AI Without Integrity? The High Cost of Bad Data

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AI is only as good as the data behind it. In this episode, Karen Lynch and Lenny Murphy dig into why bad data can derail entire strategies, how new AI-powered tools are reshaping research, and what the rise of wearables could mean for privacy, connection, and the future of communication.

Along the way, they explore a bigger question: how can the insights industry stay human in a world increasingly driven by machines?

Many thanks to our producer, Karley Dartouzos. 

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Transcript

Lenny Murphy: For the eyes were laughing. We had a technical glitch and it was like we literally solved it right as we went live. So, uh, so there we go. Happy Friday. Happy Friday. I mean, I feel like today that's like an understatement for me.

Karen Lynch: I desperately need the weekend. And, um, and here we are, the weekend has shown up. Yes. I am thrilled as well.

Lenny Murphy: My, uh, on a personal note, and you know what this is like, my oldest daughter is, um, coming to visit on Sunday from California. So yay for a couple of days. Those of us that have adult children who live away, there's that certain excitement when. I know, I know.

Karen Lynch: Well, I will also have, you know, not quite a full house because my youngest is away at school still, but my older ones are visiting this weekend also. So I think that's, you know, it is, it's very exciting for those of you who are in your 20s, and like, you know, you're saying, can't relate to what you and Lenny are saying right now. Like, just keep in mind, like, it means so much, so.

Lenny Murphy: It is. When you visit your parents, they really like it. They really like it. Maybe you guys can relate to this, that there is no better feeling for me as a father than when all of my family is under my roof. Yeah. And just that sense of, I know where everybody is. They're all safe.

Karen Lynch: Everybody's good Camp when our kids were younger we used to camp and I loved getting in a tent at the end of the night and like having everything zipped up and being like here's all my people I can literally touch all of them like three kids. Like here's one head two had three heads. Here's me and my husband. That's why I can't because of those in a four by six space.

Lenny Murphy: There is, there's something, and you don't even recognize this like low level anxiety. I mean, anxiety's probably not the right word, but there's just always this sense of, are they okay? Where are they? You know, as a parent, and don't recognize it until everybody is all together and you're, oh, that's what it is. I know everybody is okay. That's what loneliness feels like, I know this is totally not right, Well, hey, it's been a weird week. I mean, let's take it. What you know, I mean 9-11, etc, etc been a weird week. So let's just appreciate those things that bring us joy. Let's appreciate those things that bring us joy.

Karen Lynch: Yes. Yes. Yes as opposed to things that don't bring us joy like data quality issues Good segue boy, that was good.

Lenny Murphy: You like guys.

Karen Lynch: Are we gonna get us on track now? Figure out something There's a few things that came up with data quality. And I feel like let's talk about it in the context, these few pieces, because it has to do with our industry. It has to do with the kind of AI disruption that our industry is looking at. So kicking it off with these two solid thought pieces to Read. CleverX released a 2025 market research industry report.

Lenny Murphy: It's really good.

Karen Lynch: I literally got lost in it this morning and it was easy to read. It explains six market forces of which AI disruption is one of them, but the fraud crisis, data quality or data integrity issues, but it also goes into geopolitics and GDPR compliance issues. There was something in there that I thought was interesting, Lenny. I'm sorry. A lot of talking, so I dug in and I dug in. They talked about a zero tolerance environment and your reputational risk. And I thought that was a really interesting section of this report about how, and I think we've talked about it before, but how quickly trust can be broken in today's environment and how the kind of implications of broken trust when it comes to data, the implications are great. So this report, worth a read if you're... Absolutely.

Lenny Murphy: Yeah, please check out the link, guys. They had sent it to me and I wasn't minimally familiar with CleverX, not aware of them. And actually, since then, I've opened up a dialogue with the CEO. I thought it was really well done. Yeah, yeah.

Karen Lynch: And there's a quote in here that pulled up the research for... It says, it says, the writers of the report, the research firms pulling ahead in 2025 share one trait. They stopped waiting for market conditions to improve and started improving their own operations instead and I'm like mic drop. That is a fantastic statement.

Lenny Murphy: Yeah, it really really is. It's I've incorporated You know, you know, I pull lots of data sources to try and you know get a view of the industry This is now in it is in my to as one of the sources that I'm drawing on to help, you know, look at what is the, you know, what's the trajectory of the industry. So very well done. And to your point, definitely highlights the data quality issues. And then we had the, our data quality co-op open letter, the, you know, they are, so data quality co-op is trying to be a clear, you know, a clear, you know, a clear, you know, clearinghouse for data, effectively for data quality and creating, you know, scoring metric for on-site purpose dashboard to understand your sources of data and the quality overall.

Karen Lynch: It is a commercial play.

Lenny Murphy: So be aware of that. But, you know, it's a very unique approach to looking at this and having that clear clearinghouse. Yeah, good stuff. Whether it's the perfect solution for everybody, that's up in the air, but they're really pushing for a solution that helps to address the issue. Hats off to anybody who is doing that.

Karen Lynch: Yeah. Well, it says right at the top of this, it's time to stop admiring the data quality problem and start building solutions. I'm like, it's kind of true, right?

Lenny Murphy: Look at it. Talk about the problem.

Karen Lynch: Let's understand the problem. And in the world of problem-solving, if you get stuck at understanding the problem, you will never get to ideas for fixing it, developing those ideas, and implementing a solution. We've got to get out of clarifying the problem. Stop admiring the problem. I thought that was a really powerful statement. And another quote, enough has been said about the problem with data quality. Enough. We have clarified.

Lenny Murphy: We understand. Do something about it. We need solutions. And good, to your point, together with the Forbes report, because what we've been saying, this isn't a bad project anymore. Data quality is a huge issue. Risk contamination, massive, Forbes underlined that. Data trust remains the biggest barrier to enterprise AI success, limited adoption in ROI. How many of us experienced that? Even utilizing our own AI tools, you get some wonky answers, some hallucination, some misattributed sources. And automatically, it's like, oh, well. Now imagine that you're using enterprise-level data, competitive intelligence, supply chain, insights. And it's wrong. It's bad. And you've just invested a billion dollars in this AI solution across the board. It's important. Some of that is AI. Most of that, I think, is the source.

Karen Lynch: Yeah. And I think that, to your point, when you pull it all together in some sort of a knowledge hub for access throughout the organization, if you've compiled all your data sources into a singular knowledge hub that people can query and ask questions of, et cetera, et cetera, you might be driving a lot of decisions based on bad data. And AI is not necessarily, it's learning what you teach it. So we better be teaching it the right things because it's not so advanced at this point that it's going to say, you're wrong. I have never had my interactions with generative AI say, actually, Kay, you're wrong. It doesn't do that. It says, oh, you're right. Oh, I missed I see you, you know, good connection. I like it. Absolutely. I'm the one calling out the problems in our conversations. It's not saying I messed up unless I say you've messed up.

Lenny Murphy: So I've had a different experience. I have had, I've had called say you're wrong. And I've had to push back and say, no, you're wrong. I'll give the link, like, no, I'm sorry. Which was an update issue. That was, that was the problem, right? It wasn't current, we were talking about a topical thing anyway. But to your point, it, It's, it's still maybe not garbage in garbage out. Uh, that's the same kind of idea of, of, you know, the currency of data, et cetera, et cetera. You know, and it has to be high quality, you know?

Karen Lynch: Yeah.

Lenny Murphy: Yeah. Um, there's a, uh, I saw a quote the other day on Twitter. I thought it was interesting that there's a guy building another, another large language model utilizing old, uh, he has like the largest collection of, of old TV ads in And, you know, it's all old stuff. It's all analog, old stuff. And he calls it high protein, um, content. And I'm like, you know, that's pretty interesting. The, uh, of creating non-digital content to digital content as a training set. Uh, it was just, but I liked what he was doing. The idea of high protein, high protein data to, uh, to train. It was like, yeah, that's a pretty good way to think about this. We don't need sugary BS, right?

Karen Lynch: We need good high protein stuff. Yeah, no, that's a good analogy.

Lenny Murphy: Good analogy. Throw away the carbs. Yeah, well, as I can attest, that's a tough battle on an ongoing basis. A lot of product launches this week. Lots of them this week. More than usual. It was like, damn. Again.

