AI's Double Edge: Innovation, Ethics, and the Changing Face of Research

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! 

Data quality is under fire — and the industry is fighting back. Fresh from IIEX, Karen Lynch shares how market researchers are tackling fraud with interactive games, new tech (like eye-tracking and LinkedIn verification), and a mindset shift that treats data like a crime scene investigation.

Karen Lynch and Lenny Murphy also dig into big moves reshaping the landscape: the Apollo and Canovo merger, the launch of independent intelligence firm Covo, and why startups like Pureprofile are growing against the odds. Plus, an honest conversation about whistleblowers, corporate responsibility, and how the industry must stay human even as AI rises.

Many thanks to our producer, Karley Dartouzos. 

Use code EXCHANGE30 to get a 30% discount on your general admission IIEX tickets!

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Transcript

Lenny Murphy: Happy Friday. We are live. We are live. It's me.

Karen Lynch: I realize I'm probably the one jumping the gun because I, the countdown clock ends and I'm like, we're going. And then you wait until it says you are live.

Lenny Murphy: Yes. Well, I don't see a countdown.

Karen Lynch: I don't know why. Oh, that's right.

Lenny Murphy: So all you see is the, you are alive. I just saw it live.

Karen Lynch: So I'm ready. All right.

Lenny Murphy: Happy Friday. What a week.

Karen Lynch: What a week.

Lenny Murphy: What are we? Lots going on.

Karen Lynch: So what's going on? And we're ready for the weekend. But first, we shall talk.

Lenny Murphy: So let's talk because there was a lot going on this week.

Karen Lynch: Always. Oh, yeah. As always. I mean, really, we live in a very exciting time in this industry because there's always something to talk about, especially now. So but let's start with these two kinds of, you know, one quick thing on that.

Lenny Murphy: So here's a hint for me. So I spent this week doing all of my stuff for grit. Yeah.

Karen Lynch: Boy, oh boy, oh boy.

Lenny Murphy: So guys, when this comes out, yeah, this is if there has ever been a pivotal report that you must read it is this one. So talk about things happening. So I'll just leave it there. There's more coming. But boy, the head to the website, sign up for the grit forum.

Karen Lynch: Yes. You know, if you take in information that way, that's on June 10th. If you take in information that way, join us for the forum. If you're a reader and you take information that way, be watching for it, so. Yep, yep, that's happening.

Lenny Murphy: All right, now let's talk about some more.

Karen Lynch: Yeah, no, it's easy for me to pretend that grid isn't happening because it's just such a beast of a project around here, especially right now. So something had come up this week and it was like in between North America wrapping up and Europe on the, you know, on the horizon and then grit in between. What were we thinking? Anyway, we're glad it's for punishment.

Lenny Murphy: We always are. So I want to talk about this, the Insights Association and the government. Yeah.

Karen Lynch: You know, the thing I like about this story, so, and I'm going to let you talk about it more, of course, but I love to know what the associations, like the associations, you know, put on events. Yeah, yeah, yeah. We do our events and we have preferences for ours over obviously. But the work that they do, this is to me where they really make a huge difference in our world. So I'd love to shout out when the Insights Association or SMAR or any of the other associations are doing the big work, the key regulatory work. And anyway, this is one example of that. So that's why I really want to make sure people are aware of what the Insights Association is doing here. So you want to talk a little bit more about it? It's really just they're pressing the US government to modernize procedures, right? Yeah, yeah.

Lenny Murphy: Well, and I think I have some insight into some of that over the years doing healthcare research, things like that. I mean, so there's like this regulatory framework that they put in place in the 90s, but it also basically captures how research was done in the 90s. And yeah, they're pushing to say, look, it's RDD telephone sampling. Sure, we could still say it's the gold standard, maybe from a scientific standpoint, but it ain't practical and it's not cheap. And I think the press release about it also hinders innovation.

Karen Lynch: You know, we have all this kind of red tape and things take a long time. Well, you're certainly not allowing for the type of agility that innovation requires. And at the same time, we really want to be that way. Absolutely. I want to eliminate this red tape and move forward with things. So hats off to the Insights Association.

Lenny Murphy: It's pretty cool. Absolutely. They're driving much needed change. And Ford set everything else aside, right? So an administration that seems to be leaning into innovation and AI. Like, well, OK. Here's a really good example of how that needs to apply. So some good stuff. Yeah.

