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MarTech Podcast ™ // Marketing + Technology = Business Growth
Scott Brinker’s 2026 Martech Predictions Unpacked
00:47:14
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- [00:00]
Podcast Announcer
The Martech Podcast is a proud member of the I Hear Everything Podcast Network. Looking to launch or scale your podcast, I Hear Everything delivers podcast production, growth and monetization solutions that transform your words into profit. Ready to give your brand a voice? Then visit iheareverything.com.
- [00:26]
Benjamin Shapiro
From advertising to software as a service.
- [00:29]
Scott Brinker
To data across all of our programs and clients, we've seen a 55 to 65% open rate. Getting brands authentically integrated into content performs better than TV advertising.
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Benjamin Shapiro
Typical lifespan of an article is about 24 to 36 hours.
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Scott Brinker
We're reaching out to the right person with the right message and a clear call to action. Then it's just a matter of timing.
- [00:54]
Podcast Announcer
Welcome to the Martech Podcast, a member of the I Hear Everything Podcast Network. In this podcast, you'll hear the stories of world class marketers that you use technology to drive business results and achieve career success. Here's the host of the martech podcast, Benjamin Shapiro.
- [01:16]
Benjamin Shapiro
5384 that's how many martech tools exist today. A 9% jump in a single year. But more than 1200 vendors disappeared at the same time, which is an 8.6% churn rate. Everybody predicted consolidation and it didn't happen. AI didn't shrink martech, it blew it apart. Now every vendor claims AI stacks are getting messier and the problem isn't too many tools, it's that the rules for marketing and technology are changing underneath us. So how do you build a Martech strategy when the ground keeps shifting? I'm Benjamin Shapiro and joining me today is Scott Brinker, the godfather of Martech and the founder of the chief Martech.com blog. And today Scott is going to share his 2026 Martech predictions and help you navigate the chaos of agentic AI disruption and the end of the Martech playbook as we know it. Scott, welcome to the Martech Podcast.
- [02:10]
Scott Brinker
It's great to be here with you, Benjamin.
- [02:12]
Benjamin Shapiro
Excited to have you here. It has been a hellacious year in terms of technology change. Also a big year for you. You're doing consulting now, focusing on Chief Martek and I'm sure digging into all things AI like the rest of us. First off, we're going to cover a couple different topics today about predictions. Let's start off at the top here with our first topic. Tell me a little bit about what you observed from 2025. You just had your big report about the year in review and all things AI and Martech. What was the biggest takeaway that you got from 2025 that we could take into 2026.
- [02:53]
Scott Brinker
Well, apparently AI has become a thing.
- [02:55]
Benjamin Shapiro
I've heard of it.
- [02:57]
Scott Brinker
You know, what we found in the research is actually most marketers are now already using some of these AI agents. They're using some of these agentic capabilities within their MARTECH stack. But this is the. But most of them are still very early in the process. It's a lot of experimentation. In the cases where they are deploying this product to production, it's usually very limited use cases. And this is totally rational, right? I mean, so much of this capability just didn't exist before 2025, you know, and actually the degree to which we've had so many marketers start to experiment and do like, small production releases in such a tight time frame is actually incredibly impressive.
- [03:42]
Benjamin Shapiro
Yeah, the amount of experimentation is amazing. And we're all doing it. And we're all trying to figure out how to use this new technology, which in theory is supp to make work easier. What I can tell you is every time I use AI to go find a stat to do my podcast intros, it almost always defaults to 95% of marketing. AI experiments fail, according to McKenzie and according to Forbes, and it always grabs onto that statistic. Now, either Claude is trying to hedge expectations and using the MarTech podcast to tell everybody, pump the brakes on all that experimentation, or people are really struggling to figure out something that actually goes from experimentation to deployment. So, yeah, lots of experimentation. Is anything actually working?