Karen Lynch: And there's a, you know, common denominator, right? Like, though, so we've got AI in the mix, as we've, you know, been expecting and knowing these things were coming. These were a little more specific, which was interesting, you know, this is, this is, this is more than just, you know, hey, a new synthesis tool, or some of the obvious use cases. So I don't this research live covered this piece about Enlighten, an API-first survey targeting a firm based in Montreal. And I'm like, ooh, Lenny's going to talk about this one because, you know, anyway, I just know you are much more tuned into API-first survey tool and what that means and why this launch is interesting. Well, I appreciate the credit.

Lenny Murphy: I may disappoint you on this one because they were bringing me as well. So I'll only go by what I read, although I'd like to learn more. It appears, and enlightens, reaches out to us. We'd like to talk to you. I think this is pretty cool. It appears to be another data quality layer focused on synthesizing different programmatic feeds for sampling to enhance targeting. Therefore, what's the experience there? We don't need to ask all of the profile questions or the screeners because the data exists and they're helping to do that to make a better respondent experience, which should be a more high quality output.

Karen Lynch: Stop asking some of those basic questions that take up their time that we really, it's too expensive.

Lenny Murphy: Yeah. Yeah. So really, a neat, neat approach to do that.

Karen Lynch: Very cool.

Lenny Murphy: This research-wide, this one launched Pulse for Excel, AI-powered add-in to analyze datasets within Excel. One of my favorite companies for a long time was Office Reports, this plug-in into Excel. What I thought was interesting about that, again, it's functionally a utility, but the bulk of research deliverables are still done in Microsoft Office. We've been talking about forever, and that particularly, We're going to talk about Microsoft a little bit more in a minute. You can't duck making sure that whatever solutions you are providing are compatible with Microsoft. You cannot avoid that. They just leaned right into that. I thought that was great. If it makes it easier to get to the final output in things that you're comfortable in, Lukasz loves pivot tables in Excel. I understand that. Really good at them also like well, and that's the thing. I don't know how to make them so, I mean it's a pain, you know, I just I literally I just haven't learned some of those capabilities So anything that makes it easy to do those things Right.

Karen Lynch: I know it's so funny that you say that though because now I'm down this rabbit hole in my brain about like the caution the pivot tables So I'm whispering as if he can hear us talking about it. He's so good at it. It's like he's an Excel spreadsheet and gets excited. Like it's so interesting to me because that is so far down on my list of things I enjoy.

Lenny Murphy: I am still manually copying and pasting things to create a table. You know, the, uh, so those don't point is hats off research wise. Folks don't, don't blow off that. I don't want that. Those are, if it saves time, then it's hugely impactful. And this is one of those things that would save an awful lot of time in the And speaking of, so SurveyMonkey has a new suite, AI analysis suite and design tools.

Karen Lynch: So simplifying kind of insight generation and survey creation. So they have a whole new suite of products going out. Of course, a company like SurveyMonkey is going to lean into a kind of AI to do the work. It's so logical. It's like, yes, of course, you know, they have to, and they have the means to do it. So curious to see that for all you DIY researchers, you know, check out what they've got going there. You know, they're up to the ante as well.

Lenny Murphy: Yep, yep. But I want to talk about the Pure Profile because they, you know, full disclosure, they're a client. I know them well. And their own proprietary translation and coding tools are free. That's the operative thing here that's interesting, is that increasingly what I am seeing is that tools are We've talked about this. So here's an example of a company that's leaning in saying, yeah, we're not going to charge you extra for this stuff. It's table stakes. They're more focused on creating stickiness and usability in the platform. And that creates scale and growth versus nickel and diming over solutions. And there's computer power. There are costs. There's tokens. All that's true and real. It has to be factored in. In. But I think we're going to see a lot more of this. Like, I don't know the details of this, or I'm like, he's charging more for their AI analysis suite. Maybe there are, maybe they aren't. I think the trend will be that any of these new tools that are being thrown out there will not be net revenue drivers at all. So they will simply be given away.

Karen Lynch: Well, and given away to clients who are paying for a project.

Lenny Murphy: Yes, right, right, right. Right, right.

