The AI Skills That Actually Pay (Plus the Ones That Don't)

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!

 

Karen Lynch and Lenny Murphy expose the seismic shifts happening right now—while everyone debates AI replacing researchers, millennial parents are asking ChatGPT how to raise their kids, and a mysterious $10 billion funding round just dropped that could reshape everything.

Whether you're a veteran wondering if your skills will survive or a newcomer placing bets, this episode reveals who thrives and who gets left behind in the new research landscape.

Fair warning: These trends are moving faster than most realize. The opportunities won't wait!

Many thanks to our producer, Karley Dartouzos. 

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Transcript

Lenny Murphy: There we go. There we go. All right, feeling zen.

Karen Lynch: Feeling zen. I was going to say I feel very calm right now. Perhaps I feel zen. Actually, you know what I can probably attribute it to? One of my sons is home, and I got a really huge hug at about 11.30 Eastern. And he's very tall. And he's tall and lanky in his gorilla arms. And he gave me a really big hug. And I think maybe that just, what's the physiology of that? Like one super hug can kind of work.

Lenny Murphy: Yes. Yep. I think, and I think it's actually defined as 20 seconds, I think. 

Karen Lynch: It was definitely long and it definitely was effective. So that's really all I've ever needed in my work life is to have somebody back home. Say nobody else ever.

Lenny Murphy: There's something AI can not replace at least, at least yet.

Karen Lynch: There was a great list, I think, on Reddit. I didn't share it in any of the links, but somebody asked ChatGPT to come up with the top 100 things that AI can't do that are important to the human experience. And it was a great list to read. I'll find it and I'll share it with you personally. Everybody else, if you want it, I'll find it again. But it was a really heartwarming thing to read. It was just, oh, like every other one, you're like, oh, that's true. Oh, that's true. Anyway, that's good.

Lenny Murphy: Well, a big chunk that we'll get to at the end is like things that AI is replacing. So that's probably guys, we're trying to give you something to hold on to.

Karen Lynch: Are we also like, but some of these never, you know, two big acquisitions this week. I mean, you know, I think that, um, you know, it's, it's, is continuing, this kind of consolidation is continuing, and let's get into them. So you want to talk about the Ipsos one?

Lenny Murphy: Yeah. Ipsos acquired the BVA family, which really is, from the outside, what I see, it is consolidation, right? I mean, they're capturing more business in Europe, particularly in France. They're one of the big competitors in France, particularly. So that is a pure consolidation play. There's some extension, capability extension there, right? Focuses a lot on behavioral science as well as self-testing, you know, things like that, the old PRS and Vigo brand. So, yep, Ipsos has been on a tear doing that. I mean, they very steadily have been making these consolidation plays in different countries and, you know, continuing to just kind of absorb that into their machine. So there'll be more coming from them and others, I think, overall. So yeah, that was cool. Same thing, Norstat with sample solutions. B2B, so Norstat acquires sample solutions for their B2B capabilities. So they continue to expand outside of just, you know, for those who aren't familiar, used to be, they were just kind of the Nordics, right? Name would indicate they are expanding globally and become this.

Karen Lynch: I've never heard of Norstat. I was like, Norstat, that sounds like, anyway, it just sounded like something hugely sort of scientific and like a satellite system. So I went to it, I was like, what am I even looking at here?

Lenny Murphy: Right, right. They're in the Nordics. So they're the dominant sample player in northern Europe. Yeah, cool. Private equity backed, you know, and are just building out that, that overall capability is one of the next big players. So yeah, two, two big acquisitions. Yeah.