- [04:34]
Scott Brinker
Well, I actually, I find that in the content production pipeline, this is one of the use cases where people are getting pretty good at actually harnessing AI effectively. Now, this doesn't mean, like, you turn it over to an AI agent and it does the complete end to end, like, oh, concept, concept and production and distribution analysis. And yeah, I went off and I got an espresso and I came back and it's all done. No, but at the, like, each step along those ways, we are seeing people productively use AI to like, okay, well, help me brainstorm when I want to do this or help me evaluate this. Okay, all right, Now I want to create this thing. Can you take this piece of content and help break it up into different components for, you know, different channels where I may deploy it? Can you help me with the analysis of, you know, customer engagement around it? Again, these are all things that marketers could do before, but they were generally very time consuming. And we're seeing a fair number of content production use cases where the human still has to be the one driving each step of that. But the time frame in which they can get those things accomplished has shrunk considerably. That's a real world win, I guess. The other one I'd say is the chatbots on websites. Now, we've had chatbots on websites for years. We can all agree they've largely sucked this year. They've started to get good and they've started to get good for two reasons. One is, you know, they're now powered by these LLMs that are actually very good at conversational interaction. And the second thing is companies are starting to get smart about attaching these chatbots, particularly for customer service use cases, to the right data on the back end, their knowledge bases, their ticket histories, their customer profiles, so that it's not unusual now to hear companies that are deploying these seeing customer interactions with these chatbots getting a 60%, 70% resolution. Again, if it doesn't get resolved, you have to make it really easy to get to a human rep who can resolve it. But still, you know, for those cases where it can, like self serve, get the customer the answer they want, get them on their way quickly and be very efficient for the company, you know, again, this isn't rocket science, but those are two pretty good use cases.
- [06:51]
Benjamin Shapiro
Let me give you an n of 1. I hate the chatbots because, yes, they are lowering costs and they're able to execute 75% of queries successfully and then eventually they bounce to a human. I personally find the experience of talking to an LLM, A, it's very clear when you're talking to an LLM and B, it is very frustrating for the end consumer. It might be more profitable. I'm not sure how good it is for the long term relationship. So as we talk about 2026, I'm curious to see if the chatbot experience is something that gets better or starts to deteriorate brand relationships.
- [07:29]
Scott Brinker
No, it's a great thing, you know, I guess for me it probably depends on what the very specific use case is. And I say this as a person, that the most frustrating experience for me is sitting on hold listening to people tell me on a recorded voice how important I am to them. And like, you know, you are 74 in the queue. So to the questions I can get answered by a chat bot right away, I'm sort of in the camp of like, you know, I'll take that path first.
- [07:55]
Benjamin Shapiro
Yeah. And please, we want to give you a survey at the end so you can tell us how much we stink. Yes, I agree that the automated phone processing, I'd actually rather talk to a bot, I think than type to it. Okay, so you mentioned the content production workflows are getting pretty good. The chatbots are getting all customer facing experiences essentially. Are there any other verticals where you're seeing or you Predict that in 2026 we will see better use of agentic AI?
- [08:28]
Scott Brinker
I think the back office use of analysis of data. Right now actually a lot of these AI engines are very capable of doing a good job with that. The reason they're not used very much for that is because we aren't connecting the right data to them or the data we have is surprise, surprise. This is a theme that's been in martech. Since there's been Martech, our data is just not very good, you know. But this has become one more reason for marketers to invest and like, you know, we really got to get our data layer right because everything we want to do and AI is just sort of the latest incarnation of this. Everything we want to do is kind of predicated on having good data and being able to get that data to the right place at the right time. I'm not saying that's easy, but at the end of the day that really is the mission if you want to harness what this technology makes possible.
- [09:20]
Benjamin Shapiro
So if you looked back at 2025 and had to summarize in one sentence, I'll even give you a paragraph. What is the big takeaway from the adoption of AI? What did we learn this year that will be applied moving forward?
- [09:35]
Scott Brinker
We are, we are coming to grips with the fact that AI is very, this sort of generative AI, this generation of AI is very different than the kind of automation we've had in the past. You know, we've had automation and marketing for, you know, decade, decade and a half, but it's been what they call deterministic. You know, it's you, you explicitly configure if this, then that and this other thing, which is great, it's very reliable, predictable, explainable. It also tends to be very fragile and we tend to create all sorts of complex exceptions and whatnot and quickly can get a mess. On the other hand, we're starting to see as we experiment with incorporating these LLMs into our workflows and our automations, it's almost like the inverse trade offs. Okay, LLMs are not as predictable as that goes. They have variants to them. They are what we call non deterministic, you know, in how they're going to respond. And that has challenges, but it also has a set of benefits that actually these LLMs are better at adapting. You can throw things at them. You know, that would have broken one of those deterministic workflows of I'm expecting X, you didn't give me X, what do I do with it? You know, you can throw more things at an LLM. You can throw things at it that are going to change, and the LLM can adapt to it. And so where things are getting really interesting is you're seeing marketers here in 2025, and I think we'll see a lot more of this in 2026. They're starting to combine the two. They're like, okay, we're going to have a workflow, and that overall workflow is going to be deterministic and very well structured because that's what we need to run our operations as a business. But we're starting to incorporate the use of LLMs with specific steps along that workflow because it allows us to do things with like, unstructured data or, you know, generation of media or things like this that were impossible to do with those deterministic workflows. We've started to experiment with that in 2025. I think we'll see a lot more of that and start to move it more into production in 2026.
