AI Agents Are Changing Everything. Are Insights Firms Ready?

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!

With IIEX Europe weeks away, this episode zooms out from the logistics to tackle the bigger questions reshaping the insights industry: who survives an agentic future, and how?

From a $250M raise rewriting how AI finds information on the web, to the structural trap that kills promising boutique firms, to why AI may be creating more work before it eliminates any, this conversation covers the forces every researcher and strategist needs to understand right now.

Many thanks to our producer, Karley Dartouzos.  

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Transcript

Lenny Murphy: And we're live. Always by the seat of our pants.

Karen Lynch: Always actually, some days we're good. We should give ourselves more credit. Some days we are not by the seat of our pants. A day where I had to stop mid-sentence because it says, you know, we're live.

Lenny Murphy: But well, it's been a weird drink. It's like a catch-up week. I don't know about you. Well, you were out last week with your daughter's graduation and, you know, but just that Monday holiday, like this whole week has been.

Karen Lynch: Yeah. Monday holiday is a very, it just throws it off. And, you know, you'd think that then it feels like a short week, but it doesn't because, yes, Ashley, Anyway, got it. You would think that it's, you know, feels like a short week, and yet it feels like a long week because we're then compressed, right? So, um, yep, yep, 100%.

Lenny Murphy: And there's always, there's so much content to absorb, both. Things that we produce, and uh uh even what we're going talk about today, so um there's not enough time in the day for all of the all the wonderful content to absorb, yeah um on that note, uh on that note, the content to absorb content to absorb yes content to absorb, so let's talk about Europe, because before we move on too far, thank you Karley, so she's like I'm ready for you, you know IIEX Europe.

Karen Lynch: We are, we're so deep in it right now because we're at the point where the presentation is coming in. And so we're reviewing what everyone's saying. We're getting those, hey, can I tweak my title just this much or our session descriptions just this much? But it's going to be a great show. We're excited. You know, Europe, if you haven't been to the IAX Europe event, it's, it's, you know, it's a little bit. It's just got a different vibe than North America. There's only three stages instead of five. We're excited because we're bringing the competition to Europe this year. And so, you know, it's going to, that's going to be fun. You know, different energy. It's, we're just excited for it. So it's going to, it's now, you know, less than a month away. So we're, we're, we're in it. We're in it right now, up to our eyeballs.

Lenny Murphy: So, um. and an email went out today announcing the uh the finalists for the competition. So, check that out. Um, it's a good crop, it's a good crop. So, I'm very excited about all of that.

Karen Lynch: So, um, yeah, yeah, and you know, the award program, um, we're doing the same thing that in North America, which is we have three different awards that are going out. So, of course, there's crowdsourced judging for the audience favorite award in North America. That was super fun. And, there's also the judges. Kind of choosing that particular award. And then there’s the green book, which is the industry book award, the green book leadership team choosing. So there are three awards given out this year at each of these events.

Lenny Murphy: So 48 entrants and eight of those had previously entered, but 40 fresh, new companies, which is just indicative of where we are. As an industry with so many new entrants and so much disruption, which we're certainly going to get into today.

Karen Lynch: Yeah, that's cool.

Lenny Murphy: On that note, the grip form is coming up. And I think, Karley, you've got there you go. The date. So the report's done. It is incredibly in-depth. I say this every time, but it is true every time. The most important best. Version of grit we have ever done. Because just the trends, right? We see them. It's very measurable. We went years where things didn't really move on some things. Not where we are. Things are moving incredibly quickly and we're measuring it. And it's grit form. We'll talk about the high level stuff as well. All right, plugs. I think those are all of our plugs.

Karen Lynch: Yeah, well, real quick, let's just answer Nancy's question because other people may want to know: is this the first year the competition has been in Europe?

Lenny Murphy: It's been in Europe before it was years ago, uh, but there weren't as many startups, so we scaled back just to the US because there just wasn't that many new companies entering the market. Um, that's not a problem right now, so we'll be doing it again at IX West as well. And yeah, we'll see. Will we get another 40 brand new entrants?

Karen Lynch: Uh, I mean, maybe, yeah, maybe interesting, yeah, yeah, we'll see how it all turns out. So, anyway, so cool, yeah, let's talk, let's talk about the money. Shall we talk about money?

Lenny Murphy: Talk about money.

Karen Lynch: Um, we do like talking about money first. So, have you heard about Exolabs?

Lenny Murphy: Because I had not. Um, but I but this jumped out, I'm sure you both. Probably arrived at the same conclusion. Exilabs raised $250 million at a 2.2 billion valuation to scale its AI native search engine and web data retrieval platform. Yeah. Now, a similar website. There's a lot of companies in that space, but obviously nobody's got that locked up. And I just read that as the thirst for data. And it does look like they have more of an infrastructure. Model, um, you know, piping into uh into eugenic systems, etc. Etc. Uh, so that data data is new oil, and everybody wants everybody's wells.

Karen Lynch: Um, well, you know, and one of the things they're talking about in here in this particular press release about Exilabs is you know, they're stating the fact AI agents will search the web more than humans this year, and that is a that is a bold statement, yep. Um And, you know, we're as a web-based company, largely Green Book. We have, of course, our IAX brand, which is not necessarily web-based because we're largely an in-person events brand. And we have products that don't necessarily live on the web alone. But, you know, our directory is a web-based product these days. And, you know, we have an editorial system that lives online, and our shows are pushed out via. Internet. But as a web-based company, we pay attention to web-based search, that's for sure. And it just stands to reason that we're paying attention to who searches the web and AI agents searching the web. And we're doing a lot of work in this space, friends. And we want you to know that. And if you have questions about your company being found, you should talk to us because there's a reason. There's a reason why you really need to be in the Green Book Directory if you are not right now in this time of agentic search. So please reach out to us and talk to us about that. It's not just a shameless plug right now, but it's important that you understand this. And we're not going to get into it now. That would take a whole show. Right.

Lenny Murphy: But let's talk about for a second because this, this, I was on a conversation with a brand last week. This is a critical issue for them because the buying process is being changed. Right. And what an agent determines to recommend and the qualities it looks forward to recommend are very different than ratings and reviews or traditional search. And so all that applies of authority, depth of content, and authority is a big deal with all of this. That's what agents are looking for. So this entire, whether it's B2B or you're looking for recommendations for for whatever a new uh salsa right I mean it's just different so all of this is is relevant it is a what does brand mean yeah in that world uh agents doesn't give a about your brand yeah so you know that's anyway so much larger stuff yeah the I thought this was really interesting the comm score news uh commscore sold its its box office measurement business rent track remember the old classic rent track um uh to uh advea capital which is going to revive rent track yeah um and they didn't get a lot of details on what they're thinking my guess is that it'll be more than movies that it'll probably go into streaming content um etc etc again but it's a private equity group said, Hey, we see value for data related to media and entertainment. Com score, can we buy this from you? So I thought that was really interesting.

Karen Lynch: Yeah, yeah, yeah, no, for sure. I mean, yeah, yeah, definitely interesting. I did, you know, I kind of read it and I didn't have much deeper thought on that other than, you know, an interesting move right there.

Lenny Murphy: I'm glad to see a classic brand return. I mean, Ren Track was, you know, even consumers right would look at Ren Track data on movies and you know, all that good stuff. So, yeah, so that was a that was interesting. Um, uh, what do you think about this uh Futurum group?

Karen Lynch: Uh, yeah, so Futurum. Group activity, parent of enterprise technology research, combining ETR's predictive quant data engine with Futuram's market intelligence platform. To me, this just, you know, it's this combination of two things that are popping right now, right? Predictive, predictive, predictive quant, yes, with, you know, market intelligence, yes. I'm like, those are. You know, two trends that we're seeing pretty loud and clear right now. Like, yes, predictive analytics and yes, we want market intelligence. So it's a combination that makes a lot of sense and a partnership that makes a lot of sense. So, you know, that's the way I'm like, yes, when I saw this, it was like, yes, that makes sense to me, that type of partnership. So I don't know much about either of those companies, but it makes sense to me. It was one of those, yes, this one makes sense to me. So.

Lenny Murphy: Yeah, data synthesis. Yeah, data synthesis. Uh, whether partnerships, acquisitions, whatever the case may be, put the data together, throw some AI on top, unlock new, uh, new insights and value, and deliver it via an MCP. Yeah, that's uh, that's all of this, and then our friends at Rep Data, they've been on a tear lately, yeah, this is like the

Karen Lynch: 100th acquisition this year. They're catching up to NIQ. No, right? No, no one could quite catch up to NIQ. We'll get to that later. But yeah, no, OWL Solutions, Survey Programming Expertise. They are just building quite an end-to-end solution right there, aren't they?

Lenny Murphy: They really are. They really are. So the next solution. And it's interesting. You know, for these new companies coming together, they don't have the technology debt, you know? Yeah. And they're not just kind of putting an AI wrapper on a new thing. They're purposely building new solutions aligned to kind of the workflow, the modern workflow approach. So I think that that was really interesting.

Karen Lynch: Yeah. Yeah.

Lenny Murphy: Speaking of workflow, now we move into the part.

Karen Lynch: Hang on a second. Let's just pop back up because I'm seeing that Crispin, before we move, move too far away from probably a little bit of a delay, but we were talking about Excel Labs and this play about AI agents searching the web. He's talking about AEO, which is kind of like this. Or you know, AI or whatever, you know, whatever we're calling this kind of AI engine optimization. Um, IDX is looking forward to being at IAX Europe, um, and they're gonna be offering AEO audits, so find them there. And let's just also shout out the fact that they are sponsoring the competition, which we talked about earlier. So, thank you for that sponsorship, Crispin. So, I'm glad you're here and reminding us that that's a good opportunity to shout you out for that. And I'm disappointed that I'm not going to be talking to you on stage. Like, I'm still excited to be talking to. You know, you're kind of an appointee, but I'm sorry that I'm not talking to you personally. But thanks for that sponsorship. I'm really glad that you're going to be sponsoring the competition. It speaks well of the fact that you are, you know, investing in innovation in general. So, yeah, so pretty cool you're doing AEO audits there. I'm excited to learn a little bit more about your investment in innovation and pretty cool sponsorship that you're doing. It's cool.

 Lenny Murphy: I also, since Christmas, since you're here, I will give a shout out. The depth. Chris was a judge for the competition entrance, and the depth of commentary that you produced on each company was really great. And we use that data in other ways. We're unlocking new ways to leverage those things. And I just really appreciate the depth of thought. Now, I'm pretty sure that you programmed an AI to do the evaluation, which I'm all for. There's no criticism in that. Because it was great because it was still a thoughtful, in-depth commentary on the judging rubric and the company. So, Crispin, hats off to you for that. So, since you raised your hand, we'll show Crispin some blood.

Karen Lynch: Just so you know, also, people, when we take on a sponsorship of that competition, you get a spot on the judging panel.

Lenny Murphy: Yes.

Karen Lynch: So anyway, so just so you know, that's also a part of that sponsorship.

Lenny Murphy: So 100%. 100%. All right. Let's, I mean, the EY and Microsoft. Yeah. That was, I took that as a me too after the news two weeks ago of the, you know, the forward deployed engineer, you know, for. Anthropic and OpenAI, or just another help to scale AI enterprise-wide.

Karen Lynch: Yeah. So basically, for those of you not seeing what Lenny and I are seeing right now, and if you're not seeing Karley posted live, because I don't know if it goes live, but EY and Microsoft expanded their partnership with another. $1 billion five-year partnership.

Lenny Murphy: Like 15 billion being thrown into this deployment initiative.

Karen Lynch: Come on. But what's cool, if you look at this brief, yes, it's about scaling AI enterprise, but they're talking about workforce upskilling, embedding change management, continuous optimization for agentic AI transformation. Again, like you, I live in this space because my husband's a change management consultant. So I know what these enterprises are working on and it is not slowing down. This is where they are doing a lot of work in this space. And when we talk about workforce upskilling, we're not talking about, they are hiring workers with skills. That's not what we're talking about, about workforce upskilling at the enterprise level. We're talking about people learning how to prompt still. Probably our listeners are leaps and bounds ahead of where some of these enterprise employees already are. So pat yourselves on the back, but there are people at these large organizations that have a lot of work to do still. And so that's part of what we mean by this: adjusting to the change, learning how to use the tools that you may already be using every day, because you are building businesses that have agentic tools in them already. My guess is if you are here listening to Lenny and I every week, you are probably upskilled already. But that's what's happening at the enterprise level. They are not necessarily, they're still a little slow to adopt, even at, certainly they're using proprietary systems internally. They're learning how to use those. It's a very interesting world out there.

Lenny Murphy: Well this one particularly too I think that there's a dimension of this that struck me of this was a little bit of a punchback from consulting company and microsoft to anthropic and open air and like oh you yeah you're gonna try and become consultants well let's just see about that um yeah yeah uh and and the power of of trust yeah would anybody think, oh, it's a bad decision to go with Ernst ⁇ Young and Microsoft? No. So I think that it was really interesting to see those companies adapting to these massive changes of, you know, like, no, sorry, you know, AI companies, you don't get to come in and just take over everything. So we're, you know, we have value and they're finding a way to deploy that value in a specific way.

Karen Lynch: Yeah. Yeah.

