Forrester's Chuck Gahun on AI agents as decision makers in the buyer's journey

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Greg Kilstrom: Hi, I'm Greg Kilstrom, host of the Agile brand, and here's a question for you. What if your next customer isn't a person but an AI agent acting on their behalf? And what if that agent is evaluating your brand on a purely logical, data driven basis, completely devoid of the emotional hooks your marketing has always relied on? Agility requires not just adapting to changing customer behaviors, but also redefining who or what our customer even is. It demands that we build operational and strategic frameworks that can cater to both human emotional drivers and the cold, hard logic of machines. Today we're at Forrester CX Forum east in Brooklyn and we're going to talk about a fundamental shift in the customer journey. The rise of the AI agent as an influential and in some cases decision making Persona. This isn't just about using AI in our marketing, it's about marketing to AI. We're going to explore what it means when our brand's message needs to Be optimized not just for human perception, but for machine interpretation and evaluation. 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. Now let's dive in. To help me discuss this topic, I'd like to welcome Chuck Gahoon, principal analyst at Forrester. Chuck, welcome to the show.

Chuck Gahoon: Thanks for having me, Greg. I'm looking forward to the discussion.

Greg Kilstrom: Yeah, looking forward to. Definitely to diving in. Looking forward to the event today and tomorrow. Uh, before we dive in though, why don't you give a little background on yourself and your role at Forrester?

Chuck Gahoon: Sure, sure. So I cover content management, tech, commerce services and strategy. So that means I've written and researched across not only content, but also how commerce strategies are being impacted as a result of content now and all of that. Right. So I've authored Future of Content, Future of Commerce. I've written several pieces on content and commerce strategies in the age of AI. Uh, I've spent the last 25 years of my career in digital tech, so I've helped guided leaders through a lot of changes over the years. E commerce, mobile, cloud, and now AI. So it's been fun.

Greg Kilstrom: Yeah, yeah, love it. So, yeah, let's dive in and, um, want to start with, you know, from the strategic standpoint and even just to ground our conversation. Agentic AI is certainly being used a lot. There's a lot of people talking about it, uh, and things. How do you define it? And, uh, you know, how do you define it in this context? And you know, is this simply an evolution of SEO for voice, search and answer engines, or is it a fundamentally new type of audience that requires its own strategy?

Chuck Gahoon: Yeah, yeah, great question. So I'm going to give you multiple answers that all build upon each other. So the first one is if you're thinking about AI agents, I think what I would want listeners to take away is that the word you're thinking about there is agency. What is the level of agency that this AI agent has? And I think that is a good barometer to start thinking about. The official Forrester definition for an AI agent is an AI application that is tuned to act on behalf of an enterprise or an individual it can perform tasks, it can make decisions, it can interact with data and other systems, but that's really what it's doing. And the key word again there that comes out is autonomously. So agency autonomy, what is the level of autonomy that exists in AI agents? And there's a spectrum there that I'll talk through a little bit more detail in a few minutes to also orient, uh, the listeners. Uh, how is AEO and SEO like? Is this just another form of SEO? Not quite. AEO does a lot more than just SEO. There's a think about information architecture, topical depth of your content, think about third party sentiment. AEO is really curating and pulling all of that to create what are the metrics that are driving answer engines and how to optimize content for answer engines. So it's a little bit more than just SEO. Fundamentally though, I think there is a duality that exists between human consumers and AI agent consumers. So if you start thinking about it that way, there's a whole host of things that are different. We're driven by emotion. They're obviously machines, so they're driven by logic. Right. We're shaped by identity, like who we are as individuals, and they are shaped and built by value, like what is the value or, uh, outcome they can achieve. Right. That's how we've engineered them. We are influenced by trust in relationships, they are influenced by trust in context. Hence the AEO storyline. Right. We browse in deterministic experiences. So what's a deterministic experience? Think about a navigation menu on a website. It asks you to go in a very deterministic path. Right? Well, AI agents, answer engines, these are all non deterministic experiences, meaning they're actually building responses on published content, gathering third party sentiment and creating an faq, even a dialogue back and forth with consumers. I'm sure many of our listeners, including yourself, have probably engaged in all of that. We are limited by how much we can hold from the cognitive load perspective. They're limited by context windows and we reason from lived experience. They're looking for patterns. Right. Uh, and finally, you know, we orient around tasks. We are human beings, we work a certain amount of hours. And I think this is the part that's really starting to shift and change how AI agents are coming into content and commerce, which is that they're oriented around outcomes and can work 24. 7. Yeah, yeah. So if you start thinking about that in all of what I just shared in the bigger, the larger spectrum, you start to see this agentic AI era offers a new promise for businesses and consumers, a lot of opportunity.

Greg Kilstrom: Yeah, yeah. Well, and I mean it seems like the, to simplify it as kind of the next level of SEO. For instance, it's, it's kind of shortchanging the entire process to your point, you know, there's, there's a very different thing that we're optimizing for and it's, it's uh, split more than it ever has. Right. I mean, SEO felt a little closer to based on human intent. Right?

Chuck Gahoon: Yeah, absolutely. Yeah, absolutely. And SEO is, just to be clear, SEO is still a thing. It might be starting to lose its dominance a little bit. However, we still advise a lot of clients on SEO. That's an important part of their business to this day. Right, right. Yeah, they continue to be, they don't

Greg Kilstrom: get rid of things, they just keep adding more.

Chuck Gahoon: Right, exactly. That's, you know, big tech growth. That's how it goes.

Greg Kilstrom: Exactly, exactly. So, um, your work mentions, uh, combining human emotions and machine logic, which, you know, can seem paradox, paradoxical. But how should a brand strategist begin to reconcile the need for this compelling emotional brand story which still resonates with the humans, with that need for the structured machine readable data that you talked about, that geo, uh, uh, and AI agents would need?

Chuck Gahoon: Yeah, good question. I think what's really transpiring here, uh, for brand marketers specifically and brand leaders, is as agents and AI training crawlers are coming to your website, they're looking for semantically rich content. They're looking for, think about those detailed PDP pages. The great example I like to give is, remember Those old school B2B sites that had like all of those specs about the parts. That is a gold mine for these agents. However, on the other side of things, us as humans, we are persuaded by emotional storytelling. So think about those beautiful JavaScript overlays and how you scroll through and it's just invoking your emotions to get you to purchase a product. I think what we're seeing here is once we realize that, that emotional storytelling is not exactly what the machines are looking for, they're looking for semantic richness. You start to see the rise of this dual optimization happen where there are experiences for humans and separate experiences for machines. And in that motion, what's happening with digital experiences right now, and a lot of marketing leaders that I advise are investing money in this, and our data shows this too, uh, is that they're looking to redesign their current properties to be much more emotional storytelling for humans and then create specific experiences for machines to gather the Content and data and some of this AEO optimization storyline that's coming into play. That's why the investment there's Right. And these agentic channels, look, at the end of the day they're emerging. It's white space. Many of the inbounds I take around agentic commerce as an example. People don't want to miss the boat. That's the thing. Right. They feel like this is the Amazon moment happening again and they want to make sure that they are making the right moves early on. Uh, especially since these models, well, since these models are now being released so quickly. But also they're training like they're training a lot faster now so you can put out content and impact your brand and your product a lot faster than it was, I would say, a year ago. Yeah. And so the whole game is changing on that.

Greg Kilstrom: Well, and so then let's talk about operationalizing that because, you know, in addition to the models changing all the time, it feels like there's a new protocol that gets released every day. But I may be overstating that, but it happens often enough. So, you know, there's a lot to, to kind of wrap your, your head around. So what are maybe the practical first or second steps that a marketing ops or CX team should take to make their brand agent friendly?

Chuck Gahoon: Yeah, yeah, yeah. So this is a research, uh, that I just released recently and I think maybe last week it published. So we've been talking a lot about visibility with agents. Right. You know, make sure they robots txt and they can crawl your site and all that. And as I embarked on this research this year, uh, we wanted to push the envelope and say, like, how are we going to design content strategies to target AI agents? That's really where we need to go next. Yeah. Uh, and what we found through the research is that agents are looking for three things. They're looking for context, they're looking for fluency, and they're looking for trust. So as we start talking about operationalizing this, what should a brand or marketing leader be thinking about? Well, we've already got the baseline, regularly audit, tune, measure, website schema. Uh, do that, buy a tool that does that, have a services partner that does it for you, whatever works for you. But then beyond that, start thinking about what do you want to own in this space? Do you want to have a horizontal or a vertical content strategy? Meaning do you want to own depth in a product or do you want to own breadth in your sector? That is two different games that you would then be pushing content into market out for. So once you figure that out, then how do you give an agent context and fluency? Well, context is obviously about third party sentiment and all that. You have to make sure you're tracking it. You make sure that you are publishing content that targets that. Beyond that, what does fluency mean? Fluency is about, you know, I feel, I can't help but feel like we got really creative in certain places with product names and descriptions and what a brand does. And it's an eco friendly brand. Like agents don't. They need to be able to reconcile you within your sector in the same language that everybody else in your sector is using.