- [11:37]
Benjamin Shapiro
My takeaway from this, as we look back at 2025, it was the year where we moved beyond essentially content marketing into conversational marketing. And now we're making the migration into analysis using LLMs. And as you said, we have had marketing automation for 15 years or so, but now we're able to move beyond deterministic rule sets to have something that is a little bit more related to judgment. I want to move on to our next topic. A lot has been talked about in 2025 about the death of SEO and the rise of AEO. And I know this is something that you've talked about publicly and relatively frequently in 2026. Are we going to continue to see the narrative of SEO is dead? AEO is here. What happens in the SEO and content marketing space?
- [12:30]
Scott Brinker
I love this topic. Well, I'd say two things are true. One is AEO is here, and it is only going to become more important in 2026. This was sort of the first year that people really started to get serious about it, but we have barely scratched the surface. I mean, partly is the AIs were trying to influence. They're not exactly standing still. This is chasing a moving target at a much faster rate than anything we were chasing with Google Search. But the thing I would say is SEO is not dead. You know, I look at AEO as very much an augmentation, like a layer above and beyond core SEO. But here's the thing. These AI answer engines, when you ask them a question, you ask it to do research for you. It's not just going and looking at its training set that it, you know, hoovered up from the Internet like a year ago. Right, let's start with that. But it also then does reasoning and makes decisions of like, oh, I need to go out and search on the Internet to find, like, current updated sources, you know, to incorporate in this. What's it doing? It's actually. It's running searches, you know, I mean, like, OpenAI was running searches with Bing, you know, Gemini, surprise, surprise, running searches with the Google, you know, search index, you know, and so your ability to actually, like, show up in these AI answers, like, part of your AEO strategy actually needs to be like, oh, yeah, you know, a lot of stuff we did for SEO that's still relevant. It's just now we have to do more things on top.
- [14:01]
Benjamin Shapiro
Yeah. One of the things that I'm a producer of, a SEO podcast, I guess we have to call it an AEO podcast now. But to me, SEO is the foundation of aeo, and I struggle with what's the difference? Right? It was for the longest time, have great content, have backlinks, have internal links, have credibility from the author, build a reputation, know, like, trust, you know, E A T. All the other SEO terms like tla, word salad, but fundamentally it was about creating good content and having other people engage with it. Seems like AEO is relatively the same. How do you think about the difference between the two practices?
- [14:45]
Scott Brinker
I think conceptually you're absolutely right. I mean, it's all about the same things. The actual tactics and execution vary, you know. So, for instance, like, here's a couple examples. So one is, you know, SEO. The core of it was originally based on the idea of backlinks. And following that map of backlinks is a way to create authority, you know, with a particular domain. It seems to be that the way these AI engines train is they're not really mapping the world through backlinks, but they are keeping track of references, you know, particular references in natural language. And so it turns out that, you know, things of having people talk about your brand out on the Internet, you know, you know, Reddit is often brought up as one of the examples of, oh, my goodness, all these conversations in Reddit, you know, they're helping the power, you know, the rationale that AI engines are using in answering these questions. That's different than backlinks, you know, I mean again, it's conceptually same thing as like, oh, how do we get our brand out there in more places, but now it's less about links and it's more about like, where are the conversations being held and how do we make sure our brand is there and hopefully in a positive light. Another example would be the content itself that you're publishing. Again, AI engine, same as like Google Search originally it, it wants content, it thrives on content, you know, but because of the way these LLMs think, you know, it turns out things like for instance, FAQs, like sort of very structured question and answer content seems to resonate very well with the models that these AI engines are, you know, creating and then how they're going to be able to answer accordingly versus like with Google, again like they would have taken FAQs but you know, it was again sort of like a different set of algorithms of like what they were looking for in content and how they'd use it. Maybe one third thing here is like Google used to really complain and dissuade you from showing one thing to Google and another thing to a human. It seems actually with these AI engines they don't really care about that. And actually one of the AEO recommendations these days is like, you know, actually if you identify something coming in as one of these AI agents, you know, you can actually serve up a simplified version of your page. Doesn't have all the user interface crap, it's like just a markdown version of the content. I mean, again, same thing. You don't want me doing deceptive sort of things and showing one thing, you know, it's completely different from another. But basically tailoring the content in a format that's going to be facilitate how that AI engine consumes it. Again, but these are all things on the margins. You're a high level thing of produce good content, make it easier for the engine to absorb it, you know, show how you've got credibility and references externally. Yeah, those are as relevant as they ever were.
