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January 21, 2026
2025 Wrapped: The AI Moments That Actually Mattered
As AI automates more work, demand for human storytellers surges. Explore what this year’s AI boom revealed about trust and meaning.
Check out the full episode below! Enjoy The Exchange? Don't forget to tune in live Friday at 12 pm EST on the Greenbook LinkedIn and Youtube Channel!
AI is reshaping business faster than many predicted, but not always in expected ways. This year-end recap explores the paradoxes that emerged as automation took hold: shoppers guided by AI are 30% more likely to buy, yet data quality scandals threaten to undermine trust in these systems. Research professionals gain unprecedented efficiency while worrying about eroding standards. Most surprising? As AI handles more routine work, demand for human storytellers is surging—with tech companies paying premium salaries for authentic narratives in an automated world.
From P&G's AI factory to new marketplace dynamics that could reshape the internet, we examine what actually worked, what failed, and why the human element matters more than ever.
Many thanks to our producer, Karley Dartouzos.
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Transcript
Lenny Murphy: So now it's Recording. I'm going to tell them. We're Recording.
Karen Lynch: Let's go.
Lenny Murphy: That's where we are. We're going.
Karen Lynch: So what a festive day. It is our final Episode of the year, of 2025. It's amazing, Lenny. It's amazing, right?
Lenny Murphy: It is. It is. In Episode 114, it never ceases to amaze me that we've been doing this for 114, well, more than that, weeks. About 114 episodes. So it's pretty cool.
Karen Lynch: Yeah, pretty cool. So not only is it a festive time of year, happy holidays, everybody. If you're celebrating Hanukkah, happy Hanukkah. Celebrating Christmas next week, Merry Christmas. Have a happy new year. We will not be back till January because we will be partaking in festivities, as we do. But we really do want to celebrate the end of the year. So let's talk about what we've done this year.
Lenny Murphy: Yes, absolutely. Not only we can talk, we can show.
Karen Lynch: We can show. Show and tell. All right, so Lenny with a brand new shiny toy is experimenting with notebook LLMs. So Karley, thank God for Karley, shared some stats with us about what we accomplished this year, and Lenny's working in Notebook LLM, and the next thing you know, we have an infographic talking about it. So 46 episodes this year, 46. It's just so, the numbers do really floor me sometimes. 11,000 of our episodes were viewed across our listenership, so that's exciting to think about. That's significant, people, that's significant. 897 hours of content. This isn't even the CEO series or the Green Book podcast. This is the exchange.
Lenny Murphy: Just the exchange. Thank you to our audience.
Karen Lynch: Thank you to our audience. It's really fun to do this for you and to, um, and to, you know, bring you this value. But can we talk about the bottom left here, Lenny? What March 21st.
Lenny Murphy: What is it? I don't know whether that's correlated to those specific episodes, not, I'm not sure, but yes, March 21st and April 21st. Those were--.
Karen Lynch: When our listeners tuned in the most were those two dates. So that's so interesting to me. I don't know if 21 is our magic number, but maybe it is. So who knows? Who knows? But I'm down for the coincidence of the two different days. Is it any surprise what our hot topics are? Yeah, and I love that they made this one circular AI agents fraud automation ethics It's like progress, but wait progress, but wait.
Lenny Murphy: Yeah, and actually we should just point out one technical thing like literally Right before we started I thought oh, let's load this into notebook LS And it just took this list and generated this infographic with zero input. Zero direction. It just took it and created the infographic. So if you don't like it, blame Google.
Karen Lynch: Yeah, yeah, yeah. In an ideal world, this would be in green book colors, and we would have run it by marketing first and all that. But we literally did this five minutes before.
Lenny Murphy: But to your point, that's pretty cool. That it made the circle of those topics with the brain in between. It's like, that is pretty contextually astute.
Karen Lynch: This is what resonated with our listeners. And I do really want to call out, I'm so glad Karley pulled these stats together, that our number one Episode of the year was when good data goes bad, the $10 fraud shaking the industry. I mean, if you asked me to say that off the top of my head, I'd probably probably get there, the big data quality scandal that hit us last year. That was momentous for us. So of course, it's the one that everybody wanted to hear us talking about. So that makes a lot of sense to me. And look, the second one, also fraud related. Interesting, right?
Lenny Murphy: Well, even at the bottom is your research line, which is a fraud issue. So yes. And guess what? Sneak peek. I mean, it pops up again this week in new news. So we'll continue to cover these topics. Because I can argue almost everything we talk about falls into one of those buckets, to a great extent.
Karen Lynch: One way or another, one way or another. Well, except that, I guess, let's stick with AI and we will get pretty quickly to agents, but there's some holiday stuff that I want to talk about. You know, I think we've talked a little bit about this, like kind of what's going on, changes to human customer behavior. So Karley, we can kind of pull the image down because we'll move into topics of the week. We'll have a surprise for you later, another image. Tools are changing the holiday shopping game significantly. So Adobe actually reported in this article on what they have found, you know, in some of their research, but AI tools could drive $263 billion in holiday sales this year. So have you used any? Because again, I've done it again. I've gone right to, you know, chat to PT and enter some information, like struggling to come up with a gift idea for, he doesn't listen, my 24 year old son. Here's some things he's interested in. And it gave me a score of an idea. And I'm like, that's a brilliant idea. I didn't use an agent to purchase because I had to talk to Tim and then Tim had to do some other research, but the idea stemmed from AI. So I think it counts. It was an AI tool assist.
Lenny Murphy: So I haven't used it quite that way, but I've definitely, for recommendations, if I used it for search and for research specifically, I've used Rufus quite a bit. Yeah, Rufus. Yeah, we talked about it last week. Yeah, it's, yes. So, so yes, but what was really interesting about this, and this one, this is happening in real time, guys. So this is the first big holiday with agents, the shopping season. So we are seeing this transformation in real time. But the generative AI platforms, shoppers arriving on retail websites from Gen AI are 30% more likely to buy something in about four more engagements. And to your point, what is your example? That makes sense. If it's making really targeted recommendations.
Karen Lynch: Really targeted.
Lenny Murphy: That makes sense.
Karen Lynch: It makes sense because it, because it gave me the, it told me what I should, you know, gave me the idea. So I was primed to buy it because I like the idea. I want to buy this now. So I am very engaged. Because I was excited about the idea. And then, yeah, definitely likely to buy. Super interesting. You know, and I think that we're going to get more and more of this. This other article that we have that's kind of related is Stripe. I don't know if anybody's seen Stripe in action, you know, kind of a financial services company that does payment, you know, make payments easily and all that. But Stripes has now introduced a solution to help businesses get ready, not just for the purchase, but discoverability in AI, kind of helping with that, simplifying the checkout process. Like Stripe is like, we're in this game also, and we're going to make it easier for people to get this AI discoverability while we're helping them process their payments. It's just what's going to happen. So retailers really need to be paying attention to this because brands, retailers, brands, all of anybody in the e-commerce shopping equation. It's happening. It's happening.
Lenny Murphy: But believe it or not, we've talked about it multiple times. Bring it up again. What in this world where it is easy? So you still press the button, but you can see easily where you didn't, where you just set it up and let it run. When we're doing Shopper Insights, path to purchase, All that, those things are fundamentally changing. So, uh, and, and you know, it's retailers or, or brands, whoever is trying to understand, uh, you know, the drivers of selection, all of these things are now being impacted. Any, any normative, any norms we thought we ever had on predicting buyer behavior out the window guys, that it is unreliable at this point because this seismic shift is happening right now. Is it everybody? But the ship has sailed. We cannot make the same assumptions about anything that drives buyer behavior.
Karen Lynch: And you think about back to that, back to that first, uh, first piece that was on, um, you know, kind of the holiday sales, the, there was a, um, a number cited in there. I'm trying to remember. I forget who she was, but anyway, a woman, a shopper who said she usually takes about 15 hours to achieve all of her holiday shopping, like 15 hours a year, which had me, you know, considering how much I put into holiday shopping? Like I never quantified it. But you think about that, and she talks about the time savings, the efficiency gains, the ability to, um, you know, kind of delegate holiday shopping so she can enjoy the holidays. It's not dissimilar to what we do in our work world. Like if we can kind of assign these tasks to achieve operational efficiencies to AI, we're going to do that and we'll hopefully have a little more quality of work or higher level strategic work or time for those types of strategic initiatives. It makes perfect sense that consumers would ultimately start doing this as well. Why wouldn't I want to save time in my personal world?
