Thania Farrar of Burke: Building Trusted AI Insights

How can established insights organizations innovate with AI without sacrificing the rigor and trust that made them successful? Thania Farrar, Senior Vice President of Corporate Innovation at Burke, joins Lenny Murphy to explore how the firm is evolving from traditional market research toward decision intelligence. They discuss building AI-enabled systems that connect fragmented data, deliver insight closer to the moment of decision, and preserve the value of expert judgment. Thania also explains why high-quality human data remains essential, how transparency strengthens client relationships during uncertain times, and why governance, privacy, and provenance could shape AI adoption. The conversation closes with a call for greater industry collaboration and renewed attention to qualitative research, behavioral science, and the complexities that make people—and business decisions—impossible to reduce to data alone.

Key Discussion Points

• How Burke is evolving its long history of research innovation into a more intentional decision intelligence model.
• Why AI can accelerate insight production, but cannot replace quality data, expert judgment, and human understanding.
• How connected data systems can shorten the distance between a business question and a confident decision.
• Why trust, transparency, governance, privacy, and data provenance will be essential to responsible AI adoption.
• The growing importance of qualitative research, behavioral science, and industry-wide knowledge sharing.

Resources and Links

• Burke, Inc.

You can reach out to Thania Farrar on LinkedIn

Many thanks to Thania Farrar for being our guest. Thanks also to our production team and our editor at Big Bad Audio.

Transcript

[Lenny] Hello everybody. Welcome to another edition of the Greenbook Podcast. Thank you for taking time out of your day to spend it with us. And by us, we're not talking about my multiple personalities. We actually do have a guest, which is going to be a lot more fun than anything I could ever say. Anyway. So Thania Farrar. Welcome. Glad to have you here.

[Thania] Hello. It's good to be here. Thanks for having me.

[Lenny] Oh, it's wonderful. So for the audience, I've actually had the opportunity the last month or two to get to know Thania more. I've known you forever, but, and to get to know the Burke team. And so I have a, was really excited to have this conversation because I know that you are doing so many interesting things. Rather than steal your thunder, why don't you give us your quick bio, your origin story and then we can, you know, get more into the neat stuff you're doing around innovation.

[Thania] That sounds like a good plan. I'm trying to think of the quick version through this. So here we go. I am actually from Honduras and I moved to the United States to get my degree and my MBA at the University of Cincinnati, which is what brought me into town. A lot of people are curious about why Cincinnati. My dad used to work for Chiquita and Chiquita used to be headquartered in Cincinnati. And so that’s kind of a part of the journey. Burke found my resume. I wasn't planning on staying here and it's been 28 years since I've been in Cincinnati. So that's for you a little bit of what best laid plans will get you sometimes is like completely different path. So it was a life changing moment. They found my resume and offered me a job and I stayed with Burke initially for five years doing a lot of the account management and then the operational machine serving clients from that angle and just honing my research skills for a while there.

I took a short hiatus of about eight years and I worked somewhere else. Tara Marotti, if you know our CEO, calls that my mental lapse. And so I came back in 2010 and have been doing a lot of different things throughout the organization, always in service of clients and somehow always upsetting the apple cart, it seems like. But I was an account executive and served clients on the front lines for a while. I also did a little bit of the innovation role back in the day, and we can talk about that as we go through, but came back to the sales function of the client service function and managed account executives for a while. That was always fun. And again, you get to see so many different clients and so many different challenges that gives you a good perspective on that. Somewhere along the way, I've gotten involved with marketing and my last stop has been the corporate innovation role, which is a great marriage of thought leadership for marketing purposes and telling the world about the wonderful things that we're doing. So, jack of all trades somewhat, but always in service of making sure that we can solve problems for our clients. So here I am. I did not go back to Honduras in the moment I thought I would, and I'm kind of glad because this has been quite the ride.

[Lenny] That is quite the ride. I did not know that you were originally from Honduras.

[Thania] A lot of family in Costa Rica, too, if you've ever visited. A lot of people have. It's a great place.

[Lenny] Yeah, I have not, but it's on the list. There's many places on my bucket list, including Cincinnati. Cincinnati's a cool town. I used to live there when I was a kid, actually.

[Thania] Oh, so you're familiar with the town. Good.

[Lenny] I am. And of course, now that we're in Kentucky, we'll go to Cincinnati periodically because that’s the closest big town, really. So, Lexington doesn't count compared to Cincinnati. But anyway, so, you know, what is so fascinating to me is Burke, right? I mean, Burke is a storied, one of the original companies in this space. And I'm sorry, my dog just got in here and is trying to get my attention. We're live without a net folks. Um, and that role around innovation, right? I mean, that is, it is so apparent because the company is always doing more. And of course, in the last, uh, last few weeks, as I've gotten to know the business a little bit better, um, amazing how the business continues to evolve. And, I know you're central to that. Uh, give us a sense of what that is like when, you know, as we think about all these startups, early stage companies and all, oh we're going to do all this cool stuff. And, but the role of such a respected company like Burke, one of the foundational players in defining the entire industry, leading that change as well. So what is, give us a sense of that? What's that like?

[Thania] Uh, I think, I mean, I was recently at Cincy AI week and talked to a bunch of people that work in startup world and it's so different. You're right. You know, there's, there's a, obviously the tenure is shorter and the pace is faster and it's all about survival. But, um, my experience has been a little bit different. And as you said, Burke has been around for quite some time. And, you know, if you think about our founding back in 1931, you know, by a woman who was at the time, 27 years old, um, she was innovative in her own right.

Cause that was not what, you know, you were supposed to do, um, especially for a woman in that time period. And especially in the economic conditions, this was not supposed to happen, but she found a way. Um, I recently read that Procter and Gamble celebrated a hundred years of market research. Um, you know, in like last year and Doc Smelzer from P&G at the time is credited with contributing to the inception of our practice as, you know, insights back all the way a hundred years ago. Doc Smelzer was Alberta Burke's mentor. He was the one who gave her the in to sell services into P&G and start her company.

So that's how far back we go now. Inception was very innovative for the time, you know, this was a new field that was being created. So you can't, we've been innovative from the start. I like to say, and honestly to stay a viable business throughout the years has taken, um, quite an open mindset towards the new, because we're no longer doing door to door, uh, well, not as much, but like they're door to door in the way that Alberta did it is no longer phone later online. Now we're engaged with big data and then AI and technology. Like the, the constant of change throughout that time period is something that sometimes because the cycles are so long, um, we forget that we've been through inflection points throughout our existence as a company. And, um, we're not strangers to pivoting and making the adjustments. So I'm in the honored tradition of innovation of Burke. If maybe now we have an area and a group and a dedicated function to it, it's maybe a little bit different in the past.

Cause you know, you know how fast things are moving now, Lenny, and we, we have to, we have to take action more quickly than ever before. So, whereas it may have been more organic in the past, it's more intentional, um, than it has been before, but we certainly try to, to go with where the market is heading and shape, you know, the things that we can shape for our clients. And we've been doing the same thing for all that time. And that's providing support for clients to make better decisions and to feel confident about this decision. So we're still in that business and it looks very different, but it's the same business.

[Lenny] Well, yeah, I think that's it. There's an important point there around kind of the definitional aspect, right? Now I know that Burke is a decision intelligence consultancy, right? That truly at the core and everything that you do, uh, is in kind of three pillars, um, of business and three areas of focus, this design on that decision intelligence. Um, and that's not how the market research industry, uh, although maybe there's been aspirations there, but the focus has been so much on process that that's what has defined so much of the business. Um, and it seems like from my perspective, what you're charting the course on, uh, is that, that core market research perspective on quality on, you know, understanding what is the right data to answer the business question in the best possible way.

But that consultative lens, which is different than kind of the industrialization that has driven so much of the industry, uh, that gets into now, what do you do with it? What are the implications and how do you build systems around that? Um, now that language is kind of newer language that companies are adopting. But to your point, you've been doing that for a long time.

[Thania] So it's shape or form we have. Yes.

[Lenny] Yeah. So what does that, what is that like that you've been out there for a long time saying, Hey, wait, we're, we really are different because we're thinking about this in a different way that is aligned to the client's needs and business issues versus the process. It's kind of like the rest of the world has finally caught up with you. Um, uh, yeah. What's that been like?

[Thania] Uh, this is, this is interesting. We've always, and you know, we're not, we were for a while there and continue to be, we do want to make sure that we're following process that ensures that the information that you have, the data that you start with for any consultation, it's good. That's continues to be critically important. And it's something that we pay a lot of attention to because garbage in garbage out has never been truer with AI. If you are not feeding and curating the information and making it AI ready in the, in the way that it needs to be, you're going to get the same answer that everybody else is getting, or you're going to get a wrong answer or everything else. So there's, there's a different, um, there's a different path towards that confident decision nowadays, which still starts with the data, but the question of, okay, so what do you do with it?

The so what? You know, remember storytelling when it was like the, that was the thing that, and we still aspire to be good storytellers because we know that narratives help move, um, our stakeholders to action. I do believe that that focus on process that you talk about is something that we are solving for, if not already solved for with all of the technology that we have, we've been able to scale the production of insights in a way as an industry that we've always wanted to, because we have felt, and I speak for Burke, but I know that, you know, when you talk to industry partners, you hear this same song and dance, you hear clients complain about it, that insights doesn't get the seat at the table oftentimes because why? We're too slow to the party. We have all kinds of process and rules that we need to follow and stakeholders just need to make a choice.

And so oftentimes we've kind of been sidelined depending on the organization, the value of insights varies tremendously. There are some organizations it's the lifeblood and other organizations it's just like just give me the report and maybe I'll look at it at some point. So what that consultation desire has always been there because we know that we understand that data. We have something that we can bring to the stakeholders decision process that is valuable. What AI and technology are doing today is putting even higher expectation on the ability to do that because yeah, you have all the data that you need. You might not need that much more. You need to refresh and continuously learn, but access to data, creating data from consumer that's a challenge is not as big of a mountain as it used to be, but it still needs to be good where we're necessarily going. What we're trying to go is shortening the time between the question that a stakeholder asks and the decision that needs to be made.

And the moment that that insight is provided to be able to inform that decision. And we could have insights and data that is consumer data, business data, whatever data is available, be served up to a stakeholder in that moment when they have that question. With the least amount of time and space, then we're doing something different all of a sudden, because that's the holy grail is to make sure that people have the right information to reduce the risk of that decision and to feel confident that they're doing that.

So what I see is a lot of production of great insight, or there's a lot of scaling in the insight production function, but you still see leaders that are not necessarily getting what they need when they need it in the form that they need it synthesized and served up in the way. So we're very excited about what's possible now and the systems that you can build to bring that data to the forefront of that decision at the point when it's needed. And so we're getting faster at serving up that information and to the extent that it's good and high quality and we can instill confidence, I think leaders will use that more readily than they have in the past. That's my opinion.

[Lenny] I— preach to the choir. Yeah. And you mentioned this, and it's actually one of the more surprising points that I experienced as we started to get to know each other better, building systems. So we've talked a lot in the world of AI, right? There's infrastructure, there's orchestration, and there's judgment, right? And some companies are trying to be all three, right? You're building the tech that functions at the data collection, et cetera, et cetera. I see what you're doing as building harnesses more around the orchestration and the judgment layer. You have infrastructure, you're providing infrastructure, but you've invested in synthesizing things in such an interesting way that you don't need to recreate the wheel.

We're aware that you've got relationships with some other suppliers that from a technology standpoint, yep, that does what needs to be done. Where does that sit within your own orchestration layer? How do you kind of build the harnesses around that and optimize it, align to that kind of laser focus on how does this serve the client's business needs through the lens of the areas that you practice in?

And that's not something that I see in a lot of other companies. Especially of your size, right? I mean, you're not a bajillion dollar company. You're certainly one of the top 50 in the US and growing, et cetera, et cetera. But you've invested in a very smart way that I wish other companies would think about doing as well. Was that just kind of ingrained into the DNA of the business on, look, we want to do this ourselves or was AI emerged and you realized, oh crap, we need to do this or else we can just be commoditized. What drove that investment in building the systems to be an effective orchestrator and judgment layer?

[Thania] I think that a lot of it has had to do with the, you know, how technology has advanced so quickly. And I will say, I'll give that credit to AI. It opened up the ability to serve our needs in different ways because we have technology partners for a lot of different things in this organization. We don't create software, you know, as our core business. We have very capable, smart people, but that's not our remit. We've never been a platform company per se or, you know, there are companies out there that are doing a great job of setting up technology.

And some of those companies have been formidable competitors in recent years. So if you think of Qualtrics and Medallia and that ilk of platforms that came in and took ownership of the process of delivering customer feedback in a very interesting and different way. And that business for us was very similar to the survey business that you know, and we could do that kind of work, but we didn't have the software or the platforms to kind of put that on an easier plate for clients to serve up.

But once we've got AI coming into the fold and we see how quickly, you know, things like Claude have evolved to enable teams to do a lot more and you marry that with the smart people that we have in this organization, the builders that we already had and that we, you know, had joined the organization in the last couple of years. All of a sudden we're looking at this going, hmm, this is something that it's, you know, it's work, but we can build the chassis that we need to be able to put fence around information in an interesting way and then build interfaces. We already know what our clients and their stakeholders in marketing and operations like we know the use cases, we know what they're trying to accomplish.

The business questions and the business challenges are fundamentally still marketing challenges and CX challenges. It's a matter of bringing in that ability to look at, you know, what a brand, a marketer might need and what information you build those structures around and how to serve it up and for what use cases or decision cases, if you want to think about it that way, we need to be pointing those things to. And we've always done a great job of building custom solutions for clients.

So in a way, the list of pieces, how things are built and that changes as technology evolves, by the way, we have a hard time keeping up with all the releases. You know, you've got to figure out, well, how do you bring that in? Oh, that's easier now. We can do that. Let's bring it into the process. But we're still, we're trying to get better at having a consistent way of building these fences around data and then being able to customize the interface or the use case for which we're still pumping great human insight into those systems that we know very well how to produce.

And we stand by the quality of those inputs in a way that very few people can. So it's a good, it's a good confluence or, you know, it's a point of convergence around some things that we've done historically well. And then technology now enabling us to be able to do that last mile of serving it up in a way that stakeholders might be more amenable to using it. It's early days, by the way. You know, I think clients are starting to understand what's possible because this can be a competitive advantage. If you have the right data, if you build the right system, if you listen to what stakeholders need and how they're going to use it, you have a good, a good path towards having more impact as an insights professional in an organization today than maybe in the past. But it's different. We're still seeing clients going, Ooh, how do I do that?

[Lenny] Yeah. Yeah. Well, that's also, so you being so open in this conversation is also indicative of a track record of the company, right? You have the Burke Institute and you've, you know, training, et cetera, et cetera. And so it's, it's cool that you're, you, you've always distilled your knowledge and learnings out into the industry and try to help others. The, so how do you balance between that competitive advantage of like, all right, we're not going to give away all the ingredients to the secret sauce, but a rising tide floats all boats.

And, you know, you, you want to empower the, the industry and, and share that you just launched an AI training component that's on top of your qualitative component that you've always done for, for years. How do you, how do you find that balance between, all right, we, we'll work on best practices, but we're not going to give away everything.

[Thania] Well, that's, that's always a, that's been our MO from, you know, the institute is what 50 years old in 1975. We've trained a lot of people on, on how to do good research and write great questionnaires and, and advanced analytics. Like we've, we've shared and shared because yes, rising tide raises all boats, but you know, people are like, why would I then, you know, if you're teaching me how to do it, why would I need you? Well, because what is required to do things well is hard. And, you know, there’s effort behind this. We are very confident in the IP that we bring to the, to the thinking is there's a Burke way, you know, and, there’s a lot that goes into building something with quality.

Anybody can build one of these systems, by the way, you could probably code it if you really knew what you were doing with Claude and, you know, get something set up. That orchestration layer is tricky, very tricky to get that the governance and the orchestration book, but like the orchestration and that's where we think we bring value. And yeah, we can, we can tell you, but you know, building it as a different, a different story. And I do think that there's some secret sauce in there that even if I told you how to mix it, you probably might not be able to get it just quite right.

Right. And it will take you a while. So that's where we go. You know, we, we still have a very unique value proposition for clients. And there's trust that we, that we have earned through our years of doing what we're doing that we've done with the, the rigor and the validation. And like we, there's trust in what we bring to the marketplace because we still observe that level of care with everything that we do. Certainly there's experimentation and we've got Burke labs and we can, you know, go wild and crazy there. We're learning a lot through that process about, you know, where AI is really helpful and where it just needs more time. And so clients know that we're doing those things. And so there's a trust factor too, that maybe you won't have if you do it with another vendor or if you do it yourself, which is also, you know, something that clients are oftentimes tempted to do.

[Lenny] Yeah. Well, let's talk about that because I think increasingly trust is currency and potentially even a moat to an extent, right? It is difficult to earn. Once you have it, it becomes something you want to continue to maintain and it compounds over time and during periods of uncertainty, and I think we just kind of live in the era of uncertainty now, right? In so many ways. And particularly with the technological change and you said something earlier that really struck me, the, the client's not looking to understand all the ins and outs of research necessarily. They want to understand, is this the right answer to the decision that is going to move the needle for the business? That's the bottom line.

They may get more involved in that process is, you know, depending upon how their, their business is set up, but for the most part, it's not their job to be good researchers. It's their job to discern what is good research. So when you're trading on that trust that, you know, we know that if we do this with, with Burke, they have thought through this, they, you know, they, they train everybody else. They, we know it's going to be high quality. The, are you finding that as a secret weapon now more than in the past? Are you finding their, the clients really do want to talk even more than they normally do and are leaning into the relationship and the trust aspect of the relationship rather than just the kind of vendor supplier aspect of the relationship? Is that happening in your conversations?

[Thania] That's an interesting question, Lenny, because I, I do think that, you know, the way that we build client relationships when we're brought in as partners, I've got to remember now, our longest standing client relationship right now is 34 years.

[Lenny] Wow.

[Thania] So, you know, that's what comes with being a longstanding firm at the industry. But we have lots of clients that appreciate what we do and we build very strong relationships. And, you know, that's been something that we've been very fortunate to, we don't take for granted. And if there's, if there's one thing, and I know there's many more, but if there's one thing that I put at the top of the list that we do particularly well is connect with our clients and make sure that we're serving them in the best way and that we're delivering good, whatever they need and they keep coming back and we learn more about their business and we become more valuable. So that's always been the way that we've operated. And in this moment, those relationships that are already existing benefit from that dialogue.

And, you know, we have clients who are wanting to experiment with us because they know that while we don't have all of the answers, because honestly, Lenny, I'm not going to sit here and tell you, I know everything about how to use AI and how to do everything that clients need. We're living in a moment where we're learning as we go. But even being able to open that dialogue in that way with a client to say, there's a lot of unknowns. Here's what we do know. Here's what we don't know. And that level of transparency continues to engender the trust. So it's a self-fulfilling prophecy. Like you start with trust and you build it over time. So we don't take that for granted.

And I feel like listening to clients, delivering a solution that is going to help, especially what they're asking for, as opposed to here's something off the shelf and it's going to work for you at the same time, every time. That's not how we operate. So, yes, we do feel like people are looking for more information than they have in the past to just understand what do we know and compare it to what they know and what they heard from others. Because people are trying to sort through a lot right now. And clients don't honestly have time to test everything. And so, yeah, they're more likely to say, you know what, I trust you. This is what it will do. And even within Burke Institute context, we have this great AI seminar that's being taught by some of our brightest people on those topics. And they're coming into it with, you know, this is what we know.

Let's have a conversation about what you hear, what you've tried, because we're all learning together. And that's a different proposition than saying this is the right way to write a questionnaire and this is the right way to do it. It's a little bit different tenor, but it engenders trust because we're not trying to force knowledge on people when, you know, that's knowledge that is more fluid than it ever has been. So I'm not sure if I answered your question. We've always aimed for that trust factor. We've built stronger relationships on the basis of that. And we continue to see the benefit of that in a time when things are just not clear. And I don't think they ever will be. I look back on the simple days. When we went online, that feels so simple now compared to what we're going through now. We figured that out and then we just stayed steady for a bit before the next shakeup.

[Lenny] Yeah, yes. Right there with you. I mean, I think that the direction of travel is relatively clear. But boy, what the road ahead looks like. You know, there's no great signs that tell us, you know, is it a straight path? I think it's going to be really curvy. We'll push that analogy. But that leads to the next question. What do you think is next? What are you, well, let me, I'll give you a double barrel question. Sorry, I never went through Burke training. What are the biggest areas of uncertainty you are hearing from clients that they're looking for answers on? So that would be question one. And secondly, what do you think those are as you're planning within the organization, right?

Okay, two years out or hell, maybe two months at this point. I'm not sure what you think in months or in years anymore. It's more like months. What do you think is coming that you're beginning to say, we have to be prepared for this shift because that is going to recur whether our clients are paying attention to that or not, just for our business?

[Thania] Yeah, well, I think right now what's interesting is how many clients and, you know, being told, you need to go use that AI thing. You go use AI, go leverage AI. You're supposed to be more efficient with AI. Go figure that out. And so sometimes there's more specifics, but a lot of times it's not. And we just talked to 40 clients in New York City, people we know, people we don't know yet about this very topic of, you know, how do you take advantage of AI and technology today to serve the organization in the way that we were talking about? Like, how do you create a competitive advantage? People are starting to get past this idea that AI is going to take their job because, you know, there's that fear too, that you can get a lot of answers and, you know, good answers to questions. But the point is, is it distinctive?

Does it create a competitive advantage from you or is your competitor getting the same information that you're getting? So being able to build those competitive advantages, those data modes, I think that's where we're going to get to in stronger force. If I had to put my bet in one area where clients are going to say, you know what? We have data. We have a lot of data and it's everywhere. And it's a dumpster fire for most organizations, honestly. And, you know, you met Eli Moore. He's our VP of data strategy. He says to me all the time, he's like, people have had this problem for a long time where you have data here and data here and bad data, good data, all data.

And nobody knows, you know, if somebody goes on vacation, you don't get that number. You know, like there's been that dynamic for a long time. And we could have solved that a while back because we know and, you know, this is not new. Integrating data in ways can amplify its impact for a decision. We used to do linkage models, you know, back in the early 2000s and the 90s where it's just like, if this, then that, and how do these dynamics relate? So nothing new, but like data was hard to get into one place. And it continues. Now AI comes in and people are starting to realize that if they don't have their data in order, they don't have good data, and if they don't have the right data, more importantly, it's not going to happen. You know, you're going to miss the boat on being able to impact the organization. And maybe your competitor’s building that, you know, you've seen a lot of companies out there talking about bringing in, you know, AI transformation experts in the organization that are essentially doing that.

It's like, where's your data? What data do you have connected? So I feel like we have, where I see things going in the little future that we can see, because who knows what's after that? Some of the focus will turn to, are we able to build capability for insights in a different way? And forget about having 15 platforms on your, you know, on your laptop, you know, one for this, one for that, and then you have to jump around. Like, how do you integrate that into your workflows more easily? And some companies are doing that already. So I think that's where we're going to spend a little bit of time. But beyond that, it still is about moving the business and answering questions and having perspectives for marketers and for people who are in charge of customer experience and innovation, and still being able to wield that capability to have its highest impact. And I believe that's where the consultation role is going to be more important than ever. We're going to have all the information that we need and hopefully served up well. But we'll see, you know, there's always early entrance to this space. I recently read an article from MIT Sloan that somebody shared internally about how some of these companies, like, I think they talked about Pepsi and P&G, and we know others who've been on podiums at Quirks recently, Microsoft, like they're building systems, TikTok, they're building systems like this. Those are the ones ahead of the curve. They have a lot of resources, right? They can surround the problem and build these solutions, sometimes on their own, or with help from certain vendors. But there's going to be a lot of other companies where that's going to be what they want.

And so how do we help everyone else? And there's a lot of people who are going to be drawn to this type of work, in my opinion. And guess what? It needs to be fed with good human insight, because at the end of the day, the system is great, but you’ve got to keep it fed. So what is the work that we need to do to, like, what's the work that provides a perspective to organizations that they don't get anywhere else, that they don't have a business data, a secondary source, or something? It's the observational stuff of how people behave. What do they do? Why do they do it? It goes back to the foundations. And maybe we don't ask that many ancillary questions, but we focus on, I think there's going to be a lot of qual in our future, honestly. Just understanding people and their nuances. You know, Kendall Nash, maybe? She's one of our Burke account executives.

She, well, was it Kendall Nash? I think it was, I'm going to misattribute this. It was maybe Tara Wiley, another great person within Burke. But she basically said, people are weird. And because people are weird, we have jobs. That's what it comes down to. So it's how do you capture that essence of human behavior that businesses need to understand to be able to serve those needs? I don't care how much technology you have and how much data is created to try and explain those things. Sometimes it's just about observing and asking a simple question. And if we can continue to do that well, then we can feed systems with valuable inputs that help whatever decisions need to be made.

[Lenny] I agree. And it's interesting. You know, there's been a decided change in the broader conversation about the value of data at, you know, like the big tech level, right? There's some shift happened roughly in the last month or so. You saw that Palantir was kind of leading that conversation about, you know, wait, no, this is your alpha, right? Clients, this is your data. You need to find the value out of it. And everybody else flocked in and, you know, it was just a real sea of change from where things seem to be heading. And I'm grateful for it because it's reframed the conversation, right? I personally think we've already gotten to the point where AI is a commodity, is a tool, the solution set, the models, you know, how much smarter can they get? You know, I don't know. It's incremental at this point.

And from a business model standpoint, it's just about how do you leverage the information to create competitive advantage within the organization? How do you define that competitive advantage? And the big tech guys are now recognizing that, right? That the conversation has changed that, you know, look, our job is to ensure the infrastructure is there for the compute power and all that good stuff that it'll work. And we'll, we'll do that. And at the same time, then they have these forward deployed engineers that they've all invested in and rolled out billions of dollars of people, consultants to say, what's your business issue? Let's figure out how to deploy the tool to address the business issue. And those are, that's very general. I've not gotten a hint yet that there is, that there were insights for deployed engineers being put out by, maybe there are, but.

The point is the trend line seems to be aligned for what you're talking about, right? That we're getting to the place now where, okay, we can solve these connectivity issues from a, uh, with technology. We can bring the data together and we can do that in a way that is scalable and, uh, and, uh, efficient and capital efficient and can address the needs of the business. But you start to conceptualize what's the problem that we're trying to solve. And then what the hell does it mean when we get an answer? What do we do with it? Uh, so I, I think you're in a sweet spot personally. I think the industry is in a sweet spot overall. Uh, as long as we realize that we are, we don't own the means of production anymore. So we are, we are a spoke going into a hub, uh, a vital and important one, probably the most important because said people are weird and, uh, predicting can, you know, somebody predict behavior on, you know, brands that you shop at. Sure. Absolutely. So, but are they going to predict the emotional drivers of, uh, you know, brand affinity, et cetera, et cetera. Well, I think that's, I don't think we're there yet.

[Thania] There's a couple of things that your commentary brings to mind. One is, you know, I think we're going to see, maybe an uptick in interest in behavioral economics again, because the counterbalance, um, to, to all the tech and it brings the human imperfections to the forefront that we need to understand because humans are just not predictable in the ways that we would like them to be. They don't fall into neat categories. And they don't love it.

[Lenny] Predictably irrational. It was, I think that Dan Ariely.

[Thania] That was a fun era. And, and, you know, I had fun talking to Will Leach the other day. He's always a great conversation about these topics. He's so passionate about it. And it just, it's, it's the counterbalance to, to all the tech and all the, the data that's available is you gotta know you human and you're human has, has these tendencies. So that's one thing that I foresee, uh, qualitative behavioral economics and behavioral science. Like those disciplines will see a higher interest, hopefully. The other thing that might get in the way of our, all our plans has been it's the, it's the, it's the security data security and privacy and how, to what extent do we believe that governments are going to want to control, um, some of the component pieces of this that are critical for its success? I can't predict that. I mean, can you imagine a world where all of a sudden governments say, no, you can't do this.

You can't do that. You can't do that. And so all of a sudden your AI value adds go stripped down to bare bones. I mean, we're back to what is now going to feel like the stone age.

[Lenny] Well, EU just did this week, you know, the, their, uh, the AI act. I mean, you have to prove provenance. That is a huge gap. So actually, uh, we could have another whole the conversation about that.

[Thania] The, uh, it's a, it's a whole thing. Provenance. Where's your data coming from?

[Lenny] Where's it coming from? Is it permissioned? Is it.

[Thania] Yes, it’s a whole can of worms that's starting to spill out. And we're going to have to spend time and have resources to manage that part of it. Cause that's back to confidence. If you don't have your ducks in a row on those fronts, uh, clients are gonna, somebody within a client organization is going to have an issue. And we see that constantly when we deal with data, but like with these systems, I think it's how you build them back to, well, I can just find code that it's like, okay, you tell your IT, your security and compliance groups. That's what you did and see how, how much they love you.

[Lenny] That's right. And you know, let's talk to compliance, et cetera, et cetera. I, that is a fantastic point. I actually, uh, wrote about this, this issue today. Um, and you're out there, but anyway, point is it. Good, good point. As much as we think about all these are, this is a superpower and it is. But it's not fully baked yet. And there are issues that we're going to have to deal with. And that is a fundamental one. Um, and for a global company, P&G, right. To pick on your hometown heroes there. Um, yeah, I mean, they may be able to get by with it in the US but there's 24 states that are building legislation that is comparable. So, right. They have to be compliance in the States, let alone if they're going to go into Europe.

No. And Europe loves to fine people, right. I mean, it's a revenue stream for the EU to do this. So, uh, yeah, we're going to have to deal with it.

[Thania] Yeah. I think there's going to be a lot of in companies, obviously, especially in certain fields, if you think about financial services and healthcare and pharma, um, with high sensitivity, uh, you know, PII, um, leaks in those, in those areas or, or anything that even smells of a breach of trust and security violations, it's gonna, it's going to have an impact. You're going to have lawsuits. I know that the EU has started to quantify like how many dollars in lawsuits are starting to emerge. And if you're going into law school right now, you know, that's one field where, uh, um.

[Lenny] That’s one practice area.

[Thania] But you have, you know, if you have auditable systems and good, good guidelines for building, maybe that that's, you know, that's the best that we can do transparency, which is hard. You know, you think about these large language models and all they're able to do. And to some extent they're black boxes to a large extent they are. So it’s a, it's never a dull moment. Just when I thought, you know, that we were, we'd seen all the change in technology that was going to affect me in my tenure in this space, you know, we get served this amazing, uh, jolt of, of, so.

[Lenny] You know, I just kind of thought that hadn't even this whole big debate on the, you know, open versus closed models, you know, the open weight versus closed weight, right. You know, Anthropic and Open AI versus, you know, the Chinese models, but it just occurred to me, I never thought about this before. