SPEAKER_01 0:00

Every decision has a signal buried in it. Not everyone finds it in time. At Signals at Stake, this is the podcast for people who sit inside the decisions that shape how companies grow, compete, and survive. Not the lessons learned version, the actual calls made with incomplete information, competing priorities, and real consequences attached to them. Each episode surfaces one of those moments. What was the signal and what was the stake? And then, of course, what happened next. This is not a show about best practices. It's a show about what happens when the stakes are real. Hi, I'm Akonde Davis, VP of Operations at GW Consulting. And I'm Roger Wallier, CEO at GNW Consulting, and this is Signals and Stakes. So we've been reading and hearing about enterprise AI and how the spending has gotten just astronomical. So according to a study by Folio 3, there are $684 billion that have been invested into AI. And by the end of the year, more than, check this out, $547 billion of that produced no measurable results. And I think this is interesting because it's not just like, oh, it was a bad result, it was a slightly good result, no measurable results at all. That opens up the conversation today as to why enterprise AI investments are failing and what is leadership getting wrong. And to speak to this, we have joining us today Colby Renton, uh GW's VP of GoToMarket and AI Solution. So Colby, you've been in the rooms where these AI mandates come down and where budget gets approved, right? And it stands out to me, which maybe you can run with this little thought here, it stands out to me that 73% of failed AI projects have no like agreed definition of success before they even get started. So I mean, if you if you're not sure what to measure against and then you launch it, how do you know if it's successful? And I mean, what what is your experience like with those situations?

SPEAKER_00 1:42

So hi, I'm Colby. Um, and uh I've had a lot of experience in this space, Akonde, um, on both sides of the table, actually. Um, when I worked for Meta, I was on the inside trying to organize and figure out how we could save money by applying AI to some of our of our problems that we were having, particularly around campaign execution. And uh when I was working in consulting in another organization, I worked with Coca-Cola and Nike, and all of these organizations are all while large organizations, have the same kind of idea. They get this mandate from the top down of we have to use AI because that's what everybody's doing. But then they don't really detail out what it would look like if an organization actually executed against that objective. So what happens is a senior leaders say, this is what we need to do. And this is exactly what happened at Meta. They said we have to apply AI everywhere that we can. But then they had no idea what their campaign execution process looked like. And what's at stake here, and and really that meant that they didn't have a clear sense of what they were actually aiming for without knowing how long something takes and how much it costs, you don't really have an idea. You can't put something down on paper and say, okay, this costs us 9 million because you have no idea, and we want it to cost us two and a half million. And what that does is it erodes your brand. It erodes brand, the brand reputation because senior leaders are saying, this is what we need to do. But individual contributors and mid-level managers are like, well, how do we how do we operationalize that? What does that look like? So it decays the brand by pushing out garbage or junk that is not really aligned with what the senior leaders are trying to do. It also confuses the hell out of the out of employees. They tend to not know what do I do and how what does success look like for me? And how do I how do I uh make an impact here when I don't really know what the impact is and how how well it's defined. And of course, budget is a huge impact. It it really um really makes organizations wonder like, okay, we're investing a million dollars in this AI-specific uh tool, but they fail to to address the process that sits behind it. So I've seen it a lot. I saw it at Nike too, where they bought all this stuff and it became shelfware because they had no idea, they had never rolled it out and had no idea what to do with it. So it became a similar kind of situation where leadership is saying, this is what we want and this is what we want you to do, or we want to implement AI, um, but they don't really have a plan for what that looks like. And when that happens, brand erosion happens, employee satisfaction goes down, and you're just throwing budget out the window.

unknown 4:26

Yeah.