Greg Kilstrom: Yeah.

Chuck Gahoon: So that creativity needs to be standardized. That's, that's the fluency piece. And then the trust thing is like you have to keep publishing the content regularly. They have to know that you are a topical source that they can keep coming back to. And that trust not only embodies in how your brand is represented, but it also, uh, embodies in how the agents are then publishing on top or building responses on the published content, which I've just started thinking about recently, which is, you know, it used to be the last mile. Used to be you would publish content on a website or a, uh, mobile app. That was the end of the road.

Speaker E: Right.

Chuck Gahoon: That's like come back now. It's like the middle of the road. And this is some of the research I'm doing now, which is agents are taking that published content and then are building the experience, a non deterministic experience on top of that. So they are essentially generating the response. I think we all know this, but when you start thinking about it that way, you realize like, oh my gosh, my published content is not at all what a consumer might see.

Greg Kilstrom: Yeah, yeah. Well, and because to your point, you know, you use the term eco friendly. Yeah. So what is that? I know what that means to me as a human. Maybe there's some different semantic differences between one human to another, but generally speaking it adheres to some feelings and some stats and things like that. But to an agent it's gotta be very zeros and ones. Right. So what does eco friendly has to mean? Other attributes. Right.

Chuck Gahoon: And then in the sector, right, eco friendly could mean different things for different verticals and different types of products and goods and services. And so when you start thinking about it that way, you realize that you have to be really semantically clear on what information you're putting out for AI agents. Yeah. And that has become a huge focus area for brands and marketers. I mean we're calling it. You know, we have B2B and B2C marketing. We're starting to call this, this is definitely a B2Amarketing strategy now. Yeah, yeah. Like we have to start marketing to them. It is what everyone is starting to focus on just because honestly, the real reason why this is happening, just to call a spade a spade, is that answer. Engines are intermediating so many consumer journeys. Like we think about retail, that's the easy one. But think about health care. Where do I find the closest doctor? And then that ends in some kind of a. Find the physician, go to the doctor, ends in some kind of a transaction. Then you think about travel and hospitality. Right, right. You think about it's even playing out in government space. Government spaces. So like it's touching so many different verticals because it's making. Helping consumers get to answers faster. Right, right. And that's where the game is changing, especially on specific types of products and specific types of services.

Greg Kilstrom: I mean, do you think it's. I mean, I'll just give my own thoughts here, but you know, I, I feel like it's helping brands to quantify sort of the, the squishy, like unquantifiable things that they've said, but it was difficult to back up. Like, do you. In other words, do you think it's a good thing that brands are being kind of forced to quantify and, and characterize in very kind of almost binary ways what their, what their brand stands for?

Chuck Gahoon: Mhm. Absolutely. I'll give you a very discreet example of this, which was so cool. And I was also, I was talking to a brand about this as part of this research and they said, look, we have lived this firsthand. We released a product last year, it was R1. It was essentially a flop. We got so many bad reviews about it all over the web. We got like buyer beware. So we hired an agency and we said we need to optimize our content. Like we need to solve this for our brand. It's impacting our brand. What do we do? And wouldn't you know it, what they did was on their owned Property, they designed FAQs as they released the next version of the product. FAQs to target the negative sentiment and how they have addressed it so that the training crawlers would come and get that as well. Yeah. And sure enough, three or four months later, as you start running searches on their product, they showed it to me. And it literally, it says exactly what you would want it to say. As a consumer that's looking to Buy the product saying this product previously had negative reviews. Buyer beware these sentiments back in this time frame. Since then there's been a new product that's been released, it's receiving better reviews and you know, it sort of gives you the sources it's getting it from. Including their own site.

Speaker E: Yeah.

Chuck Gahoon: And so you see like that is an example of how they are targeting and to your question, yeah, it's putting brands into this space where they have to address what's happening with their product, their services and market and how consumers are perceiving it.

