← The Agile Brand with Greg Kihlström®: Expert Mode Marketing Technology, AI, & CX
The Agile Brand with Greg Kihlström®: Expert Mode Marketing Technology, AI, & CX
Resident Expert: Bill Staikos on the CX landscape in 2026
00:29:48
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- [00:00]
A
As a leader, you often spend so much time on the strategies and tactics that keep your brand growing that it's difficult to keep up with what's going on in the background with the platforms and the companies behind them. That's why I'm always glad to talk with our guest today who is both focused on the business of CX as well as the business behind CX and the SaaS platforms driving so many customer experiences. I'm excited to talk again with our resident expert on the CX and MarTech platform landscape. We talked right at the beginning of 2026 as a look back at last year. Now that we've had a quarter behind us in 2026, it's time to talk about how this year is shaping up and what we can expect in the months ahead. Welcome to Season eight of the Agile Brand Podcast. This season we're going all in on Expert Mode, MarTech, AI and Customer Experience, talking with the people and platforms behind the brands you know and love. Again, I'm your host Greg Kilstrom and I help Fortune 1000 companies make sense of martech, AI and marketing ops. Hit subscribe or Follow to make sure you always get the latest episodes and leave us a rating so others can find us as well. And make sure you check out our sponsor TechSystems, an industry leader in full stack technology services, Talent services and Real world adoption. For more information, go to techsystems.com now let's dive in to help me discuss this topic. I'd like to welcome Bill stakos, founder at BCustomerled. Bill, welcome back to the show.
- [01:27]
B
It's awesome to be back. A lot has been going on since we last talked, so I think we're going to have a pretty meaty conversation here today.
- [01:34]
C
Yeah, yeah, I know it's crazy to think it's been a matter of weeks. I guess a couple months. But it's been a matter of weeks since we last chatted and yeah, lots to to talk through. For those that didn't catch our last conversation, why don't you give a little background on yourself and your role at Bcustomerled?
- [01:52]
B
Sure. So after spending 25 years as an operator in the customer experience space, buyer of technology, also as a seller of Technology on the SaaS side, I started my own consulting business in August of 2025 and a couple of different things just helping organizations think about the operating model around customer experience. But obviously tech is a big part of that, so staying very, very close to the tech space is sort of near and dear to my heart. Anyway, And a lot going on in this space as you know. So.
- [02:20]
D
Yeah, yeah, definitely.
- [02:22]
C
Well, yeah, let's, let's dive in then and so maybe start with if there is a contrast. Let's talk about that. You know, what were you seeing, you know, what are you seeing so far in 2026 and is it, are there differences than, than what we were seeing in late 2025?
- [02:40]
B
Yeah, there's a couple of things and I think we talked about this on the first episode we were together on 2025 there was a real shift from how do I use AI to save money to how do I use AI for growth opportunities. So the promise of AI was really strong and front and center. I think 2026 and there's a little bit of a backdrop that I think we can get into relative to the private capital space. 2026 I think is where people now are starting to ask where's the business outcome and the result. Show me hard metrics now. And last year there are a lot of software companies, they got attention just for even adding generative AI features to their capabilities. This year I think that bar is gone. The bar is now way higher. I think buyers are starting to ask very pointy questions around proof that this is going to lower my cost to serve, proof that this is going to increase conversion, proof that it reduces handle time, retention, et cetera. And that shift, I think that's showing up across the market, not in any one particular space. A lot of that driven by pressure for even contact centers being tasked. You have to deliver an AI solution this year to even just something that's even less sort of forceful. I think the second big kind of thing that feels different. I think the space between categories are breaking down a lot faster. And what I mean by that is design tools that move into campaign execution or customer data, customer service platforms now deeper into agentic automation. So there's now more blurriness between what one platform used to do versus now what multiple platforms used to do versus now what one platform could do. Right. Like Zendesk buying forethought and closing on that. That's a great example. Right. And these aren't like random tuck ins as use like private equity parlance. These are like real market moving, platform enhancing capabilities. Finally Greg, really quickly the one thing also I'll kind of talk about is the data conversation really has fundamentally changed and it's very practical like brass tacks Now. So maybe 2025 you had more people talking about data as an asset, a little bit more of an abstract way. I Think now the conversation is way more operational. So, Ken, can my data actually support decisioning or personalization or service compliance, even risk? That is a fundamental shift now they're looking at as an asset, but in very practical and operational terms.
- [05:33]
D
Yeah, yeah.
- [05:33]
C
So I want to talk about all three of those things actually. So maybe start with. And this is based a little bit on what I'm seeing as well is, you know, maybe the first and the third points. So. So essentially, you know, what I'm seeing is there are definitely, to your point about the pragmatism is last year or even the year prior was all about, hey, let's try some stuff and let's slap some gen AI on it. And isn't that enough kind of to say we're in the game or whatever? Do you think there's a relationship between those pilot projects that could be kind of done off in a corner somewhere, whether they were successful or not? They could be done and AI could be implemented or whatever. But now that we're starting to talk about operationalizing these things and seeing returns, the first thing that in my experience that or these orgs run into is, is data. I'm just going to call it data problems, because that's what they are. And so the. The data piece is just kind of necessitated by, okay, we've got to do not just pilots, not just shiny stuff, but like we got to do real stuff, but we can't even get there until the data's in the way, you know. So in other words, like, how connected do you see those two things?
- [06:51]
B
So they're super connected. So like the last of the last 12, let's say even 18 months, Greg, were, you know, running pilots. Right. Or about running pilots. Like leaders should have been redesigning the underlying operating model. Right. Like the shiny demo and the shiny tool syndrome really hit hard last year. There was so much pressure from executives and leaders to put something into place. We want to show investors that we're actively doing something with AI. And I think something like the number of times AI was even mentioned in quarterly analyst calls, it was parabolic. Right? Right. So not as much time being spent on the underlying operating model. And that's why I think a lot of pilots, frankly failed and didn't show the result that people thought now tested pilots, they tested chat, they tested content generation. But what they didn't fix was like, who has decision rights? Or how does the machine sort of make decisions? How do we unify the data so we can get better output? How do we think about sort of Process debt that we've accumulated over the course of the last 20, 30 years. What does this process now look like and do if we just put a. On top of it? Right. So you hear a lot around like, oh, these. And I'm not bashing the conversational AI folks. I think there's a lot of great capabilities out there, but, like, the AI will hand it off to a live agent. Right. If it can't answer the question. It's not that it can't answer the question. It's that your process and your policy is such that it's not manufactured in a way that actually AI, you can use the automated end of that AI, right? So it's got to point pass it off. So a lot of that stuff is now coming home to roost. And I think people are. And that's why, like, okay, way more to this than we thought. How do we get much more sort of practical about sort of these solutions? So I think you're going to have the gas kind of like come off on more pilots, more testing, and like, here are the three kind of use cases, problems that we need to solve. Let's go fix the foundation and then put AI on top of it.
- [08:55]
D
Yeah, yeah.
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C
So to get now to the second point, I mean, you know, another thing that I'm seeing is, well, I, you know, I always say, you know, just because you can do something doesn't mean you should. But at the same time, you can do an awful lot with, you know, whether it's vibe coding or, you know, agentic and all these things. And so, you know, I do wonder when do. When does kind of the Sprawl, this feature Sprawl and. Or does it. Does it ever end? In other words, do we end up with 20 platforms that do everything and they do the same thing? And, you know, right. Right now, the things that prevent that from happening are many. You know, there's, there's even, you know, brand and market position, there's tech debt, there's. There's all kinds of reasons. But when it's so easy to just either acquire a company and, you know, tie it in and. Or you just build it yourself. Like, is this leading us to a good place? Or again, are we just going to have a bunch of platforms that do everything?
- [10:02]
B
I think we're going to be in the messy middle for a little while, to be perfectly honest with you. Right. Because at an enterprise level, who have. They've got the resources to go build even internally, the question now is, can't we just build this we're spending so much on AI already. We've done all these pilots, we've learned a ton. We have now maybe an organizational structure in place to kind of manage this in a much more effective way. Why can't we go build this? I hear that a lot, frankly on things around experience, analytics, pulling together disparate sources of data, analyzing them at scale. Yeah, you can do that with a couple of really good engineers, let's say a year's worth of dedicated time. You can build what a lot of these platforms have today. Back to your point of could versus should. But that's years of maintenance and on. Right. I think that with the. We can go build it quickly and add it on internally or at these sort of SaaS providers. Plus the fact that there's market environment is very different. I think people are more cost conscious, at least in the US certainly given sort of like what's going on in the world. There's just this weird dynamic happening right now where I think that people are going to try to build things on their own, probably fail as a result, or put in the wrong solution and then the next up and coming thing kind of comes around and says we've got a better mousetrap, but I can't use that for another couple of years because of where I am with the current solution. So I think that this will shake out probably two to three years, but it's going to be awkward for a couple of years, I think.
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D
Yeah.
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C
I mean, I wrote this article for CMS Wire where I don't think I coined the term or anything, but like I use the term creation sprawl, which is like, you know, again, I do it. I mean, I'm not right at the moment, but most hours of the day I'm probably vibe coding something to help me do something better. So why wouldn't anyone? And at the same time you have all of these essentially ungoverned tools and processes and things. So yeah, you know, I think the
- [12:18]
B
real interesting thing that's going to probably create a lot of noise for company is like you and I, we're on the same team, we're both vibe coding solutions for ourselves. Right, Right. So now, now magnify that across 50,000 or 100,000 or 300,000 people in an organization, like how do you even maintain one? That's probably cost prohibitive if we're all like hitting tokens left and right. Right, like number one. But number two is like how do you kind of capture that level of innovation, govern it. But also then Consolidate it so you can impact many versus you and me as individual, like mini innovation labs. Right. So that to me is a real big problem for CIOs that they're going to have to absolutely think through and solve over the next couple of years.
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D
Yeah, yeah.
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C
Because I mean, to your point, it's. I think I love the freedom that, you know, I never, I wrote a little action script back when Flash was the thing, but you know, never, never really a coder myself. But so I love the freedom that, that doing that stuff gives. But you, where you gain individual freedom to be able to do this stuff, you lose that collaboration which can admittedly lead to bigger innovation and stuff like that. So I agree, like there's got to be, there's gotta be a little, like people need a little room to play because I think that that helps. But then there's gotta be that some governance for the sake of, you know, innovation and really the company.
- [13:47]
B
Yeah. And maybe AI can help us do that too, I don't know. And just feed it to middle managers to better manage their teams and the things that they're creating. But there's a real solution to that problem in there somewhere. So.
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D
Yeah, yeah.
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E
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C
So, you know, looking back at the next, at the last several months, any surprises, any missed opportunities, you know, anything you're seeing in the market, I think
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B
certainly the one around, you know, we already talked about one like not, not thinking about sort of the underlying operating model that more and more is now front and center of the conversation. That's probably like top one, two or three conversations for the work that I've been doing. I think one big surprising piece is how quickly the market started rewarding. Companies that connect all these disparate pieces from creation all through action. The voice, AI and the solutions coming up now proliferating in the contact center space. They've gone parabolic from a growth perspective. I'm not sure that people were necessarily ready for that, but boy, if there was any space where you can quantify impact immediately is in the contact center. And then another surprise for me is what's happening in the private capital space. You've got these big private equity companies that are now publicly coming out even and saying we overpaid for some solutions because we overestimated growth rates. I won't name the company, but, like, direct quote from one of the founders. You have a lot of challengers out there saying all these companies are way overvalued and you got to start marketing these to market much better. And that's impacted the market. And then third, like, I mean, I don't know if I saw this company coming. Maybe others did. Like the fact that like, the anthropics of the world are developing solutions that are fundamentally challenging entire categories of software that everything from cyber to, you know, Vibe coding. Right. Like, you know, there's a lot of companies that last, let's say, two, three years, and all of a sudden now you've got, you know, Claude Code and cowork. Like, those companies are dead in the water at this point. Right? So, like, you know, that to me is super surprising. So, you know, I was always looking at, like, these models will continue to get better and evolve, not like, take out, potentially take out, like big swaths of software providers out there. So.