Karen Lynch: You know, you're paying, they're paying for a project. This is an incremental add on for, um, you know, to kind of up the value of that product down the road. It's like, you know what? You can also do this. You can also do this. And on some level, maybe the assumption and without knowing what pure profiles intentions are, but, um, you know, heck if, if they cut out the middleman and some client requests, I mean, I certainly, you know, a lot of times clients would come back after the report and say, Hey, was there, was there anything like this? In the data, can you just go back in and check this?" And that, you know, that takes the researcher's efforts significantly longer to get back into data again after they have finished the summer. So if that process can be, you know, can be streamlined so that the client's like, I don't need to bother my research director on this, I can go right into the data myself. I think there's a big cost savings and probably time savings on behalf of the providers.

Lenny Murphy: And it builds stickiness of brand loyalty and all of those things. I guess just to sum up, because this has come up a lot this week. Increasingly, just have to say, if you are a technology player, your moat is not your technology. It's just not. The car has a steering wheel. It is table stakes to expect that my car has a steering wheel. Your growth strategy has to be based on something else other than process. And here's an example of a company that is recognizing that these process efficiencies are valuable because they increase brand loyalty and stickiness and usage, not because it's indispensable as a solution, but because there're 1,001 other solutions emerging that can get to the same place.

Karen Lynch: It's funny, because a few years ago, when I was at InsightsNow, they were really pushing for, you know, clients to ask, I'm sorry, to be able to, you know, access the dashboard, right, for the data dashboard. Now, this is 2017, 18, 19 was when I was working there. And it feels like just a little bit more ahead of its time, right? Like one of those, and this, we've talked about this a lot, too, like a lot of people who are forwards, thinking as that team is, forward thinking, like see these things that they're like, it's really necessary, it's really necessary, but adoption is slow. You know, clients weren't really doing that. They were still asking someone else to do it for me. And now that the tech has sort of caught up and then clients' mindsets are catching up a little bit, I'm like, now's a good time to launch that tool that you developed, you know, eight years ago.

Lenny Murphy: And there's the next, you know, the good example of the next thing, the Forrester, you know, a self-service AI Now I think that's, it's interesting. So it's to help clients validate ideas, align the best practices, and improve decision-making. So those are use cases, but effectively they're taking all of their massive data of information, making that now accessible through a series of, you know, AI tools and prompts. And one of the use cases they call out in the article is simply, oh, I have a question about that data just to go in and get the answer to, to those past data sets, right? Let alone use that to do, oh, I want to test an idea against this. So, so yes, creating those solutions so that clients can just go in. I've been struggling with insomnia lately, right? And it's a whole other thing. Anyway, I was up at three o'clock in the morning last night and, working on a proposal on my phone on Perplexity based off of a data library I've built in perplexity. So that's the world that we live in, right? That I could just access that while I'm laying there in bed, trying not to disturb my wife, you know, type in a way to draw on.

Karen Lynch: Because that is not what I'm doing. 3 a.m. I am sleeping soundly now.

Lenny Murphy: I have really struggled. It's been going on. It's too long. My sleep has sucked lately, but anyway, that's a whole other thing.

Karen Lynch: We can talk about that too.

Lenny Murphy: Apparently, we just need to have a personal conversation these days.

Karen Lynch: I guess so. Bless Yvonne because there's big tech developments. There are big tech developments. Interesting week. Really, start with this Microsoft. There's an article that we're sharing about Microsoft buying AI from Anthropic, which on some level, has been integrated into something. So this is when you get to like them, this is sort of misleading. This isn't necessarily brand new, but now they're going to integrate Claude into some Office 365 app. Again, there's been other integrations and other, and Claude's been a part of it. And they've, you know, they have, they have grok integrated with some things and they, you know, they, they have a lot of integrations. We'll just leave it at that. But I think the diversification and the, to your point, you know, That's one thing, but to your point earlier about Excel and our reliance on the tools, let's recognize, this is the world where Tim lives too, let's just recognize how the Microsoft tools are used by what percentage of the business world? And that's why we talk about this stuff. I mean, a huge percentage, if not a solid majority around the world, is leaning on Microsoft tools. And all of this is being integrated. And they are also experimenting with which integrations will serve our customer base well, and what's being, you know, moved into our different products. So, so much is happening there. Yeah, I did see it.

Lenny Murphy: We don't we can talk about next week that today that there there was news that they negotiate a deal with with chat GPT, too. So you're right, this was a little misleading. Think they are moving off chat GPT? No, it looks like they're just integrating everybody.