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Greg Kilstrom: Doing that across multiple teams. You know, CX marketing product it you know, how do you recommend that leaders do that? You know, do this cross functionally because you know, it's, it's they've been used to doing this, you know, one way, you know, maybe a couple ways over the last, you know, 20 years since the, the Internet. So um, you know what, what does this look like when it's done well, cross functionally?

Chuck Gahoon: I'll give you one example that is a very powerful cross functional example. And then I'll give you another example in how to, how uh, leaders should perhaps think about content and content strategy in this era because they're both a little connected. The, the example that I got from General Motors and I was talking to their head of search earlier this year and his. We published this in the research. Their story was very interesting. They wanted to use answer engines to help consumers find more cars. But let's be real, they don't sell cars. The dealers sell the cars. Right. So what they did was they embarked on a cross functional ngm, cross market dealer powered optimization strategy for cars. Offers pricing, availability, all of it across angel engines. So that's, they did that together in, in concert. How did they really achieve the scale so that it started impacting their bottom line? And they wouldn't tell me what the bottom line impact was, but.

Greg Kilstrom: Right.

Chuck Gahoon: I uh, got the sense of where it was relative. It was quite positive. But he wouldn't tell me how much. Uh, but the, the thing I'm trying to point out there is as they went about that, what they did was they also did what we call earned authority. So they also bought advertising to amplify that across paid channels. And both of those strategies put together has given them more of a foothold on answer engines. When you ask questions about General Motors or even consumers are curious about a GM car.

Greg Kilstrom: Yeah.

Chuck Gahoon: It's a very curated response that the answer engine will give. So that's the operationalizing it across teams. That's what good looks like.

Greg Kilstrom: Yeah, yeah. Teams and car brands and all that.

Greg Kilstrom: Right?

Greg Kilstrom: Yeah, yeah.

Chuck Gahoon: And then the other one that's more content strategy related, which is if you start thinking about, you know, your question about how should teams be thinking about operationalizing something like this? I think we've been stuck in this world which is that, you know, uh, I was talking to Harman International, they own jbl. Yeah. And their sentiment was, you know, when you start thinking about content strategies for answer engines, why would we promote content that basically talks about good headphones for runners? That is a very crowded space. So they have deployed literal teams across their org to think through content strategies that help them think about white spaces, which is how might a consumer search for this? And even if they do search for it and we do surface it, how do we draw the consumer to the next step into a white space? Area rather than a crowded headphones for runners, you know, sweat wicking, all of that. How do we pull them to the other parts of our product? And that's an example of where they have teams deployed, you know, around the country thinking through content and content strategy in this case for headphones.

Greg Kilstrom: Yeah, yeah, well and that still seems like something humans could do, could do well as opposed to uh. Yeah, as opposed to the agents themselves. That's great. So let's talk a little bit about measuring, uh, measuring and proving value. Certainly you know I feel like I'm sure you're hearing the same but you know everyone seems to be asking to prove the ROI this, this year. You know like last year it was all about experimentation. Now there's a lot of, you know, the, the bills come due so to speak. Um, you know, what's the business case for investing in this now? And you know, how can a marketing leader, you know, connect optimizing for AI agents to things like, you know, whether it's revenue, market share, things like that.

Chuck Gahoon: Interesting you asked this because just in the last two weeks there have been acquisitions and build and buys like ah, we have Contentful, uh, was acquired by Salesforce. We have sitecore acquiring company called Scrunch which was doing a lot of AEO optimization and we even have optimizedly building out their own AO platform. And uh, what everyone's going and Google is releasing insights on their dashboard on merchant center. What everybody's starting to go after is this concept of like data and insights for answer engine so you can understand connect the prompts to the performance of your content basically. And as this start, this space starts to mature. What we're going to start finding is not only that marketer is going to be able to target it better but through the measurement and being able to get some of these insights we'll be able to start connecting it to ROI and connecting to larger content programs. So what is the business case? What should you be doing as a marketing leader around this to build the case? This is a traditional content strategy business case in really what would be more of a white space frontier for your brand? I think that's the best way to put it. And when you step back and you say like what is required to do this? The advice that we're giving folks actually is this is not about tech implementations, this is about taking the tech you have and building your content strategy, your information architecture, your topical. You might have to republish content like build a content program. That's the business case. It's not for a tech investment. It's more for a broad content program that drives measurable results for your business over time. And that also gives you a chance to see how your content's performing for machines versus humans in the broader strokes of your brand, like over time. Right.