Lenny Murphy: 100 percent. Look at the example of that infographic. It took Karley more time to pile those stats than it took to create that infographic. Now, is that a deal breaker? Does it maybe enhance the experience, the storytelling? I would argue, maybe not in this specific scenario, but in general, likely yes, to your point. So there's hours of work, you pay a designer, blah, blah, days, right? We're now achieving in minutes. Is it perfect? But the efficiencies gained and augmentation, right? Potentially, actually a better experience across the board. All of these things, we cannot argue against.
Karen Lynch: And we're not the only ones who feel this way. So we have an article or a link to the Insights Association article. Crispin Beal is behind this piece or put his name to it with some information they gathered kind of looking ahead, what aspects of technology excite you the most or concern you the most in terms of impact on the insights industry? So it's kind of a summary of a bunch of different professionals that, you know, chimed in with their, you know, kind of things they're excited about and things they're concerned about. Full disclosure, I took that piece and I threw it into an LLM and I said, can you summarize this? What's the biggest concern? And what's the biggest thing that people are excited about, right? Because, you know, I didn't read for too long. But the biggest excitement across that piece was transformative efficiency gains. Like, basically, that is it, because AI is speeding up research, you know, turnaround time, freeing the team to focus on analysis, et cetera, et cetera, improving the participant's experience. Like, there's a lot going on, and those AI efficiency gains are really what the industry is most excited about. I share that excitement. So it also said that quality is, guess what, the biggest concern. So it said misuse or erosion of quality when AI is adopted without strong human oversight. I think we talked a lot last week about human oversight over AI and that partnership between humans and AI. So the biggest concern is that it's a little bit unyielding.
Lenny Murphy: So very interesting. It's also, I thought, that it was interesting that the folks in there were more from smaller agencies, uh, uh, which are probably the companies that are adapting the fastest, uh, overall to this. Cause just, you know, uh, they're just more nimble. Uh, so it was, it was interesting to get that perspective from the, the, uh, you know, the bulk of the representative of the bulk of the industry, right. Our, our small to midsize agencies. So, yeah, that was interesting.
Karen Lynch: Interesting stuff. So, you know, no surprise then what the majority of this kind of news is about this week, right? So, show me the money right there.
Lenny Murphy: Show me the money, right? Fluency, 40 million.
Karen Lynch: Fluency raised 40 million in Series A to boost automation in the Genetic AI. What do you know about Fluency? I don't know much.
Lenny Murphy: It's an ad management platform, but it has built-in metrics, right? So, I mean, they're doing, I don't know if they're going as far as brand lift, but you know, there's certainly an advertising awareness and exposure component in there as well. So it's not just, just a marketing component. Um, uh, yeah.
Karen Lynch: Just yes. Once again, money, that's where the money is. And, um, can we just say, is that all rummaging through there? And she's no, no, that was a dog getting comfortable.
Lenny Murphy: No, that's Iggy. There's a chair back there, and he likes to sit on top of the chair on the cushion. The gate was closed, but evidently not closed firmly. One quick note, though, just anecdotal on that. And I lost it.
Karen Lynch: Because I distracted you with your dog.
Lenny Murphy: I guess. Me the, um, nevermind if it comes back, all the money, money, money. So, uh, somebody asked me this week, I was talking about something else. I was like, well, what's, what's the, you know, what's the VC activity been like, uh, so far this year, I don't pay attention. It's like, dude. Um, and, and so I put, you know, we don't need to worry about here, but, but I just pulled, I just did a search and pulled all of the, the, like all of the investment activity in this industry this year. And I didn't quantify the numbers or anything, but there's a hundred at least. So, um, so anybody who's in, here's just one more example, right? I mean, money is just pouring in. So, uh, yeah, I expect Simon Chadwick will do some, uh, they usually do that analysis and I, I think this will probably be one of the biggest years we've ever seen for VC, I guess. All right, more products, Integrated Ad Science. They launched their IAS agent. This, again, kind of gets into activation and insights. They measure everything on the marketing side of things, but with data. They've been out here, actually. They've had multiple new releases this week. In the past couple of weeks.