- [17:34]
Benjamin Shapiro
So what's a marketer to do when the strategy used to be create, get great content, publish it online, try to get other people to link to it. Right, Traditional SEO, now we have this AEO practice. Are people going away from content marketing as a channel? Are they thinking about expanding it? What's the balance look like? They're thinking about content?
- [17:58]
Scott Brinker
Yeah, no, I think content is as relevant as it ever was. And again now it's also like different kinds of content, being able to provide videos, things that humans love. But as it turns out, these LLMs also love. I think the challenge for content marketing is we got a bit spoiled with the Google era where we had these relatively short feedback loops where we could see, okay, we produce this really great content, it's going to show up in these search results, people are going to click on that search result, they're going to come and then we get track them and we see what leads to customers. And so it was this very well instrumented system. The problem we have now is not that this content isn't being used or leveraged by these AI engines and ultimately then consumed by the end consumer. It's the fact that because now so much of that conversation with our content and the interaction with it is happening inside the AI assistant, the AI engine and we don't have the direct visibility into that. It's not that the content isn't being used or it isn't valuable. It's that we just don't have as much visibility into the top of the funnel of that practice. And so I would, I would definitely not say you should like stop doing content marketing, but how you actually measure this and your expectations for what you can measure. They've got a shift shameless plug.
- [19:25]
Benjamin Shapiro
Everybody should start a podcast instead of a blog. Take your video content, turn it into audio, use an LLM to turn it into text, and then put it on social. You get the best of all worlds. I hear everything. Dot com. I'm sorry, I cannot help myself. It's absolutely shameless. Let's go on to our next topic. I want to talk to you a little bit about context. A lot has been said about 2024 was the year of prompt engineering. 2025 was the year of agentic. I think personally 2026 is the year of context engineering. How important is context and how should marketers think about understanding context as we go into 2026?
- [20:05]
Scott Brinker
You know, there's probably like a parallel here of what AEO is to SEO is a little bit what context engineering is to prompt engineering, which is to say, you know, most context engineering sort of originated with this idea of prompt engineering of like, okay, if I'm going to ask the AI to do something on my behalf, I need to feed into it as clear information, instructions as possible to make sure I, you know, it doesn't go off and invent its own thing. It gives me what I want. Well, you know, it's sort of just like aeo expanded SEO context Engineering expands on prompt engineering to say, like, okay, well, it's not just what we want to describe as the instructions to the LLM. It's also that we want to point it at access to data that it might then be able to use in its processing. Because these AI engines are getting agentic, which means they can take actions. You know, we might also want to provide it with access to certain tools, you know, that it can use to like, oh, okay, actually you can go out and you can query, you know, for this information, or you can book this appointment. And so it's that art, that practice of saying, okay, now when I ask the AI to do something, I want to bundle up instructions, I want to bundle up access to the right data for what it might want to need to do. I want to like, point it at the tools it can use in executing that. And that's what context engineering is all about.
- [21:32]
Benjamin Shapiro
I have a. One of my guests this year is a mutual friend of ours, your former coworker Nicholas Holland, from. Nicholas, the head of AI from HubSpot. And in my conversation with Nicholas, he said that basically the LLMs are so good now your prompt is kind of irrelevant. Like you can misspell words and not get everything exactly right, not in the order, and the LLMs will figure out essentially what you mean or what you're trying to accomplish. But without context, as a filter, everything gets dumbed down to the norm. How do you think about creating the right context when you're building some sort of an agentic process? What's enough information? What's too much? How do you figure out the right balance of. Here's the boundaries of the information an LLM is looking at, and here's what I'm asking you to do.
- [22:27]
Scott Brinker
I so love the way you frame this question, because most of the challenges that people have with AI aren't really challenges with the AI. You know, if you took the AI out and you say, I'm going to have a human who's going to do something for me, not the LLM, we're going to have a human do this. And you're like, what instructions do I need to give them? What data do I need to give them access to? What tools, you know, are they going to need to use to execute it? It turns out for a bunch of things that we're asking AI to do, we don't like, have. The answer is that, well, I'm not actually quite sure what data it's need or where I would get that data, or wait, what tools might it want to use, you know, and so if you really want to get value out of these things, you got to sort of step back from the AI piece of it and say like, okay, what's the job to be done? What is the specific task that I want this thing to accomplish? What information, what tools is it going to need to execute and pretend? I mean, you can even fake this with like, hey Joe, you know, Mary, you know, come on over. Okay, here's what I want you to do. Here's the tools, here's the data, you know, can you do it? And they might ask questions of like, well, wait a second, this data isn't right. Or you know, what about, you know, this other data that you didn't give me to. That is all, where all the hard work is. You know, we hear the same thing with some of the AI automation things and people like, like, hey, I can't get AI automation to work for my process. Okay, well, step one, can you describe your process? Oh, no, not really. Do it different ways all the time. And you know, you're like, okay, until you really know what your process is, it's kind of hard to get AI to go unautomated for you. I don't mean to sound flippant about it, but these are really the hard challenges that we have got to overcome to tap the capabilities that AI is in a position to deliver.