Greg Kilstrom: So I mean, is this, uh, I mean, is it kind of a distraction to use some of these, I mean, marketers and we all love our acronyms and everything like that, but you know, is this a, is this a new Persona then? Is this a, like, what's the right way to think of it without getting kind of bogged down to your point in the, the tech investment part of this? And, and you know, it sounds like it's almost just, um, another nuance to content strategy as, as, as you characterize it.

Chuck Gahoon: It's a new nuance of content strategy. And I think the one way to think about it is that you, yeah, you have a new, I don't know how to say this, like segment or new Persona. Definitely that's a machine. Yeah. You have a lot of human Personas. Sure. And now you also have a machine Persona. And over time, my fundamental belief to the research that as I've just wrapped it up and then I'm embarking on the next set of research on this, is that we are going to fundamentally have different types of agents over time.

Greg Kilstrom: Yeah.

Chuck Gahoon: And through that we're going to need to build different types of agentic strategies. So I'll give you one to tease and just leave the audience thinking with about which is a question that I ask in my, in the research paper is would you ever design a agentic loyalty program or a specific drop on an agentic only channel like Nike does drops all the time on their mobile app. Right. Would you ever do something like that and build hype for humans? But it was only available in the Gentec channels, meaning my consumer agent can go find that, but I cannot go find that as a human on a mobile app or a digital experience. So like you, I think over time we're going to see very quickly that marketers are going to start targeting specific strategies like that using content to build demand before humans can maybe browse it. Emotionally, that might also be another indicator. And then you can see how, then that transverses to loyalty, which is also very interesting. Like how do you get them coming back? Like if I'm a loyal customer. Google already is thinking through that in their agent to commerce spread of how to add loyalty into their merchant center. And so if you think about that, then, well, if you Know that I'm a loyal customer to whatever brand would you surface things that only my agent can get to through that loyalty. Right, right. And so you see this, this world is emerging. So when you say, when you ask me like, how should a marketer be thinking about this? This is just another buzzword. It, it is, uh, we have to start thinking about standing up the whole host of machine Personas over time.

Greg Kilstrom: Yeah.

Chuck Gahoon: And how you want to target them. And that's going to be different. The cool part is that's gonna be different for every brand. It's gonna be different for every product family. Right. Like think about product like jackets that are purchased and use in the north in North America versus EMEA versus apac. Like you can start thinking about how you target differently in different regions. There's a lot there.

Greg Kilstrom: Yeah.

Speaker E: Yeah. Wow.

Greg Kilstrom: Yeah, definitely. Well, yeah, and I guess you know, to, to that end and you know, talking a little bit about the, the future as, as we wrap up here, we're still early days, you know and you know, as I mentioned, you know, there's still protocols and updates to protocols coming out every, every week or so. But what does a mature agentic commerce ecosystem look like? You touched a little bit on it just then, but what should we be expecting in the months to come?

Chuck Gahoon: 2 major lenses to look at it from owned environments and non owned environments. So the agentic commerce ecosystem is going to be stood up in both of those facets. So you're going to have more and more chatbots, you're going to be able to do more on these chatbots on your owned properties. Uh, and then there is this idea that we've been talking so much about distributing your content for answer engines, AI agents, they're going to come and get it, you're going to push it. All of that's going to happen. That's the other half of agenta commerce. Over time you're going to find that we're going to get to a point where the thing that's really going to be holding us back is consumer trust and the payment protocols. We just released metrics yesterday. In fact, one of my colleagues, Lily, who covers payments, shared with us that, you know, release research basically saying that consumers are very relatively apprehensive to be sharing their payment details on any of these. And it's for all the reasons that you would expect. Right. They're worried about fraud, they're worried about liability. 44% of consumers are saying, well, if I engage in a commerce task on an answer engine and something goes wrong, who are you going to hold liable? And 44% are saying the answer engine. Think about that. You buy something from a retailer's website, something else shows up on your door, who are you going to hold liable? Yeah, yeah. So, uh, there's. We've got to cross some of these trust thresholds. How will the agentic commerce ecosystem eventually evolve? I think eventually we will get to some motions of autonomous agent E commerce back to where we started, from agent to agent interactions. And what that looks like is I have delegated an agent to refill my toner cartridge. When it goes to a certain point, gets below a certain threshold, the printer sends a signal. I have authorized it once. After that, it has its own autonomy. So every time that goes low, it refills it. Uh, I do not authorize it again. Now if I were to keep authorizing it, which is kind of where we are now with Amazon's Buy for Me, where you can authorize an AI agent on Amazon to go buy a shirt or whatever product you want when it hits a certain price. That said, that is semi autonomous in our mind, which is that we are authorizing the agent to do something very specific. And when it's done with that task, it's complete. But on the printer, the ink cartridge example I gave you, it had an objective, an outcome. Don't ever let the cartridge get empty. So it's going to keep operating against that. And that is what works. Sort of like full autonomy. Where have we seen this so far? Honestly, not many places. It's actually interesting because in B2B we have seen some motions of this happen where think about like intelligent factories wanting to refill. We've started to see agent to agent communication to just keep factories running. That's starting to pop up. I think over time that will probably take off, uh, bigger and bigger. But that's kind of long answer to your question. But yes, the ecosystem will evolve in many ways.