SPEAKER_02 4:26

And that's like the foundational core of this, right? Like the leadership is not understanding what they're buying, why they're buying it. They're just been kind of told you have to make this work. And I think that kind of eventually now we're seeing is the downstream of effect of like all of these investments. So when Conde talks about at the very beginning, like X amount of billions of dollars are either unaccounted for pretty much, like we don't know how to relate that or what ROI is. The people in the room with the budgets getting approved are not the people who are going to deploy it. So they're just approving budgets, wanting something in return, and that gap between what leadership thinks is bought and what organizations are really capable of doing is pretty much like the first failure. Like that happens right off the get-gate. And, you know, I think one of the things that you mentioned, Kobe, about like Nike is like we're purchasing all of these things, we're having all of the software purchase, but it's not a platform, right? Like you're not implementing like a platform, and then you're gonna see it start working. Like it is a capability, right? Like, like it is like a a problem. Like it's data, it's defined outcomes. So, you know, it's not like something that you just buy and you implement and then you run on with it. And that's where I think they're where all these project failures are kind of kind of happening. Can you talk to is that a leadership problem, Kobe, or is that like fundamentally just a business problem?

SPEAKER_00 5:42

It's both, actually, to be all to be fair to the leaders, it is both. A lot of C level and board level organizations are saying, we need to get on this but on this bus. We have to figure out how to use AI to be to do all these wonderful things that they think AI promises, but they can't translate that that idea into what specifically needs to happen. What strategy do we take? What do we implement? Where do we implement it? They're they're not giving that information because they don't know themselves. And so it's even it becomes even more difficult when you have leadership saying use AI, but they're not clear about like what does use AI mean to us and what is the strategy. Um and I and as you the more you read about it and the more you look at it, it's and look at what's happening in these organizations, it it usually one of the one of the big failure spots in implementing AI is a little lack of a clear strategy to execution and what what leadership expects to have happen.

SPEAKER_02 6:41

And I mean that that also, yeah, I mean, and that also carries over to like, you know, data, right? For example, like if if if people are not like people who are making these decisions about budgets, like they don't understand or have any clue about where the data sits. And I know you work very specifically with a couple of our clients talking about data readiness as a fundamental layer. Like it's not one of those things you buy something, implement it, and then all of a sudden your data is not even remotely close, right? Like what what are like what have you seen in like the data realm? I guess I would probably say.

SPEAKER_00 7:12

Yeah. Yeah. So most of our clients and most of my clients over the years, I tell them when it comes to AI, data is the foundation. And if your data's not in order, they then you need to start there. Don't apply some AI or some agent agentic tool to your bad data because it just makes it break faster. And that's ridiculous. So, and and I see it all the time and I don't understand it. But in in the case of uh a client I'm working with right now, um, what they were told from this the president was that his one of his top three priorities was to operationalize AI and drive effective revenue through AI. And when I asked the leader, the VP, who I was told who I was working with when I was um having a conversation with him, I said, what does that mean to you? And he said, Well, we're working on that. We don't know yet. And that's where we need your help. And it's like, okay, well, these senior executives are saying this is what needs to happen, but they're not bridging the gap between, you know, we want to use AI, we want to operationalize, we want to improve our operations through AI, but they're not, they're not clear at all about where are we gonna do that? How are we gonna do that? And who's going to do that? And ultimately, who's accountable for driving it and measuring it to make sure that it actually does change? Because without those pieces, it's the those initiatives are just not gonna happen. They're gonna fail, like you said.

SPEAKER_02 8:34

Yeah, I mean, and I think the go forward strategy is just let's just figure it out. Like, let's just fucking make it work. Like, what have you what have you seen? Like, is it I mean, I a lot of it seems like a lot of people are really kind of shooting from the hip. Like they don't really like and and they're shooting from the hip, like logistically throughout from start, like even actually, I wouldn't even say from start of implementation, because you don't implement this, but like figuring out where they want to even use some of this budget, right?

SPEAKER_00 9:01

So yeah, that's absolutely true. Then they don't know where to start. And they so they say, what's the easiest, the lowest hanging fruit? What are most people doing? And when you read about AI application, particularly in marketing or in sales, what you see is either content creation or campaign execution. And those are the two spots where you're seeing it first. And that's where unfortunately not a lot of return is coming back, and organizations aren't seeing what the return is because they applied it to an existing process. They applied AI or automation to an existing process, and that never works. The processes have to be rebuilt around the capability of AI as opposed to building uh having AI and then creating some process and hoping that it'll fit in AI. It has to be designed with the with the skills and knowledge of AI included in that diet in that dialogue.