- [24:12]
Benjamin Shapiro
Yeah, one of my big struggles as we've started to build out podcast os, the infrastructure we use to produce all of our podcasts is actually not overwhelming the AI with context. Right? Like I want to go and give it a 20 page master strategy document and then an hour long transcript and then the, the guest's entire LinkedIn page bio, including all of their posts for the last six months. It's too much information. It actually, practically speaking, some of the operations we wanted to execute can't happen because it's too much information and we just get everything to time out. And the thing that's actually been surprising to me, the problem isn't how do I give more rich information and let the machines sort through it and figure it out, it's how do I limit the information so it's only what's relevant so then the LLM can digest it. And I think that that's the problem with context engineering. It's not just give the LLM everything. You actually have to find a balance. And, and, you know, not too little, but also not too much. We have a little bit of the Goldilocks problem is that goldilocks what's the three wolves? Yeah, three bears. Three wolves. Anyway, we've got a problem of finding.
- [25:29]
Scott Brinker
Balance 100% I more eloquent than anything I could have said.
- [25:36]
Benjamin Shapiro
So let's move on to our next topic. We talked about what happened last year. Context, engineering, AEO versus SEO. Let's talk a little bit about Martech and tooling. We saw an expansion in the number of Martech companies, but we also saw some churn, right? We saw a little bit over 8% of the companies that are Martech companies just disappear. If you're building a martech company in 2026, what verticals are you thinking about? Where there's opportunity for expansion in Martech.
- [26:09]
Scott Brinker
Ooh, wow, that's a. You know, I mean, if I could answer that question, you know, definitively on demand, you'd be vibe coding it right now. You know, I think one of the challenges that is happening now in the environment is it used to just be like, okay, if I have a better mousetrap, if I have a way to build a better, you know, solution than the incumbents, you know, I can do that. I find my unique strategy, my niche, you know, I go after it. And it was very much about a battle, a competitive battle with commercial solutions. Oh, is my commercial solution better than yours? Where it's getting very tricky right now is because AI has made it so easy for people to build software. I mean, professional software developers, you know, leveraging leaks, coding assistants. I mean, you talk to people who are really good software engineers, and the way they're leveraging these AI assistants to like 10x their productivity, it's pretty impressive. And then on top of that, you have, you know, for more of us amateurs, you know, these were vibe coding things that, okay, we can't use for creating big complex software, but boy, actually using it for small little apps and small little automations can be very valuable. But between those things, you've got a place now where this ability for businesses to create their own custom software that really tailors to their particular operations or their particular customer experience that they want to deliver. This is a new player in the market. And so now if you're thinking about bringing a commercial Martech product out to the world, you've got two sources of competition. You're one, like, okay, well, I'm competing against all these commercial solutions that already exist out there, but wow, is what am I able to create and produce better than what my prospective customer could just build on their own and maybe even build better on their own for their tailored uses. I'm sure there are still going to be apps that pass both of those tests, but I think it's a much smaller universe, you know, than what it was just a year ago.
- [28:18]
Benjamin Shapiro
Yeah, I've heard it described as the era of personal software. Right. I can go and I can develop my own solutions to solve personal point podcast os. Right. How we created what this. Not to talk about it all the time, but like I created and Vibe coded 100% of it, a process that goes end to end to produce podcasts. And sure, there's humans in the loop and that stuff's important, but like it is me building software for my company and my specific needs and then trying to replicate it so other people can use it. The application of software is totally different now. Where it used to be, these off the shelf, you know, platforms and then you had point solutions and now we have personalization. I didn't hear you actually answer the question, but I think what you're saying is I would build some sort of a solution that facilitates the development of personal software. Am I putting words in your mouth or is that where you're going?