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D
Yeah, yeah.
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C
Well, I mean, do you think it's, you know, there's. There's always been danger of disruption, of course, but do you think it's getting
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A
easier to disrupt at this point?
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C
You know, because there's some. There's some pretty entrenched players out there, but it also, it feels like it's getting easier and easier to scale, you know, to some of those. Those levels of functionality and stuff like that?
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B
Look, I vibe coded a CRM for myself, you know, two months ago, right. So, like, you know, I don't have to necessarily pay for that now. I mean, I'll do on some level, right. You know, for Codex. But like, you know, now I think at the enterprise Level, I think that there are going to be buyers in the market for these big kind of core systems. I mean, again, I don't want to mention names, but one of the bigger CRM players comes to mind. I don't think they're going to go away. Yes, there are people out there saying your business model is now fundamentally disrupted. I don't think they're going away anytime soon. It would cost way too much to build something similar, even exponentially more to maintain that ongoing. That doesn't make sense to me. So I think like some of it is certainly overblown, but I think if you're in like that mid market or upper small business, like let's say 7,500 employees, I think that you're trying to figure out how do I bring my cost down, create solutions that are much more bespoke for my business. Yeah. And that certainly is going to impact the software space.
- [18:53]
C
Well, yeah, I mean it's kind of the, at that, you know, at that lower mid market space, it's, at least from my stand, it feels like there's a lot of artificial barriers being put in place in software to make you either upgrade to enterprise or you just don't, you just don't access it unless you have X xyz, number of employee seats, what, whatever the case may be. So to me that feels like the place that's certainly ripe for disruption in, in particular because. Okay, cool, you know, if I have to pay 10 times more for my CRM or whatever the platform is, I'll just vibe code that feature and I'll live with whether I love tech support or not because it's me, but it is what it is and I'll solve my own problems. Right?
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B
Yeah. Look, even for myself, there's free CRM solutions out there or free levels of CRM solutions. I still vibe coded it because one, I want to challenge myself. Can I do this right? Two, could that help me? And then three, like, yeah, I don't, you know, I don't want to be constantly peppered with up, you know, upgrade, you know, sales pitches, you know, at some point. So yeah, it's pretty exciting.
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D
Yeah. Yeah.
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C
So, you know, I know we've talked a bit about this already, but you know what, you talk with a lot of leaders, a lot of C suite leaders and stuff. You know, what, what are you, what's your advice to them over the next, you know, over the next six months? Let's say to, you know, based on some of those things that you're, you're Seeing and hearing.
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B
I think there's a couple of things. One, I think that, you know, stop looking AI as like a feature set. I think that you really need to be looking at this from an operating outcome perspective. So every investment in AI needs to be tied to some small set of hard metrics, right? Like lower cost to serve, higher revenue per customer, faster resolution retention or lower churn, better conversion rates, better productivity among your employees. That's all measurable stuff. If the vendor can't show you the economics very clearly or put you in touch with someone who's non competitive in your space, that is using their tool to drive those results, that's a red flag for me, number one. Number two is I think that you should simplify your tech stack before you scale the ambition. And I think back to the point of the foundational elements being there, I think that's really critical as well. Third, I'd say treat data and workflow as one problem, not two separate problems. Right. I think the companies that really are starting to get this are the ones that connect data in action. And frankly that's why CDPs orchestration, service automation, that's why these have A started to blur and come together, but B have really grown as well. I'd also start looking at how do we design the human role now? I think last year there was way too much conversation around the term human in the loop, which is a term I personally do not like. I think this year, particularly as organizations start thinking about the operating model and how things work, I think people are going to start to design where is the human, the whole loop? What are the journeys that we fundamentally cannot put AI in the loop of and just keep that human element. And then what are those handoffs where they should exist, whether that's machine to machine, machine to human, or human to human, really getting crystal clear on what those are. So I think those kind of things are big management or leadership issues right now that need to be solved, not at some point in the next 12 or 18 months.