SPEAKER_01 9:56

Yeah, I think I think basically what I'm hearing is there's a hard gap to close because you have leadership wanting one piece, you have the teams not really being sure what's happening, boards are demanding ROI. And of course, you know, as it goes, vendors are promising transformation. Uh the last episode that we did was that this rollout of Salesforce and Claude becoming Claude Force, which is exciting, right? Um, depending on where you sit on that. Uh, but 84% of CEOs are are anticipating that this transformation is gonna take longer than six months. So now you have leadership probably caught between an investor timeline and the actual reality of what that's gonna take operationally. You know, we we talked a little bit about the strategies missing, but the timelines are still there. With that in mind, I have another uh I love data, I love it, I love statistics. So I have another statistic that I want to use to lead into our next sort of topic. SP Global found that 42% of companies abandon at least one AI initiative in 2025. That's that's pretty massive, and it's up 17% from the year before. Now, when we think about, and Colby, you kind of mentioned this, there's implementations happening, but things become shelfware. Maybe the question to bring to both of you guys is are organizing are organizations getting better at doing AI implementations, or are they getting better at saying, hey, this is not the right pivot. Let's get rid of it, let's let's go a different direction. Is it they're executing better or is it they're recognizing what the problem is a lot sooner and just stopping?

SPEAKER_00 11:23

I I think uh unfortunately, again, I think it's a little bit of both. But I think the the reality is that the um organizations are are buying up technologies because I mean there are, I'm trying to think, Scott Brinker started his chief Martech View in I think 2011. And at the beginning it had about 150 techs on it. Now it's got over 14,000, and the AI category is the largest category on that, on that supergraphic. And so these these companies are popping up left and right, and they're they're winning because people are thinking, well, this is the new shiny object. I mean, think about, and and I I personally I I really like Sixth Sense, but think about when Sixth Sense came out. It was a novel concept, it was a novel idea. I hate to do something.

SPEAKER_02 12:06

It's okay.

SPEAKER_00 12:07

I know. Well, I'm just using it as an example, so don't be around. But um, but it's it's an it's something that that people put into place and thought, okay, this is fairly easy to put into place. But then they started getting the data out of it. And then it became a well, what the hell do we do with this data? And now nobody, now they're like, do we add it to scoring? Do we what do we do with it? Do we add it to their profile and we just know this about them? And then when, you know, if they bubble up in our scoring algorithm, then a customer service person can talk to them, that kind of thing. It it's just become uh it it's not people don't know what's the execution, right?

SPEAKER_02 12:41

Like that's the gap in execution. It's like and like yeah, there's two sides to this. And I think we talk about this quite a bit here. It's like leadership is chasing things that they don't know or understand or have an idea of. So then it's trickling down to the people doing the work and the staff executing on whatever the leadership guidance is that has nothing to do or may actually, and it may have something to do with businesses, may not have something to do with businesses. No one knows, right? It's all based off on the executive, the understanding. So people throw out this term like shiny object syndrome. So all these organizations are kind of changing or chasing, I would say, this shiny object and trying to figure out really how to get it done. And I think that's where it really like tacks on the dollars, right, Kobe? Like it just really tacks on like as you're because failing in implementation of a set product is one thing, but failing in something that's charging you per token or whatever their pricing model is gonna get expensive pretty quick.

SPEAKER_00 13:38

Absolutely. And what happens is staff starts to experiment and break things, and they they're doing things the wrong way and they're not using it the crazy, they're not using it as intended, or even aligned with the business objective, which may or they may or may not know, as we previously discussed. But what happens is what I've seen happen anyway is that these technologies are adopted, they're brought in. Half of the staff will openly say, I have another client right now who said we just bought X product and it was only because our CEO told us to, and we have no idea what to do with it. What is that? I mean, why are we doing what what I don't even know what that what the value of it is?

SPEAKER_02 14:12

I mean it's like every conference, right? Like every conference has some stupid new framework, every competitor sends out some press release about what AI transformation is. And like senior leaders, I think they feel pressure to either respond, and I, you know, you've worked with them quite a bit. Is it, I guess, is is the pressure more of the idea like we're feeling left behind as like a leader? Or it's like shit, I really need to figure this out because you know, there's so much information out there, and you don't know what's true and what's not true, right? Like you don't know if someone actually had an AI transformation, or they're just saying they had an AI transformation because they want to sound good to investors or the board or make their company look better, right? So, like, where is that gap? Like, is the pressure leaders feeling like real, or is it just kind of like self-induced?

SPEAKER_00 15:01

A little bit of both, but I think it's real. I mean, I think, you know, when I worked at Ernst or worked for Ernst and Young, rather, not they were one of my clients in doing um automating a lot of this, these we are design redesigning processes to enable them to go down the AI path. And I think it's it's um leaders not being clear about what it is they want the business outcomes to be at EY. We were we we were very clear about what we wanted the business outcomes to be, but the but the piece in the middle of what do you how do you get the staff to use it? How do you get staff to to want to use what what we've put in place? It gets very fuzzy in there, and it's a lack of clarity creates havoc because people will be like, oh, cool, new shiny tool I get to use. And then individual contributors will go in and they'll start using it, and they could be using it and and not asking the right things or not. I mean, even with LLMs, we were like Claude or Perplexity or any of those. That that those simple little those tools can help with um day-to-day productivity things. Get this written done faster, get this email done, like those basic little, you know, little things. They don't have a huge impact.

SPEAKER_02 16:09

Because I sound all rude. And I think that's the other thing, right? Like, and this is why I think organizations like run multiple AI pilots, because it's not that they're running these multiple pilots just because they can. They're trying to figure out with no which one would they even need because they don't have a clear owner, they don't know how to measure the outcome attached to any of them. You know, I think McKinsey makes a very specific distinction about this that the 6% of like high performers and everyone else that they're not running more AI initiatives. They're actually running fewer, they're not running multiple pilots, they have a very dedicated strategy with a dedicated goal and an outcome and a you know some sort of some sort of result to say, yes, this is going to work, but this is not going to work, right?

SPEAKER_00 16:51

I said it's and it's got to be crystal clear. If it's not crystal clear, it is not going to happen.

SPEAKER_01 16:56

Yeah, and and Roger Colby, to your point, what strikes me is how predictable the pattern becomes once you've seen it a few times. You know, the the strategy is component is is missing. Maybe AI literacy is there. We have multiple pilots going with multiple owners and multiple different initiatives. No one's really asking whether what I'm doing is being connected to what my business, what the business actually needs in that moment. Now, again, I love reports. Let me just jump in here with some other numbers here. Um KPMG 2026 Global AI Pulse survey that they released showed that only 8% of companies that had an average budget, check this out of $186 million, report tangible ROI. Now, that's 8% with an average budget of $186 million. Now, I, you know, I know that ROI is hard to prove in the home, but if I get any budget for anything, I got to show some kind of return on it, let alone $186. So it feels like progress when you see the amount of ads, the campaigns, the content, but there's really no clear line back to a number. What's the ROI that's being pulled out of it? And that's, I think, when that AI investment starts to feel like a cost center rather than a growth driver. But Colby, Raja, what are you, what are your thoughts on that?