- [29:16]
Scott Brinker
Yeah, well, actually, so the challenge with that is there's already a lot of companies that do that, including now like, you know, Google, you know, their new anti gravity, they're always lovable. So yeah, I probably actually wouldn't try and build a new personal software builder. Where I think things could be really interesting is that there is actually a big gap in the market right now and it's around this concept of orchestration. So we've always had a lot of moving parts in marketing and anyone in marketing ops will tell you as we've gone more and more, that's just become really hard to keep track of everything, make sure things aren't breaking. I was disintegrating to this other thing. It's a lot of work now with AI and you start talking about empowering all sorts of people to build all sorts of agents and automations on their own. All of a sudden it's like in this perspective of 10xing, the amount of complexity and things that are running around in our business that's not stable. It's one thing to say like, hey, for an individual you can do all these wonderful things and whatever you want, that's great. But when you have a company of 300 individuals all doing that, okay, now this starts to become a bug, not a feature. And what is really needed and everyone kind of largely agrees on this, is like, okay, we need software that is going to serve as the guardrails, as the orchestration engines. So that, yes, we want to empower people to do lots of things on their own, but they have to fit it within a certain set of structures and rules. And right now we don't have great systems that really provide that sort of orchestration and guardrail for the company across all of these different kinds of AI capabilities. I think we're going to see that software emerge. And probably the only challenge with it is I think a lot. I think pretty much every major company in this space all wants to be in the business of being at that center of the orchestration. But, you know, one way or another, we're going to get that orchestration capability as users.
- [31:17]
Benjamin Shapiro
It's funny, we see this actually on the creative side where, you know, there are lots of solutions. AIR is one of them. There's a sort of whole host file stage, I think, is another one where when you're doing creative work, it automatically checks your brand guidelines and makes sure that, you know, nobody in these large organization publishes an Anheuser Busch ad to a place where kids can see it because it's regulated out for beer ads to be on certain channels or, you know, whatever the example is. And so we've got very strict brand guideline tooling, but now we're talking about orchestration tooling that has to sort of fit into the company's guidelines of how we're developing software. Because essentially what has happened this year is you've gone from your team of 300 people where 50 to 100 of them were engineers. Now 300 of them are engineers. Right. Some of them are in the engineering function, but the marketers are building their own software to do their own things, and there's a lot of risk there and a lot of instability. So you're saying that rules and regulations in orchestration is really where there's an opportunity?
- [32:21]
Scott Brinker
I think there's a lot of opportunity there.
- [32:23]
Benjamin Shapiro
Are there any areas in Martech or any verticals that you think are really in danger in 2026?
- [32:32]
Scott Brinker
Hmm, well, I mean, so many of these things have just basically been absorbed into the core AI assistance, you know. So, for instance, like, there was a whole category of software for helping you with writing category. Yeah, I mean, some companies still around, but yeah, no, I mean, it's like this has just been acquired by, you know, Chat GPT. You know, some of the other examples, this idea of like, oh, I want to research a prospect, you know, like again, to basically go to ChatGPT or Gemini and say, like, hey, all right, I want to talk to so and so at this company. Find out everything you can about this. You know, the. It just, you know, and these used to be categories of, like, competitive intelligence, you know, and again, it's not that there aren't edge cases where people can be like, no, no, no, I can still do more in this category than, you know, the core LLM can do. But for a lot of people who just need, you know, the edge, 80% of the value for 20% of the work, so much of that can just be done by these LLMs natively that, yeah, it's a real threat to a lot of those categories.
- [33:41]
Benjamin Shapiro
I was having a conversation yesterday about demand generation and building a go to market, and it used to be, well, you go into Sales Navigator and you build the list and you go to the company and you take the data out and you go to ZoomInfo and you, you try to extract something. Then you go to another tool and you get an email, and then you have to validate the email and you have to da, da, da, da, da, da. To try to get something that is relatively relevant to your core ICP. Now you go into clay and you say, I want a list of every B2B marketer with over $10 million that has a podcast that's, you know, has a brand marketing team, and it's there. And then you can ask for all the details about whatever show that is. I'm spouting off our target market.
- [34:23]
Scott Brinker
I figured this wasn't just a hypothetical.
- [34:27]
Benjamin Shapiro
What's on my mind, hypothetically? You're running a company called I Hear Everything. But the moral of the story is, like, there used to be these really sort of complex processes for us to do the most minute thing about just demand generation and even just list sourcing. And now it's like it's all one tool. It's all done and it's all immediate. What is the output of that right? When we have all the information at our fingertips so quickly, other than a total sense of overwhelm because the world is our oyster, what do you think that does to the market?