Karen Lynch: Very cool. So, um, yeah. And what's interesting is, you know, that, that we've got, we've got this focus on like kind of growing capabilities at the same time, we're also talking about improving capabilities. Right. So, um, I Yes, thank you very much. I thought really hard for 10 seconds on that one. But I was thrilled to see when you and I do what we do, how much data quality has popped up in the West. Because it seems like, all right, it's about damn time. The industry is wrangling it. Maybe we'll have to see how effective it all is. Maybe some people are saying, well, again, it's about damn time. But it shifts, in my head, to this proactive approach to it. Even if it's responsive, they're still doing more at the moment. So it's a good time for data quality, starting with rep data, introducing the first ever no-fly list in market research to permanently block fraudulent respondents from surveys. So very cool for them.

Lenny Murphy: Very cool for the companies that are running that software. Been a challenge of the network effect, which exists very much in research space. But sharing that data, no one's ever wanted to do that. It makes perfect sense for a company like Repdata to be the intermediary. And yeah, flagging folks and saying no, don't get that shyster Lenny Murphy, that fraudster who's in there trying to game the system. Put that out there.

Karen Lynch: You say those things and then someday this transfer is going to be loaded into an LLM and then you're going to be spit out as a broadster.

Lenny Murphy: You can't say those things. Well, technically, neither of us should be participating in surveys anyway, from a screening standpoint. But yeah, very cool. And then our friends at GRBN, the Global Research Business Network, kind of the association of associations in GDQ, their new global online sample study, I took it. Encourage everybody else to do that as well. They're trying to understand sentiment around quality, cost, and future use. So they'll put the report out. So help them help us. Click on the link and take the survey and give them a sense of what you're experiencing out there. It was very short. It was a relatively painless survey.

Karen Lynch: Yeah, cool, cool. And speaking of reports, the Data Quality Co-op put out a white paper elevating data quality through collaboration, right? So how, you know, people are coming together for more reliable, repeatable insights. So take a look at that white paper. This could have been included in our, like, two-Read later, but since it is about data quality, I, you know, I figured let's pull it up and make sure people know the context. There's moving and shaking happening around data quality this week. Good stuff. There is. There is.

Lenny Murphy: Well, and similarly, go back to the rep data, right? I mean, there, what data quality co-op is you would, that's what they're trying to do is to be kind of a clearinghouse, centralized clearinghouse and tools to monitor those things. So that's great, filling a real need in the industry across all the different players. So yeah, very cool. So the white paper was the result of an internal research on research that they did. It's not a promotional piece. They did a study, you know, where we're measuring what they were seeing across these different sample sources. So very interesting. And then SMR, you want to touch on that one?

Karen Lynch: Well, this one, yes. This SMR has updated their ICC, their SMR international code. It's a major revision, so we have the link here that will bring you to the website with kind of the latest and greatest up there, kind of showing the emphasis for both scalable and trustworthy insights, like how can we move ahead. And to me, this is what people turn to SMR for, is sort of this global guidance on ethics, integrity, the things that only an association of that size or an organization of that size can be doing holistically across the ecosystem. So I was happy to see this one.

Lenny Murphy: I was as well. I have two reasons for that. I think it's challenging when there's no teeth. But as an aspirational goal, a code of conduct that we should kind of aspire to guidelines. Uh, I think that's fantastic. And certainly that one forms their advocacy work. Uh, I'm sure the insight association and other org, you know, we'll adopt very similar things. I just worry about what it really, you know, bad actors does, whether people actually adhere to those guidelines put forth.

Karen Lynch: Well, look, you have to kind of know where the lines are as you, you know, proceed in any kind of a space, like know where the lines are and know what is expected of you. And then decision-making comes in, whether you're going to step out of the lines or go against the guidelines. But then that becomes a personal choice, because you know what expectations are, whether it's society's or industry's expectations. That counts for us as human beings, right? When they're little kids, you need to know what's expected of them. And if they aren't told what's expected of them, go haywire, right? So it's acting like the parents and it's up to all of the companies, whether they're children, teenagers, or, you know, or adults to decide if they want to step into those shoes. Agreed.

Lenny Murphy: One last thing though, that worries me about this is that it's great when you're in, you know, our family, people that are not in our family.