SPEAKER_00 18:04

Well, I think that the the clear thing is that they're they're investing in the wrong things. And what's at stake is a negative customer experience. And you don't have that much time anymore to have a to create or enable a positive customer experience for anybody who's visiting your brand or your brand uh sites or whatever is out there, what you know, your content out there. But when it comes to campaigns and content, that was the low-hanging fruit. People thought we can we can activate AI in campaigns and run a completely agenda campaign process. That sounds great, but it requires a bunch of tools to do that and a bunch of people who know how to do how to manage those tools and the budget to employ all of those different technologies to execute a campaign from start to finish. And that's a that's a big use case. Another easy and the low-hanging fruit that everybody took was creating content, using agents to create content, write new content. But now we have content fatigue. We can identify, you can identify, my kids can identify AI written crap over what somebody actually writes. And so it's it's gone a little too far on those couple of use cases where you really can't prove, and the numbers show it, that you that people are not engaging with this AI created content or AI-driven content. It's just not there. And so it's there's human in the loop is an absolute necessity if this is going to work. And you have to be able to show that that the customer experience has moved in a positive direction. Your customer's sentiment has moved in a pro positive direction. And if it hasn't, then you're clearly your investment was the wrong investment and or that you're not using it correctly, which is more likely the case.

SPEAKER_02 19:42

Yeah, I think investing in the wrong things is probably like one of the biggest categories. Like the we talked about multiple pilots, we talked about, you know, uh content creation, I think is one of them where people have invested very heavily into content. Kobe, I think you you had you've highlighted that before. And then all of a sudden you don't see a big jump. You don't see a variation, you don't see that generated content that's so amazing. And the result is kind of exactly what you expect, right? More content, not better content, and it's just flooding everything to the point where now I think even Claude and Anthropic and other companies are putting in some sort of like code that says, hey, you know what? We're gonna mark this as AI because so you know that this is AI content generated. And I think that's really when we talk about signals and stakes, that's really what we're talking about. Like we're talking about like that signal of why everything is failing based off on these what we've covered, is a huge signal. And I think that's a signal that I would probably add um is that we need to be looking out for. When is too much, you know, so much?

SPEAKER_00 20:46

A lot of organizations will say, well, we need more content. We need more content because somebody that that they work with, some agency is telling them content is what you need. You need it to deploy more campaigns, to deploy camp campaigns faster. But is that real? Is it more content with the with the business need, or is the business need actually smarter content driven towards a very specific type of individual, a specific type of buyer who's showing and demonstrating active buying signals and giving them and serving up the right content at the right time through the right medium? And if they're not doing that, I mean, I feel like we've been saying that for years, but that's what that means has changed. It used to just mean the right email, you know, at the right time or the right ad being shown on Facebook at the right time. That is not what this means anymore. Showing up is totally different. It's it's multifaceted. There are 15 to 20 things at play at the same time, all hitting the same customer so that that customer knows that what they're they're what they're looking for is visible in front of them at all times across every platform and channel that they use. And creating that experience for the customer is is really critical. But if they especially now, that's a differentiator for sure. Sure, but if they're if they're investing in the wrong things and investing in the wrong kind of content that they're going to reproduce, it just because you're creating it doesn't make it good. And it's, I think that's the human in the loop element there is that like a lot of companies just started pushing out content that was AI generated. When the reality is just generating AI content is just creating what has become known as AI slop. And that's known for a reason. It's because everybody recognizes that it's garbage and we need to go back to this other place. In fact, I think there's something interesting that I just that I just observed over the weekend because I actually watched TV for the first time in a long time, is I noticed that Chase and FinServe Financial Services has always been on the forefront of AI and same with retail. They're on the forefront of this. But what I noticed this weekend, I saw this ad several times of Chase promoting new locations. They're opening a ton of locations because they say in their ad, people want to talk to people. People want to engage with people. And so they're putting up more and more, they're investing millions in putting up more structure, more bricks and mortar, because they see the pendulum swinging back the other way. People want the content and the engagement to come from direct people. And I wondered, I is this a lead indicator of what's about to happen in the market?

SPEAKER_01 23:17

Well, I think that's I think that's one of the stakes, right? The stake is when spend keeps going up and the returns aren't coming, I think organizations are going to think about their AI investment a little bit differently. And it's not going to be the ones necessarily just doing it without the strategy. They're going to be investing in the transformation as well. So they're investing in a larger version of what's already not working. That is going to cause a problem for everyone that is going to compound year over year over year as they snowball this issue. And every initiative, every every AI transformational initiative that doesn't have a return is going to be harder and harder to prove, and a lot are going to get cut.