Lenny Murphy: Since been in the news almost as rep data in NIQ.

Karen Lynch: I know. Pay attention to these names because they're doing something. They're doing something to stay in the news.

Lenny Murphy: Well, very smart. We've talked about this ad infinitum. Since in the data business now, they're connecting human data aligned to business issues and that doesn't necessarily mean a survey. So now they've integrated into the Salesforce partnership with an AI suite for Slack. So I assume it's through the Salesforce integration of Slack.

Karen Lynch: That's a big deal for me.

Lenny Murphy: Go where the buyers are instead of making the buyers come to you. That is a fundamental shift that is affecting and since on top of that, right? They're deploying their asset of access to humans and data in new ways. I encourage every company to think about that.

Karen Lynch: Yeah. Yeah.

Lenny Murphy: All right. Well.

Karen Lynch: Let's talk about NIQ. Here's our weekly talk about NIQ. And you know, we joke about it. I almost, when I typed this in here, I almost literally put NIQ, ha ha ha. And then I'm like, delete, delete, because I'm like, don't write, don't write ha ha ha. But here we are. We're laughing, folks, because if you don't tune in weekly, you don't hear Lenny and I saying NIQ has launched another feature. What they're doing strategically, and why we call it out, is because they're in the news cycle weekly with a new product or feature launch. They're shipping. They are shipping. And they're doing it so strategically so that people keep talking about it and so that people stay in the news, they are raising brand awareness. Weekly so that they are top of mind as people who are innovating and launching and innovating and launching, and they're top of mind. It is like a brand awareness game that they are playing and doing very well at. I may not remember the name of half of these product launches. I shouldn't say I may not. I do not remember the name of all of these, but what we are remembering is the frequency of launch. That is happening, right?

Lenny Murphy:

It's and that is something to be noted. And the business model of the, they've moved away from projects, you know, which they always were, they were never really so much in the project business to begin with, but they're unlocking value through the combination of their data and their capabilities with partnerships and extensions. And, you know, they're creating systems. They've become a node. Around various things. So, this particular and I keep discovering to connect consumer sentiment with real purchase behavior. But what this really is, like, oh, we got a bunch of data on at least my tape, we got a bunch of data on behavior. Now we need to ask some questions to fill in gaps of information as a seamless system overall. So, and which creates this virtual cycle of feeding back in and building training data. You know, that is your IP around these specific things. So, yeah. So, hats off, NIQ.

Karen Lynch: Yep, yep, very cool. It's done.

Lenny Murphy: Yep, pretty cool.

Karen Lynch: Ipsos. Ipsos, right? Getting in the game. I had the same thought. I was like, all right, Ipsos, I see you getting in that game. Launching Product Studio. So an AI and data science enabled platform for faster product testing. This is where we start the AI product launch series. Right? So this next bunch, like, of course, you know, this is the time when Lenny and I start talking about all the AI product launches that are coming up. So, yeah.

Lenny Murphy: Yeah. But, but, good. And if you're a full service research company, Ipsos is a full service research company, right? The very definition of one, although, you know, large and relatively diversified, they are creating products. They're leveraging their IP, access to data, streamlining the process. It's going to be lower cost. And they're undergoing that transformation. They did the same thing when automation hit back in the and now they're accelerating that.

Karen Lynch: So half off. Quantilope.

Lenny Murphy: This was a no-brainer. What did you do?

Karen Lynch: Yeah, yeah, no. Yeah, another no-brainer. And so they've launched QuinnSearch, AI-powered knowledge base, taking, you know, an organization's entire project history, turning it into a knowledge base where users can query their past research. You know, you can type in, get an answer to a question, et cetera, et cetera. So yeah, no-brainer. I think they use the language, you know, it's just as easy as asking a colleague a question. So, yeah, making past research accessible. Yes, I feel like everybody should be doing that. Didn't we say that the last time we didn't meet last week because you were on with Sarah, but like two weeks ago, didn't we say that? Like, yes, that's what everybody should be doing. If you should be, this feels like yes, yes, 100%.

Lenny Murphy: I mean, bring bring down. Bring down the silos, reduce friction, increase utilization. And absolutely. And platforms like Quantilope are uniquely qualified to do that because there is a historical repository there. Same variation on a theme. Cervicate rolled out a research hub, AI research repository.

Karen Lynch: Have you heard of them before?

Lenny Murphy: I had not heard of them before. So a company I'd not heard of. This little level of geekiness creates editable source length reports. We've talked about this before but most research is still delivered via PowerPoint. So creating editable documents is one of those just, you know, oh, you know. Whatever, my steering wheel is leather, it just makes it nicer, you know.