- [22:47]
C
Yeah, yeah, well and I think to that last point, I think there's an important point to be made as far as we do want. I know the robots are listening right now as I say this, but we want them to be working for us and not vice versa.
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B
Totally.
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C
Right. I try to keep that in mind. I'm forgetting the name of the author right now, but somebody wrote a great article about this a few months back and it just, you know, I think I think about it often. As far as, you know, am I, am I doing work so that AI can do something? Or is AI doing work so that I can do something? And I think, you know, there's probably in the middle of things, there's going to have to be a little bit of each or whatever. But like, what's our goal? You know, is our goal just to, to for us to be feeding AI more information and instructions or ideally the other.
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E
Right.
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C
Is to make our jobs easy, be more strategic, so on and so forth.
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B
Right, yeah. Look, when I think about, you know, I've worked with someone on this in the past is when I think about efficacy of AI, you need to look at three levers. One is financial impact for sure. Two is operational leverage. So like, am I reducing friction for my customer, team to team, employee to employee? And then third, and this is a big one, is am I amplifying human capabilities inside my organization? If I just employ AI and take the cost save, I'm basically telegraphing to the world that I've run out of ideas. Don't dig a hole, fill it with something productive that could be more AI, whatever that might look like. But you want some level of production filling that void too. And I think that's a big thing that I think some are still missing or many frankly are still missing. But yeah, I think that that conversation I'm starting to see kind of bubble up more and more, which is encouraging.
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D
Yeah, yeah, I love that.
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C
Well, so looking ahead, we'll talk again in a few months here. What are we going to be talking about in a few months? What's on your mind as far as months ahead?
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B
I'm going to put a prediction out there, but before I get there, I think there's a couple things. One is I think the market is going to tolerate less and less your standalone point solutions. I think that people are going to want to see the capabilities they invest in, just do more. Number one, I also think we're going to start to see know category collapse. Right. All labels are becoming less useful. Right. It's kind of legacy buyers, legacy capabilities, a lot of AI native players kind of bubbling up. So entire categories are being disruptive. And I think we're going to see sort of this, you know, the market still kind of splintering or separating into three groups. One, I think you're going to have sort of your core platforms, distribution, install base and I think, you know, like that big CRM name that we were talking about before, certainly in that category. I think second, you're going to find some point solutions with genuinely differentiated capability and then third, everyone in that messy middle. And I think that's where the danger zone is. And finally, I think I'm going to put something out there. I think we're going to have, particularly given all the private capital issues going on in the marketplace right now, we are going to have a major category player disappear. And I think, you know, I won't again, I won't mention any names. Obviously there are a couple that I'm looking at pretty closely. But nonetheless, I think we're going to see a major player disappear from the market this year.
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C
All right, well, yeah, we'll have to keep talking here. So definitely interesting things ahead. Well, Bill, thanks so much for joining today. Last question for you. I know I asked it to you last time, but what do you do to stay agile in your role and how do you find a way to do it consistently?
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B
I think it's just having a system in place, right. And I'm always adding tools and plugging those tools into the system. But whether it's thinking about content generation and putting sort of my voice out there in a marketplace, whether it's developing, thinking or ideas around potential clients that I want to be working with or clients that want to be working with me, you got to have a system in place and that's really critical. Otherwise it's tough to scale. Otherwise.
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D
Yeah, yeah, Love it.
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A
Well, again, I'd like to thank Bill Stacos, founder at B Customer Led, for joining the show.
- [27:15]
C
You can learn more about Bill and
- [27:17]
A
B Customer Led by following the links in the show notes. This episode is brought to you by Tech Systems. They're leaders in full stack tech services, talent solutions and helping companies put it all in action. You can learn more@techsystems.com that's teksystems.com and thanks again for listening to the Agile Brand podcast. If you like the episode, hit subscribe and drop a rating so others can find the show too. And if you're interested in consulting, advisory work, or if you need a speaker for your next event, feel free to reach out. Just visit GregKilstrom.com that's G R E G K I H L S t r o m.com the Agile brand is produced by Missing Link, a Latina owned, strategy driven, creatively fueled production co op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. Until next time, stay curious and stay agile. The Agile Brand.