Karen Lynch: Yeah, yeah. Don't give up, they don't care.

Lenny Murphy: I don't give a rat's ass. The one time, the one and only time I was asked to speak at SMR, uh, at Congress, uh, and, uh, and this was the topic I touched on. This was 15 years ago, probably the, uh, when Google surveys entered the market and all the questions were, are Google surveys going to, you know, join SMR? It's like, no, why would they, they would never. Do that. So the type, we have to recognize that, that it's a continual, it's a challenge as new technologies and therefore new entrants come into the space, which is probably another good segue to new products. And then we'll go to the caveat like, you know, guess what's involved with these new products.

Karen Lynch: Right. Let's just call it out. I don't think we have shared any kind of a new product launch that isn't AI-assisted on some level in weeks now, so it's driving all the innovation. If so, introducing collective innovation and AI-enabled service, helping brands to discover and prioritize growth opportunities.

Lenny Murphy: That does have non-AI stuff in it though. That was pretty cool. There's qualitative, traditional qualitative. They're pulling together different threads to have an innovation hub. That utilizes lots of different data sources and methodologies, including good old traditional qualitative. So it's cool that there's an AI.

Karen Lynch: It's not an AI method of collecting research. It's an AI assistant. It's an AI assist in discovering the growth ops right through all the data. Yeah. And I think that that's probably really an important point is, you know, there's AI as a method of collecting data. There's AI as a method of synthesizing data. There's AI as a method of examining, doing deep research into your research. The AI assist isn't obvious anymore. It's everywhere in all of those different facets. So how each company is deciding to leverage the tech is what we should all be paying attention to. It's like, oh, that's a cool use case for it. And figure out what your company needs to do next. Because maybe you don't need the AI tool because you're a traditional ethnography company. Maybe having AI to be able to extract themes across all of your ethnographic research in the last five years is a super value-added offering.

Lenny Murphy: Absolutely. Related note, Blue Yonder launched their Sprint AI for Agile product testing. That's that whole speed and cost, it's deliberate, but 24 hours. Quick turnaround, so that iterative Agile approach, test and learn, test and learn, test and learn. Uh, cheap and fast. Um, that's a trend we've seen for a long time. Just makes it cheaper and faster. So, uh, so hats off to them. And then a price agent, the same thing, uh, fast, affordable pricing studies, uh, cross businesses of multiple sizes. So if you are, uh, a challenger brand, uh, on Amazon, I, um, or Etsy or whatever the case may be. Uh, and, uh, need to look at doing a price analysis for your product versus others. Uh, that would usually be pretty hard and expensive to do. They're making it relatively inexpensive to do that. So leveling the playing field. So that's cool too.

Karen Lynch: What's interesting about this is where my mind just went with this was, um, you remember a few, few years ago, I mean, we're talking, we're talking not even 10 years ago, eight years ago, I feel like in the late teens, everybody was talking about agile. Everyone wanted to say they had an agile method. And I remember a few times thinking like, is this agile? It's still taking us weeks, you know, like, is this really? And I think they were using the word for like, to mean flexible, right? Whereas product designers were like, no, agile means like you instantly respond and you can move faster. And it's all about kind of, you know, iterating, whatever. It's still hard to do that, certainly at scale, like be that agile, which to me is more about responsibly changing. Anyway, what's interesting is that AI is allowing agility, yes, and faster, yes. But I think what's important for us to call out is there's also the expectation now of improved quality as a result. I don't know, it's just, yes, we can do it faster, but the ROI, because they're spending on it, the ROI is also, like, the expectations are for that ROI to be solid. Like, we're not just doing fast, inexpensive research here. We're really dialing up what we expect in terms of quality. So I think all of these are positioned to help with that. I think so too.

Lenny Murphy: Well, in the interest in the deficit of quality, I would also argue now is depth. Yeah, yeah. It was somewhat limited with just the automation component. The AI does allow for an augmentation of information and some exploratory contextual analysis that is missing when it's just a dashboard. That's part of that quality definition.

Karen Lynch: Yeah. It's pretty cool.

Lenny Murphy: This one was Head scratcher.

Karen Lynch: Okay, we're making a very rough segue into big tech developments this week because the tech developments that were out there are the type that made Lenny and I pause big time. We're like, oh boy. They're big ones. They're big ones. And the reason why, I think I want to explain to people, the reason why we're talking about them is for what is the signal of these big tech changes. And I really want you and I to kind of connect some of these dots about, like, why, right? So let's make this relevant to people. Why are these, especially these three, you know, tech things being talked about? Let's connect dots for people. Anyway, that's just my big segue into, you know, I think I found this, Miramarati, who, you know, was one of the brains behind OpenAI in the first place. She has created something called Thinking Machines. It has a $ 10 billion valuation backed by top VC firms, including that Anderson Horowitz talked about. So Bloomberg reported on this, but there's a lot of people reporting on this because she doesn't even really have a product yet.

Lenny Murphy: Nope. Nope. That's the thing.

Karen Lynch: Yes. That's the thing. I just got chills when I talked about it. They are betting on her for this concept of thinking machines and paying attention. So if you are not following what she is doing, this is a big fricking deal.

Lenny Murphy: They're betting on her big, big, big bet. So the next generation, we can, I think a comfortable assumption is it's the next generation of, of AI in some form or fashion, the, uh, but applied in for that much money, 10 billion seed round guys seed round. So without a product that we know of I think it's game changing.

Karen Lynch: Yeah, I heard her speak at Qualtrics a few years ago. She was one of the thought leaders that they brought on stage. I think it was now three years ago, the first year I went to Qualtrics. And I was like jaw to the ground at the intelligence of this woman and ready to just jump out of my seat and say I'm not worthy. Way. So extraordinary. I love seeing it. I can't wait to find out more about this thinking machine.

Lenny Murphy: So just make a note for Google alert. Yeah, and we should point out that there have been other examples of companies like that, that were the next big thing that never materialized. Yeah. Something leap. Company, they're, they're supposed to basically make, you ever seen the thing of the, like the, the whale jumping out of the basketball, uh, in the, in the, in the gym and the whales jumping out. Um, so it was supposed to be a visual thing, billions and billions of billions, um, uh, put into that without a product to show. So hopefully it's not one of those things. So it's not a guarantee of success, but it's certainly a guarantee of the signal. Of where the interest lies. So, yes.

Karen Lynch: And people that are able to think, she is one of them, are able to think about, like right now I feel like many of us are like, what else could it possibly do? Like, you know, our brains get to a point where there's only so much we can envision. She's a visionary. She was able to envision a world where open AI hits the scene and boom. So that's this vision. Visionary thinking that not everybody has. So anyway, all right.

Lenny Murphy: Well, the name may be a hint, thinking machines. I would assume it has to do with some type of new operating system, you know, within technology that is probably scary. Um, cause there's, if you've watched the Dune movies or the Read the Dune books, this whole idea of the Butlerian Jihad thinking machines.

Karen Lynch: I have to take my sweater off. It's making me sweat just thinking about it.

Lenny Murphy: Yeah. So anyway, interesting. The other one, I found unsurprising in many ways. Yeah.

Karen Lynch: And we had some internal discussions here. My husband and I, Tim Lynch and I, talking about OpenAI is developing chat GPT features. So speaking of OpenAI, chat GPT features that are going to kind of rival Microsoft Office and the Google Workspace. So now imagine if you are one of the users to open AI, and now you're gonna use it like, you know what, yeah, let's have document creation, let's have spreadsheets, let's have our email right from here. So, whereas the other ones have incorporated AI into what they had, they're now going to... First, be AI first, and that's a whole... Anyway, I actually got really excited to see this. I'm like, cool, because I always feel like I wanna give a little run for their money just because. I always feel like they've just been so dominant, and I like the idea of them seeing some competition. And I know that the Google ecosystem versus the Microsoft ecosystem, it's been like one or the other. Are you Google or are you Microsoft in the workplace? So I kind of like the idea that there's some added competition for those two. But also, when you think about world domination, Right.