Karen Lynch: So, yeah, yeah, I hadn't heard of them either. And, you know, when I was trying to kind of check them out, I'm like, this is this, this is just one of those new pop-ups to me. I like new pop-up because they can, because they can exist. So I was like, this is interesting. So here they are.

Lenny Murphy: Here they are. A bunch of recommended reading, but one wow.

Karen Lynch: And I'm so glad we saw it. Now I'm like, I'm so glad I'm looking at the time and I'm like, I'm so glad we can do some of this stuff because there's a lot here. And anyway, so yeah, you want to, can you talk about Jim Whaley's piece first? Because I thought it was really important.

Lenny Murphy: So I thought it was important.

Karen Lynch: Yeah. All right. So Jim Whaley MR. Right. Yeah. He posted on LinkedIn. So we'll share the link. And it's one of those, like, you know, kind of, you know, thought pieces where he's taking a step back and he's reflecting on something. And I just thought it was really interesting because he's talking about, you know, smaller companies that are kind of overlooked in the industry. And when I was reading it, you know, I was kind of thinking, He's talking about the long tail of underserved insights teams. And I didn't, I kind of got tripped up on that. And I'm like, how's, you know, anyway, I read the article and I'm like, I'm not going to get tripped up on the phrase. I just want to read what he's talking about. And then I was like, what? What he's talking about is really interesting. It's about how a lot of these smaller companies get started. You know, you're a professional and you end up leaving the firm that you worked for, and you've got a really great reputation and you're really smart, and you have kind of a business idea, and you and you leave and you take some clients' kind of history. You leave and you take some clients, and then you get some more clients, and you start a really kind of a good business model, and you have some more clients, and you kind of scale up a business. But and you have a good brain like you're it's sound right it's a sound business, but you you haven't necessarily thought through the structure of what your business is going to become and here we are disrupted right and and maybe just maybe this type of business doesn't have the infrastructure to compete right now and anyway so it's just this kind of read where I think it's a good read for those of you who might be struggling right now because you had a really good insights practice for years. Yep. But right now you might be struggling. I just think it's a really interesting piece to think about the way he phrases that, where it's like, you were a really smart guy who started an insight or gal who started an insights business, but there's a ceiling because of this structural issue.

Lenny Murphy: Right. Right. I mean, it's all about scale and capital and, you know, all of those things. But I thought that was a really good dovetail into the CB Insights report.

Karen Lynch: Yes.

Lenny Murphy: So CB Insights released a report on professional services firms and how they compete in the Agentic era. Excuse me, I'm sorry. And the top line was, which we've talked about, you're orchestrating agent stacks, activating project data, productizing services. But all that was based on, and this was the connection to Jim's for me, the judgment, the human judgment and expertise to do those things, because everything else is kind of a process component.

Karen Lynch: Yeah.

Lenny Murphy: And, and, and I think it's tied into, uh, into uh Jim's take as well, right? When you're a small business, you optimize as best you can, but there's not a hell of a lot of money to invest in that. So you just focus on just getting it done. And a lot of companies, earlier this week, had the opportunity to talk at the IA virtual CEO summit they do quarterly. And, you know, everything we talk about, you know? Yeah. Point was, you know, these, the bulk of them are, you know, small to mid-sized research agencies, full service agencies, and at this place of, you know, all right, how do you transition from a process-oriented business model to take your IP, your expertise, your trust, you know, your relationships, those inherently human things. And now make them fit into this agentic world, right? Of workflows and infrastructure and connectivity and productization. So, I would encourage everybody, really check out both Jim's piece and the CBN Science piece because they're two sides of the same coin.

Karen Lynch: They're describing the same challenge because what AI can do is give advice and be consultative, right? Like that's been proven, right? That AI can assess things. Can look at candidates and give you input into it. When I was looking at job candidates recently, I asked the AI's opinion. What do you think? Who would be the best fit? In your opinion, AI, who would be a good fit for this position? It doesn't mean I didn't also think. But I did ask for its opinion. You know, obviously, some of the judges at the competition may have consulted with AI and said, who do you think best fits this criteria? We are asking AI for advice. We talked about Steve Phillips, the new kind of AI tool that he has, right?

Lenny Murphy: CFO.