Karen Lynch: Well, it's interesting. This next piece also, Anthropic and Block and OpenAI with some others created the AgenticAI Foundation. And Integral Ad Science was kind of quoted in that. So I'm like, well, that's interesting because the idea is that they want agentic AI tools for advertisers and marketers to stay open and collaborative. And then Integral Ad Science will have a better product as a result, right? I've got some of this open model. So I just thought that it was really interesting that they formed an alliance.
Lenny Murphy: They did. Well, and just a point, Integral Ad Science runs off of a panel. So, I mean, they have a large global panel with some passive metering technologies, my understanding, for measuring ad exposure, et cetera. Et cetera, so that humans and AI come together, but it is driven by human data. So yeah, interesting. Pretty cool. The Alchemer. Alchemer Pulse. They're applying things like, I suspect, similar to notebook LMs, my guess, trying to take data into intelligence and actionability. So we're seeing a lot more of that. It's interesting. Do you see a heads up? It's right now. The first wave was all about data collection.
Karen Lynch: And now we're really seeing a push towards actionability, you know, of crossing the chasm to and this one, you know, something I read in this brief is also about their AI power insights automation. And so now, and the next article that we have also is about some kind of automated insights. So it's nice to see the dots being connected from AI and automation, you know, kind of working in tandem. We've talked about automated insights before. We've talked about AI driven insights before. Now we've got AI driven automation. So anyway, kind of full circle. So, you know, so yeah, so we just shared about Alchemer, but Amplitude was introduced. Their automated insights and they're working on. This is interesting. It does say in this brief, and I'm not sure I'd have to fact check this, but they say they're the first AI platform that truly functions as an expert analyst, not only reporting what happens, but explaining the why. They're claiming they were first. I'm sure we've had this conversation before about other ones saying that they're the first. I don't know if anybody can really claim that they're the first because there's so much happening concurrently right now. But yeah, I like the idea of, you know, like we're analysts, you know, we've got that going in tandem. It's not just data collection. We are analyzing what's happening and we're making it usable.
Lenny Murphy: And in that particular scenario on product data, right? So why did product A do better than product B? You know, why are more people going for Heinz versus, nevermind, you know.
Karen Lynch: Versus the Trader Joe's ketchup that I bought that my family will never forgive me for.
Lenny Murphy: Yeah, some of the Trader Joe's stuff.
Karen Lynch: Mom, when this one's done, can you please go back to Heinz? I'm like, oh, sure.
Lenny Murphy: All right. Broader tech developments. You found this one. This was interesting.
Karen Lynch: Well, this was interesting. So there's an article. Has outlined how P&G is pairing AI with some of their traditional methods and I thought it was interesting because I don't know if it's just last week or it was two weeks ago with Rick but we shared what Unilever was up to and you know saying like you know take a look at what these you know behemoths are doing with AI because don't think for a minute that all the other brands aren't going to try to emulate that and work towards that if they haven't already. So I So anyway, so yeah, so obviously part of what was interesting is, and I don't know if you know of, because I know you are close with a lot of folks at P&G and have gone to their vendor fair and et cetera, et cetera, and consult with them regularly, but they have an AI factory, which has like a vehicle to rapidly develop and test and deploy and monitor, et cetera, et cetera, to help with their production. And they gave this great example of Pamper, and the MyFit application of Pampers, which uses the results of an AI-driven questionnaire to provide parents with diaper fit recommendations that are 90% accurate for preventing leaks. So here we have a real pain point, leaks. Anybody who ever changed a diaper knows leaks are just unacceptable in the world of diapers. Like, no, you want your child to be comfortable. You don't want leaks. You don't want to, you know, anyway. So big, big pain point that has to be solved with the diaper. It's kind of the reason they exist, 90% accuracy with diaper fit recommendations. And it's an AI driven questionnaire. So I love that they publicized this and have this very strong use case for it. But I also think it's really interesting that they have, you know, this AI factory, like, basically, they've put internal resources towards all the other use cases that are cited in this article. So, you know, go back, listen to the Episode again, I can't remember last week or two weeks ago, where we talked about the Unilever article about what Unilever is doing as well. Read them in tandem if you are on the brand side. Pay attention to what they're doing and make sure you're keeping up with those Joneses.
