performing a task and it does that task the same way a human would do it logically in sequence perhaps. But obviously it can also do it all at the same time. An AI agent could interview 3,000 people simultaneously at the exact same time. It doesn’t have to do it sequentially. So it’s something I had never really thought about, but it’s a fascinating mind bend only in that because when you do this, to your point, the human AI workforce

you could deploy certain things in certain ways that you wouldn’t have done them in the past. Work plans that used to be linear can be less linear than they used to be, if that makes sense. And an AI agent can help you do that. So just a rapid fire summary of these are the four priorities according to CB Insights in order to capture value in the.

era of AI agents that they’ve identified. One is orchestrating the AI agent tech stack. So that’s opportunity number one is that you can be helping the client solve for that. Activating proprietary data for smarter agents. think the way you and I broke that down, it’s like you can help your clients activate their proprietary data. And you can also be thinking about how you navigate your own proprietary data and make it useful and accessible for clients. Turning services into scalable products.

Productizing, we’ve talked about that. And then building the human AI workforce, sort of the four key priorities. So, all right, now, we’re swallowing a lot in a short amount of time. If you want to go deeper on AI agents, I highly recommend doing it through the CB Insights book. I’m talking to listeners, not you, Jeff, you already did that. So, let’s talk about what it means.

Jason Mlicki (29:56.872)
Let’s talk about what it means and what are the implications here. And then this is where you wrote a really nice piece on those implications that we want to point to in the show notes. So let’s start with that. of dig into that a little bit.

Jeff McKay (30:12.267)
Now I’m starting to a little more comfortable. If it wasn’t obvious to our listeners, we are not AI experts.

But we do know a thing or two about sales and marketing and thought leadership.

Now we’re moving into our bailiwick here. I think having digested all this information, the counsel I would give our listeners.

across the areas of sales and marketing would be number one, is you really have to take a step back and look at your competitive landscape.

There are so many players moving into this space that weren’t there yesterday that are small, fast, efficient, and produce outcomes that your clients want. And you could get blindsided very quickly. Your example of the research firm is a perfect indication of that. It’s just a reinvention.

Jeff McKay (31:29.973)
And it comes by really fast. and I’m sure firms are thinking, yeah, yeah, we’re keeping our eye out or keeping our eye out. Are you really? cause this is, this is moving awfully damn fast. And like I said, looking at this report, I, you know, one of the things that struck me, struck me. I maybe was familiar with a 10th of the brands.

in that graphic, maybe 20%, there were so many new firms on there. Never heard of them, never heard of them. So really go out and make sure you understand what’s happening in your competitive set.

Jason Mlicki (32:20.69)
Yeah, I think, you know, to piggyback that a little bit, you know, I don’t want to belabor the point, but I just think the competitive dynamic is changing a lot. the way I set it up and we were talking in the pre-call is like, you know, I think firms are used to competing with other organizations that look like them. They’re used to competing with their peers, you know, so a firm that approaches the problem in a similar way.

and maybe the point of separation is your experience. You’ve worked with certain types of clients or your perspective and your point of view. They’re not used to competing with a totally different type of business that’s showing up at the totally different approach. I’m a law firm, I’m a large law firm. We’re used to competing with other large law firms. They’re not used to competing with some software as a surface player that’s coming in and saying, well, why are you thousand dollars an hour on

on legal fees, what if we just automated the whole bottom of this and wiped out a third of that? We can do that way more efficiently, way faster, whatever it might be. So I just think there’s a whole new type of competitor that’s approaching the marketplace for firms that they’re just not used to competing with. And they’ve got to really think differently about their value proposition. It’s not just that we’ve got better, smarter people or a

more proven track record and better case studies or, you know, it’s, it’s, it’s a totally different dynamic. you know, and, and what the research one I gave is the example is, you know, I’m a research firm and I’m getting, I’m proposing on a qualitative research project and I’m going to interview 12 people and it’s going to take six weeks. And this AI thing shows up and says, we’re going to interview a thousand in a week, 3000 in a week. Right. It’s a totally different game.