Narrator: Yeah.

Greg Kilstrom: And let's talk a little bit about the risks as well. And you mentioned some of the lack of trust. And I mean, that brings me back to the early days of E commerce where people didn't want to type their credit cards in. But I feel like some of that's going to hopefully be, um, you know, all the risks will be mitigated. Um, but you know, what are the primary like, pitfalls or maybe unintended consequences that brands should be wary of now? You know, as they're, as they're beginning to adopt AI agents?

Chuck Gahoon: I think brands have a lot to consider. You know, we Another track of research that I just completed is something called distributed commerce strategy. So as businesses are thinking about this, they need to be thinking about a lot. This isn't like, let me just turn on my product catalog and let's the answer engine get it. You have to think about things like can this make money? You have to model your full cost serve, think about returns. Eventually you're going to be thinking about things like ad fees. What is it? What is the content overhead? What does the content program look like that we discussed then? Can you meet each channel's target content requirements? Question mark. There's a difference between Google UCP and OpenAI's ACP. And yes, you have to optimize your content differently for both. Is this something you want to do? I don't know. Is it going to be profitable? I don't know. That's. You have to do the math. Does your strategy flex for local and global? Like we found so many irregularities in the research for global regulations. So if you're a global operator, there's a lot in play on how you're going to bring agentic commerce or your products to market on agentic channels globally. Right. And then we've talked about tariffs, inflation, you know, wars and so on. But like, what are the economic shocks and can you survive that? Like, do you have cash on hand? Can you flex quickly? Like, how tight is your OPEX budget running, all of this? So those are some of the things that we are guiding leaders thinking through. In fact, we've got a workshop here called Around Agentic Commerce that's diving into that. So folks can consider without just, you know, we're calling it strategy over urgency. A lot of leaders are feeling like they're being left behind, but we're guiding leaders to say be more strategic in what you're doing, what products you're selling on what channel and why. So that you can remain profitable as we go through this. Yeah, sounds great.

Greg Kilstrom: Well Chuck, thanks so much for joining today. I know, um, Forrester CX Forum east is kicking off in a little bit here today. What are you looking forward to most?

Chuck Gahoon: I am most interested in the keynote on consumer trust. That is we've got some data that's being unlocked there and I'm really excited to see how we're going to close that gap in the age of AI, because I fundamentally believe that once we start closing in on that gap, AI and the adoption of AI, especially agentic AI, is going to skyrocket. Yeah, yeah. Love it.

Greg Kilstrom: And last question for you. What do you do to stay agile in your role? And how do you find a way to do it consistently?

Chuck Gahoon: Good question. So I tend to read before Sunrise. That's something that I started doing a couple of years ago. So before the day begins, it's still dark outside. I start my day by learning I have like personally curated feeds and the podcast that I listen to. So then I usually go for a run or go to the gym to let it marinate. But that's generally how I keep up with what's happening in our crazy AI ah world.

Greg Kilstrom: Yeah, love it. Well, again I'd like to thank Chuck Cahoon, Principal Analyst at Forrester for joining the show.

Greg Kilstrom: You can learn more about Chuck and Forrester by following the links in the show notes. And thanks again for listening to the Agile Brand podcast. If you like the episode, hit subscribe and drop a rating so otherwise 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 GregKillstrom.com that's G R E G K I H L S T r o m 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.

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