Speed vs. Judgment: How AI Is Reshaping Research Careers and Tools

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!

Can AI make you more valuable by working faster, or does judgment matter more than speed? Karen Lynch and Susan Griffin tackle a viral debate about AI's impact on professional careers, then connects advertising measurement principles to event strategy and breaks down the three types of AI reshaping research: generative, predictive, and suggestive.

The conversation examines AI-moderated qualitative research, fraud detection consolidation, and new tools from Nielsen and Listen, while raising critical questions about agent training and transparency.

Many thanks to our producer, Karley Dartouzos.  

Use code EXCHANGE to get a 15% discount on your general admission IIEX tickets!

IIEX North America

IIEX Europe

Take the GRIT Survey! 

IIEX.AI Call for Speakers 

Apply for the Insight Innovation Competition 

Stay Ahead of the Curve! Subscribe to The Exchange Newsletter on LinkedIn Today! 

 Transcript

Karen Lynch: There you go. And we're live. We are. Hi, everybody. It's so good to see you again. You obviously know me, Karen Lynch, head of content here at Greenbook, but I'm joined today by a special guest, Susan Griffin. Susan, just remind our viewers who you are. Oh, wow.

Susan Griffin: Okay. I'm a marketing consultant. Griffin and Skeggs Collaborative is our company. I've been in this industry since Moses was in Boy Scouts. So I've seen a lot. The Green Book team calls me up sometimes when they've got stuff that nobody else has the time to do. And I guess that's The Exchange for today. I'm The Guest Host.

Karen Lynch: You have had The privilege of doing this with Lenny before, but you and I have never had The privilege of doing this before.

Susan Griffin: Oh my God, that's right. And as I posted on LinkedIn, you are genuinely Karen, one of my favorite people, no, my favorite person in The industry.

Karen Lynch: Stop, stop, stop. I love to hear that. So if anybody else feels the same way, you can feel free to let me know because I am a sucker for a compliment. So, um, you know, sidebar, like people have talked about like, um, love languages and all that other stuff. Like I'm a words of affirmation person. So like, if people say nice things to me, they can get away with almost anything. Like really, sucker for a compliment, so.

Susan Griffin: Like my post, repost it, and comment about Karen.

Karen Lynch: I will print it out and put it on my wall.

Susan Griffin: But seriously, I mean, the stuff you guys do in The exchange and in you personally with The podcasts and just overall The content at Green Book, it's great stuff. So let's get into it. Into it.

Karen Lynch: Let's talk about it. So did you watch The Super Bowl, Susan?

Susan Griffin: I watched part of it. I won't tell you which part of it. No, I've got Seattle fans in my family. So I was, you know, obligated to watch. But I do. And, you know, the ads are always a draw.

Karen Lynch: It is always a draw. And that is like literally since I got my mark degree. I have tuned into The Super Bowl specifically for The ads because it's a big deal right now that they released some of them ahead of time. But anyway, I wanted to share that New York AMA newsletter this week that, you know, and Karley has linked to subscribe to The New York AMA newsletter as well because it's a great newsletter for all of the marketers that are listening. I just love this newsletter. I'm a little biased, but I really like The newsletter as they put it together. Anyway, they had a link to a CBS News video that ranked The best and worst of The ads across all brands and all categories. And we could probably spend a lot of time talking about that. But you then told me about something that came your way, Susan, which was in a Nielsen email, which we also have. Tell me what you learned about The Super Bowl commercials this year. It was interesting.

