Smarter Data Wins: Following the Money in AI and Insights

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The insights industry is being reshaped by AI and capital flows that prioritize smarter data over bigger data. This episode explores how companies are embedding expert knowledge into enterprise workflows, why users are still experimenting across multiple AI products, and what major acquisitions and partnerships signal about the future of research tech stacks.

From AI interviewers to predictive behavior partnerships with cloud giants, the conversation traces how AI is moving from experimental tools to core infrastructure while highlighting a persistent gap between insider enthusiasm and consumer adoption.

Many thanks to our producer, Karley Dartouzos.

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Transcript

Lenny Murphy: Now I'll jump out. All right. Happy Friday.

Karen Lynch: Happy Friday from Friday to Thursday.

Lenny Murphy: All right. Happy Friday to our audience. Happy Thursday to Karen and I, because we were recording this late in the day on Thursday afternoon, because it's a complex week. A lot going on. We had some conflicts that we had to navigate. So there we are.

Karen Lynch: Navigating complexities by pre-recording. Yes.

Lenny Murphy: Hopefully, there's no monumental news that drops between now and noon.

Karen Lynch: Seriously, if monumental news drops between 4 p.m. Eastern on Thursday, April 16th and noon Eastern on Friday, April 17th, somebody better call us out on the live stream when it's live tomorrow. That's right. Yes. We will say, sorry, folks. It's a complicated week because our team is up to their eyeballs in North America, IAX North America Logistics. Cue the thing, Karley. We are all about IAX North America at Green Book right now. If you are emailing us about anything else, most likely our response will be, can this wait till the first week of May? Pretty much everything that can be kicked, every can that can be kicked to the first week of May is being kicked to the first week of May at this point, which means the first week of May is going to be particularly busy for almost all of us, right? So I almost put a meeting on my calendar for the first week of May, and then I thought, you know, I really ought to just settle down a little bit, because that's going to be a loaded week as well. But we are right around the corner. It is going to be such a great show. I'm very excited. You know, I don't even know where to begin with the things that I'm excited about, so.

Lenny Murphy: Everything. And be there or be square.

Karen Lynch: Although I will not be I'm square again the one I don't know what dance why they they schedule all this dance stuff April begin to May so I will not be there because my daughter has a dance competition, but Anyway, so I'll be square Yeah, a very small window of time that you will be doing these dance competitions as a former dance mom actually fun fact on May the 3rd I think I told you this, my daughter will be dancing in a performance at her school in Maryland, at the University of Maryland, for what will be her final dance performance of her entire dance career. So I will be doing that. It's on a Sunday because she's not competing anymore, but there is an end at the end of the tunnel. It is there, Lenny. It will happen.

Lenny Murphy: And I will be sobbing, wishing for the days that you are currently in. Sure, I will. Yes, I'm not bemoaning my fate. I love it. We have two shows this weekend, et cetera, et cetera. And hence why I made the decision that, you know, this is my, it's my youngest, my baby, the last one.

Karen Lynch: And by God, I'm going to be there.

Lenny Murphy: Yeah. So anyway.

Karen Lynch: Anyway, well, I will be bright eyed and bushy tailed. I will see you all on stage on Wednesday, April 29th. There was a code on that. By now, you should all be registered. If you're not registered, reach out, get registered, find the website.

Lenny Murphy: Please, we will see you there.

Karen Lynch: I can't wait. Yeah, lots to get into. We always start with following the money. Show me the money, Lenny. Show me the money. Of course, some capital investments. Let's just talk about them because they point us in a direction, and this week, it's pretty clear where we're absolutely.

Lenny Murphy: The theme stands out, but let's get into it and see who picks it out. This first one, after query, 30 million Series A Series A at a 300 million valuation. Turn expert knowledge into enterprise AI systems. Scaling IP, scaling expert knowledge. They don't use the term synthetic intelligence. Or digital personas or anything of that nature, but that's what it is, and embedding it into workflows.

Karen Lynch: When you click through to the website, there's a quote that says, the future of AI won't be trained on more data. It will be trained on better thinking. And I'm like, that is such a great quote for all of us to think about, you know, when we're talking about also integrating integrating, you know, talk about integrating, you know, human thought with AI in general. And I'm like, yeah, you know, we are, we are training it on data sets, but there has to be thought behind it.