They’re playing a different game with a new set of rules and you’re just maybe not used to competing with them. So you just have to really rethink, well, what’s our value proposition again? why would you do this with our way and why would you do it with us? Right. So I think that’s a really important thing for firms to think about is really where the competitors are coming from and how they’re approaching the problems that you’re usually hired to solve.

Jeff McKay (34:40.781)
One of the other things that struck me in the report was that the cloud providers are starting to offer implementation services. And you see with SaaS companies some professional services and some customer success types of roles to support the ownership of

Jason Mlicki (34:50.964)
Yeah.

Jeff McKay (35:10.709)
or the use of the software. But now these firms are coming into direct competition with their partners. And that’s going to create some interesting dynamics too. How are you going to market and position against those big boys? How do you sell against them? And how do you deliver better, faster, cheaper than

They ever can. so you’ve got the big boys being attacked by bigger boys and you’ve got big boys coming down to, you know, the middle market and you know, where traditionally smaller firms play as well. And then you have these pure natives coming in and playing at all levels. So, um, it’s going to be interesting.

You gotta be on your toes and you have to be quick.

Jason Mlicki (36:15.308)
What’s it mean? What are the implications from a brand perspective? How does it, how does it, you know, what should we be thinking about there?

Jeff McKay (36:23.541)
I think this seems to be a theme. Brand is even more important. And I think it’s why the big four and Accenture and the big three have such a strong competitive advantage right now because they’re going into this with these prestige brands, right? That are very trusted.

It’s the people that are trusted. People will often hear me say that brand is nothing more than your reputation and your reputation is shaped by behaviors. But now those behaviors.

are agentic and buyers are going to start looking at the quality of the outcomes from the agents that are being created. Again, going back to my comments about the workforce, that these are people like, right? And are they producing the outcomes? So your agents have to be as trusted

as your people are. And that’s incredible.

Jeff McKay (37:47.511)
I don’t know. It’s something you really have to be conscious of.

Jason Mlicki (37:53.628)
Yeah, you wrote some really nice things about this, how it’s sort of like, to your point, your reputation is your people, but now it’s sort of about…

encoding the proprietary judgment of your people into your systems. Right? You wrote also results, you know, shifting from past case studies to real-time performance. So it’s like.

You

So some of this, seems, it strikes me as is as a firm productizes a little bit and says some of the stuff that we’ve historically done in a bespoke way with people is now going to be done by software, then.

people need to trust the brand that’s providing the software.

Jason Mlicki (38:46.364)
And so it’s sort of like, you know, going back to how do you build an organizational brand, not just one that is built on the reputations of the people within it.

And that’s a little hard, right, for some firms.

Jeff McKay (39:07.009)
And there’ll be some halo effect. But your brand is associated with people. It’s not associated with software. Microsoft, Google, SAP, those are software brands. Accenture is not a software brand. KPMG is not a software brand. So it’s going to take time, and it’s going to take proper diligence.

to build those brands. And I think there needs to be a plan in place for how you’re going to build those. Because the goal is still building brand preference. Whether it’s a people product or it’s a software product, you want to be the preferred choice. And I think the three drivers of brand preference for professional services are still relevant. It’s still going to be expertise.

And the report talked about creating data motes, that proprietary data, right? That expresses your expertise is still as relevant as ever. The results aren’t changing. It’s just becoming clearer. That’s what’s being bought. And it’s going to be outcomes. I need an outcome.

And it’s going to be one of those big three. It’s going to be faster growth, going to be more efficiency, or it’s going to be risk reduction. And then the third one we’ve already kind of alluded to is a Simpatico, right? Instead of just syncing with your people, agents are going to have to sync.

So I think, and maybe this is hubris, but that model around brand preference still holds.