Lenny Murphy: Well, so, you know, there are all these rumors that were going around, but the tension between Microsoft and open AI for a variety of reasons, like, Oh, well, here's one like, Oh, thanks for your multi-billion dollars. Now, you know, we're going to create a competitor to your, your, uh, your flagship product. We'll see. I must say I've seen a couple outputs of charts and graphs generated in chat GPT. And everybody knows that I'm more perplexed. And Grok user, but those charts and graphs look pretty damn good, and I thought, maybe I need to get ChatGP another try from that standpoint, because it was impressive what they could do.

Karen Lynch: Yeah, I feel like, you know, I pretty much am ChatGP first, even though I do like Perplexity, and I have used other things, I've been in Notebook and all that, but it's my go-to for a lot of day-to-day things, and I feel like a month ago it was glitching on me too much, and I was annoyed, seems to have fixed some and now it seems to be solid, presently, this June 27th. As of this moment. We're very good friends again, so. But yeah, let's talk about that, because another move in this space where Apple is exploring, acquiring perplexity, and I'm like, Apple must be like, you know, us too, like, you know, and I'm like, all right, go on in there, you know, you can go in the playground, play with me.

Lenny Murphy: Well, they've struggled with the AI strategy. Which was always kind of surprising to me, the company that brought you Siri, right? I would have thought they would have been the leader but no with no, you know, no, no shade guys, it was just a just a little bit of surprise the And it makes sense and perplexity has done a really great job not just from a search standpoint, but building tools into the platform That make it really usable from productivity standpoint, etc, etc. So yeah, I certainly could see the value in, uh, in doing that. Um, so let's make it, this is what I want to do.

Karen Lynch: And we didn't talk about this ahead of time, but I really want to say like, okay, these are these, we're watching these big players and it's like, all right, we are going to connect dots. These are signals for us. And let's kind of riff on, um, on the why. Cause as I was sort of looking at these and I'm thinking, um, there's something about these large environments that sends to people in insights and analytics and data providers, data collectors.

Lenny Murphy: Yes, it's systemic. Yes.

Karen Lynch: And so what does that mean for the businesses? It means one thing that came to me is sort of the interaction that end users have with all of the research platforms and tools and everything. There is this desire to kind of simplify and bring things together and have this ease of interoperability is very important, right? Because why is all of this happening? It's not just about the tech players moving their money around and making financial gains, sure, but it's pointing out something else on a macro level that, anyway, that's my take, is I think that this is all going to lead to a different expectation that end users of research will have for how they interact with our platforms, programs, survey tools, quality scale platforms. 100% seamless, seamless, 100% agree with you.

Lenny Murphy: That's what I think about, you know, these are Steve Phillips who has a great from Zappi gave a great presentation a few years ago at IX, on the platformification of research. And this is before the AI era, right? And that in the idea was, who was going to be the Microsoft Office or the Google of research? Well, it's going to be one of these companies that from a Genetic flow connection standpoint, that's the hub. That is going to be the hub. You will execute these things from a prompt that you have embedded into your OpenAI Office solution, for instance. That's what they're angling for. And who's gonna win? Don't know. It'll probably, it may wind up being just like it is today. There's four or five that dominate the market. But everything else will be simply orbiting around them.

Karen Lynch: And if you are, I could be wrong, I could be wrong. But if you are a company that has a platform, cloud-based, whatever you've got going on, you have to be thinking about where it's housed, you know, like, uh, I don't have the right language for it. You have to be thinking about how you're building your infrastructure so that it has this, this power behind it. Um, and isn't. Yeah. Yeah. That makes sense. I'm like, it's super fragmented in my head because now I'm talking too much tech and it, it, it hurts my brain a little bit, but these are all the things that the big development that the developers of these platforms need to be thinking about the big picture is where is everything living? Where is it housing? Which clouds does it operate on? Which operating systems, which? Yeah.