Karen Lynch: Right. So, the brain, right, the artificial intelligence brain is replicable of the human brain on many levels and in some cases, maybe smarter. So, the building, the implementing, the orchestrating, the constructing of the AI tech is what you are what the human has to keep doing. And the building of the platforms or the how to orchestrate the AI technology, that still has to stay in the human's hands. Yep. And that's what these firms, the professional services firms or the insights firms, have to keep doing.

Lenny Murphy: Right. Yep. 100%. And I'm glad you brought up the judge piece, right? So I'm imagining, well, I don't go there. I know every day now at this point, point I have built skills I have built you know uh standards for you know absolutely within my solutions because there's things that I just do all the time and and the more I do those things so I wrote those I'm the one who said this is how this is the this is the ip this is the context this is the information here here's the sources here's all the things that I would do manually on a regular basis Leverage this based on my predefined perspective, my contextual judgment on those things. And create the deck because I don't give a shit about creating the deck, right? Whatever. I've never been concerned about the output, other than it was simply meant to communicate something. So my point being that I am a consultant. That is how I pay my bills. So in this world that we are in. We have to decouple from the process and think about those skills. We're going to get that here in a minute too, right? Is the, how do we channel our context, our judgment, our creativity, our, our IP, et cetera, has the, as the initial frame. Don't worry about the process. Let the AI do the process. You know, it's cheaper and faster, et cetera, et cetera. And then the judgment on the back end to make sure it's right and accurate, and we add more value. And what I'm finding more and more is it's like, you know, we spit out stuff all the time. I there's more people who want to talk to me now than ever before. They're not interested in reading stuff, right? They want to talk, they want to explore. You know what happens, what's this mean in my business, in my world? That's that human expertise that there's not a replacement for. And that's what CB Insights and both Jim are talking about. But that middle process piece, sorry, and I'll shut up with this. That's the barrier to growth is scalability. So these tools do let us scale, right? They give us, at the very least, increased bandwidth. So, um, so anyway, pay attention to all that. This is, it's, it's just where we are. And anyway, sorry, I went off on a soapbox, Karen.

Karen Lynch: Well, I think, yeah, yeah. I think that the bottom line is you can use all the tools, but you need human judgment. And the human beings, the human beings are the ones that are going to determine whether even the processes are the right ones and whether the output is the right one. Because if you don't look at the output, you're going to be judged for it. That's what I think.

Lenny Murphy: Yeah.

Karen Lynch: So, all right. So, here's all these. Yeah.

Lenny Murphy: Yeah.

Karen Lynch: You know, listen, friends, we have talked a lot about AI. This is, I think, the first one. Like, remember, like, like when we very first started talking about this, I think the big debate was AI friend or foe? Is AI coming for our jobs? Is AI, you know, is AI going to be? Displacing all of us? Is AI going to make the industry obsolete, all of our jobs obsolete? Like that was the big debate across a lot of industries. Here we are, still standing, how many years later? So, we have a couple of different pieces, three that we're going to share with you today that all kind of approach this debate from a different angle. The first one, the first one is from every. It's argued that AI automation is creating more knowledge and work coordination. It's not reducing workload. So even though we've said a lot about how, oh, it's making everything much more efficient and we can argue that it does make us more efficient, but it's actually requiring more work from us. And it's a good piece because you may have noticed that in your own work if you're using it. So, but this piece talks about how it's changing things. So it's not just replacing tasks, but it's adding a new review layer. Yep. More coordination, more judgment. And in my work, because I use AI every day as well, I am using it. I am interacting with my AI very differently. It is a critique partner of mine now. The way I'm using it is pushing back more than ever before. I'm saying, I don't think so. I don't think so, AI. Like, I'm not sure I agree with you. I'm being, I'm using much more of my own critical thinking than I may have even done before.

Lenny Murphy: And it's spurring more, isn't it? I mean, it's spurring you to think. More.

Karen Lynch: It is. I am doing way more thinking than I was before. And that I think is interesting because I remember even having the conversation with you before where I was, you were thinking, oh, it's going to make me lazy. I don't think that that's what's happening in our brains. I think the lazy period has come and gone. Now, some people may still be lazy. I don't think that's what's happening. I think for those of us who are using it with our intellect. We are pushing back. We're battling. I saw one of the members of my team, she's been working on a prompt. When I say working on a prompt, when she showed me what she's been working on yesterday, I was like, damn, her work on this prompt is so genius, but it's been like, she's been working on it for a few days too. Perfect this prompt to get it to get to the results. That I was like, that is such strong, solid thinking going into the right prompt. That level of prompt engineering is what I'm talking about. I was so impressed with that. That is, to me, creating more workplace coordination and not reducing workload at all. It is how we're going to optimize what we can get out of AI. And that's where I think we are today. And I bet others out there have experienced that, not just here at Green Book.