Jason Mlicki (41:03.09)
Yeah, I I agree with you. I think it does. So I don’t think it’s hubris at all. I think it still holds. think I think the and the way you point out in your piece is that the what underpins each one is going to change some. I also like a section in your article, you made this comment that it’s sort of like if you think about an agent, why would I deploy an agent from McKinsey versus an agent from somebody else? And

Obviously it has to be substantively better. It has to offer me more value in line with the core value that McKinsey provides or whatever. And that is all built on the expertise and results in Simpatico you always talk about. So it’s almost like there’s a value wedge that firms have to create with whatever they’re gonna do around software. And that value wedge has to say that there’s real value and merit

in getting this from a Bane versus getting it from a Google, whatever it might be.

So let’s talk about thought leadership. I still think it’s funny. I think thought leadership.

is still as important as it ever was. I think in fact, it might be more important in that I think there’s a case to be made that’s more important in case it’s less important. The case to be made that’s more important is that I still see it as the primary pre-purchase brand lever. It’s the best way to start to earn trust before a relationship occurs. It’s how you show up. It’s how you educate clients. It’s how you articulate a point of view on issues that matter.

Jason Mlicki (42:50.26)
So if you’re not doing those things, it’s like you don’t really have a foundational value wedge. So what we just talked about, this idea of like having a product or whatever you’re going to do from an agentic AI perspective, let’s say, if it’s built on brand, well, if you don’t have any thought leadership to fuel the brand, then you have a real problem on your hands because you don’t really have a wedge. So I think it feels…

It feels more important than ever. it makes me think that you’ve heard me talk a little bit about, just there’s a, with, with generative AI affecting the buying process, there’s a couple of ways to play this. And I’ve talked about one is sort of lifting up your people and making them more visible. And the other is building sort of branded content experiences and building like sub brands and building things that people you become known for. And this definitely wants to probably steers you toward the left.

because you’re trying to build authority around the organizational brand rather than people, because you may not be delivering through people products anymore, as you said. You might be delivering through software products, or you might be delivering through people and software together, right? So, I think that’s big. And then the last thing with thought leadership I’ll say is, I think at the end of the day, it’s the foundation for everything. So like, if you’re trying to build an agent and you don’t have any proprietary data,

at all, that’s coming out of your thought leadership program, then what are you training it on? And then the point of view that sits on top of that is the reasoning model. So it’s like you have the foundational data is the data that it needs to exist. And then the point of view is the reasoning model that will make the software valuable, what would create the lever. So it seems to me that

All of this points to you better be doubling down on your investments in primary research so that you actually have something unique that nobody else does. And if you don’t, then what are you building an AI agent around?

Jason Mlicki (44:58.522)
nothing unique, nothing different. Right? So.

Jeff McKay (44:58.657)
Yeah. Yeah. Yeah. And I thought one of the great things about the report, if firms are struggling with where do I play in this AI space? I mean, it’s a rich environment for you to identify white space to come in and play, but it’s clear from the report that the thought leadership white space is orchestration for one, because

You know, this is a complex tech stack and how are you going to orchestrate not just the technology, but the agents themselves? I mean, that is really rich for analysis. the data infrastructure, the security data governance. mean, these are all kind of rich areas for firms to explore. And then even on top of that.

It’s underdeveloped and definitely plays to…

Most or I should say the best professional services firms is the domain expertise, right? Whether that’s industry or function, go deep on that. And I think firms could actually matrix all of those attributes and really identify, know, key spots to go after to start moving their brand in the direction and take advantage of this new.

AI epic that we’re in.

Jason Mlicki (46:36.04)
Yeah, it’s interesting. think in the report, too, it said something like that only the majority of what’s being rolled out is being rolled out functionally or horizontally, not vertically. And I think it sort of made the case that for a lot of firms, their vertical orientation is going to be really valuable here because they understand they do understand their clients needs better than the software company does.

I’ve criticized how well firms really understand their clients. I think there’s a little bit of hubris that they think they understand better than they do. But I’m confident they understand them better than their software peers do. And I think that that’s a big deal. All right, let’s do sales and marketing. That was the last chunk of this. wanted to kind of implement. So we did implications to the competitive set, how it’s changing, implications to the brand, how it’s changing, implications to your thought leadership program, how it’s changing. So let’s talk impling.

implications to sales and marketing. That’s a lot.

