Embracing AI Innovations and Ensuring Data Quality

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In Episode 45 of The Exchange, Karen Lynch and Lenny Murphy talk about how crucial timely communication is in the ever-changing world of market research and consumer insights. They kick things off with a deep dive into Apple's big AI strategy, showing how it could transform mobile research and why suppliers need to get on board with these new technologies. They share some great examples from companies like The Clorox Company, U.S. Banks, Mondelēz International, The Coca-Cola Company, L'Oréal, and Adore Me to illustrate how AI is driving innovation across different industries.

Next, they chat about synthetic samples and data quality in marketing and research, focusing on the collaboration between Cint and Conjointly. They highlight how important it is to have high-quality, genuine respondents on platforms like Conjointly to ensure the data is reliable and credible.

Wrapping up the episode, they discuss the impact of consumer data fraud on business decisions and the vital role of data quality. They look at how alternative data sources and AI can help maintain and improve data quality standards. Throughout the conversation, they emphasize the need for industry professionals to keep up with the ever-evolving technological landscape.

Many thanks to our producer, Karley Dartouzos. 

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Transcript 

Lenny Murphy: There we are.

Karen Lynch: Hi everybody. Happy Friday.

Lenny Murphy: Happy Friday.

Karen Lynch: Okay. Can I just say it is June 14th, which means the month of June is halfway over and that feels very surreal to me because it's like my favorite month of the year. It's not okay that it's moving fast.

Lenny Murphy: Yes. I was making changes to my calendar earlier for July. Yeah. Like what? Really? We're already there.

Karen Lynch: Okay. We're there. We're there. So hi everybody. I hope you are all well. I hope you are all having a happy Friday. Um, we're, you know, we're excited to be, um, to be here both in, in good moods and good places today. So you're going to win.

Lenny Murphy: Yes, and glad to be back. I mean, I'm glad that I wasn't replaced by somebody other than your husband, right? It's like, that's allowable. But if you had brought in somebody else, I would have been really, really hurt.

Karen Lynch: I know. Well, the options that were going through my head is who's a good substitute? Really, the only one I could count on is, you know, in that kind of a desperate situation is Tim Lynch. But friends, listen, if you ever want to pop in like that in case of emergency, when one of us is out, like, go ahead and drop us an email to theexchange at greenbook.org. And let us know, like, hey, I'd be interested in being a substitute. Put me on the substitution list because, you know, things happen.

Lenny Murphy: Yep, absolutely. On that note, since you put the email, we want to acknowledge that apparently it was broken. We didn't know that. So sorry if you did email us. It wasn't getting to us. We did discover that it was broken and now it is fixed. So please do. Please email us.

Karen Lynch: Yeah. And if you, if you, you know what we're talking about, like, you know, um, you know, items of interest coming in there, things you want us to cover, things you want us to see, because it might not be on our radar. Lenny and I both curate from a lot of sources. Um, but if there's something that you're like, I really want their eyeballs in front of this new product launch or, you know, interesting industry conversation. Like if there are things that you're like, Oh, I wish they'd talk about that this week, please go ahead and email that email us at that. Um, email address. Yeah. Karley has shared it there. And I think, you know, the only reason, like I said, we know that it wasn't working was because Tim Lynch emailed it to me on my personal email address and said, are you getting this? And I was like, Oh my goodness. No. So the only reason we knew it wasn't working was because somebody said, by the way, I've tried to reach out to you there. So now we know we've apparently solved the problem and please reach out. We'd love to hear from you.

Lenny Murphy: Yes, and even up to like literally we were putting in at least I put in an article 30 minutes beforehand So that's not a great practice.

Karen Lynch: But but seriously, that's why we do this live like breaking news I'm going to get my water so I don't recommend you reaching out to us 30 minutes prior Yeah, this was a big week in in certain tech circles, those of you who are in the Apple ecosystem, you might have been paying attention to, you know, the big Apple event this year. And this year, this, you know, the 2024 WWDC events that they have, was all about AI, like, I think there's an article that we're going to share. And if you, you know, click on the article and read this piece, the company is finally going all in on AI, which is, you know, seems like, well, of course they should. But now when, when we say all in, they're really going all in there, there, there's an umbrella called Apple intelligence. So all of this is being worked on there. There's new features for the, um, operating system and you'll be seeing new features on your phone and new features on your iPad and, you know, on your laptop, like anybody in the Apple ecosystem, you should check out the, excuse me, YouTube video. You talk to them in a way.

Lenny Murphy: Okay, yeah, I'm not an Apple user, but it is interesting. It's not just Apple's AI, they're there, which is unusual for Apple, I think they're collaborating with multiple additional AI providers, open AI, etc, etc, to integrate in and across the entire ecosystem, all of the app providers, etc, etc. And I think here's what's interesting about not being an Apple user. What this does mean, though, is that we have optimized for mobile research as an industry so we could reach consumers where they are and the devices that they prefer to use. And this is going to open up a ton of new capabilities that's going to generate a lot of creativity for things that we could do now because simply the technology allows us to do it in new ways. So I mean, I would predict a new way, integrating voice, integrating new ways to do ethnography, video and analysis of images and all types of, you had brought up creating emojis.

Karen Lynch: It's going to be an AI powered emoji creator. So based on what somebody types, the sentiment of what they're typing, AI might create an emoji just for you. Just think through that. The idea of Remember, like, maybe you don't know, a couple years ago, we were all about, like, you know, even doing emoji research, like, what can we use emojis instead of options and surveys? Like, can we try to capture some human thinking with these, you know, cute little, you know, miniature miniature visuals, and they can create new ones based on sentiment. I love this concept. I can't wait to see that roll out. I mean, there's a lot of voice memo functionality, you know, which is a feature of your iPhone. They're going to add transcription to that. That's like, to me, that should have been happening. I recently checked voice memos and I'm like, really, I have to load this into something else. So it was a big surprise that they didn't already have transcriptions. So that'll be in there. There's going to be some AI assisting for photo imaging. I mean, editing, there's going to be, um, you know, AI generated notifications, you know, summarization, email wrangling, like there's going to be a lot or mail and, you know, mail wrangling, not Gmail or email, but the mail app messages, you're going to have like more auto replies for your messages, which has started, but now that's going to be, you know, a little bit, a little bit more integrated. So yeah, there's, There's a lot to check out with some of these new features, but the implications for research are just going to mean, you know, accessibility research, like for research, like all of that effort that everybody put into great mobile platforms for your research could potentially just be really enhanced with some of these add-ons.

Lenny Murphy: So. Absolutely. I think especially the, I mean, the qualitative, the scale, right. The, like your, your emoji thing of the, um, You know the semiotics and and there's so many interesting possibilities this opens the door for so Audience be prepared for new Innovation. Yeah with existing suppliers not just the new there will be there will be new suppliers and immersion here I promise you and I mean if you are a supplier you you need to be like taking in those sorts of

Karen Lynch: Announce the ones that Lenny and I are sharing with you, but this one in particular and being like, okay What does this mean for us? What does this mean for our platform? What can we, what can and should we be investing in from a development standpoint to, to, to build on some of this? Because it will start to become table stakes. Like, like I said, voice memos didn't have transcription and it already was bothering me. Right. You know, these things, once they become everyday life for iPhone users, a survey taker will start to expect that level of quality.

Lenny Murphy: Right. And it will go into Samsung as well, right? I mean, it's the arms race. So the, uh, it's unusual for Apple to kind of lead the charge, but, um, yeah, it's just interesting times in, I don't know if the horse is around, but, um, we've spent a lot of time already thinking about analysis and everybody's kind of gotten that point now where everybody has some AI flavor in, there we go, uh, in their analysis, but There's all new things coming, right? That affects form factor and opens up the door to new methodologies and to drive new value, new ways to engage. And it's not enough to say, Oh, we have a transcription. Yeah. Yeah. And I'm sorry. That's so six months ago, right? And I don't mean it to sound dismissive, just recognize that the pace of this technological innovation is so fast that we need to think through that and experiment. And yeah, anyway, I think we beat that horse enough.

Karen Lynch: Well, yeah, no, the horse, the horse is here, I should not have had the horse so far away. But I think I might have told you I was having to keep the horse away from Maggie, who was finding creative ways to get it off my desk. So I had to anyway, Maggie, my golden retriever friend, so Maggie really would like to just have that dead horse make it really dead. No, actually, Maggie might show the horse a lot of love. But that's not what we're here to talk about. I really do want to talk about this. This new product alert. Or I guess it was, you know, alerting everybody that there is a new product launch that, you know, I'm not in the co-pilot ecosystem. We're not Microsoft here, Greenbook. Although I know you are, you know, Lenny more embedded in that. I certainly know Tim is my husband and, you know, much of the business world, but it's called invisibility. And it is a, it is an interface that allows you to kind of go, go work amongst all of the LLMs, instead of having to be like, I'll use cloud for this, or I'll use chat GPT for this or whatever, like it's all integrated in there. And I was like, that is a win. Like for me right now, sometimes I choose I'll use cloud for this, or I'll use chat GPT for this, like I'm choosing. And I might have my implicit reasons right now, which, you know, aren't really articulated. But the idea of me not having to do that juggling is actually really interesting. So I love this particular app. What else can you tell us?

Lenny Murphy: No, I think that's it. You saw me looking around because I was trying to remember. I actually downloaded something similar for Chrome, and I can't remember the name of it. But it's the similar concept of integrating all of the various LLMs into one interface. And I think that's you know, it's like the application of the LLM stuff. That's interesting. And we'll see more and more of that deployed across all of our devices. So we won't have to pick just one. So yeah, some things do certain things better than others.

Karen Lynch: Yeah, yeah. Now that one is super cool. I was like, Oh, man, I read and also, for those of you who are, um, who are still grappling with this, when you click on the website for this particular site, which I know Karley shared this, you know, it's all via product hunt. When you see how many LLMs there are, branded LLMs there are, you start to realize how small your world using this technology really is. You know, it's like, if you're like me and you're like, I use, you know, ChatGPT or I use Claude, like that's my short list, right? Yes, maybe occasionally, I pop into one of the other platforms, but it's not even on my active memory in my brain about which ones to go to, right? So the fact that there are so many, I think, just shows us that even those of us who are tracking this have limited knowledge of all that's out there. So the other thing I liked about this is broadening your knowledge of what exists.

Lenny Murphy: Yeah, and the one that I was thinking about that you saw me craning my head. It's called MaxAI.me. Yeah, I just sent you the link if you want to pop it out there for everybody else. Say the same concept where invisibility is for Mac. This is for Chrome.

Karen Lynch: Yeah, it's good stuff. Good stuff So, you know here we are talking about AI innovations, but there were a few announcements this week that I want to talk about, because they are brand usage of AI. And, you know, we've been, Lenny and I've talked a lot about, you know, that brands are kind of following and relying on partners for this, at least they have been. But I wonder if we're at a tipping point, because this week, there were two big things going on, one in the world of Clorox, one in the world of U.S. Banks. So Clorox, there was a release that Clorox is accelerating their innovation process with Gen I investment, right? So they are using it in their innovation process too. It's a huge investment, developing, here's a quote, hundreds of digital prototypes at a time, testing them with millions of consumers instead of just 20 in a room as in the past. That's interesting. So they are putting this out there to use AI to test with millions in their innovation pipeline. I just thought it was super cool to hear that Clorox is doing that.

Lenny Murphy: Absolutely. I mean, that's, yeah, it's really interesting, right? And now what does that look like when you get to iterative, very agile, very iterative, Early stage concept testing and then move into okay. Now we're gonna boil it down and read gets optimized and you know if yeah Yeah, and we're you know, we've seen that with advertising. Yeah already and now we're seeing it with product concepts . It's pretty amazing. Yeah, yeah, there is a spoiler alert.

Karen Lynch: Spoiler alert, y'all. I interviewed Nick Graham from who's now at Mondelēz, former Pepsi, now at Mondelēz for the Green Book podcast, episode will air for a couple weeks. But I interviewed him yesterday and we talked about what Mondelēz is doing, how his team is using AI and some of the really neat stuff they're doing when it comes to innovation. That was almost along the lines of the AI, the models being trained to facilitate ideation, which was a fascinating facet of that conversation. So I can't wait till that gets out there. And you all can hear it too. But Mondelēz is certainly exploring all their use cases as well now. Like it seems like again, we have now tipped and brands are all in. The article that we were linking to, you know, had a few other links within that article, you can find them. But Coca-Cola is investing 1.1 billion in the technology through a partnership with Microsoft. L'Oreal has some R&D initiatives going on with AI for their personalization and their kind of innovation within the beauty category. Adore Me, which is owned by Victoria's Secret. They are allowing customers, again, to kind of design their own, you know, their own sets, lingerie sets. So, like, these companies are going all in now, and it's really exciting. I don't know, I just think it's exciting.

Lenny Murphy: It is, and interesting. So, I will share, this is almost a horse thing, maybe. Somebody, the CEO of a sample company, was traveling and talking to their peers, and He said no one was talking about this. They were all just talking about Just sample quality, which that's great. That's if you're a sample company you need to become a sample quality But I think it goes some of the other data we've seen recently that there's still a lot of folks that are not paying attention to this and

Karen Lynch: ...and I just got to say you're wrong Um, it's a bad business decision if you are not in full disclosure to everybody listening, you know, we, there's what we have, what, like four bullets on data quality and integrity to cover before the, you know, maybe we jumped to those after we talked about this us bank. We are not, you know, minimizing the importance of data quality and integrity. We know it is also an important issue, but, um, it's not one or the other right now. We need to talk about both.

Lenny Murphy: Right. Right. Because. You know, brands are doing it for themselves, right? I mean, they're driving innovation themselves.

Karen Lynch: And so like, I think you found this US bank article. Um, that's when I didn't click up, but it has to do with avatars.

Lenny Murphy: Yeah. Yeah, but how AI avatars machine learning significantly reduced development times for new marketing campaigns, right? I mean, it's the idea that they're using some type of synthetic sample. That's why I've been hearing that word avatar. That's what they're doing. They've created personas. Those personas are based off of existing data, and they're utilizing those to test new concepts and embedded within the marketing. And there's a lot of platforms out there on the marketing side that are doing exactly that and incorporating non-conscious measurement, psychographic profiles, et cetera, et cetera. Yeah. It's just interesting.

Karen Lynch: Let's jump ahead to, because it's all related. Karley, it's the very last thing on the brief, just because Karley's paying attention. This is on Evidenza.AI.

Lenny Murphy: Evidenza, yeah.

Karen Lynch: Let's talk about that, because I know we were going to maybe talk about it later. It was the last thing. This is the thing that Lenny shared with me at Friends.

Lenny Murphy: It was. I was on a call with somebody at the ANA conference in Florida. And these guys came out of stealth there and presented. And it's driven by the former, former head of B2B at LinkedIn, something of that nature. I'm sorry, if we're not getting that totally accurate. But, you know, basically, it is a synthetic sample. And We survey AI copies of your customers to build finance-friendly sales and marketing plans in minutes, not months. It is based on synthetic sample personas based upon your existing customer base. It's trained off of that. They presented, and my understanding was that E&Y said that they were doing A-B testing side-by-side, real surveys versus evidenza, 95%. Right, it was, we just need to recognize that. And it gets into the sample quality conversation as well, against the importance of a good sample to inform these things. It's not just primary research, it's now these new platforms.

Karen Lynch: Right, if we're building synthetic samples, we certainly want to make sure we're building it based on quality. That's an excellent point.

Lenny Murphy: Yes.

Karen Lynch: Well, I also like semantically, by the way, I like that, like, we know what they're talking about synthetic data, but I like that they're like, we survey AI copies, like the AI copies of your customers. And I really sat with that for a while when I looked at this. And I thought AI copies of your customers makes it sound real, right? It makes it sound like we just call on your people. Which is interesting on some level, right? It's a different semantic way to wrangle and understand what synthetic is, which seems fake. So anyway, encourage anybody who's in this space to really maybe do some research about the language that works and what these things mean to people right now, because synthetic might mean fake. Copies of your customers might imply a little closer to reality. I don't know.

Lenny Murphy: Right. And look at the different business use cases. These guys are not selling to market research organizations. Yeah. Excuse me, they are selling to marketers. In the business use case is to skip over primary research in these specific use cases to say we already have the data, we don't need to ask new questions. We can do this with these digital avatars based on all the existing information we know about your customers. Not going to be appropriate for every use case. There's still got to be a validation phase, all of those things. But they are proving that it can be pretty darn effective under the right conditions. Anybody who dismisses this, that's all BS. I would not recommend utilizing that example if you don't know the answer or don't know much about your consumer, right? Then it's not going to be appropriate. But if you have detailed information about your consumer and you want to test a hypothesis with that population with known data, then why the hell would you not?

Karen Lynch: Yeah, yeah. The classic example of, you know, kind of garbage in, garbage out, which I think is what you said before in the show. If you want to go down this path, make sure what's going in is really good, unbiased data with integrity, so that what you get out isn't the opposite. Right. Right.

Lenny Murphy: Absolutely.

Karen Lynch: Yeah. But let's stay with data quality, because there were a lot of things that came up this week in the world of data quality and integrity. We can bob back up to the other things, Lenny, just for process-wise with you and I. I didn't read, oh, oh, oh. We just got a comment. I want to shout out Matt Valley. This is easily the most insightful analysis I've heard, a re-synthetic sample.

Lenny Murphy: Well, thank you, Matt. We appreciate that.

Karen Lynch: Thank you. Yeah, I really do appreciate it. Oh, look at you, Karley. What?

Lenny Murphy: Karley, you rock. So that's awesome. I love that.

Karen Lynch: Thank you. By the way, we really like what we do, don't we? It's just so fun. We have fun. Anyway, thank you, Matt. I'm glad it's anyway, it's all good stuff. So tell me about Cint and Conjointly. This is one. Admittedly, I didn't get to this like the last press release I didn't get to this morning because I then got distracted by Evidenza.AI. So what do you know about this partnership?

Lenny Murphy: Not that much, actually. So so so when I first saw the headline, My thought was, you know, conjointly, they've actually pushed back a synthetic sample, those types of things. They conjointly, out of Australia, built a platform really for this kind of conjoint. It does a lot more than that, but it was, you know, designed as a platform to facilitate very high-end, complex research. They've expanded, they've integrated with Scent. And it's positioned as a data quality play, particularly around ghost samples. They don't call this out. So I'm going to guess, and if anybody from the center conjointly is listening, please tell me if I'm wrong. My guess is that they are going to integrate some elements of some of the tests that Conjointly has designed. Basically almost as a red herring or as a new indicator within the sample that it's a real person. That's my guess And that goes along with, you know, some other solutions. We've seen where we're talking like the next one around integrating facial coding or implicit measurement. And in utilizing those as a way to identify this is a real person. So I think we're seeing some interesting cross-pollination occur there. And this is vital for a company like Scent, for any of the marketplaces that have probably taken the worst hits on the quality argument. To find really innovative new ways to build that in to ensure that we are getting the highest, we're getting real people, highest quality respondents flowing through the pipes into platforms like Conjointly or anybody else.

Karen Lynch: Yeah, yeah, yeah. Well, you know, you mentioned this next article, you know, the headline is one that grabs you, right. So it's, um, it's about consumer data fraud impacting $1 trillion in business decisions. I mean, I had to look at the T for a while. And say like, what tea? And then I'm like, oh, this is what we're talking about. We're talking about this level, right? We're not talking millions, billions, we're talking trillions. In business decisions being impacted with potentially fraudulent data, it is unacceptable. When you look at it that way, it's like, that is unacceptable, right? So then I went down this rabbit hole and I don't know if you had seen this in there. In this article, Karley just shared the link, of course, but I jumped from page to page. I'm like, there's this, Quality Pledge, right, that Realize has put out there. And I'm seeing these names on it, Kantar, Sago, Qualtrics, Valence, you know, Repdata, Forced, Detect, you know, Bounce. I'm sitting there thinking, like, these are a lot of our, a lot of our, you know, people in our community, a lot of our customers and partners. And I was really excited to see that they are all committing to this challenge. I was like, I really would like to see even more on here on their behalf, right? But then I also saw Flowers Foods.

Lenny Murphy: I thought now- Shout out to Andy. Right?

Karen Lynch: I know. Anyway, I have a fun story about that that I'm not going to waste our time with. But anyway, I thought that was really interesting because they're first and foremost on there, probably not even known to everybody. But the reality is that it is a brand taking the Quality Pledge. Remember Lenny and I talked about you know, last year, brands were relying on their partners to shore up data quality. And this year, some of those great results were showing us that like, they're like, Yeah, you know what, if you're not doing it, we are. So anyway, I just think it's an indicator of that trend of brands taking this so seriously. So listen up.

Lenny Murphy: Absolutely. Well, and it goes back to the previous conversation, right? What's another solution? So we looked within the grid, it said, look for alternative data sources. And you think that's primary research. Well, you know what, it's not just primary research. It is also leveraging AI to synthesize existing information and create personas. So you don't conduct primary research at all. It's about the quality of the data that informs the decision. And so that's another permutation of brands doing this themselves. You know, Andy, shout out to Andy and Flower Foods. They're also part of Case, the Case for Quality. You know, that's a bunch of brands that have been driving this for, for years, driving the conversation. So Yeah, we're seeing lots of interesting stuff there. And that's great. And then I guess, last on that, being aware of the time, our friends in Canada, CRIC released the guide to data quality and online research. I think this is adjacent to the kind of the larger quality initiative going on with SMR and Insight Association and MRS, you know, where they're all kind of tag teaming to do that. But it's great. They're exploring at least putting information out, and here's the things that we need to look for in helping to drive the conversation. And because, again, the flip side of this is, it's not just a resource project. It's also now the data can contaminate an entire ecosystem of data that can have really significant consequences downstream from just the project.

Karen Lynch: Right, right. And what I like about this report is there's some very much like evergreen information. I mean, there's a glossary, I love a good report that starts with the glossary, right? It's like the nerd, the nerd in me is just like, I love that they're level setting with definitions, because there's a lot of people who might be newer to taking in the concept of data quality. I mean, we know, we know those of you who are like it, right. But there are some that might be like, I should start to pay attention. Maybe I haven't yet. And I like when we have a foundational document. So that's how I viewed this report. I was like, this is actually quite foundational. So a good starting point for anybody who's starting to really roll up their sleeves saying, okay, it's time.

Lenny Murphy: Yep, absolutely. I think we can squeeze in these last two interesting reads.

Karen Lynch: I think so too, Lenny.

Lenny Murphy: Well, all right. So let's do it.

Karen Lynch: All right. So, yeah, they're cool, right? Now, so when we say interesting reads, you know, these are literally almost like editorial pieces. They're things that you can read if you want a deep dive into these topics, both AI related, big surprise. But this first one, AI is transforming the nature of the firm, is kind of the net takeaway there. And it is all about how AI platforms are really changing corporate structures, changing interactions, changing I'm sure teamwork, and anyway, it's just a really interesting piece for those of you who want to think at a higher level about what it means for the organization, the firm, taking in all these AI challenges. And anyway, there's a pretty cool quote that I don't mind sharing. When the world gets confusing, say, for example, AI remaking the entire technology landscape, These frameworks can inform the choices you need to make. The better you know these theories, the more instinctual their lessons become, the more prepared your intellect is, the faster you'll be able to react to new opportunities in front of you. And when change is happening fast, like it is right now, speed is one of the biggest advantages. The reason I shared that quote and why I liked it when I read this article is what we are trying to do is We have all this disruption and chaos in our brains, but if we can strengthen our intellect around this topic, which is what Lenny and I really try to do with you all, strengthen our intellect, then it will start to feel more instinctive to make the decisions around this technology, which is the goal. We know so much of leadership and decision-making is instinct. And when you're disrupted, you can't do that as easily. So this is a great article to read if that is something that you need a big aha for, right? Strengthen your muscle on all these conversations around AI and changing technology because it will be easier for you to adapt if you have more knowledge.