Lenny Murphy: Yeah. It's a reallocation of time and energy spent. So again, I'll just go back to that example. I don't spend time creating, creating a deliverable per se. That's not, I don't need to do that now, but I need to edit. I don't need to create them, which I'm not particularly good at anyway. But that directing, here's what I want and here's how I want it. Here's the context. And, you know, all of that work that goes on the front end. And then all the work on the back end around implications and thinking through. And it is a, it's kind of a synergistic, almost biofeedback type of thing. Yeah. Because it's, I'm doing more. More, but I'm doing more things that are more important, ultimately, that create more value and impact than just the rote stuff, right? That's just not, and I think that it's that. So, that goes into this other piece that Axios. I guess there's a debate between OpenAI and Anthropic on, are we going to kill everybody's jobs or not?

Karen Lynch: Yeah, but this one. So, okay, so here's this piece from Axios, right? This one I thought was really interesting because this is this fear versus optimism debate, right? So, Anthropic is, and this, so, okay, full disclosure, I threw this into AI to analyze this piece because I'm like, I. There's a lot in here, and I don't have time to read this whole piece. So, here's what's interesting: so it talks about two different competing sides: fear versus optimism. Anthropic is a doom narrative, and open AI is the hype-pivot narrative, right? I don't know if that was your take when you read it.

Lenny Murphy: Oh, definitely. Well, although it's interesting, Anthropic just closed another round and is closing in on, you know, a trillion dollar valuation with their doom narrative.

Karen Lynch: Your doom narrative. So that's what it got to next. So then I'm like, okay, tell me why this matters, right? Because now I'm engaging with AI over this because I didn't have time to read the article. So again, engaging with your AI. And then it says, well, this is their brand strategy. Anthropic's brand strategy is that tech is so dangerous. You need to fund us to build it safely. So then I'm like, son of a gun. I never really put that together. But Anthropic, it's interesting, right? Anthropic has built part of their strategy that you need to fund build this safely because it's dangerous. Whereas OpenAI's brand strategy is that we are an enabler, not a destroyer. So of course they're optimistic because the human part of employment is irreplaceable. We enable humans to be more efficient. And I'm like, damn it, it's all marketing.

Lenny Murphy: And like it always is. When you're a trillion-dollar company, it's all marketing.

Karen Lynch: So, anyway, so then I'm like, okay, cautionary tale. Don't take either of these at face value. But like, if you, and I'll probably go back and read this now that I had AI help me analyze it before this show because I didn't have time to read it. But like, check this piece out and I'm going to read it with that lens. It's like, read it. Fear versus optimum, take in the stories, consider the marketing angle, because that's as insights professionals, that's where I wanted to get pretty quickly. Is like, as insights professionals, how can we interpret this and not just go to like fear versus optimism? Because these are competing narratives about AI's impact on jobs. And I think it's really interesting.

Lenny Murphy: Well, and it, but also the undercurrent is exactly what we just talked about, right? And it's, it goes back, it's no different than you know, from the horse and buggy to the car to the, you know, what can be automated is going to be automated. If we can gain efficiency, we're going to gain efficiency. So in some, some jobs, some skills will go away. Others are born. Even from the, you know, from the blacksmith to the mechanic, right? Whatever. So we've been saying for years, we, we, we knew exactly when this started. If you make your living doing a process that can be automated, probably not the best place to be. And, but that was true five years ago. We just didn't imagine exactly what the technology was going to look like, right? The text coding and text analytics. We knew eventually text analytics would replace coders, right? It just wasn't quite there yet. So yeah, no, um, so fundamentally, all that is true, while also this marketing angle, um, overall, and it still comes down to my mind of where do humans create value.

Karen Lynch: Um, yeah, so uh, and then right, I thought, yeah, I didn't get to this piece, I didn't even get, I didn't even get to ask AI about this piece.