Karen Lynch: And this next one, I think this is probably on, you get a lot of the Advertising Bureau information. So the Interactive Advertising Bureau and the Media Rating Council released new attention measurement guidelines. This is interesting. And this one, correct me if I'm wrong, they want public comment on them. They want to standardize things, but really it's just that there's too many different types of measurements. So it's hard to compare apples to apples is how I interpreted this story.

Lenny Murphy: Is that your impression too? Yes, absolutely. And there's like an advertising component of that. Of what it really is attention if you are exposed to an ad for 20 seconds, right? Okay, fine. Although some would say it's five, some would say it's 30. To your point, lots of stuff just related to that of what counts as exposure, but this focus more on, okay, but exposure is one thing, attention is the other, which gets into non-conscious measurement and there's lots of solutions now being deployed to understand understand actual attention, eye tracking, obvious one, you know, those types of things. So, um, yeah, they need to, to, uh, to do that work. You know, uh, ARF is part of this in the background. So hats off to, to, uh, the advertising research, uh, foundation. Uh, these things are important.

Karen Lynch: Yeah. Yeah. So pretty cool. Good work. Good work. Um, so, so before we get into the, you know, list of new product launches, because we predicted that there would be, you know, in these months, like so many new product launches, and it figures out what their AI moves are. You know, now we've got all these AI product launches. But first, I don't know if you know, because we, you know, Forrest is such a solid partner of ours, what do you know about this acquisition of InMoment, expanding their AI powers CX capability?

Lenny Murphy: Only what was in the press release. Actually, I have to admit something. I forgot that Press Ganey owned Forrester. I mean, I knew it, but I didn't think about it. So it was a good reminder of, yes, there's a much larger organization. And Press Ganey has done lots of CX, and they're a very large consulting firm, and they do all types of stuff. They own Forrester, the focus on data collection, and now expanding in moments. Which is more qualitative, has broader applications around CX, but also UX. And there's lots of capabilities around all of that to expand that. So they continue to, I mean, effectively build out a competitor to Qualtrics. That's what I was thinking too. I was like, all right.

Karen Lynch: I feel like, you know, like Qualtrics is the one to beat here. We all know it. We all see it coming and go with it. I don't want to call anybody an underdog because in this case, it's not an underdog.

Lenny Murphy: It's just, you know, like you're going up against a behemoth is what's interesting. I brought in thinking about cause I've been in the grit world all week. Um, you know, this tension between technology and service isn't, isn't resolving, right. There is still, even with everything that's happening with, you know, AI and yada, yada, yada. Uh, obviously tech is, Tech is not just winning, tech is dominating but service is still required. So it is interesting in this particular configuration of press Ganey, you know is a large Yeah, there is a consultancy as well as lots of different capabilities that are specialized Building that tech forward maybe a tech first approach Yeah, but still having that capability which is a little bit different than let's say, of course that they have service, but they don't talk about it much, right? They'd rather lean into the tech. So this is dynamic. It's just an interesting dynamic of business models that, here's an example, it's gonna continue to play out. Yeah, yeah.

Karen Lynch: Yeah, and you know, they talk about, in this press release, you know, they talk about their healthcare, the healthcare, and employee, which of course, you know, those are the things that like, you know, Qualtrics talks about frequently at their event, is like their employee, experience, their healthcare experience. And so, so yeah, good, you know, good luck with the merger and or the acquisition. And, you know, we'll keep watching. Yeah, absolutely. Absolutely.

 Lenny Murphy: All right, we're gonna move into something more fun. Yeah.

Karen Lynch: I mean, certainly when we talk about these medical assets, I really want to go there for a minute and start with that. Because when we say more, when Lenny and I say more fun, we're talking about, okay, news aside, let's talk about tech, which I never would have predicted that that would have been, you know, the exciting part of our jobs. Maybe you could, but anyway. So last week, you know, I was at this Yale Insights On conference and there was a speaker from Meta there. And she was wearing glasses when she was delivering her talk. And she was talking quite a bit about the research that went into the Meta glasses. And so I was already sort of primed to be listening to that because of our conversation. About the Metaglasses and all that. And then at the end, she said, can I take your picture? And everybody in the audience kind of froze for a minute. And then she said, Meta, take a picture. And then it happened. We're like, OK. I don't know how I feel about that. But then I read these super-sensing, literally they're calling them super-sensing capabilities for facial recognition. And I thought to myself, OK, because apparently, and I haven't I just I'm going to get up. I have to get a pair. I literally have to get a pair because I like to take pictures. Just saying it out loud and having it happen was really cool to me. Seeing how easy it was to take a photograph when you're looking at something because it's whatever you're looking at is what's photograph. Anyway, it was cool. But then this other idea of facial recognition where I just kept thinking, so if I'm out somewhere and I'm like, oh, shoot, I know this person, but I don't know them and maybe my glasses are going to tell me who this person is. So I started thinking about my personal use of this feature. And then I started to think about everything else, you know, and I'm like, Oh man. Yeah.

Lenny Murphy: Well, the ethical stuff, I mean, we, you know, Tim, I don't know if you're listening, but you know, as a fellow glasshole, uh, from back in the day, I mean, that was the beginning of thinking about those implications of the two pieces. Like, wow, this is really cool in a V in many ways. There's no doubt about your point. I can think of 101 practical applications. 101, yeah. But there's a whole Big Brother component of it as well, which includes just ethical, personal, all those things that are inescapable. And we have to get a handle on it because it's- Yeah.

Karen Lynch: Well, and also it's not like, I imagine it's, you're out in public, right? So, or you're in a public place. I have no idea if I'm walking down the streets of New York City who might be wearing Metaglasses at this point. I have no idea. It's just happening. They certainly don't have to stop everybody and say there's Metaglasses in the environment. It's the strangest thing to think about it in this context. Anyway, like I said, they were really sharp looking. I think that's only going to improve. They were very deliberate in their partnership with Ray-Ban. She talked quite a bit about that. They had to find a brand that was going to have enormous appeal. So the partnership was very deliberate and all of the research going into it's been deliberate, but I don't know, it's this super sensing capability. So the idea is that, you know, it is going to be sensing whatever the wearer is looking at. And AI will be a part of that. And then you can have this sort of live AI happening. So you are literally interacting with AI as you're looking at things. Anyway, it's very cool. And I think that the, I don't know, the appeal went up tenfold when I saw them, and I saw her using them the way that she was using them. But now I keep thinking about shop-alongs. And, you know, it's not a big expense for any company out there to just be like, here, please go purchase your... I mean, just the act of somebody shopping on the shelf with those glasses on, like...

Lenny Murphy: Absolutely, yeah.

Karen Lynch: The eye-tracking possibility is, from a different point of view, really cool. It's just, it's so seamless without having to wear all the, it's so cool. Right. But, uh, and Tim, glad you're listening.

Lenny Murphy: It did point out, we learned how to behave with the tech, but that we didn't solve that in the glass whole days, right? The, um, I mean, we started to, so that yes, interesting times, right. That we knew that wearable technology, no one's going to give up on that. So, and then you later They are in AR and VR. I'm sure that there was at least an augmented reality component to the glasses. Well, I think by default there is. But yeah, there's other stuff to consider.

Karen Lynch: So- As a consumer, the appeal is extraordinary. Again, without my researcher hat on, which I think is also extraordinary for just that shop-along concept. That alone I think would justify the cost of every researcher having them. To a consumer and say, please go pick out your, you know, your diapers and, and, and watch how they scan the shelf and where their eyes are going. And like, exactly. It's, I mean, come on. So that alone, but then as a consumer, I think about like, you know, we, we talked a lot about, we were talking a lot about North America recently and the venue and how people were navigating the venue. My glasses can have a floor plan. And I can be like, Do I turn left or right? And it will, it will tell me like, the use cases for navigation are extraordinary, right? What am I looking at? Like, if I'm, you know, if I'm at a kiosk for a brand, you know, tell me more about this company. If somebody is not there, say somebody who has a kiosk went to a talk, and they're not at their kiosk, I could say to my glasses, tell me more about this company. And I could tell them, I could, I could scan QR I mean, it just, I start to flip out a little bit at the use cases once I start to think about them as a person. And I think that's where I am with this, is me as a human being, I'm suddenly seeing it based on the demo. And that's one of the things she said is when you put it on, when you give these glasses to people, everybody wants them, but it's just, you have to get them in people's hands because most people are little, anyway.

Lenny Murphy: Bob, we have one here. It's one, just a plain, I agree with everything that you said, but as a parent, do I want people recording pictures of my children, my daughters? I don't think I do. And so here's just this balance that we just have to measure and figure out. It doesn't mean that the tech is bad by such imagination. No, there are huge positive implications. Yeah, we also, let's recognize that there are privacy issues that are significant and we have to just factor in. And an obvious one is- How do you consent to being a part of this world that somebody else is in?

Karen Lynch: How do you contend that? You can't. Yeah, right.

Lenny Murphy: There were cases that went during the Glass Hall days where they banned them in restaurants. There were places where they said, No, you cannot.

Karen Lynch: And it was obvious what it was because they're so, you know, distinctive looking, but these are not, I mean, these, these are anyway, I'm telling you one of these days I'm going to have them on and you're going to be like, Oh, she did it. It is not going to take me much. It's going to happen.

Lenny Murphy: I hear you. I mean, I, I was one early with the OT to get a, to get class. So the, uh, for me, the other, the last component of that is the, The biggest barrier for me was I hate contacts. As long as they can offer a prescription glasses version that allows me to maintain my regular glasses.

Karen Lynch: They can.

Lenny Murphy: Apparently, they can. Google had just gotten there where you can do that before they decided it's too early. Fair enough, Tim.

Karen Lynch: I just shared on YouTube for everyone listening on LinkedIn, Tim just shared on YouTube, I know who's running the sunglasses this afternoon. So, um, yeah, it's not going to be this afternoon, that's for sure. But maybe tomorrow. So anyway, other cool shopping.

Lenny Murphy: Yeah, I mean, there is other cool stuff, right? Perplexity and PayPal teaming up perplexity is one to watch. They, they, they have some ambitions. Yeah, yeah.

Karen Lynch: So perplexity and PayPal teaming up for agentic commerce capabilities. That's the article that Karley will share. And there's another article I kind of looked up this morning because there was another talk at the Yale Insights On conference that I went to, and it was Theresa Yu. She was the VP of Brand and Content at IBM. And she was saying that Visa is, you know, kind of has recently unveiled their plans for AI agents to do the shopping for you. Right. So you can, you know, you can call on your agent to actually go and, and buy the thing. So I think that we are quickly getting to, and somebody else was talking about, you know, kind of Google search and all that.

Lenny Murphy: Like we are quickly getting to agents shopping for us. Yeah. Which we've talked about was for research. Yeah. Let me talk to the primary shopper in the home.

Karen Lynch: Right. That's my agent. Right. Exactly. Exactly. So, um, Yeah, that's really interesting. And then how will you have that? Will you have that kind of same response to the products that you purchase if you're actually not the one making that decision or or where in a world where people are, you know, hand feeding you a few different options and you choose from a set of options rather than you doing the work to find the exact thing? I think that's really it is that the consideration set will be narrowed down at the very least by somebody else. By or by something else. That's, you know, a brave new world, a brave new world. So yeah, so I don't know if I have that article, Karley, the other one, the, the one that talks about the visa agent, I think I just slapped it in there without context. So anyway, so that's that. Yeah, the e-commerce applications, think about it for grocery, you know, Instacart, if we don't even, I had talked to my friend about kind of Instacart and online shopping and all of that. But imagine if it's making the decisions for you, if you're like, you know what, I really just want to make tacos tonight. And it says, gotcha.

Lenny Murphy: And you don't even have to say, break it down for me. It's just. I was in a conversation this week with a company that provides receipt scanning identity resolution technology to many of these companies and the things they were talking about, how Instacart and DoorDash and those companies are thinking about leveraging their data in new ways. I can't go any deeper than that, but the, uh, uh, yeah, very, very interesting. Um, and I guess for the next story, the, uh, Google DeepMinds Alpha Evolve, um, which fundamentally, So this was a multiplication algorithm that decreased computing costs. But the other big piece of Alpha Evolve is it builds technology. It self-codes. So the barrier to entry on developing these agentic solutions and anything that is AI-based, it just keeps coming down across the board. Google's decreasing computing costs and time while also creating technology that you just describe, here's what I want it to do, and it programs it. I actually saw, I was using Perplexity earlier this week, and for some, I keep telling them, I just noticed it. I was doing some analysis on grid data, and I noticed it pulling in Python code, and saying, oh, I need to do this. And it was pulling in Python code to do the analysis in real time, without me prompting. I just said, here's what I want. And it was figuring out what it needed. And it's just, that's the world that we are in now.

Karen Lynch: I know, I know, I know. It's cool, it's cool. You know, all of these advancements I think are great. And this one, I think, you know, you talk about the costs, cutting computing costs. I think many of us have heard that the cost of AI is significant, you know, when it comes to, you know, kind of how much energy it uses and is burning through and how detrimental that is on a big scale, even though we aren't gonna stop ourselves from using it anytime soon, because we're like, but wait, all of these applications. So anything that we can do to kind of cut computer costs and the cost of usage, I think is going to serve us well in the long run and feed the machine of wanting us to improve the AI so that we are realizing some of the benefits from using the AI at the same time, instead of, you know, the unnerving, think about how much it is not just literally financially, but also costing us in terms of the global footprint. So interesting times.

Lenny Murphy: Interesting times. It was interesting watching news this week of the news in the Middle East and the major investments of Middle Eastern oil producers in AI. And the flip side of that was they wanted to power it. So it was just, to your point, there's just lots of big things happening, right? It has nothing to do with judging whether that's good or bad. The world is being reconfigured for an AI-based economy, including the issues around energy production and computing costs. And there are trillions of dollars, literally.

Karen Lynch: It's really easy for us to stay focused on, and we will. We have a lot of product launches to cover in the last few minutes and we'll get to them. And we couldn't even get to all of them, but we'll cover the ones that we can. And it's interesting to talk about just how we're using them and forget about the big meta conversation that's happening in our world. You know, I don't know.

Lenny Murphy: So yeah, interesting. So, yeah. Transformative.

Karen Lynch: So let's talk about the specific. Let's go back to the application layer. You know, it's not a surprise. Like I said at the beginning of the show, that we're seeing all of these AI product launches, right? And I think that, oh gosh, one of the, I think I put in my LinkedIn quote, like one of the quotes for this event really is, it's not about you having an AI feature, it's about how you're using this AI feature for the good of your customers. So like, let's not just be excited that we have them, let's be excited about what it's actually doing, because we're way past the, have one too. But anyway, Redpoint Global, I don't know them. But they do so Redpoint Global unveiling a data readiness hub. So solving speaking of CX, right, solving, you know, pertinent issues and customer data quality for enterprise AI and CX use. So here's another player in the CX space. And they're doing what they need to do, you know, with their AI platform to clean up some data quality issues. So certainly hats off to everybody who's cleaning up data quality right now.

Lenny Murphy: Absolutely foundational, right? Garbage in, garbage out. Garbage in, garbage out.

Karen Lynch: So pretty cool. Pretty cool. What about Data Axle? Do you know them too? Like a lot of players are showing up.

Lenny Murphy: So no, and we just own that guys. There are so many new companies emerging that we're all kind of going, Oh, who's that? And trying to get up to speed. Here's another example, Data Axle, their profile uses that this connects business consumer identities. This goes into what we were talking about earlier with meta, connecting data. You've got your glass on, oh, that's Lenny. It's going to be companies like Data Axle and others that are synthesizing that to feed into these applications for identity resolution. It's the next generation of the third-party data providers that we all hate in many ways because they're synthesizing all of your information. Now going into that to drive applications like this. Yeah. Pretty cool.

Karen Lynch: Content Square launches something called Sense, which is an AI agent that acts like a digital analyst. Let's just call it what it is. It seems very straightforward to be able to say, yes, let's have AI analyze, but this is more than that, right? So this is their language, kind of accelerating insights, but optimizing user experience decisions. So now we're bringing in agents or this platform is giving us an example of bringing in agents to not only look at the data, but then literally get right to the decision-making that has to happen.

Lenny Murphy: So whether you know them or not, take a look at it see what sense is all about because it's it's planning and acting yes keyword a couple weeks ago I think it was waxy that I saw if it's that's right they build websites every point was they're incorporating that type of technology you actually customized the website on the fly yeah based on the individual user which is just kind of a mind-boggling concept to think about. I mean, obviously, there's gotta be some framework, but that's where we get into these, the practical applications of personalization, of not just recommendations, but even overall experience. So, yeah. Interesting, interesting stuff. Yeah, yeah. Upscale, Upscale AI. Debuts for the 5.5 million funding round seed fund Yeah, or upscale studio the first Nate AI native platform for creating optimizing performance TV ads on streaming platforms So think about everything done with that testing, right?

Karen Lynch: This is coming out of the gate. Do that 5.5 million dollars like I mean, that's what struck me about okay, you know, like, there are there are, you know, entrepreneurial minds out there who are like, I see an opportunity. I've now got the tool.

Lenny Murphy: Let's go and you build it for the weekend.

Karen Lynch: Yeah, sorry to anybody who's working at like, let's build AI into what we're already doing. Because it's like, these guys are just gonna run into your competitive set at this moment, that they are.

Lenny Murphy: And that's why it doesn't call that out. But I would bet 5.5 million of their money that that's based on some level of synthetic sample, right? There's some normative, you know, benchmarking data, some personas that are built into that real time recommendation optimization of digital ads. I mean, it's like, it's not even a B, it's like advanced a B test, because if you're creating it, also, you're creating and testing all at the same time, creating testing, measuring all at the same time.

Karen Lynch: Yep.

Lenny Murphy: Yep. All baked in. Uh, yep. Uh, we, two more, two more, two more. Okay.

Karen Lynch: The Panaverse.

Lenny Murphy: Welcome to the data repositories, right? So it's all about powering enterprise decision-making by structuring fragmented research data.

Karen Lynch: So I don't know if this one is like, I, you know, I was kind of taking this one and I'm like, this doesn't seem that new and novel, but then when you kind of dig into it, it's like, guess what's powering this new change, right? So there's the AI component, which is what makes this different.

Lenny Murphy: It is. I actually have a, uh, I'm going to soapbox just for a second. So I have a theory, uh, well, two seconds, um, that it's really become apparent to me that the, the differentiate saw, Sorry, guys, if you're in the SaaS business, I think software is dead. That was always a moat, right? What drives things going forward is client retention. And what drives client retention, there's two components to that. But one of it is going to be your data is already there. So then there's like an inertia component, right? Well, my data's already there. I don't want to mess with it. And there's lots of companies in our space chasing that idea of optimizing the user experience with data so they do not churn. Because the software itself is meaningless now. Anybody can clone the capabilities. It's about leveraging the data. A new company like Panoply coming out, leaning into that of like, we're sure we have these data collection capabilities, but that's not the point. The point is, we have the Panaverse, where you customize and leverage your data, in real time to fuel the research process. And that's where we are. Yeah. Yeah. I know.

Karen Lynch: I do feel like the players that had their knowledge management systems or their research hubs, they didn't really get a fair chance because I feel like the benefit of all of that, it was like so many people were kind of slow to get to the benefit of those knowledge hubs. And now all of a sudden, it's like, Kazam, and everyone's like, Oh, got to get into those knowledge hubs. Sorry, guys, like, we saw you first, we get it.

Lenny Murphy: But some of them are actually doing pretty, they're pivoting well with that idea of being purpose built, right? So that is still my experience, using the off the shelf AI solutions. Sure, they can do some of those things. But they miss a lot of context that is specific to our category and the types of business issues that we want. So it's very general, and that's great. But they don't unlock, the off-the-shelf solutions don't unlock the type of value that, let's say, a knowledge management system could do. They may get there. So there's still niche expertise in that kind of app layer. It's still important, and I think those companies still have real opportunities to engage from that standpoint.

Karen Lynch: Pressure's on for them to lean into the design thinking and that agility to make some changes and some tweaks to get there. Absolutely. Because you know it's going to happen. It's sort of like, oh my gosh, what's the name of that platform that you had shared with all of us that was doing marketing options and content options?

Lenny Murphy: Sparky. Sparky, right. Sparky.ai. Shout out to Sparky.

Karen Lynch: Right, shout out to Sparky. It's sort of like what Spark is doing is like, no, give me a use case. Like I'm just the right person to kind of take your feedback and build it. So I do think that some of that's gonna happen with these new players is they're gonna say, give me your use case because I have not just the technical ability, but the thinking and that agile mindset to make it happen for your use case. And then guess what?

Lenny Murphy: Then they're gonna, then they're going to be more appropriate for what- 100%. I will give an urn media shout out real quick to Rick Kelly at FuelCycle. They publicly announced their new agentic solution a few weeks ago, and we talked about that. But Rick gave me a demo. I asked him for a demo. It reminded me of Sparky, of that idea, to your point. So here's the first time I've seen that in the research context of, here's my business issue. That's what you start with. Here's my business issue, and the agent almost everything else. Yeah. And that is why many other companies are doing that. So guys, don't get offended. Well, we're doing that too, Lenny. I hadn't seen your demo. I saw the fuel cycle demo. And that whole process because it's customized, right, the prompts and the underneath that are customized for the research process. And that's where we are. Yeah. All right. We want to end with our friends at Morning Consult.

Karen Lynch: Because this is cool, right? So Morning Consult launched Morning Confluent AI, it's now in open beta offering, you know, global, this is the marketing talk, right?

Lenny Murphy: Global customer insights through a real-time AI chat tool built on 30,000 daily interviews across 40 plus countries.

Karen Lynch: So anyway, so there you go. So they're putting it out there. They're synthetic in that. What else is going on in that one?

Lenny Murphy: I don't know the details.

Karen Lynch: I will say it is interesting.

Lenny Murphy: Morning Consult is one of those companies who has never actively engaged in the research space, but they had a very large presence at IIEX.

Karen Lynch: And they sponsored the Yale Insights On conference. Last year, it was just Suzy. This year, it was Suzy, BCG, and Morning Consult. So I was like, oh, I see you. I see you, Morning Consult. And what, now what, and they own theirs, so I believe they do some custom work, but the bulk of their business is, you know, their own proprietary tracking studies. And that's what they're leveraging.

Lenny Murphy: So the data is their asset.

Karen Lynch: And hint, hint, hint panel companies. That's so they're leveraging that in a new way, as they should. So it's a very large, extensive database that if that's feeding them to explore building synthetic, exploring hypothesis testing, all types of stuff, that's fantastic.

Lenny Murphy: Not everybody has syndicated products, of course, but Nielsen, Cercana, I mean, there's lots of folks out there that do, and they're moving in similar directions on leveraging that data asset in whole new ways.

Karen Lynch: And is that gonna minimize?

Lenny Murphy: So I don't know if that minimizes custom research. I think it changes the process of custom research.

Karen Lynch: I think you go here first and you explore and then you go forth and you test. Unless you're, you know, upscale and you just test automatically and build in.

Lenny Murphy: But it's just, it's a different way to rethink the workflow, to rethink the value of data, to rethink, you know, the insights function from a process standpoint, right? That's really where I think these implications are cost, speed, impact, but also just function.

Karen Lynch: Well, that's where we're wrapping. It's 36 minutes. That's all we're going to do. I mean, keep them coming. Keep them coming. We'll keep doing our best to tell the world about them. That's all I can say.

Lenny Murphy: And if you're on YouTube, hit that like and subscribe button and share this.

Karen Lynch: Look for the newsletter that Karley does such a masterful job of summarizing all of these early next week.

Lenny Murphy: Fantastic.

Karen Lynch: And we'll see you in a week. Everybody have a great weekend. You too, by the way, Lenny. You have a good weekend.

Lenny Murphy: Thank you, Karen, you too.

Karen Lynch: Bye.

Links from the episode:

Insights Association Urges Reform of Federal Government Research Policy 

IAB and MRC Release Attention Measurement Guidelines for Public Comment 

Press Ganey Forsta acquires InMoment 

Meta’s new AI glasses could have a ‘super-sensing’ mode with facial recognition 

Perplexity, PayPal team up on agentic commerce  

Visa is testing AI agents that automatically shop for you  

Meet AlphaEvolve, the Google AI that writes its own code—and just saved millions in computing costs 

Redpoint Unveils Data Readiness Hub to Elevate Enterprise Data Quality 

Data Axle Unveils ProfileFuse™ 

Contentsquare Announces Sense: an AI Agent That Plans and Acts Like an Analyst 

Upscale AI Launches With $5.5M in Funding and Unveils ‘Upscale Studio’ 

Panoplai introduces the Panoverse

Morning Consult launches MorningConsult.AI in open beta