Lenny Murphy: Yes. We can succeed and deliver more value to our customers. It all feeds into that. I thought that it was interesting to have that article on how it's changing the nature of the firm, organizational structure, etc, to this next one, that white-collar jobs are back. Because we all thought that there would be a decline in those things from AI, and that may still happen, but the data does not seem to indicate that. And I'll read a quote. So, the market angst remains high as the fog around the economy's direction fails to dissipate. We'd note, however, that it's precisely that condition which presently defines the current state of the economy. Everything is positive but muted. Growth, jobs, wages, business, consumer spending, inflation, sentiment, etc. All of which points to massive inertia in favor of the status quo. So You know, that's, we, we may not see this big disruption. You know, I did, uh, last little shout out if anybody saw, uh, old Elon this week talking about the Optima, uh, Optima robot. I mean, that's certainly his plan. Our robot overlords are going to be released in the next few years. Um, although those still seem to be, uh, kind of I hate the term blue-collar, white-collar, but more, more production-oriented tasks, physical tasks versus intellectual tasks. So, you know, AM may not be here to take our jobs for those that work in this category of things.

Karen Lynch: We must adapt. We must adapt. We must adapt one way or the other. And the new professionals will be, you know, will be able to adapt.

Lenny Murphy: And, and therefore, going back to the previous one, Grow your intellect intellect so you can be one of the adapters. Absolutely. Absolutely We're not gonna be left high and dry No, and we hope that you guys are I love how you said that Karen. Thank you. Why our goal? Why do we harp on these things? We're trying to help even though you may get tired of hearing us. I think maybe they're not tired of us. Maybe they keep showing up, right? Oh, yeah, by the way, by the way, let's give a shout out real quick. Karley, the brilliant and amazing Karley, took it on her own initiative, as far as I know, to start this newsletter, which is the summary of the exchange we had like Well, like, you know, a bajillion people sign up in a week. It was crazy.

Karen Lynch: Hasn't even been a week. And I think the first day, you know, a thousand people signed up on the first day. And yeah, she killed it. So, yeah, there will be now a, you know, there'll be posts on LinkedIn and follow up. But now there's a LinkedIn newsletter that will capture the essence of every episode. So, yeah, shout out to you, Karley. Good job. Good job.

Lenny Murphy: Yes. And thank you to those who signed up. So we appreciate it. I guess you do find value in our ramblings every week.

Karen Lynch: Yeah. Thank you. Thank you, everybody. We will see you next time. Yep.

Lenny Murphy: Bye, everybody. Take care.

Karen Lynch: Have a great weekend. Yep. Bye bye.

Links from the episode:

WWDC 2024: Apple Intelligence, iOS 18, macOS Sequoia and Everything Apple Announced 

Apple To Launch “Apple Intelligence” 

Apple Intelligence Preview link 

WWDC 2024 link 

Invisibility - One Copilot for All AI Models on Mac 

Clorox Accelerates Innovation with Generative AI Investment 

Coca-Cola is investing $1.1 billion in the technology through a partnership with Microsoft 

L'Oréal - generative AI to advance personalization and innovation within the beauty category 

Generative AI-powered tool from Adore Me 

How U.S. Bank Dramatically Cut the Development Time of Its Latest Campaign with AI Avatars 

Evidenza.AI: Pioneering Data Integrity in AI Applications 

Cint and Conjointly Target Survey Fraud 

Why Consumer Data Fraud Impacts $1T in Business Decisions 

CRIC Releases Guide to Data Quality in Online Research 

AI Is Transforming the Nature of the Firm 

White-collar jobs are back