Lenny Murphy: I had a conversation with somebody at Unilever this week that I can't get into details of why, but they were embracing a fully AI-driven answer process. We'll call it a research process because it's different. No primary research involved. But in their specific use cases, which were interesting, challenging, for them, having a human expert utilizing AI to get to the answers in specific business issues was like, where have you been my whole life? I mean, it was revelatory for them. Pretty cool. Yeah, 100%. I thought OpenAI, now finally opening up third-party apps inside ChatGPT, we'll see how that plays out. But I thought that was really interesting. My guess, if you build off of OpenAI, any app, including research apps, now they have an app store.
Karen Lynch: Yeah, yeah. Well, which is interesting, and I don't know where in our sequence it was exactly, but I don't know who Casey Accidental is. I don't know who that is, but you found this kind of an op-ed. Somebody who studies scale or scaling, really talks about how these agents are really changing perceptions and usefulness of marketplaces. And so anyway, so if you're tuned into this and your ear is perked up a little bit when we're talking about these third-party apps, take a look at this other piece, too, and think about what does this mean for the marketplace model? Not to call out any names, but you know who you are. Take a look.
Lenny Murphy: Well, it goes back to the shopping thing. It's the same thing. It's about there's now an intercessor in between. And what is the role of the marketplace, and when, because you used to go to the marketplace, and then the discovery process through the marketplace. There's another piece there. And yeah, I thought that was interesting. Let's go back to this meta one, because I thought this was- Yeah, for real, right? This is definitely more in our wheelhouse, and I'm aware of some other stuff that Meta's been doing. Meta, new partnerships to ingest real-world conversational data to improve its AI. They also, I happen to know that Meta is spending significantly to capture behavioral data outside of their ecosystem, as many other companies are. So, they took an approach we didn't talk about . A few weeks ago they published a paper on the human-AI collaboration that is the best approach to get to AGI. And it was really wonky. That's why we didn't publish it. It was no big deal. But they seem to be really leaning into that and spending money overall, this idea that the perfect combination is AI-driven, curated by humans, and driven by human data. And that's going to be a place for their bets.
Karen Lynch: What this piece talks about is that Meta's platforms, whether it's Facebook and Instagram or whatever, it's not necessarily original human content anymore. There's a lot of resharing of things, but it's not, users are no longer like, you know, Facebook, the big thing used to be like, what's on your mind? And people would type in what was on their mind, right? Back in the day. And so they were getting all of this original thinking, but now it's a lot like sharing this or sharing that or forwarding this article, memes and all of it. So, you know, same with Instagram. If you're on Instagram, yes, of course, there's pictures, but there's a lot of people you're following who are producing professional content and that content is being shared and shared again. So they don't necessarily have the real world conversational data that they deem important in to grow and nurture their AI models. And then it kind of kicked it over to Reddit being, you know, like the bomb, the place where all these conversations are happening, which just makes you think, hmm, you know, Reddit. Like, you know, Reddit is developed, because it's anonymized, their models might end up being stronger. I wonder what their future play is when they have all of these human conversations taking place. What's going to happen over there? And when are they going to get into this kind of conversation? I don't know the answers.
Lenny Murphy: Well, I mean, they're licensing. One of the major revenue streams now is licensing to AI. I think I've seen that Reddit is the dominant feed in almost all LLM.
Karen Lynch: Yeah, when compared to search and all of that. Like if you're looking for something, yeah. Reddit pops up quickly.
Lenny Murphy: And they're making a ton of money there. But I'm not a Reddit user, so I do not know what the bot issue inside Reddit may be like, I just don't. I'll click a link once in a while, but I never go on Reddit for anything. But two points, human data, human data.