Lenny Murphy: Well, your wonderful hubby just made a comment. Apple AI seems to be going the BASF way. They don't make the thing. They make the thing that everyone uses to make AI things. Hardware and silicon is what many AI apps use to code on. Agree. So there's NVIDIA, right? For instance, NVIDIA Intel, those that have hardware infrastructure, plus the power resources to do that, hence why Apple's invested in nuclear power plants, right? Or I'm sorry, Microsoft. But yeah, and then there's the cloud infrastructure, Amazon, Microsoft, then there's the code. But the code is where the utility and the monetization comes in. So everything else is a cost center to support the development of the code. These are going to be the platforms that the code is going to be deployed on and integrated into overall.

Karen Lynch: It just has me thinking about the new entrance to the industry, and these are people that think that way. So many of the new entrants, they didn't come out of the research world and say, I want to develop a new product. They came out of this coding space and they're like, we can do it this way. That's why those competitors are to be kind of looked at with a different lens because they're not necessarily, they, they didn't come at this through the eye of a researcher.

Lenny Murphy: It's an engineering problem, not a research problem.

Karen Lynch: Yeah. Really interesting. So I guess all of these research companies should, you know, be investing in the engineers they bring on board at this point also.

Lenny Murphy: And everyone pays attention. I would caution anyone though, to think that we are that, that war, is still there. Who's going to win? I don't think there is going to be one winner. And it's probably a good segue, the Menlo Ventures. So some recommended readings, guys. 2025 State of Consumer AI. That was looking at AI adoption. But there's some posts in there as well around the companies. So this infrastructure thing is still a big deal. Look, you can't bet against Grok just can't bet against Tesla because Tesla is going to have the real-world data by them You know just because that's what they built they built cars that record everything for them to function correctly. So that's a that's a very significant Advantage that they will have open AI has their they were the first out of the gate and have the most integrations You know, but you can't discount You can't discount better Even though they seem to be struggling You surely can't discount Google or Microsoft because of just their sheer size. So stay nimble. Don't get wedded to any one thing, either, because we don't know who's going to win. Yeah, yeah.

Karen Lynch: More on this Menlo Ventures report. So, you know, I looked at it this morning and, you know, then, you know, dug in. And there's some interesting sections of it where they talk about white space opportunities. So for anybody who's kind of like wants to dig in there because you want your There's some ripe for innovation thinking in there. But also, it talks a lot about usage and how consumers have caught up, which we've talked about in the last few weeks also. But one of the things they're saying, very high usage for millennials, in particular millennial parents. You can get to this point. I thought that was really interesting. So millennial parents are turning to Gen AI for that kind of assistance. Anyway, so if you work with consumers and you want to understand your consumers, that's like, there's one reason to dig into this report and that's the kind of the tech business development strategic thinking we need to do. Also, if you market to consumers, there's some really interesting stuff about consumer usage of these platforms and what is changing like real time right now. Point in case, sitting, and the mother, at the end of the day, they're having some exchange about different things, such as going out in the sun and potty training and disciplinary behaviors and all that. And the mother keeps sharing with my daughter the GPT answers to her questions. So when my daughter asks the mother questions, the mother is asking generative AI and giving that information to my daughter. And it's a fascinating concept for me that that is happening.

Lenny Murphy: It's a little scary based on what we covered last week about the reliance on AI, limiting your cognitive abilities.

Karen Lynch: But say your target market is millennial mothers. You need to understand this. You need to understand this dynamic of why are they trusting that? Who don't they trust? To me, that's a big thing. And what is the need gap in their information? How can brands fill that gap and help educate these women who are looking for intelligence?