Jeff McKay (47:36.034)
We’ve talked about this and I’ll put a link to some of the podcasts that we’ve done related to what I call the IC triad, right? The sales, marketing and delivery or the thinker sellers and doers. And I still believe that the IC triad needs to be fundamentally rethought. It needs to be aligned with these thinker seller doer and the six

core roles that I say are important to drive growth. I think this makes it even more important to do that. The silos of sales and marketing in delivery are not going to serve anyone well, I think long-term. So the faster you rethink your commercial engine and how you get it aligned,

to produce brand preference, the better off you’re going to be.

Jason Mlicki (48:39.208)
Yeah, I was just in my head wrapping around something you said is this notion of like delivery is instantaneous perhaps. If it’s a product, right? It’s not a schedule, a backlog, a work plan, it’s access. And so essentially the delivery team, you made a, let’s say you made a complete leap and just became a software business, which not which firms aren’t going to do, but if you did that.

The delivery team is essentially development group, AI enabled development group, not a team of people that are being deployed to go into the client. firms are probably going to end up somewhere in the middle, right, where they have a mix of all of this going on. And it just, to your point, it looks radically different. And you better understand what you’re getting into. Over the years, we’ve…

I think we’ve worked with three or four different firms that wanted to launch SaaS products. That’s a pretty common refrain. And usually they fail. And we try to help them avoid failure. And what I’ve noticed in trying to help them is that most firms struggle to understand that the economics of the business are radically different than the economics they’re used to. And they don’t make the mental leap soon enough.

to recognize what they’re getting into. They just get excited about this idea of a recurring revenue stream that they lack in their project-based model. And then they don’t realize that it’s really hard to get to. the marketing investments look different. Everything looks different. it’s a real problem. I think the analogy here holds. It’s going to be the same type of issue.

Jeff McKay (50:10.529)
You

Jason Mlicki (50:30.766)
that you’re trying to do something that you’re not used to doing and you got to be prepared to do things differently.

Jeff McKay (50:37.749)
Yeah. Yeah. I think you’re spot on. And what, what, what do you need to rethink beyond just the delivery is the entire buyer’s journey or the customer’s journey, you know, not just the buyer, you know, cause that just goes to point of sale, but the whole life cycle of being a client, it’s just right.

for opportunity and deeper understanding.

Jason Mlicki (51:11.412)
Well, I was even thinking about when you talk about your brand model and Simpatico and Simpatico about being sort of aligned worldviews and people that work together. But in an agent, it might be user experience. That’s what Simpatico is, right? so, you know, that comes back to your IC triad, your idea of like, well, delivery looks different here. So all these things are interconnected. So.

Well, all right, let’s wrap it up. I do think it’s a great report. I think it’s very thought provoking. think if you’re the leader or the marketing leader of a mid-sized firm, it gives you a sense of what’s going on in big firms and how that’s going to change the marketplace. And I think that’s really important.

And it also gives you a sense of all the change that’s happening around you for where the opportunities might lie. Or quite frankly, if you’re seeing, if you’re struggling right now, you know, if you’re struggling to figure and you don’t know why it kind of does shine a light on that a little bit of like, you know, there are things happening around you that maybe you’re not aware of that are changing what’s happening around you and you don’t even notice it. So, highly worth the read.

I thank you for, I guess, sharing it and bringing it up and take it to wrap. Anything else that you want to share or anything that you would want to leave listeners with after this discussion that we haven’t said?

Jeff McKay (52:52.727)
I think we’ve beat this one up pretty well.

Jason Mlicki (52:57.812)
All well next time I’ll send my agent and we’ll get the agent, post-production agent up and rolling. It’s probably within the hour. I think that should be done, right? So, see ya.

Jeff McKay (53:07.309)
There you go. Sounds good. See you buddy.