Lenny Murphy: Okay, so uh, this is actually the second appearance of Benedict Evans. We had uh, he did a state of AI. It was called AI Eats the World last week. We had on, this was a deeper dive. He's an analyst. Yeah. Job exposure. And he argued that predicting AI job exposure was harder than scoring roles or industries because the workflows and business models had also changed. And that was a, I think that was an important point as well. Why are they putting, why, why is $15 billion being invested for the deployment layer? Because it's a pain in the ass to change how you do things. It's not just anybody could, we all downloaded AI and started playing, right? That's not the point. But infrastructure, systems, that's a whole other ballgame. And imagine a company at the scale of you know, as I always pick on PNG, right? Changing PG is a much bigger deal than changing Greenbook, you know? So, or Gentoo advisors. And even that, we struggle. We don't have a standardized approach within Greenbook. Yeah, we don't have the infrastructure. We haven't adopted these tools in a systemic way. We're just beginning to do that. And as we do, that has for business models, et cetera, et cetera. So, I think this was just a really useful contextual layer that it's easy in isolation to look at one thing, you know, AI moderation, moderation. Does that affect moderators? Sure, absolutely. But for that to become an enterprise-wide replacement for all qualitative research and the systems you use for qualitative research. That's a different ballgame.

Karen Lynch: Yeah, yeah, yeah. It's complex, man. It's complex.

Lenny Murphy: It is. Well, we live in complex times. We do.

Karen Lynch: So, all right, who's this? Matt Valley, I think, right? Hey, Matt. All right. My general sense is that AI is making more work possible. Human resources flow both to gaps that have always existed and to new opportunities that were not previously possible. The pattern is like prior disruptions, for example, automation, the internet. This is why I don't foresee mass unemployment in our industry, or more broadly, that would precipitate systems like universal basic income. Creates new things for humans to do.

Lenny Murphy: I agree 100%.

Karen Lynch: It has created new things for me to do, that's for damn sure.

Lenny Murphy: Absolutely. And even now, it is interesting. We touched on this last week, and I wish that you had been here because it is interesting. I am optimistic about creativity. Capabilities, I think we're going to see an explosion of content creators. We need to recognize that there is a backlash on some of these things. And a couple of studies talking about last week that were documenting this AI backlash on kind of gen, alpha. And so to your point, Matt, some things will, more things will multiply, right? And we'll create new jobs. Some things I think would be cool, like, creator economy, new ways to create. There's also some people who are getting sick and like, I don't want to touch anything, any AI-generated creativity. We just, we don't, we don't have equilibrium yet on any of this. So, but I guess, I guess we're, we're optimists from the optimist side, Karen, aren't we?

Karen Lynch: So, I'm an optimist for sure. I, um, I've always been kind of on the optimist side. And and I I actually think that um, like I know that there's been, you know, there's there's been people that have you know that have been hurt by some of the disruptions, so I don't want to I don't want to discount the people that have been hurt, the people that have lost jobs, the companies that have been struggling, like I don't want to discount that ever, um but I do think that there have been, you know, companies that have had opportunities that have that have risen you know from out of nowhere. There have been, there are companies that are going to be like Phoenixes rising from the ashes. And I mean, yeah, I mean, there are companies that, you know, that are just popping up out of anywhere. So, so yeah. So I think that, you know. I think that this is an interesting time, but I think we will all be here on the other side of it in one way or another. Is this our therapy session? We haven't done one like this in a while. Yeah, I feel like we haven't really needed it, though, which I think is the good news. So maybe that's also just because winter's over and it's summer. Maybe. Yes, that's on that note. Right? Touch grass, go outside. You know, I got, we've had two weeks of rain. I got to mow my grass this afternoon. And I'm looking forward to stepping away from AI and all this world, the digital screens, and just be outside doing stuff. So I hope everybody gets a chance to do that. I hope so too. I hope so too. And we will see you next week when we're into June. Yep. And this weekend feels like it should be Memorial Day weekend because I know, I know, it was weird. It was weird. Last weekend was too early. So have a great two days, you know, the first kind of official weekend of summer. So and a blue moon, right? Once in a blue moon. Two, two, two full moons in the same month. Yes. So enjoy it, everybody. And we'll see you next week. Yeah. Everybody take care. Bye-bye. Bye.

Links from the episode:

Exa Labs raised $250m 

Comscore sold its Movies box office measurement business to Advaya Capital 

Futurum Group bought Aptiviti 

Rep Data acquired OWL Solutions 

EY and Microsoft expanded their alliance with a US$1bn+ five-year initiative 

Cint deepened its Salesforce partnership with an AI suite for Slack 

NIQ launched Survey Groups in NIQ Discover 

Ipsos launched Product Studio 

quantilope launched quinn Search 

Survicate rolled out Research Hub 

James Whaley explored the “long tail” of underserved insights teams 

The Future of Professional Services: How firms will capture value in the AI agent era 

After Automation, AI progress creates more work for humans, not less 

OpenAI and Anthropic dig in against each other on AI jobs apocalypse 

Benedict Evans: Predicting AI job exposure