Lenny Murphy: So there is. And I, you know, slightly go off on a tangent, but even right before this, I was doing some, you know, some work in the industry with my partner at this point, perplexed. And I, It, it's trained. I, it, it, it thinks exactly like I do at this point and pulls together tasks and, you know, but it does the things that I, just as I would do them and expect them and connects the dots the way that I connect them. Um, and not because it's, well, maybe they're probably smarter than me, but yeah, but I've trained it on what I do. And, uh, and that's an example of that.

Karen Lynch: Yeah. I think, but you know, I'm going to, I'm going to jump way ahead and let's do it. Go ahead. So the verge published this open AI memo. I don't know if you had a chance to read it, but, um, on the competition with Anthropic. And so the chief revenue officer, Denise Dresser, she published in this memo, um, which again, the verge article. So, so sorry, Karley, this is way down. Good thing you have some time to pull it together. Um, they're talking about building a moat around their AI products because what people are doing is they are, um, they're bouncing between products, right? Which is what I do. We're bouncing between products. Some of us are bouncing between products as opposed to sticking with one. And they're saying that, like that particular behavior, people are looking between one and everyone on the charts. They're giving it a try. We're not necessarily sticking with one right now because new releases or new training means they're better at this or better at that.

Lenny Murphy: And they keep leapfrogging each other.

Karen Lynch: Yeah. And so here's a quote from that. Multiproduct adoption makes us harder to replace. Dresser wrote, we should stop thinking like a company with separate product lines. We should think like a platform company with multiple entry points and one integrated enterprise offering. So that's where they're going. But when I'm reading this, I'm thinking, it's true. I am switching. I had been relying on a custom GPT. I had built in chat GPT for a long time for one of my tasks. And I was getting really frustrated last night and I was like, you know, screw it. I am going into notebook LM and seeing if notebook LM can do this for me. And it was like, it was like easy peasy. And I'm like, son of a gun. Like this task that notebook LM couldn't do for me, you know, six months ago when I had tried it now could handle it in a hot second. It was so clear. So anyway, my point of all of that is back to, you know, what you're dealing with perplexity. I just love that, you know, if you are, if you are not experimenting, you are missing out because you have to be able to say, let me pivot real quick, because right now, until they have built these moats and these enterprise level, you know, things that we get locked in, we, the users have some flexibility. We should, we should keep doing what we're doing.

Lenny Murphy: 100%. Well, and I want to make it clear, it's not about perplexity, but to your point, the reason I like perplexity is it's multimodal. It applies the model that is best to, and not their models, that is best for the task. I'm in that place. I may have adopted that as my orchestration layer. It's my default place, go-to place to start my workflow. But the models, I trust they're going to keep updating the right models, so I'm getting the best of whoever based on the task.

Karen Lynch: Yeah, I got to do the financial analysis of what, you know, paying for, you know, paying for open AI and chat to be a team monthly versus paying for perplexity monthly, I have to do the analysis.

Lenny Murphy: Do it. And it is expensive. It's, I will even say this, I would rather. So it's about experimentation, right? So the flex has another mode called computer that's using, you know, that's building. Yeah, it's using agents in most of its clauses. The point is it's expensive. I really go burning through the tokens. But I have found that for the tasks that I've been doing just in kind of the LLM that, that, you know, when I do those same tasks and using the agents, yeah, the outputs are light years better. Yeah. I, they're, they're amazing because it does more, right. It just, it creates stuff that, uh, So there, but the cost benefit analysis and that's, that's the issue. And the theme that we're going to uncover throughout all of this, but for real, yeah.

Karen Lynch: Workstreams are changing, even ours, right? Even at our level, work streams are changing. So, um, let's talk about rep data because what else are they going to buy this year?

Lenny Murphy: Rep data, they're tearing it up. Um, yeah, so they acquired side X, our friends at side X, they've been, uh, uh, a long time, well some exhibitors and sponsors at IAX events. So it's interesting, Repdata you think of primarily as a sample plus sample quality. You know, they bought these solutions and all that. Now they buy SideX. SideX is a very sophisticated data collection platform. It's the work stream. So now they've got full service research, response quality, quality controls and then research workflow. That's their, I mean, the workflow from data to execution. So we're gonna see more of that as well. So congrats to that whole team, all the teams.

Karen Lynch: Yep. What I might add is, you know, with a very solid positioning, I mean, nobody can argue with that. And I think that that's what's, you know, them from everybody else's, you know, they, you know, they obviously have permission to to stand out from the pack with their, you know, strong focus on data quality, like, anyway.

Lenny Murphy: Yeah, absolutely. Absolutely. And it's a plug. I mean, side x always stood out to me because they were really good at communicating results and complex results. They did, you know, it did a lot of complex stuff from a survey standpoint. So which is more like max diff conjoint? Your quality data really better be pretty damn good when you're doing that type of hardcore research Yeah, so that integration makes an awful lot of sense I Don't know anything about buy-in or TV TV vision insights so this Really violent is another that's more on the ad tech side um, uh, side of things overall, the, uh, the marketing data and advertising data, and then buying TV vision, um, to get attention measurement data. And I think if I recall correctly, this was around, uh, local television more so than broadcast, which is still absolutely a force, but it's the workflow, right? Connect it from advertising metrics with, you know, attention measurement metrics, uh, to get in competitor Nielsen basically. Um, but in their own, their own way, uh, there was a $40 million deal, $40 million deal. So it integrates workflow data into the workflow and, uh, that takes to our, to our next one. This is not the listening lab show guys. It's really not, but they did win the competition two years ago and we are learning why the hell they did because...

Karen Lynch: Speaking of integration. And, you know, another reason to come to North America, right? Because they, of course, are one of our sponsors in North America. Lizzen Labs partnered with Lovable. I mean, really, of all platforms. I was like, of course they partnered with Lovable. Anyway, supporting user research across Lovable's community. And, you know, when you click on this link, like, you know, the first thing that came up for me, of course, is the comment from, you know, one of the Lovable co-founders, I didn't know his name, Anton Osika, also from Sweden. So I'm like, of course. Okay, of course. So these two young men, both from Sweden, both building amazing platforms are now partnering. So anyway, if you haven't experimented with Lovable, I think I've talked about a couple weeks ago, my husband uses it. All the time to experiment with building, you know, in this AI world. So congratulations to that team. To both those teams, actually, because it's the idea that Lovable can actually build in some consumer learning right there in their interface. You know, there's a whole world of UX research where right there in their platforms, they're going to be able to integrate, you know, listening for the user experience. And, and it's sort of once you once you once you realize the realm that Alfred has broken into, it's fascinating.

Lenny Murphy: It is. And I think you bring up a really good point. So we're talking about workflows, right? The and as the theme for this week, but insights, insights being embedded into workflows that previously was a pain in the ass or is expensive or whatever, you know, to do that. And we're seeing that we're the friction being reduced and that's where these type of stories are important for all of us to recognize is you said they were breaking in you know finding ways to to create more impact and use of data and insights right in in incredibly rapid ways the people using lovable well you're when you're vibe coding creating that stuff you're talking about hours right not talking about days so you know to have that instant feedback capability built-in off of user basis. It's amazing.

Karen Lynch: Continuous feedback embedded into the platform. It's super cool. It's cool stuff. Anyway, I haven't seen it working. Similarly, so Yobi, who I don't know much about partnering with Microsoft, they're bringing predictive behavioral AI in their database. I'm not in the Microsoft ecosystem, but I've heard of Azure. And this is also at the enterprise level, but it's a similar sort of thing, right, where these analytics, this behavioral AI or predictive behavioral AI specifically is going to be embedded into this enterprise level platform. You know, getting this kind of continuous feedback, so or not feedback, continuous information, continuous input for decision making, it's going to an interesting world we're in.

Lenny Murphy: Yeah, well, this is more like synthetic. I think that you know, it's built predictive models on behavioral applied, applied behavioral science, right? Yeah, it's my sister for that type of stuff. And yeah, people build you build your application, your either your application or your platforms, certainly many of your businesses, from a website standpoint, you know, sure is underneath all of that, and have all that embedded in. So across the board integrated into the workflow. Yeah. Yeah. Uh, and that in the next one, Google cloud, I mean this, you don't get any more obvious than that. Google with Tom Bravo. Now Tom Bravo is a big ass private equity company, right? And they own many companies in our space. So, um, uh, to bring the Gemini models, uh, the enterprise software, So basically they're, I imagine they've said to all of their portfolio companies, we're now, everybody's a Google shop now. And integrating all of that in, all of the Gemini solutions into their workflows and into their products.

Karen Lynch: Yeah. Yeah. And, and yeah, it's also further down. Sorry, Karley bouncing down, but there's also, you know, in, in our tech development section talk about Google testing their desktop agents experience in Google. Google Enterprise, right? So we have Google Workspace, but we're also talking about Google Enterprise and the entire, you know, they're, they're, they're growing and they're growing in that way also.

Lenny Murphy: Well, Microsoft too. Microsoft is rolling out their enterprise AI agent inside Microsoft 365, right? Which is their office, their work, you know, cloud-based office version with Copilot. So yeah, it's all it's integrating the agents into the standard applications that everybody uses in some form or fashion to, you know, kind of run their business.

Karen Lynch: Yeah, there's a really cool, like, you know, I love this stuff, like I, you know, I'm in the different browsers checking them out and seeing how they work and anyway, so I and I love that and I love the experimentation of it. But also, on some level I can just imagine a year from now when we log into our computers it will look very different from what it looks like today. I can guarantee it will not look the same as it looks right now when we log in, because our browsers are going to look different. Whatever page we open up to is not going to look the same. Our emails are not going to look the same.

Lenny Murphy: Fully integrated. It'll be interesting, I guess, back to your previous point too, but I kind of toggle back and forth between the Microsoft ecosystem and the Google ecosystem. Google ecosystem while using, you know, perplexity is my AI orchestration. I'm not quite sure how all that's going to work. Right. But I do see that they all have plugins, MCPs and APIs into each other. So this idea of competition, I'm not sure that that's going to work exactly the way that we're used to it. I think that they all seem to be deciding we're going to be interconnected and just let the consumer kind of choose what thing they're most comfortable with. Yeah. But without there being firewalls in between.

Karen Lynch: Right. Because I have, we have access to Gemini, right. And Gemini is right there. And we have asked Gemini and we have notebook LM, which is a Google product. So that's all there. Right. But I do step out of it to go to some of the others. And, um, you know, we'll see what happens there. So anyway, a solution for the right job. Yep. Yep. All part of our tech stack. If you do not like figuring out what your new tech stack looks like, then you are behind. You have to, you know, yep. Anyway, you're all rebuilding our tech stacks. That is not unique to the insights industry. But, um, anyway, and within the insights industry, we are rebuilding the insights tech stacks, right? The stacks being rebuilt from, you know, panels to interviewing, concept testing, you know, rebuilding. So let's get into some of those because we've got a lot.

Lenny Murphy: I mean, we do the Yeah, sure.

Karen Lynch: Talk about Frank.

Lenny Murphy: Yeah. So pre-launch Frank, uh, AI customer interviewer. We talked about that a couple of weeks ago, the return of voice. Um, so, uh, more than 30 languages. So an AI voice interviewer, um, the, uh, so that's really interesting. Um, uh, our friends at a rival group, which, you know, they've always had, there were like three disconnected companies. Seemingly, right? There was Rival Tech Platform, Angus Reid, the panel company, and good Lord. Reach 3? Thank you. Thank you. It's late in the day. Forgive me, guys. Anyway, interconnecting all this, right? Interconnecting that workflow data to technology to consulting, right? And launching the rival audiences. So, uh, they had very high quality. I mean, anybody who knows Angus Reed, uh, you know, the, uh, starting poll is a pollster, right? He takes data quality really seriously. So, uh, yeah. So that's really interesting. Similar note, D scout, um, their discount AI studio, uh, you know, discounts have been out there doing, yeah, kind of gig oriented research for a long time. Not your traditional, uh, So like I saw a lot of meals uploaded to D-Scout, one of my very first studies using them.

Karen Lynch: So super cool. Yeah. Anyway, really, really fun. I mean, really, it was like the first year that D-SCAD existed. It was incredibly fun, actually.

Lenny Murphy: Yeah. Really neat company. And Michael Winnick's done a good job of repositioning. Here's another example.

Karen Lynch: I mean, these all just kind of remind me of, yep, these all make sense. Yep, here's this company's AI launch. Here's this company's AI launch. So expect more of these friends, or I expect more of these as each company kind of gets on board with these.

Lenny Murphy: Yeah, yeah. Now this was Kantar a few weeks ago, they announced a partnership with quilt. Yeah, but they didn't really, they talked, they were launching a product, right, that came out, right, the evaluate Explorer, early stage innovation tool. So that's the, you know, Kantar, basically, you know, kind of bolting their IP onto quilts platform. So that's neat too.

Karen Lynch: Uh, I like to see, you know, I, I checked out this site, you know, cause I spent a lot of time in the innovation space and mapping out white space and brainstorming and ideation and blah, blah, blah. And you know, working with clients on taking insights into innovation, that was sort of where I lived. And so I'd still love to see how this actually works. Um, anyway, because it's, you know, it talks, it talks a good game, but I'd like to see it in action. So anyway, Raising my hand and seeing that in action, see how it actually works. Because I want to know when they talk about it as humans kind of in the mix of it, which is implied. Like, OK, is AI just giving you the trends?

Lenny Murphy: Where are they? It's drawn from a Quilt. Based on that, I assume there's some Kantar data in there as well. But Quilt primarily draws from social data. So it is, so definitely humans, it's human driven. Yeah. Data into the models.

Karen Lynch: So, yeah. So, but, but yeah, I guess, but what my point is, is then what does it do? Is it, you know, how is it, I don't know, how does it, how does it kind of get to a recommendation stage? That's what I'm, that's what I'm wondering. Like, is it just saying like here, you know, like, you know, where, how does, how does it take these ideas that are potentially and then flesh them into actual ideas. I don't know.

Lenny Murphy: I'm just curious. I'm very curious about that. Yeah, me too. Well, I think Kantar, I heard a rumor that they're going to have a good presence at IAX. So, uh, you know, can we give you a demo? I, bear, bear in mind, Kantar does own a world panel, um, which is, you know, a shopper panel, uh, as well as a relationship numerator, et cetera, et cetera. So there's, they, they have access to some pretty healthy, uh, real world, uh, purchase data. So yeah, I, our friends behaviorally continue to, to, you know, go from, you know, from just traditional pack testing, their new transaction path shopper suite to relaunch.

Karen Lynch: So they've made tweaks, right? So something, something, something's better, something's different. And I don't know those nuances there. So if you've heard of this before, You know, you're not imagining it. This is a relaunch. They've been out with it before. They've done something new and better, you know, to kind of get it up to speed. There's a sudden nuance there.

Lenny Murphy: Yeah, I think it's AI-ified. I have not had a chance to talk to Ally about it.

Karen Lynch: AI-ified. That's a real word, but AI-ified.

Lenny Murphy: AI-ified. They sent out a lot of data, right? So I think that they're leveraging that now in new ways within the product suite.

Karen Lynch: All right, hold on a minute. This next one deserves a moment.

Lenny Murphy: It does.

Karen Lynch: It does. Pause every pause and just take a moment, because before we got on this call, I wanted to just jump right into this one. And I said, no, no, no.

Lenny Murphy:  Let's wait.

Karen Lynch: And give it its proper place, because it doesn't really fit with everything else. But when I saw this, I was like, OK, for a lot of reasons. So go ahead and explain. And then I will walk you through what I experienced when I opened it up.

Lenny Murphy: So go ahead. All right. So Steve Phillips, founder and CEO of Zappy, a competition winner back in the day, one of our kind of crown jewels because they're just, you know, kind of gone through the process. Steve was still at Zappy, so to be clear. But he's, you know, as a founder, he's kind of stepped into a different role now. You know, he's not actively running the business anymore. But he's lost another one, uh, called CEO friend, uh, which is an AI advisor platform for strategic intelligence and competitor analysis aimed at CEOs and founders. So basically it is your virtual advisor, um, for CEO. So if you're an early stage company. No. Uh, if you can't afford to pay people like Karen and I, uh, to, uh, to be on, uh, to help advise you on a regular basis.

Karen Lynch: Dave, Bill. Here is your early board of directors.

Lenny Murphy: Here is your early board of directors.

Karen Lynch: Holy cow. I'm sorry. Now jumping in. I opened this up and I looked at it and I'm like, well, damn. I was like, this is genius. This is, if I were starting a company, if I had the makings of an idea right now, like I want to start a business, I could go like, go to this and, and and start to get early stage advice from an LLM that's trained in this kind of thinking. Talk about what we talked about in the very beginning about this kind of expert knowledge. So I'm like, use case expert knowledge, this is trained on expert advisory knowledge for a very specific use case. There's a subscription fee you will pay, right? So I'm like, they've monetized it cheaper than paying an advisor. So now it may not be, it may be different, right? You know, but there's a use case for this. And then when I was looking at it, I was thinking, okay, pretty cool. Like, I, conceptually, I really like this way to go, guys. I'm really impressed that they probably built it fairly quickly and had the idea built quickly. Again, because that's all right now, so that was the other kind of thought that I had. But then I started to think about it this way, and I'm curious about this particular use case. Anybody who's self-employed right now and not looking to grow a business, not looking to start something, there are people that I have talked to, and I used to have it, who have, we have created like our own kind of boards of directors that are really like just like other people that we consult when we have questions. So they're not like paid, or even real advisory board members. They're just like our, like the, like the posse of people, right? Almost like our own little mastermind group. And I started to think about that use case for the self-employed professional that I used to be not looking to really grow, but who needed occasional business advice. I was like, that's the use case for the solopreneur who is not looking for a board. That's where I found the sweet spot. And I was like, damn, if I was self employed again, that's who I'd be using right there.

Lenny Murphy: So I'll do you one better.

Karen Lynch: You're right.

Lenny Murphy: Yeah. Huh? So we're talking on Monday. So if you're a solopreneur in this industry, as a moderator, as a consultant, uh, as a, a, uh, category expert in any way, shape or form. Right. Um, maybe it's a business issue. Maybe it's, you know, healthcare, whatever the case may be. The limiting factor for, uh, money it's time. 

Karen Lynch:  Yeah.

Lenny Murphy: So, imagine if there was something like yours. You know, CEO friend, uh, that actually just gave you access to an on-demand board of experts and whatever your issue was. Yeah. Um, and, uh, was built off of just the, the, the greatest experts in our industry on specific things.

Karen Lynch: Yeah.

Lenny Murphy: The spinoff, the spinoff is the industry expert, but it could be any industry expert. Yeah. Yeah. So building your, your expert board, you know, your circle, um, in whatever category it happens to be in to, uh, and help people like me, people like you, you know, others, uh, and, and company, I looked at the other people on the thing and I was like, I don't know who these people are, but way to go, Steve. Oh, absolutely. And, and you know, that's the cool thing. Steve's during that transition. Of not being a CEO, they pay him to think. And here's one of the ideas he's come up with.

Karen Lynch: And here's some thinking that he did.

Lenny Murphy: Very cool stuff. Very cool stuff. All right. We touched on Microsoft and Google and The Verge.

Karen Lynch: Yeah, yeah, yeah. Let's jump down to some of these articles.

Lenny Murphy: So we got the meta one. This was an important one.

Karen Lynch: Meta will overtake Google. Where the hell was the meta one? Oh, Meta. I see it now.

Lenny Murphy:  Yes. Meta will overtake Google in global digital ad revenue by the end of this year.

Karen Lynch: Oh, interesting. So interesting.

Lenny Murphy: So interesting. And boy, where are they spending all their money? Off of all of their training data off of all of their platforms. Why are people spending more money?

Karen Lynch: and advertising with meta.

Lenny Murphy: Yeah. Oh, it's not because our audience is bigger than Google.

Karen Lynch: That's for damn sure. They're spending an awful lot of time over there. That's what I think they are spending. They are spending more time on meta platforms than they are on Google.

Lenny Murphy: That's right. And they are spending and that is leveraging that data to be able to make a better, you want to deliver the right message to the right person at the right time. And, you know, they are in their Lambda, I think, uh, they're, they're, they're pumping all the money in to do that. And you gotta give them, it's, it's working. So, uh, to overtake Google as the largest thing, global digital ad revenue, that's a big fricking deal guys. I mean, these companies are their primary source of revenue. So people keep discounting. There's companies that they discount all the time. Meta and X, I think it is wrong to discount Meta and X. They are both doing amazing things.

Karen Lynch: And there's the proof. All right. Let me talk about Ali. Ali Henriquez. So if you do not know Allie, then I'm sorry, because I adore Allie. So she's the executive director of market research at Qualtrics. And she shared this TechTarget article in advance of her session at IAX North America. She will be there. And this one argues, it's everything that we're talking about, that we, Lenny and I, are talking about today. So the timing was perfect. And she will be talking about this in North America in her session. This TechTarget article argues that front office teams are now rebuilt around AI-first workflows with implications for how insights teams function and operate, of course. But basically, it's all about reorganizing workflows, and with this more integrated stack. And anyway, she called it out in the LinkedIn post. And I was like, Oh, my gosh, that is the week that Lenny and I are having right now. Timing could not have been better. She'll be talking about it in North America. And I was like, I have to talk about it on the exchange. Because it's like, you know, Lenny, you and I talk about the Zeitgeist and like, how you and I are often like, oh, we know exactly what's coming up on our show this week, because the things that we're sharing, she was in it too this week.

Lenny Murphy: Yeah.

Karen Lynch:  Yeah.

Lenny Murphy: Have you ever heard of the concept of the new sphere?

Karen Lynch: I forget who came up with it.

Lenny Murphy: Anyway, it's a concept that there is a collective, the zeitgeist, collective consciousness, whatever, right? There's something that wires us humans together. And often, ideas just all kind of come at the same time, right?

Karen Lynch: Yes. It's very very cool.

Lenny Murphy: So yeah, we got a lot of panel stuff here real quick. I think we're just for this. Stephanie Francis argued that panel companies remain critical infrastructure for the future consumer insights. We've been saying that since this whole thing started Connecting to people to share information is foundational to the whole global frickin economy at this point, right? I mean period, so they all talk about AI; it all comes down to data. And humans create the data. So panel companies, stop thinking that you're just slinging samples. You're not, you are slinging, you are connecting humans to resources that need to understand them. And that was Stephanie's piece. Did you Read Brian's piece on synthetic?

Karen Lynch: Okay.

Lenny Murphy: That was kind of a late addition to the Brian Lamar shout out to Brian Great guy at the ROI rocket the Panels thick data are stronger together. Would take this step further and say there I don't think there's even it's not a fight it's not an argument the you know panels synthetic is simply one of the things that panels one of the outputs the panels so Brian makes a great argument that this this isn't an either-or thing either, right. They're Complimentary they you know, it's the right tool for the right right resource. So that was good.

Karen Lynch: Um, do you, uh, you keep going, keep going? All right. No, and I actually have questions about these because I'm like, you know, but Ember back to the type pronounce that NBER, NBER, no idea. Yeah, NBER.

Lenny Murphy: Just published new research on how C-suite, CAI affects productivity in the workforce. It's still kind of all over the place and still early. That was my key takeaway, right? People are still feeling their way. There's been some wins and there's some like we haven't seen it yet, which makes perfect sense because we, this week, integration in workflows, that's when I think you see the productivity increases. It's not that we, you know, could write something faster or whatever, that's a piece of it, but that's kind of where we were now, but the agentic thing that changes everything for that standpoint.

Karen Lynch: Yeah. Yeah. Cool. And this last one's the Stanford AI Index. Yeah, same.

Lenny Murphy: Disconnect from AI insiders and Uh, the broader public, I think, yes, I continue to see data. Consumer adoption is still relatively low and consumers are still not really sure about this whole AI thing. Right. I mean, the impact on, on jobs and so many different, you know, just kind of bread and butter, uh, uh, foundational aspects of people's lives. Um, we are still in such early innings on this. Um, but Business is all in.

Karen Lynch: So. Yeah, absolutely. So yeah. Yeah. All in. And, um, and certainly insights is all in. So I think that's, you know, that's really, that's really the bottom line.

Lenny Murphy: We are all in. Yeah. Well, and maybe that's the right way to even kind of end this, wrap this up. Right. Cause, cause I'm sure you've thought about the same issue. I mean, business is about efficiency. Right. Profitability, growth, et cetera, et cetera. That is, that is the frame of success for business. So therefore they are always going to be early adopters of technologies that can deliver greater either top line growth or bottom line savings. Yeah.

Karen Lynch: That's unlocking more value creation.

Lenny Murphy: Yeah. Consumers. We don't think that way, you know, the, in our daily lives, I don't, I try not to slip into like, CEO mode in my family. I'm a dad.

Karen Lynch: I'm a husband, you know. I mean, even if I consider myself like a household manager, you know I have Gmail for my personal use. I've never once hit Ask Gemini to summarize my inbox for my personal emails. I have hundreds of them over there. I've never tried to get to inbox zero for my personal email. Yeah, I don't operate that way because I'm like and you know, like it's just not that important when I'm in personal mode, it's just not, you know, that's not, that's not what's important to me. What's important to me is spending time with my family. Sure, I pay bills, I start my bills when they come in so that I can go back. Oh, yeah, got to get to the bills. Yep. You know, that's about the extent of it. I write back to my family if my family comes in that way or something.

Lenny Murphy: Yeah. Yeah. Is that the difference? Is that how we live our lives? We're actually softball for second, because we're only 40 minutes away. We're on 40 minutes and we've been running like 45, you know, and it's the end of the day on Thursday, but no, the consumers, it's interesting. Somebody let's do research on this. I would argue just out of this conversation, I live my life on more of a tactical basis, right? Outside of work, work is my strategic thing, right? That's thinking about the connections and that's what I'm paid to do and all that stuff. Daily life. And pay the bills, we'll make it for dinner, help the kids with homework, whatever. It's a series of tactical decisions. So that don't carry, I mean, certainly some carry a lot of weight. Most don't, not really, what do we have for dinner?

Karen Lynch: Chicken or steak? The question that never ends.

Lenny Murphy: That's right, right, right. So it may seem like a big pain in the ass question. We're trying to balance everybody. What do you want to eat for dinner?

Karen Lynch: We have five different palates. Oh my gosh, oh my gosh.

Lenny Murphy: Terrible question. Yeah, but is that maybe why we see this disconnect? Is that we haven't found the unlock in AI from a consumer standpoint to really address the decisions that we deal with on a daily basis. Because efficiency and productivity, et cetera, et cetera, aren't the drivers of daily living. It's the driver of business.

Karen Lynch: What do you think? Very well be, yeah. No, I think for sure. The AI that I would use on a weekend, for example. Imagine it's a Saturday and I have pretty hard boundaries on my weekends. I really try not to work on weekends if I can avoid it. I know that's not the case for everybody, but I try very, very hard. Otherwise, I burn out too quickly.

Lenny Murphy: I look forward to the weekends. It's time to work.

Karen Lynch: I'd rather work 12-hour days, which I do a lot of. I would rather work 12-hour days than do the weekends because I want to spend time with my grandbaby and kind of indulge in my young adult children in a way that I don't during the week. Anyway, enough about that. So on a weekend, what do we do? Every now and then I may shout to Alexa and I might ask her a question. I might wish that I could shout into the ether and ask for an assist, but it's because my hands are busy doing something else. Maybe I am cooking in the kitchen and I wish that the little robot was around. I would like the help, but I'm not sitting with the tech tools. Like that's just not what I'm doing. Because I'm engaged with my environment. Whereas at work, I am sitting with the tech tools.

Lenny Murphy: Interesting. It'll be interesting how all that progresses. But to your point, we are now 42 minutes. We gotta wrap. We gotta wrap. But the signal's getting clearer and clearer, right? If you guys can't see that, I mean, it's a fricking air horn at this point, right?

Karen Lynch: There is, there's no debate.

Lenny Murphy: So get on the board, get on the train. All right, we'll talk next Friday.

Karen Lynch: We will talk this Friday. I cannot tell you what kind of mood I'm going to be in next Friday, but I just don't remember what I was like, at this time last year, because I was saying to Tim, I just don't remember being this kind of all over the place last year. I truly don't remember. Was I this way last year? Am I this way every year, two weeks before I asked North America? I truly don't recall. So maybe that's something in and of itself.

Lenny Murphy: You don't come across that way? You seem to me more poised and calm than you were in the past, for whatever that's worth.

Karen Lynch: Thank you very much, sir. I'll take the compliment and try to figure out what we're having for dinner tonight.

Lenny Murphy: You can ask AI.

Karen Lynch: All right. Have a great weekend and we'll see you tomorrow.

Lenny Murphy: Yep. Take care. Bye.

Links from the episode:

AfterQuery Raises $30 Million Series A Round at $300 Million Valuation 

The Verge published OpenAI’s internal memo on intensifying competition with Anthropic 

Rep Data Acquires SightX 

Viant Announces Agreement to Acquire TVision 

Listen Labs partnered with Lovable 

Yobi partnered with Microsoft 

Google Cloud partnered with Thoma Bravo 

Google develops its own desktop Agent to compete with Cowork 

Prelaunch launched Frank 

Rival Group launched Rival Audiences 

Dscout launched Dscout AI Studio 

Kantar launched EvaluateExplorer 

Behaviorally relaunched its TransactionPath Shopper Suite 

Steve Phillips launched CEOfriend 

Microsoft is working on yet another OpenClaw-like agent 

Meta Set To Surpass Google In 2026 Ad Revenue 

Ali Henriques shared a TechTarget article in advance of her session at IIEX NA arguing that front-office teams are being rebuilt around AI-first workflows, with implications for how insight functions operate 

Stefanie Francis argues that panel companies remain critical infrastructure for the future of consumer insights 

Brian Lamar argues that panels and synthetic data are stronger together than either approach alone 

NBER: Artificial Intelligence, Productivity, and the Workforce: Evidence from Corporate Executives 

Stanford report highlights growing disconnect between AI insiders and everyone else