- [35:00]
Scott Brinker
This is the recurring challenge of technology adoption in go to market. I mean, more broadly, but certainly in go to market, which is a new technology enables a capability, a set of early adopters are like, oh, great, here's how I harness this to get a competitive advantage. And they do get a competitive advantage. And then it crosses the chasm and it becomes something that, like, oh, well, everyone, you know, kind of gets that capability. And guess what? It becomes the new table stakes and it's no longer a competitive advantage. This has been the cycle where it's played out. I mean, certainly for the decades that I've been, you know, doing this work in Martech. The only challenge now is it feels like the tempo of that is just accelerating where, like, you know, you can come up with some things that, like, give you an edge today. But the degree to which, like, yeah, most of your competitors might be in a position to have that same capability, you know, 12 months from now, it's. It's hard. This is, this is the new treadmill's the wrong word because treadmill is just too damn slow. This is me like, you know, trapped to a rocket ship or something. You know, I'll try and keep up with it.
- [36:18]
Benjamin Shapiro
This is the new private jet of treadmills.
- [36:21]
Scott Brinker
Yes.
- [36:22]
Benjamin Shapiro
All right, Scott, I want to move on to our last topic. The martech podcast turned 8 years old this year, which means that you've been on this show for at least eight years running. Thank you. And we've always done a year end prediction for the upcoming year, and we've done some predictions so far. But I want to open the floor for you and I want you to close your eyes for a second and just imagine what you're going to be talking about, what happened at the end of 2026. So when you think about where we are in December 2026, what do you think the world is going to look like for the martech industry?
- [37:05]
Scott Brinker
I believe very strongly that the AI revolution of 2026 is not going to be AI for marketers. It's going to be AI for customers, for buyers. You already start to see this emergence of buyers basically taking control of their journey. I mean, we've gotten frankly very good as marketers of structuring these very well defined journeys that we would keep pushing people to like, no, you have to do this before you can take this step. You have to fill out this form here before you do that. And, you know, customers may or may not have always enjoyed that, but they sort of played along as well too. And we build all these playbooks and processes around this. Well, now AI is giving a most prospects and customers to be able to say, like, you know, I actually don't want to play that game. I'm just going to have my AI agent do the things that I want and answer my questions. And you as the marketer, you can choose whether you want to support, you know, what my AI agent is doing. Are you making that content available so it can consume it or not. Are you trying to put it behind, like, you know, barriers or whatnot? But I don't really care about you anymore because these AI engines are giving me the ability to really take control of the journey the way I want. This already is starting to happen here in 2025. I think the narrative of 2026 is it's going to, like, take off like wildfire. And that is going to be the thing that breaks so many of the existing playbooks that marketing has been doing. But the good news is it's an opportunity for new playbooks.
- [38:42]
Benjamin Shapiro
So I think that this is an extenuation of an existing trend we've seen. Number one, the customer journey is not linear. I've been saying that for years. But the second thing is, and mostly since 2024, but now really accelerating, is that the power is in the consumer's hands. Right? They don't want to talk to sales. They want to do their own research and then come to you when they're ready to execute. So when you talk about the customer journey being more an extenuation of that, you know, power of the consumer, what are the consumers going to be doing to continue to research? Are they building their own AI agents to source products for them? Are they having personal assistants? Are our agents talking to their agents? What. What do you mean?
- [39:36]
Scott Brinker
Yeah, I'm sure there will be some who take it very far with like build, particularly B2B customers, you know, that can invest some effort, but most of it's just going to be naturally through their use of AI assistance and agenc browsers. Like a great example of this is. All right, pick. Pick a Martech company out there that is a large one with a complex product and a complex pricing scheme. Go to their pricing page. Now. You, as a human, you can look at. All right, let me try and calculate this. What do I need? What is this going to work? Is this the real price? Is it the, you know, how do I know what I should actually pay? These are things that people have actually, like, we've gotten used to as customers of like, ah, crap, I figured this out. Ultimately there's going to be like some bespoke negotiation with sales and maybe eventually I'll figure out what the actual price for me is going to be. If you go to these pricing pages now and you use an agentic browser, you know, like say ChatGPT Atlas or, you know, perplexity Comment, and you're like, okay, my agency browser, can you. Here's what I'm going to be looking for. Can you tell me what I should expect to pay? And it will do the analysis for you of breaking down all these different scenarios. It will draw upon all the information it's collected across the entire web of like, and here's what we think we know about, like, the discounting practices of this company and here's what you should be expecting to pay and oh, would you like to see a comparison to the pricing of, you know, like two or three of the competitors, you know, of this company? I've done this with people. I've actually walked through on stage with folks for this too. And like, first of all, like, the people who are buyers in the audience are like, oh, wow, that just, that's wonderful. That's, that's exactly how I wanted this to go.
- [41:23]
Benjamin Shapiro
I'm going to go get a golf membership because I don't have to do pricing comparisons.
- [41:27]
Scott Brinker
And then meanwhile, like, anyone who's like a sales manager or sales director, you know, from a vendor in the audience, you know, like, they start looking for the bar because, like, you know, this blows out the entire control playbook, you know, pricing and discounting and things like that. That used to be where the leverage was in saying, okay, at least here becomes the choke point where we can now fit people into our process to extract the information we want. And you get to a place where like, buyers are like, no, we don't have to play your game for that. We, we actually have the, the information asymmetry starts to shift and it is actually that the buyers have more information than the sellers do. And that's going to be pretty wild.
- [42:11]
Benjamin Shapiro
What do you think the downstream effect of the consumer, consumers taking control over the process is in terms of like, business performance?
- [42:21]
Scott Brinker
You know, my Pollyanna answer to that is at the end of the day, it comes back to having great products, great brands, great services, you know, people. That's still ultimately, at the end of the day, what people want. We've just gotten into a mode where we got so good at so many of these, like digital marketing go to market practices that we, we felt we could, you know, good product or not so good product. You know, we had a lot of ability to like, you know, put our thumb on the scale, you know, of how we might find and win customers. I think we're going to lose a lot of that leverage, you know, that we've had. But at the end of the day, customers are still looking for great products, great companies, great services. And I think the companies that really like, lean into making that their top priority that's, that's going to be how you perform.
- [43:16]
Benjamin Shapiro
Here's what scares me about what you're saying. It's about predictability, right. When, when you don't have any control over what our pipeline looks like, what is our conversion rate. Right. You don't own the sales cycle, we don't own the, the push mechanism to go figure out what our reach is. It becomes very hard to predict what the output is. And so the thing that scares me a little bit about, it's great that consumers have all the choice and all the control and you know, they hold the remote now. Sorry, that's a big fight at home over who holds the remote. I've got two young kids, the consumers hold the remote. And the problem with that is there's going to be a lot of businesses that you're going to see big ebbs and flows. And you know, some good products might not be able to survive because their business has fluctuations. Right. They don't have anything that they can predictably bank on. And so I think that volatility creates some concern for me.
- [44:16]
Scott Brinker
Yeah. Although I'm not convinced that it's going to be dramatically more volatile, you know, because again, if the core product or service has a certain amount of demand, you know, there was a world where we had this before the web, before digital marketing took off and you actually had relatively, you know, predictable like, you know, sales projections and cycles on this. Like we didn't have as much information, we didn't have as much micro level controls, you know, but there was, there was still a fair amount of continuity. And the other thing is like, it's not like all the levers have gone away, you know, our ability to, hey, listen, I, I need more pipeline. Okay, well how do I have customers, like discover me more? Well, okay, there's so much I can do through like aeo, but like if I want other ways of doing it, like, okay, well where are my customers? You know, where's the conference I should be at here? Where should I be having a billboard? Where should I be looking at doing paid advertising? I mean, and again, this kind of harkens back before all the, you know, instrumentation and digital magic we had, you know, the past 20 years, you know, the way in which companies help grow demand on a stable and predictable way was like, okay, we've got all these other channels where we can do that. So it's, I don't think all the levers have gone away, but some of the levers that we've gotten really addicted to over the past 10 to 15 years. Those are now shifting in ways that we're going to have to adapt.
- [45:48]
Benjamin Shapiro
Yeah. My big takeaway is the things that don't change when technology does is the importance of having a great product, the importance of having a great brand and being customer friendly. Right. Being someone that people want to work with. And I think that those are things that will carry through agentic AI and the era of the customer. As Scott, you've said 2026 sounds like.
- [46:09]
Scott Brinker
It might be lovely.
- [46:12]
Benjamin Shapiro
All right. Well, Scott, I always appreciate you coming on the podcast. If I don't see you before the end of the year, Merry Christmas, Happy New Year's, and you know, year number eight, God willing, we'll be back here in a year for year number nine and God knows there'll be more to talk about.
- [46:29]
Scott Brinker
Sounds great. Benjamin, thank you so much for having me back. Have a happy new year.
- [46:33]
Benjamin Shapiro
You too. And that wraps up this episode of the Martech podcast. Thanks again to Scott Brinker, the godfather of the Martech industry, for joining us. If you'd like to contact Scott, you could find a link to his LinkedIn profile in our show notes or on martechpod.com you can always visit his website, which is chief martech.com it's chiefmate. M a-t e c.com if you haven't subscribed yet and you want a regular stream of marketing and technology knowledge in your podcast feed, hit the subscribe button in your podcast app or on YouTube and we'll be back in your feed every other week. All right, that's it for today, but until next time, my advice is to just focus on keeping your customers happy.
- [47:17]
Scott Brinker
Foreign.
- [47:36]
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