Lenny Murphy: As the trusted resource, trusted partner, trusted source.

Karen Lynch: Super cool report. I really liked it. And I'm sure you can find more. It was an analysis of AI adoption across 5,000 US adults.

Lenny Murphy: Want to run through these other ones? Again, suggested reading links, guys. These really are. Yeah.

Karen Lynch: Why don't you take these two that are linked? I'll take this first one because I haven't read it yet. The Shaper.

Lenny Murphy: Go ahead and talk about that one. Sharper. Donated company. Sharper. Sharper. It's just a good piece on why Insights teams struggle with AI. And so some internal research that they did and some strategies for high performance. So if you're still scratching your head of what the hell, you know, what do we do and how does it fit within the research organization? It's a little more focused. Suggestions there. So thank you to the friends at Sharper.

Karen Lynch: This really the next three, this is a huge topic we should have left 10 minutes for.

Lenny Murphy: We should because it's all pretty darn interesting.

Karen Lynch: Here's what's happening. We've got a LinkedIn post by Carolyn Hyde talking about AI's dual impact, right? So it's partially driving workforce reduction, while at the same time, fueling record compensation deals. So what's happening in this blog post, you can see some people are getting big bucks right now for their AI expertise. And some people are either going to lose jobs or potentially not get hired at the entry level. So there's two things happening in this space. So her blog post really articulately talks about that. Then we've got a Read for that. I think that you had found from 8000 hours how not to lose your job to AI. So skills that you need to kind of future-proof that. And then I did want to call out, I didn't mention it this week, but because I just saw it this morning, Kristen Luck wrote a thought piece about the experience gap and how AI could disrupt, in our industry, the path to a kind of professional mastery, which is part of this. So these three reads in a row, take them all in. Take in Carolyn Heights' post, the how not to lose your job and then Kristen Lux's think piece because it tells the picture of what we need to do to make sure that the future of the industry is secure and that we are raising leaders and thinkers from those entry-level hires, young professionals in their 20s and helping them get to mastery so that they can get to where many people in the industry already are. And what is mastery?

Lenny Murphy: I would argue that we keep coming back to the same and even the comment about the mom, right? That critical thinking, that's top there, right? Critical thinking, problem solving, the ability to ask questions, to think through a problem, to think through second and third order implications. And not just hypothetically, but with a sense of mastery. We've seen this before. Those are those core skill sets. And there is still that piece, goes back to our very beginning of our conversation, you know, the hug, human to human, you know, intuition, contact, understanding, those are all, those are all things that I think are important in a knowledge worker, white collar type of world to focus on to create that. And the benefit may be, and I heard early on, Altman had said that we would see, you know, the next generation of billionaires that were like one company, one person companies, right, type of thing. So we may see that as well. There's going to be a lot of opportunities for specialization and winning relationships because you're smart. Utilize these tools to compete effectively against large organizations. So that could be really interesting as well. And that last thing, we're going to talk, this Gartner predicts, but over 60% ofogenic AI projects will be canceled by 2027.

Karen Lynch: You know why this is a good bookend? Because first of all, everyone is like, you know, AI agents, AI agents, AI agents. That is where so much mental energy is going. But most of them will either fail or be canceled. Most of the efforts in this space are going to fail or be canceled. And that doesn't mean we shouldn't do that. Right. It's an option. Right. It's just what's going to happen. Everybody's got to try these things out, see what's effective. But you have to have that in your strategy. You have to have these projects right now or you won't break free with the one that's going to win. That's how I interpreted this whole thing. Gartner has a lot of events coming up in the next six months that I'm going to tune into as best I can also to kind of watch this particular trend. But yeah, there's a lot of, whether things work or whether there's ethical risks, whether there's governance issues, there are going to be reasons why a lot of these projects don't succeed. So but it doesn't mean don't try because 40 percent of them will.