Karen Lynch: Reddit is to me, my use of Reddit, full disclosure, is like, I needed a new planner for 2026, and I was sick of the planner I had, and I end up going into the planner community to see what everybody has to say about their planners to kind of see if anybody speaks my language in that community and the next thing you know I've bought a new planner which is the best planner and I'm very excited about it but it's that kind of thing like I go into reddit for a very specific like I need to I need to Read what are people saying what are some reviews of what real people are saying so yeah you're what you will it's a very specific use case for reddit that pops up every now and then well I wonder if though you know some point you know things like discord or whatever may or even medium comments or substack comments or whatever, right?
Lenny Murphy: There's lots of opportunities there where those organic, authentic conversations are happening. And those are increasingly important as our research communities and primary research.
Karen Lynch: Let's segue into research communities, shall we? We have big news. We're getting towards the end of our show, but big news is coming out of the Insights Career Network. As you may or may not know, I've served on the What is now called the Advisory Council. So kind of a board that was, again, an advisory board. But they have announced officially this week, Monday was a big meeting, where they've launched ICN 2.0. It is officially a 501c3 status organization. And they're going to be, you know, scaling up career support and, you know, research for research and analytics and insights professionals. It is now a new governing board led by Simon Chadwick. And so, you know, from where they began at the end of 2021 into 2022, totally volunteer-led, of course, but they have grown with a membership of over 3,200, LinkedIn following 30K, like, you know, massive, massive growth. And it's great news to see that this new status will allow them to collect some funds to pay for some programming and just really help them develop the resources they need to help serve the community. So pretty cool stuff.
Lenny Murphy: It's very cool. A very fantastic resource. Big fan. Hopefully, we'll find some opportunities to partner with them.
Karen Lynch: Well, they're contributing content with us regularly, which is great. So we have an insights and career kind of expert channel on our site, and the powers that be there are producing articles for us to publish. We're trying to get those out there to be a resource for people, and we always do something at IIX, at least in North America. So yeah, we just keep on keeping on, so it's exciting times.
Lenny Murphy: Very cool. Well, and that's probably a good segue to the final article, which I thought was just really, really, really interesting.
Karen Lynch: It is firewalled. So unless you are a subscriber and not see this article, I'm disappointed, although I have seen it corroborated in other places. So you go ahead and talk about what you found interesting. Short story is a Wall Street Journal article talking about storytelling roles kind of surging at these tech companies, which everybody who knows anything in insights knows storytelling is a big part of what we do.
Lenny Murphy: But that's just the tech companies, though. I mean, so I'll dig. Karley, before we post that, I'll see if I can find a non...
Karen Lynch: Non-firewalled link.
Lenny Murphy: Yeah, because it really was interesting. It's become a big chief storyteller, right? Things like that, big roles. Back to the jobs, folks, two, $300,000 roles, considered central now across the organization. To get to effective storytelling. My thought was, well, I know a buttload of researchers that are ideal for this, and especially qualitative researchers. And what really stood out to me was this idea that, okay, data is ubiquitous. We're creating infographics in a second, right, whatever. But to humanize the connection and really get it over the line for people, I think as automation increases, the need for authenticity and connection is increasing as well. I see that in my kids. They hate all AI-generated content, despise it because it's inauthentic. They want storytelling, they want context, they want connection. It's cool that the brands seem to be recognizing that and that is what the Wall Street Journal would say here.
Karen Lynch: Yeah, pretty cool. So speaking of how quickly stories can come to life, we have one more graphic for y'all before we leave, which is a graphic. Thank you, Notebook LLM, right? A graphic that shows kind of the themes for this Episode. So, you know, we.
Lenny Murphy: Literally like five minutes, 10 minutes before we went live, just loaded up the links to the articles into notebook LM, which is free by the way. There is a throttle on how many production I already hit my throttle on my, my limit on presentations, but
Karen Lynch: That's so funny, but there are a couple of things we like about this. So this is a recap of our episode today. So it starts off with that shoppers using AI assistance convert 30% higher. That's worth paying attention to. So I'm really glad it pulls that. Rise of agent optimization. Yes, we talked a whole lot about agentic AI in this, right? The marketplace models are vulnerable. Yes, we talked about that. So human value moves from analysis to storytelling. So who was it? There was the piece where they're like, I think it was, anyway, I'm not remembering who it was, they were talking about like, you know, they're now doing analysis. They're the first, you know, and it's like, yes, okay, good storytelling. Like our AI is not doing that yet, even though we did a lot of automation.
Lenny Murphy: So, um, I have to say just that if you please, please experiment with, with notebook LM, uh, uh, as a tool, I can see it fitting into so many workflows in the research space. Um, I have not gotten to the point where I could custom, where I've tried to customize any of its outputs, right. But, um, so, but it is still amazing that this is contextually accurate. It's not just AI slop, right? I mean, these graphics that are compelling and interesting and contextually relevant to the content, that's pretty crazy. And again, this literally took like five minutes. And that was just creating it. That was the time of it just creating the graphics. I didn't do a damn thing. Things, except load up the content. I literally loaded up the links that we have. And clicked the button for an infographic.
Karen Lynch: And you know, my suspicion is always, um, well, two things. Let me, let me know. My suspicion is, well, like, you know, site source AI, but we know that that 30% is the number. Um, and that 14%, you know, kind of engagement, those were numbers we were going to be talking about. We saw that in the article. So they didn't make that number up. It's really, from what we shared. I also like that sometimes when we've done this in the past, uh, the images that they pull aren't necessarily, they don't really help communicate a story, right? But here, look, there's that robot holding a package, you know, down at the bottom, we've got a, you know, data Providence is the new competitive mode that looks like a castle to me. And, you know, and it's got some of these, um, you know, kind of walls up protecting that data. That's interesting. This is a woman that, so again, to bias, bottom left, a lot of LLMs were criticized for not having enough kinds of females at the ready. You know, here it looks like a woman based not just on the type of hair, but also the style of clothing, like it seems to be. Like, this is a female storyteller insights professional in my, like, I have no real, I'm not quite sure about the water up here on the right, but
Lenny Murphy: Yeah, I'm not sure.
Karen Lynch: I'm not sure what that means, but I'm not going to judge it because the rest of it I can and understand the story it's telling. So cool stuff.
Lenny Murphy: Cool stuff. It is. And takeaway here is, guys, and this is beta, to be clear. This is beta. So this is a tool free in beta. It's going to get better. It's going to get better. So we need to just experiment over the holidays. I've been having fun with this. Like, literally, I'm like, oh, I'm going to make an infographic for something I would have never made the infographic for before.
Karen Lynch: So funny. I can almost guarantee I will not be experimenting over the holiday break.
Lenny Murphy: That's it, but it is kind of addictive.
Karen Lynch: It's different, I know, I know. I understand. Um, I, and, and I will save my experimentation for January. I plan on, um, I plan on doing some, uh, some good old fashioned R and R over this break. There's, you know, been a lot and this one feels like I need a reset. Start my year 2026 with a new everything, a new kind of excitement for the year to come, because 2026 is going to prove to be a very exciting year, I'm sure of it.
Lenny Murphy: It is. I'm right there with you. Our oldest daughter and our foster daughter, whom we don't see that often, are coming in next week and looking forward to just having the whole family watching Stranger Things on Christmas Day. New Year's relaxing. I hope our entire audience does as well. I agree, 2026 is going to be a hell of a year.
Karen Lynch: Yeah, it really is. It's exciting. Thank you everybody for, for, for tuning in. Like I said, going back to that desk, thank you for showing up for us. That's why we keep showing up for you and um, have a wonderful, wonderful, have a wonderful, wonderful time until we see you again.
Lenny Murphy: So happy holidays. Happy New Year. Talk to you in January.
Links from the episode:
Stripe launched the Agentic Commerce Suite so businesses can sell through multiple AI agents.
Alchemer unveiled expanded AI capabilities via Alchemer Pulse
Amplitude introduced “automated insights”
Meta formed new partnerships to ingest real-world conversational data and improve its AI.
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