SPEAKER_02 23:56

What I kinda brought up is very good. So, like, what is the signal, Kobe, like based off on what you're thinking? Like, so we know all of these things are happening. Like, what is the huge signal that the market is talking about? And what should leaders be on the lookout for? Or how should leaders handle or even respond to this?

SPEAKER_00 24:13

Broadly speaking?

SPEAKER_02 24:14

Broadly speaking, of course.

SPEAKER_00 24:16

Broadly speaking, I think that the most critical thing that leaders can do is to is to use strategy to action method to identify what exactly this initiative is. If it's an AI operational, we want to improve operations through through leveraging AI. What specifically does that mean? What do people have to do? What skills do we need to enable our people with to get it done? And and then what is our our specific outcome? What is the measure of success here? What does that actually look like? Because if you don't have all of those things, and and the strategy to action, I would argue, is is the part where everybody is following, is falling down rather right now, is that like they just don't know how to take that. We want to uh improve operations through leveraging AI. They take that idea and then they don't know what should happen next. So I think the the big takeaway and the big gap here is that investing a lot of time and resources into understanding what that strategy to action looks like, what who's gonna do what, assigning those owners and making sure that people are doing what they need to do within the business at different levels in order to realize the positive return and the results from the client from the investment.

SPEAKER_02 25:29

Yeah, and the stakes aren't abstract either, right? Like so we have like what $7.2 million per failed project, $547 billion globally that produced absolutely nothing that people can't track. And organizations are kind of treating the strategy conversation that you're talking about as something that just happens after the purchase, like implementing some product that's already there. So if that's the signal, and we already know money's at the stake, money's at stake, like you know, investment is at stake. What is at stake for leaders if they do it wrong wrong?

SPEAKER_00 25:59

For leaders in particular, it's it's really about making themselves look like idiots. I mean, if they don't, if they take the mandate and say, yes, we can do that, but then they don't actually action it and they don't they don't get the execution or the return that they were that they promised, then they look like idiots. I mean, they look like they don't know what they're doing, and CMO tenure is down.

SPEAKER_02 26:20

And the and and they'll probably get fired, to tell you the truth. Like they're probably gonna find someone else to do it. So right.

SPEAKER_00 26:25

That's like because everybody wants to be on the AI bus and that a CMO tenure is going down, it's decreasing year over year. It has been for years. And I think there's a reason for that, and it's because this see the CMOs can't be.

SPEAKER_02 26:37

Do you think that even now, like so talking about CMO tenures, even like back during like just the strictly operations era, it was low. Now, with this understanding of AI or using AI, uh involvement of AI, or however you want to use that term, do you think it's gonna be even faster? You think it was a chance to be like, hey, you know, average CMO tenure, I think a couple years ago was like a year, maybe a year and a half. Do you think now it's like, hey, you got three months, get in, figure it out, or you're out. Like get the fuck out. We're gonna find someone else. We're gonna find someone else. And obviously, the age of CMOs now is getting younger and younger. And do you think it's because of that?

SPEAKER_00 27:12

I think it is. I think it is younger and younger because of that, because I think they that the perception is the younger generation is more uh native to AI and tools and technology, and they understand it better. They understand how to leverage it and create an impact with it. And so I think that that younger generation is gonna step in, but I also think they're underprepared as leaders, and that's gonna cause us uh a turnover, also anyway. So it's almost like it's better to stick with the CMO that has the leadership capability, that has the budgeting experience and all the other things that you need to know as a CMO, not just the piece that is the automation piece. A smart CMO, in my opinion, would hire somebody that is like a CMO that would that can that thinks about the business from a macro standpoint, but understands that how AI works and what it needs to do to drive efficiencies in their business and drive better customer engagement in their business. But I do think getting fired is a very serious risk right now. I've seen so many CMOs online looking for work on LinkedIn. I mean, I people that I've known for years that I'm like, how is this person out of work? And they're out of work because they're not keeping up with what's happening in the industry around AI. And all these companies want it at the top level. I think it's something like 94% of boards and CMO or CEOs are saying that that they want to move towards an agentic environment. And they don't know how to materialize that, they don't know how to operationalize that. And that's that's gonna be the downfall.