Karen Lynch: They're integrating everybody deliberately for different products. And yeah, so interesting. So we'll keep paying attention to what they're doing, but it would be, it's foolish to think that it's going to be simple because it's not. And just like we're experimenting with different tools at the kind of individual user level or small business level, at the enterprise level, of course, they've got to find the right tool for the job, right? Not everything, not everything needs the same thing. I want to talk about AI.

Lenny Murphy: That is because it is interesting but to your Microsoft point, it's also an individual comfort level, right? So I've kind of stopped experimenting with the other platforms because I have become comfortable Yeah with perplexity. Yeah, and with croc so I don't feel the need to experiment with the other platforms now because I know how this works and let's not underestimate that right that the apathy I'm just used to doing it this way.

Karen Lynch: So again, at the individual level, like, you know, so I, I use a lot of, uh, chat GPT because I have my custom GPTs in there, but I also use perplexity for more, some of that, like, I really need some research here. Like, you know, chat GPT, I like what it does with the GPTs that I've built that serve my purposes in my work day. But when I need to step outside and do some more research, I'm perplexed. So I think that that's the other thing for an individual professional. You have to figure out what the benefit of this platform is? What is the need that I have because there are some things like everyday use like Yeah, yeah, this can help but bigger projects. I have to switch to something else. I'm sure it's the same for you. Like , what do you need?

Lenny Murphy: Yes, absolutely. Yes. I would like to go do stuff. I hope that Copilot is replaced by something better because I would like to just do it in the office, right? But anyway, hold the conversation.

Karen Lynch: Also, let's point out, small business, you know, my whole operation, we're a Google enterprise and I work on a Mac. So I don't work in an office. I mean, I have Excel, I have access to it, I have PowerPoint, I have access to it, but the majority of my work is not done on those platforms, right? The majority of my work is done in- On Windows and Office.

Lenny Murphy: Yeah. I mean, I use Google because we do it for business, right? Yeah. I don't like it. What I usually do is do an Excel and upload in sheets or something. But OpenAI made some big moves this week.

Karen Lynch: OpenAI made some big moves. I don't know if you checked out this jobs platform. I didn't go there yet, but they introduced a jobs platform and OpenAI certifications. That's pretty cool for them. They're teaching people. Get some coursework in if you need to upskill or up your skills, upskill yourself.

Lenny Murphy: Yep, yep. It's a job matching service that effectively matches AI trained workers with employers that validates proficiency. You know, that's we've seen similar things, you know, certified Salesforce, you know, they do things like that. So, so really interesting. But I thought it was even more interesting, right was them buying the A B testing platform starting for one $1.1 billion in an all stock deal.

Karen Lynch: I read this and I was like, okay, okay. So they say, they say it's to accelerate their product development. Of course, right now it's all internal. This is just what we're doing for our internal purposes.

Lenny Murphy: Bullshit.

Karen Lynch: So sure. That's your red.

Lenny Murphy: Anyway, you know, pay $1.1 billion for something that really is the cost savings of accelerating their product development process?

Karen Lynch: I mean, there will be a cost savings to their own product development process. Sure. But it's a much bigger play than that. Right. So let's keep paying attention to that stat sig. It's called SDA TFAG at SIG. And it's saying like, you know, right now that is still in existence. It's like, okay, interesting. So let's watch that. And if you're in that kind of A-B testing space, pay attention.

Lenny Murphy: It's functional, it's usable. Yeah. Yeah. That's, you know, so that is what it does. It is to test usability on products.

Karen Lynch: So. So will it be leaned in? Will it be rolled into GPT, for example, where you just say, hey, can you AB test this for me? And then one of their agents goes out and does it and reports back in. So I'm just sitting here saying, which website should I use, which landing page should we go with here at Greenbook? Put them both in, it does what it does. And then the next thing, you know, like that is the, that is what Lenny and I are, you know, both went to is, well, that's going to be available coming soon to Ethereum near us.

Lenny Murphy: Absolutely. So your early stage testing of your product concepts, your website, usability, Yes. That is a research play. Think about UX and usability, those things, it's adjacent now. It didn't used to be. That is a research play. They spent a bunch of money to acquire a capability that is fundamentally an optimization platform. For product development. So pay attention. Pay attention. All right, you got the whole New York Times article. I feel so bad.

Karen Lynch: It feeds into the one that you found also. It's a New York Times article, so it is gated, but it's an article exploring how AI can make smartphones pass it, right? And what's coming next in terms of devices. Lenny and I have been talking a lot about this, like there is about, we are, what do you call that, on the precipice of an explosion in other things, other AI-enabled things that, you know, it might not even be your smartphone. That may not have all the power. There may be other things that are powerful. You might be wearing your glasses, you know, down the road and just be like, oh, call mom to your glasses. You may not even need your phone. Classes may be able to have that phone conversation. Like it's, we are not far from a different level of connectivity when it comes to wearables. Um, and it might seem experimental and it might seem like it's still too far off for consumer use or whatever. And it's like, do you know how quickly we, wait, do you know how quickly we are changing right now? I don't know. I don't know. So talk about the one, the article that you found this alter ego piece.

Lenny Murphy: Yeah, that was really interesting a Near telepathic wearable silent thought speed AI interaction Now this gets yeah, so this is not like the neural links on an implant, you know, I don't fully understand the technology. Although I assume there's some level of biometric involved here, yes, but it is fun, fundamentally a thought, you don't have to say a damn thing. You don't have to say a damn thing. You think so.

Karen Lynch: I'm looking at the shelves, which heat mapping and all of that has always been a thing, like eye tracking, all of that stuff. But now it's going to track my thoughts. So I may look at something on the shelf, stay there for a long time, and it's got some of my biometric activity. But those studies always had to be up with some qualitative to say, now you lingered at that logo for quite a long time, what were you thinking? Imagine if it knows a little bit more about what you're actually thinking, and the technology can assess what that thought is and say, oh, you know what? A little bit of sentiment analysis right there in our eye tracking, easily done. How? I don't know, but technology is evolving. And that near telepathic wearable stuff?

Lenny Murphy: It is. And that's where it gets, what about the I mean it takes it all types of interesting places of you know, well, you've got one and I've got one in work Yeah, there's all types of like you know With my qualitative researcher hat on just imagine if somebody's telling me something and then I get an alert like that It's not gonna say right, right? They do model right, right?

Karen Lynch: Yes, right. Imagine if what they're saying does not track with what they're thinking and you know, we used to have these diagrams. We used to have people who still have them. I'm just not executing qualitative anymore So, you know the think-say, you know picture where people would look here's what I think about You know adult diapers, here's what I here's what here's what I'm you know saying about old up adult diapers Whatever was always used for some kind of sensitive subject, you know, and we would then explore that qualitatively Imagine if we don't need those projective exercises because we're getting data from a wearable Yeah.

Lenny Murphy: I don't know that I want anybody to know what I think on a regular basis. It's probably, but here we are. These technologies exist. That's an episode.

Karen Lynch: That's an episode of an exchange where underneath it says, here's what Karen's really thinking. I think, you know, everybody loves it.

Lenny Murphy: Our, they love our, our, uh, dynamic and repertory is they're thinking what we're, what you're probably often thinking about me. Look, Lenny, just shut the hell off. I mean, that could really ruin the whole thing.

Karen Lynch: I just think it's really funny because, anyway. Anyway, let's go, we got two last things. Pay attention to the wearables because it's not as far off as we think.

Lenny Murphy: And follow the money. I mean, again, we have not, there have been so many articles on wearables over the past few weeks that we have not included in the show. Yes, it's true. But just, there's a lot still happening there, right?

Karen Lynch: What's going to happen is this week we're going to get bombarded with wearable articles. So you know, yes, even more. Now, we have two more to wrap up talking about this, the death of the RFP, because we were talking about this.

Lenny Murphy: We have it. So this was the KSR. Just enterprise tech buyers are reshaping procurement away from RFPs. A couple weeks ago, we posted this thing, you know, the day in the life of the agentic researcher, which was just an attempt to try and get a handle on what this looks like. We've been talking about this, uh, uh, news that's coming out more and more. Here's more just independent validation that, uh, it's not just any process. Procurement is a process. Any process is being shifted. The traditional approach of setting an RFP, um, is now being supplanted by something that is, uh, looks a hell of a lot more programmatic and agentic in nature. And this is another, uh, another. Data point on that.

Karen Lynch: Yeah, yeah, pretty cool. And let's wrap this last piece up. A little special, you know, shameless self-promotion on some level. But I, full disclosure, have not been able to read it yet. This was...

Lenny Murphy: We need to talk about it.

Karen Lynch: Lenny, somebody talked to Lenny, wrote a piece about it. That's what this is.

Lenny Murphy: Yeah.

Karen Lynch: So tell us more.

Lenny Murphy: It's just a series called What I Know Now and in the Research World. And it was just really, it's not your normal interview. It's about the kind of lessons learned overall, not just in business, but in life.

Karen Lynch: Retrospective.

Lenny Murphy: Yes. So, I really enjoyed that approach. If anybody's wondering, you know, what, what kind of makes me tick a little bit more. You know, I talk about my journey of sobriety. I will talk about my failures in business. I talk about all of those things because that was the point of the conversation. And I just, I like that approach overall. It's not appropriate for everything. But I think it's good that when we let go, we give room for humans to breathe. And this was one of those approaches. So hats off to research doing that. I appreciated being one of the folks that they interviewed. And yeah, it was just different. It wasn't me pontificating about bullshit of the future of the industry and blah, blah, blah. It was like, yeah, I really screwed up with that. And you know, that was a painful lesson from that.

Karen Lynch: And we should just use the phrase, you know, screwed up at bat to, you know, in conversation with somebody who's met a real driving me crazy right now. So on that note, you brought me right back down again.

Lenny Murphy: No. As a qualitative researcher, you know what that is like, right? I mean, you know, getting to know people on a deeper level.

Karen Lynch: Yeah. But hats off to you also for being authentic that way. And I think that's, you know, like full circle, you know, we talk candidly in the beginning of this episode about what it's like to be, you know, parents of grown children. At this point. And we talk about how we are parents, both of us are parents. And yes, we have our jobs, but also we have all of the other things as everybody in the industry does. So I think it's important to just remind us of those things. And yes, and past things that have shaped us, whether it's failures or whether it's trials and hardships, all of these things make us who we are today. So hats off to you for being authentic and sharing, because I always appreciate that about you.

Lenny Murphy: The world needs more empathy and authentic human connection.

Karen Lynch: Yeah, yeah.

Lenny Murphy: Because those are the things that unite us rather than divide us. And so I won't take that any further. You can read headlines and know where my head's been about that. So anything that helps perpetuate people to be closer and think about things that make us connect, I'm all for.

Karen Lynch: Same.

Lenny Murphy: Yeah.

Karen Lynch: Same. Yeah. So that's our show for the week. September 12th. Next week we're already going to be on the 19th. I can't believe it.

Lenny Murphy: I know it's fun. I mean, the kids want to get the Halloween decorations out. It's like, no, we can't on October 1st, but like this is right around the corner.

Karen Lynch: So I settled down. Yeah. So we'll be back next week and then we're going to need a game plan because I'm going to a smart Congress. So that Friday before SMR, I'm not going to be here. So we have to either pre-record in two weeks or something. We'll solve that problem on our own.

Lenny Murphy: We'll figure that out, but we won't miss that week for sure. So all right.

Karen Lynch: We'll talk to you all soon.

Lenny Murphy: Bye.

Karen Lynch: Bye.

Links from the episode:

CleverX released its 2025 Market Research Industry Report 

Data Quality Co-op issued an open letter calling for shared, systemic solutions to market research data quality 

Data Trust Is Still The Biggest Barrier To Enterprise AI Success 

Survey targeting firm founded 

ResearchWise launched Pulse for Excel 

SurveyMonkey Launches New AI Analysis Suite and Design Tools 

Pureprofile empowers clients by sharing proprietary AI tools free of charge 

Forrester Continues To Accelerate Its AI Leadership; Unveils A Self-Service Offering To Deliver Trusted Advice Faster

Microsoft to lessen reliance on OpenAI by buying AI from rival Anthropic 

OpenAI aims to shake up hiring with a new AI-powered jobs platform, taking on LinkedIn 

OpenAI acquires product testing startup Statsig and shakes up its leadership team 

A.I. Could Make the Smartphone Passé. What Comes Next? 

Alterego's 'Silent Speech' Could Be The Answer To Dictating Text In Public 

The Death of the RFP? How Enterprise Tech Buyers Are Transforming Their Procurement Process 

What I Know Now... Lenny Murphy