Susan Griffin: So I've been involved in ad testing back in The days when I was at then Brain Juicer, now Sister And so Nielsen sent an email. It included their audience measurement ranking, how many people actually saw this Super Bowl versus previous Super Bowls, et cetera. But then they had three different takeaways for advertisers, what they should learn from The Super Bowl. And basically, in a nutshell, they said, by The week, not just The game, i.e. Plan for leveraging your investment before, during, and after the game. Leverage all the screens. Leverage all The channels. Make separate plans for The strategy for The ad across all The channels in which you're going to distribute it. And incorporate measurement from the start. And I thought about that. And sure, that absolutely applies to big investments in advertising like this but actually insights people who invest in exhibiting at a conference like IIX. You got a plan for before, during, and after. You've got to leverage all the channels in which you are going to telegraph the fact that you'll be at an event. And then you've got to figure out your metrics for success. Sure, investing in a kiosk at a conference is a lot smaller than a spot on The Super Bowl. But if that was like, duh, yes. Plan before, during, and after. Leverage all your channels. And figure out what your metrics are going to be beforehand. And measure, measure, measure. So that was my takeaway.

Karen Lynch: I love The forced connection also Like, yes, this applies for, you know, anybody who's developing an ad campaign, but also then connected to anybody who's a sponsor or anybody who's exhibiting. I love that connection that you made.

Susan Griffin: Well, it's top of mind, you know, for those of us who look at promoting our brand narrative in live events, you know, it's just, you can't just show up, you know, if you build it, they will come. No, you can't just just do that, you've got to really think through how to maximize your investment. Yeah, yeah, absolutely.

Karen Lynch: So yeah, I see Bridget, by the way, go Seahawks. And Bridget, I was 100% thinking about Kara and Bridget on our team who are Seattle-based Green Book employees the whole time. I was thinking, I hope they're really happy. So I didn't have a stake in this particular game because in the New York area, it's almost like a lot of us chose The Seahawks.

Susan Griffin: Boston family, and I got Seattle family.

Karen Lynch: Yeah, we were OK. I have a lot of Boston family, but they weren't with me. So anyway, all good things. I was really hoping for them in every project.

Susan Griffin: But after The Super Bowl, your week turned ugly.

Karen Lynch: To say the least. We haven't told the people that hosted the Super Bowl party that we went to, but my husband and I were both knocked out with a virus starting Monday morning, a four-day virus. So I was sick all week, yet I managed to do a webinar with Thomas Ramsey from Neurons. So speaking of maximizing potential, let me tell you what they did. And I think Karley can share a link to this particular webinar on demand. They thought through a plan. They bought two webinars at once, and they were like, you know what? Here's how we want to handle it. We want to present in January. They have a new product for media testing, speaking of media testing, a new media testing called The Creative Loop, which is about using predictive AI and suggestive AI, as well as generative AI, all The different types of AI for The ad work that they're doing. But they said, we're going to present it, but then we're also going to do a follow-up fireside chat to make sure that we kind of fully explain the science behind it. So they had two differences, they had a plan well before they executed against it. They're like, we're doing two, we want one to be like a presentation, then we want one to be kind and have a Q&A afterwards with a lot of audience engagement. And anyway, I just think it's a stellar example of using different channels, using different methods, and really being spot on with messaging. So I think it's a good example.

Susan Griffin: Just a quick aside, Karen, for the listeners who don't know what suggested AI is. Right.

Karen Lynch: And if you look it up, it's also called AI. See, this is something, say what you will about, we have many, many solid, strong, intelligent partners in The industry, but I always learn something from Thomas. And what he explained is generative AI, we all know what that is. And predictive AI, we all know what that is. But suggestive or prescriptive AI is trained actually to give The recommendations, to be The mind that takes in all of The data and then can say, here's what you should do with it. It's a little bit of an LLM that's been trained to be strategic thinking or a strategic thinking partner. So it's an interesting part of a trifecta that we're not talking about a lot yet in our industry, but we should be. And Thomas is already building it into his models, but yeah, it's either called prescriptive or suggestive AI. So probably we'll hear more because it's a very relevant concept in our industry, right? Because one of the things that is about later is humans in The loop. But anyway, let's just pause on that as I talk about qualitative research a little bit.

Susan Griffin: Yeah. Yeah. And there's so much to unpack from QRCA, and you were there on the ground. And so thanks for sharing. And there's a link, right, to what you shared.

Karen Lynch: Yeah, which is, it's a great conversation also happening on LinkedIn. You know, last week, if you tuned into The exchange last week, Lenny, I did kind of brief Lenny a little bit on my takeaway from The conference. And then this week, I was able to kind of articulate for a LinkedIn post, and I've started drafting some articles that we'll start publishing on Greenbook next week, really about AI moderated interviewing, or, you know, AI moderation in general, sometimes The acronym is me, A-I-M-I. And so I started chatting about it online and talking about really where I see it fitting when it comes to sharing a wallet for research. And it's doing a great job compressing the time to results compared to regular qual. It's expanding engagement compared to regular quant. So it's getting quality scale fully into The mix as a viable option for many brands at this point. That is The word on The street at this conference is brands are saying we can do survey work, we can do qualitative, or we could do this in between, which is AI moderated qual, which is quality scale with The help of AI. And so the discussion turned into when is it directionally the right decision. And knowing it's a viable option. It is perceived as a viable option. And, uh, and in many cases, speed to insights is going to be more important than depth of insight. And it is going to be up to The insights professional to determine which of those is more critical. Do we need depth of understanding here or do we need speed here? Um, yeah. So it's definitely in The consideration set. It is not just exploratory or experimental at this point. It is a solid option. So we had a lot of discussions happening live. I'll have more articles about it. And I shared that LinkedIn post because it is very interesting. It can, it can outperform some quant. It can't perform as in depth of some quality, but it has a place and everybody has to just accept it. It's rough.

Susan Griffin: And the insights professional who can discern The right solution for The right scenario is going to be The one who's going to add value to their clients.

Karen Lynch: That's right.

Susan Griffin: So I think more about it later in this episode. Yes, exactly.

Karen Lynch: Exactly. But yeah, the qualitative researchers, there was a great talk. Again, one of the first pieces I'll write is talking about Lauren McCluskey, who wrote about AI, you know, what people really think about AI moderation. And, you know, from a participant standpoint, people who are perhaps used to doing surveys are like, that was great. Like, that was a great experience for me. So we've upped the participant experience, which will help with completion rates, right? Because we know that the respondent's experience for survey work is way down. So there's real value to that. But we really, she then kind of dove into specific use cases. And here's the key. She's explored all the tools, and she is now an asset who wants to maybe say, hey, let's pilot some AI-moderated qual. Will you help us as a consultant? And maybe we'll do some supplementary human-moderated qual to help us understand those results more, bring them to life. But that is a solid positioning. So shout out to her who was leading The way there for what I think The true qualitative research consultant of The future. Or what it'll look like,

Susan Griffin: That's great. That's great.

Karen Lynch: Really cool stuff. Really cool stuff. So before we get into too much more of that, let's plug some things, shall we? Some shameless green book plugs.

Susan Griffin: Yes.

Karen Lynch: OK. Friends, The GRIT survey is still in The field. We really need your help with this. You've probably gotten an email about it. You can get a link here, probably one of The links that Karley will be a link to take it. We need your help to get these completed. It's in the field until February 22nd. So we've got just shy of 10 more days for it. Anything else you want to add there, Susan?

Susan Griffin: No, just that this is a way of getting everybody's voices into the results. And so it's important. It's important.

Karen Lynch: Yeah. And I think that one of the things that we are seeing is that more people fill out The survey for The business and innovation wave because that results in The grid top 50 and people are very vested in that for certain reasons. But this one we really need your help with because it really informs insights practices. And right now I think insights practices need your input for The good of The greater industry. So that's why this one matters so much.

Susan Griffin: And what's top of mind as opposed to interesting, but not necessarily something we'll use. That's really important for the industry as well. Actually, the other thing that relates to thought leadership is that the call for speakers is open for IIEX AI. Now that one you got a longer lead time for it closes in March. However, The call for speakers for AI this year is going to be trickier for those of you out there who think you have something to say, because it's going to have to be more than just we're doing conversational surveys, or however you are applying AI, there's going to have to be that potency proof, maybe with case studies or use cases, and it's going to have to be something new. Because IIEX AI was one of The, if not The most heavily attended virtual events for Green Book last year. So yeah, you've got till The end of March to submit to be an organic Speaker, but you're going to need all of that time to create a really powerful submission.

Karen Lynch: And yeah, and let me tell you The, because it's a virtual event, The submissions, it's going to be very competitive. We've already gotten some in, which is interesting. So normally we get a big influx sort of The week we close, but we've already gotten some. There are some people that like it. So, because they've got their idea. This lead time right now, you've got some time. What's going to be the idea that makes it different from last year's event? It can't be the same. We're talking about AI all the time now. So what's going to elevate us? To get you on this virtual stage with thousands of people tuning in. So I'm excited for that one. And I can't wait to see what you all bring to me. You know you've got it in you. I can't wait to see what you do.

Susan Griffin: And as for live events, registration is now open for both IIEX North America in DC in April and IIEX EU in Amsterdam in June. Is that right?

Karen Lynch: You do you do. And we have a code for all of you listeners exchange gets you 15% off the general admission tickets. Go ahead and thank you, Karley. You know, all of these links are available to you. But yeah, let's get your registration in at a discounted rate while it's still available. They're going to be great events. I'm really excited for them. You know, I just recorded a podcast with a Futurist Honoree and you know, they take to The stage Those are some of my favorite sessions at these events. The brands showing up are great. The partners that are bringing brands to The stage are in greater numbers than ever before. So I'm just really excited this year.

Susan Griffin: And one of The highlights of The live events is The Insight Innovation Competition, which this year will be in North America, EU, and IEX West in The fall.

Karen Lynch: We're not really talking about right now because we've gotten our call for submissions done for IEX West, but we haven't opened up registration or anything like that yet because we're focused on our other events. This competition, let me tell you, I mean, every now and then something comes up where I think about, and we'll talk about some of our winners later today too, you know, winners from the past. We've had some big names win this competition. This year, we're going to have some other opportunities that are, you know, we have our big winner who gets The $10,000 check and The opportunity to speak, you know, kind complimentary at next year's event. Winners have been The likes of Zappy and Dana Kim at Highlight. And of course, we've had Alfred at Listen, and last year was Rashad at March of Insights. We've had so many great winners over the years that have gone on to do some amazing things. And we're going to also have The choices that are not just crowd-sourced also we're gonna pull out this is who The judges said that's really The winner winner and then we'll also have The these are The people's The people's choice because sometimes they're The same right somebody might be like The people choice and The judges everybody saw what's really making this a commercially viable product but we're also going to have those two things.

Susan Griffin: What this means to you who are out there is The insight innovation competition submissions for The first manifestation of The competition in a live event is for North America, but that submission window is closing soon. I think it's also like either The 21st or The 22nd of February. So, you know, you have nothing to lose, folks, except missing this opportunity to submit and being considered for and The inside innovation.

Karen Lynch: Yeah. You have nothing to lose. You should definitely not rush the application. You should block some time to do it. Make sure you put your best self forward because why not? Right. And you don't know what somebody is going to see. Um, and, uh, it's definitely worth it. And even if you've, if you've entered before and you did not win last year, enter again, um, you know, The, The judges will look at everything fresh and, um, Got to play to win.

Susan Griffin: Last year's winner, Orchard, actually was a finalist. The previous year, didn't win, but won last year. So you got to be in it to win it, guys.

Karen Lynch: And they were a great example of kind of iterating and saying, OK, what do we need to do differently this year? Because it might be the same product, right? But your presentation, your pitch, everything has to come together. And anyway, a great example of somebody that pulled it all off. All right stuff because Susan I'm talking for 20 minutes and we haven't even gotten to like news No, no, we knew that was gonna be you knew that was gonna happen It's a ball.

Susan Griffin: Hey, I said that was predictable. Hey, I said that was predictable.

Karen Lynch: Yes So, okay, if you have not seen a viral post from somebody named Matt Schumer This is your this is your permission to go down The rabbit hole later today. Matt Schumer is a tech entrepreneur and an investor, CEO and co-founder of something called Otherside AI, which is behind a writing assistant called HyperWrite. So AI tool, big AI investor and entrepreneur. And he wrote this blog post, this article post, it's a LinkedIn newsletter. It went viral. It's been all over X, millions of views, LinkedIn, millions of views. And following up on this, because I've been tracing this story before we talk about what's in it, you know, he was interviewed on CNN last night, and lots of business magazines have picked up on it. Business Insiders reported what some other AI scientists and leaders are saying in response to him. So he poked bear with this essay. And for those who, you know, have no idea what I'm talking about, we'll share the link to his post on LinkedIn. But he's basically framing the magnitude of The AI changes for a non-tech audience. And he says in here, and I'll quote, and then I want you to hear Susan's take. This might be the most important year of your career. Work accordingly. I don't say that to stress you out. I say it because right now, there's a brief window where most people at most companies are still ignoring this. The person who walks into a meeting and says, AI to do this analysis in an hour instead of three days is going to be The most valuable person in that room. Not eventually, right now. He goes on to say, learn these tools, et cetera, et cetera. So at first glance, it's a provocative post, right? Which, look, Susan just twitched a little bit. She's like, I don't like it. I don't like it one bit. And we've gotten some rebuttal posts as well. But Susan, go ahead and tell us your take right away. Because when you saw this- I read this.

Susan Griffin: I Read The article. And I looked at it. I used AI to do this analysis in an hour instead of three days. And so I'm gonna be the most valuable person in the room. And what I felt like was that the most valuable person in the room is gonna be the person who did the analysis in an hour rather than three days. And basically said, and this is what I learned about that analysis. Versus what I could have gotten in three days. And here's where we damn well better use this. And here's where we might want to think it through. It's kind of like what you said earlier, Karen, in terms of, you know, The AI moderated call. The person in The room is not going to be who's most valuable, is going to be The person who can then advise everyone else as to how and when and with what caveats we are going to use this tool, not that it's The fastest. And that I sat with for a while. And then last night, Karen, you shared with me an article you found that it's not The point counterpoint, but it's more contextualized. It's from a woman named Anne Handley. So you found it, Karen. You frame it. Up in terms of...

Karen Lynch: Yeah, so she's a digital marketer, content expert, chief content officer of Marketing Profs, The organization, founder on LinkedIn. She's got something like 500,000 followers. She's an author. But she argues that we should... So she points to this post of Matt's, but she says, we should replace this AI panic with sharper questions, better briefs, so insights teams can focus on framing the audience . So what she's saying is figuring out what we need to think about. The AI input is how we are helpful. The friction between idea and expression, between intention and execution, is not frivolous. That's where the thinking happens, verbatim. So again, she's in the context of marketing. We need to connect some dots for people. But the idea is just our brains, it's not just speed of analysis, it's what our brains then do with that analysis.

Susan Griffin: And she used some incredible analogies relating to, you know, OK, so Matt talks a lot about lawyers using AI, right? And she talks about how you don't hire a lawyer because they can do something faster. You hire The lawyer and she uses The term judgment. You know, they have The judgment. To know how to frame an argument in front of a court, in front of a jury. I mean, this whole idea, she talks about judgment, which I found to be very interesting because earlier in The week, Rashed Chowdhury from Orchard Insights, our winner of The competition last year, posted a comment on LinkedIn about a Harvard Business Review piece that explores how workers develop good judgment in The era of AI. And they said, AI simultaneously increases the need for judgment and erodes the experiences that produce it. And Rashed dug back into his own experience. And I'll read what he said, because it's really important. He said, I learned about judgment by being in the weeds, by making mistakes, missing things, and realizing after the fact what I should have noticed. And that's how I still continue to build judgment. It reminded him of his early MapQuest days for those of you who remember MapQuest, people blindly following directions into places that clearly didn't make sense. The tech worked right up until judgment was required. So the question that I'm sitting with, this is, I'm quoting him, as leaders rush to implement AI, how are we designing organizations where judgment still develops, especially for folks early in their careers. And as AI, you know, we talk about how AI is gonna remove the things that are, you know, manually intensive, and there are a lot of jobs that are gonna go away that juniors used to do. Yes, but how then are we going to take juniors and give them the learned experience you know, The falling down that teaches, ah, judgment, I should have noticed that. And, you know, as Anne says, she's not a Luddite, she uses AI. It's just The corollary that I wish I had heard in Matt's post, but there are enough people out there who are, sharing that voice.

Karen Lynch: So yeah, judgment, judgment, the endangered species, injured species, which is judgment, and the opportunity to learn judgment, right? That's what we need to offer. Friends, look, I will tell you this. So Karley can share all of these links from this section, because there's still so much to cover Susan, we're in, 28 I'm fine. But I highly recommend you go down a rabbit hole on Reddit, there's a subreddit thread for artificial intelligence, check out what they're saying about this post, The original post from Matt Schumer, and you can see The good, bad, and The ugly, and all of these anonymous opinions. It's an interesting Read, it will stimulate your thinking on the subject matter, and our collective two cents is don't forget judgment. All right, we have to talk about some news items because there were some, not as many as we'd like to because we're a half an hour in already, but we must talk about Repdata and their acquisition of Redem because that's a big deal for those of you who are following kind of data quality providers in our industry. Yeah, Susan, what do you think about this?

Susan Griffin: Well, I saw it and what I came away with was, you know, this consolidation isn't an indication that fraud detection is going away. If anything, it got me thinking about all the other companies that are talking about fraud detection. And every time there's a more powerful detection system, the fraudsters get more clever and innovative in terms they are going to create survey fraud. So, you know, there's a whole bunch of people who are still out there. I mean, God bless, you know, Repdata and Redem, one plus one may equal five, but you can't swing a dead cat and not find people from sample companies to people like Kantar claiming fraud detection tools Yeah. And there's some suspicion that it's so complex that you don't need just one. Yeah.

Karen Lynch: So I think there's probably people that are now saying, OK, at least now maybe I can lean towards one at least for some of our needs. So I think my takeaway on all this is cool. So now we've got kind of an end-to-end solution. Maybe cover a couple of different needs with this partnership. Really take a look at what they offer. I think for anybody who is listening who has not gotten their data quality tools in place, this is a good time to do research. See what this acquisition now sets them up for, see what The others in The industry are doing, and do something. Don't do nothing. Right?

Susan Griffin: Exactly. Exactly. Yeah.

Karen Lynch: All right. A couple of product launches that I want to hit. One of them, Susan, spoke of The Super Bowl and Nielsen, what they're doing. I don't know if you saw this, but, you know, they introduced a co-viewing methodology to better capture audiences. And they started with this Super Bowl incorporating a wearable measurement device. So like, instead of, you know, you doing your Nielsen log after the fact, they are seeing, they're like, no, no, we're gonna just check your, check your skin response.

Susan Griffin: This movie, neuroscience. Remember the days when we had fMRI and people were going to strap diodes to your head? Yes, we're capturing synapses snapping. But what did they mean? Why did I get excited when I saw The Coinbase ad? Did I get excited because I was saying WTF?

Karen Lynch: Well, yes, we could talk about it.

Susan Griffin: Any methodology that's going to get to implicit response, I suppose, is a good one. But I don't know. My smart watch tells me some different things. But anyway.

Karen Lynch: My aura ring says, go back to bed, honey.

Susan Griffin: Exactly. All it's been saying all week is. Exactly. But what else did we get?

Karen Lynch: They introduced something called Compass, an autonomous research partner analyzing past projects also to recommend new work.

Susan Griffin: This I loved, and I'll tell you why. There's a lot of knowledge management tools that are out there that are going to give you the ability to be able to look back into other research you've done to say, didn't we ask this question before? This, if it lives up to The promise, is saying you asked this before, but here's how you might want to think about asking it again within The context of how things have changed and how you can ask it differently. So this was really interesting to me.

Karen Lynch: Yeah, yeah. Yeah, so UX teams and CX teams, you know, start mining that historical data. Yeah, I thought it was a pretty good one. So we have one other launch which kind of leads into our or later reading of this episode, but Listen introduced a new product called Research Agent this week, which basically takes a look at any data from any other study, and we'll do some of that data synthesis. So they're moving beyond just The conversational AI, The ecosystem that they created with their tool, right, about doing quality scale, and now they're moving into you know, this research agent, which does this analysis of data.

Susan Griffin: Yeah, I mean, you know, there's this whole idea about AI agents who will do things for you. Yeah. And there are a lot of companies talking about, well, we need an agent that is research specific. So I think we're going to hear a lot more companies banting about with this two word phrase, research agent. And The devil's going to be in The details. Yeah. What are these agents really doing for you? Yeah. So more to come, obviously, but let's see some use cases, some proof cases, you know, case studies.

Karen Lynch: Yeah, yeah.

Susan Griffin: To actually get a better definition of what this really means.

Karen Lynch: Yeah. And how are they built? How are they trained? Like, I think these are great examples to be like, okay, how have you taught your research agent so that we know that the synthesis that they're doing feels up to snuff, right? Because they may not have learned judgment. I don't know if you can see Nancy on our team chimed in saying The opportunity to learn judgment is her motto for 2026. The opportunity to learn judgment.

Susan Griffin: I want a quarter every time you use that, Nancy. But there were some other LinkedIn posts this week that really are a pause for thought, you know, and coming from some folks who, who've got some street cred in The industry.

Karen Lynch: Yeah, yeah. So Steve Phillips, you probably saw Steve Phillips from Zappi, by the way, speaking of competition winners, and listen as a competition winner, we have to, you know, kind of always shout out these friends of ours. But Steve Phillips laid out kind of why using cloud code and research. So cloud code is, you know, another tech rabbit hole to go down, learning what it's all about from Anthropic, but why insights leaders should watch this developer tool and its implication for kind of our research workflows. Basically, it's making, it's a development tool that allows anybody to be a developer. And so pay attention, right? Steve's post is a bit of a cautionary tale. But also what will happen is that anybody can create research agents right now pretty. So we have to be paying attention to what they're doing, and we really have to look under the hood, I think, and see what's coming out. Just because you can doesn't mean you should. Plenty of good, credible entrepreneurs will be showing us their agents, but there will probably also be some that are not that great, not up to snuff. So did you have anything to add? Any other thoughts on that?

Susan Griffin: Yeah, just, you know, it's interesting. I talked to some folks whose development teams have been using The AI tools, and one of The comments that was shared was, it does things so fast, but my brain hurts because it used to be I had these interstitial moments where I could be thinking about The structure of The code that I was building, Now that time for reflection is taken away. So I'm just wondering if in these tools that are making everything more efficient and making everything faster, if we can just have that pause for, you know, how are we going to QA this stuff? And it's inevitable that that's going to come. And that process itself may be faster and enabled by AI. But that comment I made about Matt's thing, The person in The room is most valuable. It's not the person who says, I did this in two hours versus two days. It's going to be, and this is the difference in what I got out of that. But then you found something else.

Karen Lynch: So, you know, Kevin Carty, he's The CEO and co-founder of Intuify. He posted about a Qualtrics demo arguing that training AI on organization specific data materially boosts task performance and usability for CX and InsightsWorks. So a well-trained, well-trained LLM is actually going to perform really well. So there's that concept again of is speed to market really The goal or is a quality product really The goal, right? And I think that what we can all say is say what you will about Qualtrics, but they have quality products. You know, that's been right from the beginning. They were able to do what they did. So I thought this was really interesting too. So training AI on organization-specific data boosts task performance. So if it's well-trained on very specific data. You might have a great outcome there. Right.

Susan Griffin: And specificity count

Karen Lynch: Yeah.

Susan Griffin: No, I mean, we know this in research. I mean. People who specialize in health care have got some really strong chops in terms of The science that goes into disease states and The chemistry behind how drugs work, that's a very specific core competency. And I think that that is what is being inferred here. Train around things that are specific to the business problems you're solving.

Karen Lynch: Yeah, yeah, yeah.

Susan Griffin: And then, of course, all these companies have to figure out how to articulate their own brand story to differentiate how they're better at doing this than their competition. And that's my marketing story, and I'm stuck.

Karen Lynch: And then, of course, my shameless plug again is then, and then get yourself in front of people who are coming to an IIEX event to learn about these new technologies. I mean, it is the place to go to explore what's new, explore who's doing what, explore all these tools and the way you can implement them. So we end with two names for those plugs there in a way, right, Susan?

Susan Griffin: Well, then let's tie it all the way back. And if you come to an IIEX event, you get to meet Karen in person. Oh, stop, stop.

Karen Lynch: Just add it to the list of visits to attend.

Susan Griffin: Oh my god, this was super fun.

Karen Lynch: I'm so glad you joined us. Thank you. By the way, just so you all know, Lenny is off with his family and was therefore not able to join us. And because I was sick this week, I was unable to figure out what to do until my fever broke. I kept saying, I don't know what to do. I don't know what to do. And then my fever broke yesterday. So I'm like, oh, I've come out of The fog. I don't have to cancel. Susan!

Susan Griffin: Yes.

Karen Lynch: Yesterday. So very quick on your end. Thank you.

Susan Griffin: This is like The understudy getting called saying, The leading lady is sick, not I said Lenny's The leading lady, but you know, I think I might use that. But The leading lady's out six, so can you be at The theater by six? Theater by six, so yes.

Karen Lynch: And to Nancy's point, said, what about meeting Susan in person? Susan, you will be at these events this year, won't you?

Susan Griffin: Oh yeah, oh yeah, oh yeah. I wouldn't miss it. To see you in person, Karen.

Karen Lynch: Thank you, thank you. Well, and it is a mutual feeling, and also Nancy, come on, really, we win all around. Bridget, we win all around.

Susan Griffin: In person, it can't be beat. So see you at IIEX.

Karen Lynch: See you at IIEX. And I will see the rest of you next week when Lenny is back.

Susan Griffin: The leading lady will be back.

Karen Lynch: There's so much I can say that I'm not saying right now. Bye, everybody. We'll see you next week. Susan, thank you so, so much.

Susan Griffin: Thanks, Karen.

Karen Lynch: Bye, everyone.

Susan Griffin: And Karley, thank you.

Links from the episode:

CBS News video ranking the best and worst 2026 Super Bowl ads 

Subscribe to the AMA New York Newsletter 

Susan shared a Nielsen email 

Greenbook Webinar with Thomas Ramsoy, Neurons 

Karen Lynch: QRCA conference 

Matt Shumer frames the magnitude of current AI changes for non-tech audiences 

Ann Handley argues we should replace AI panic with sharper questions and better briefs 

Rashed Chowdhury 

How Do Workers Develop Good Judgment in the AI Era? 

Here's how smart people in tech are reacting to Matt Shumer's viral essay 

CNN Video recap of an interview after his post went viral 

Rep Data acquires ReDem 

Nielsen launches co-viewing pilot program to further enhance TV measurement 

Voxpopme introduces Compass 

Listen introduced Research Agent 

Zappi’s Steve Phillips lays out the why for using Claude Code in research 

Kevin Karty, CEO and Co-Founder of Intuify posted about a Qualtrics demo