SPEAKER_02 28:39

And what about for companies? Like what what what do companies have to lose? I mean, aside from you know, businesses going completely out because they haven't either they didn't implement AI and they chose not to and said, hey, this is just a fad, or two, tried, failed, and lost what, market share? Like is that I obviously that might be the end goal of it. Like what else like are for businesses, like what's at stake?

SPEAKER_00 29:03

Yeah, I think brand erosion is one of them, certainly, and and losing customers is is right in line with that. Employee satisfaction and employee turnover is gonna is going to continue to climb because they they are being asked to do too many things that they don't understand and they're not being given the tools to learn and educate and understand what those things are. So I think that's that's also a business impact. Another is around operations. If you spend six months trying to redesign uh or or input or implement an AI tool to do any number of things, and it doesn't turn and yield that that return, it doesn't give you what it's supposed to do because you set it up wrong or because you're not using it the right way, or because you're not maximizing its capability or functionality. What's happening is that that people are are frustrated and tired and getting miserable at work. And that's just that's just a recipe for disaster. I mean, if your entire marketing team walks out tomorrow.

SPEAKER_02 29:59

Yeah, I mean, do they even have six months? I mean, it seems like you know, one of the things actually uh we might talk about on the next episode um is do how how much time do you really have? Like this whole multi-year, we've talked about like these multi-year plans where people have one year, two year, three-year plans, and then AI comes, by the way, I can do everything with even better than I did two months ago, four months ago, five months ago. So one of the things for companies to kind of take into account is timeline. Like your six-month plan, if it takes you six months to pilot something, more than likely, that's probably already outdated because you're gonna have to redo it. So moving quickly is even one of those things that is impactful for, you know, as is at stake for companies.

SPEAKER_00 30:43

Absolutely. And organizations that move too slow are being left behind. I mean, the leaders and laggards that that when you read the read the research and the data about it, the the leaders and laggards are so far apart in this. It's so different than when marketing automation platforms were introduced back in the early 2000s. That was like slow burn. That was a slow ramp up. This is not, this is not the same. I mean, it's the same in that it's as as disruptive to a business as marketing automation platforms were back in the early 2000s. It disrupted the way that we marketed, it turned demand gen into a thing that didn't exist before. The same thing is happening here. It's it's going to accelerate, but it's accelerated and it's at a speed that if you're not totally engaged, totally in in lockstep with and totally like, I know what we're gonna do, we're gonna do it, and you deploy teams or pods to execute it, you're you're done. You're absolutely done because they're not there, these companies, uh their competitors are moving on it. They are making making ground or getting gaining ground on it. And if you don't keep up with your competitors, particularly in the day in the age of AI, I mean, you're just done. There's there's no way around it. The brand, those brands will just disappear. It'll be like blockbuster. Like they fail to fail to go along like the Netflix model. They failed to get there and invent and reinvent themselves. And organizations do have to reinvent themselves to enable AI as as part of their ecosystem, not just as a technology, but as part of a business process.

SPEAKER_01 32:15

So, my question to anyone listening is this you have an AI budget and you probably have some kind of initiative running now right now. Most people do. Can you answer these three key things, right? So, what does success look like as an actual number? Not just, hey, it went well, um, you know, we saw some productivity results. What is that number that you're holding it to? Who is going to be the person that owns the outcome? The agents can't own the outcome of agents, so somebody has to own that, right? And when was the last time that somebody checked on the results or the progress or the status or the success itself? And if you can't answer those three questions, that's where the work starts. But thank you guys so much for tuning in to Signals and Stakes, where we talk about the signal in the market and what are the stakes if you don't follow it. We'll see you guys next time.