Lenny Murphy: Right. And if it can add value. Yeah. You know, with value being, you know, kind of your own definition, kind of, you know, wiggly there. But if it delivers value, it will succeed if it doesn't deliver value or makes people's lives harder. Then it won't. So encourage you to think about where's the value creation at the front end. And then to your point, try it. So we'll see. All right, we will not be here next Friday. We will not be here next Friday.

Karen Lynch: We will be celebrating, for those of you tracking the dates, the 4th of July. So Green Book, actually, if you're looking for us, Green Book office is closed the week of 4th of July. It is our way of thanking our team for traveling on weekends to all of our events. Events throughout the year. This is sort of, we get a pass on a couple of work days so that we all freely travel on weekends to and from our events. So yeah, we will not be in the office next week. We will be checking emails, but we will not be live next Friday.

Lenny Murphy: We will not be live, nor will we be prerecorded.

Karen Lynch: Nor will we be prerecorded.

Lenny Murphy: There will not be an exchange next week. But if you really, if you miss us so much, On YouTube and you can go back through you know, the whole all right I mean, so what is this episode like, you know bajillion?

Karen Lynch: No, I just keep doing this. I can't believe we keep doing it and we have no intention of stopping.

Lenny Murphy: We don't actually really. I just saw today that YouTube is rolling out a genetic search within YouTube. I haven't tried it yet. It's supposed to summarize the videos so if somebody wants to go through our entire catalog and do a synthesis of all of the topics and share that with us. We will showcase you, because I think it would be really fascinating.

Karen Lynch: Yeah, yeah, no, absolutely. Yeah, I shared that. Anyway, I don't have to talk about sharing it with the SEO team. Not relevant to this particular conversation. Oh, how are you? Good to see you.

Lenny Murphy: Hit that like and subscribe button. We appreciate it.

Karen Lynch: And I love when people pop up like that, you know, It's really good to see you, and I'm glad, you know, she was one of our first AI speakers, actually, she came to, I think it was our first AI event, Aisha Lee, so good to see you here. Yeah, and we'll see you all in two weeks.

Lenny Murphy: Two weeks. Everybody be safe, enjoy, stay cool, or warm, I guess depending on where you are in the world. If you're in Australia, all my Australian friends are like, it's cold! Oh, come on, you're in Australia. It's not cool.

Karen Lynch: Anyway, get those hugs in, you know, I, I, I each of you to make one, one hug last in for, you know, at least, you know, at least several, several seconds, if not 20 seconds, if not three minutes, go for six minutes, if you can afford it.

Lenny Murphy: So, you know, and kid hugs are the best kid hugs, spouse hugs, family hugs.

Karen Lynch: Yeah. Yeah.

Lenny Murphy: All of them. All right. Everybody take care. Bye.

Karen Lynch: Bye. I made peace out.

Lenny Murphy: That's right.

Links from the episode:

Ipsos finalizes acquisition of The BVA Family 

Norstat acquires Sample Solutions 

Rep Data introduces the first-ever 'No-Fly' list 

GRBN and GDQ launch Wave 2 of their global online sample study 

Data Quality Co-op White Paper: Elevating Data Quality Through Collaboration  

ESOMAR: 2025 Update to the ICC/ESOMAR International Code 

Ipsos introduces Collective Innovation  

Blue Yonder launches SprintAI  

Priceagent debuts “Price Check” 

Murati’s 'Thinking Machines' raises funds at a $10B valuation 

OpenAI is developing ChatGPT features to rival Microsoft Office and Google Workspace 

Apple is exploring a potential acquisition of Perplexity AI 

Menlo Ventures: 2025 State of Consumer AI 

Sharpr (a Dynata company) explores why most insights teams struggle with AI 

LinkedIn post: Caroline Hyde on AI’s dual impact 

80,000 Hours: How Not to Lose Your Job to AI 

Kristin Luck: The Experience Gap 

Gartner predicts over 60% of agentic AI projects will be canceled by 2027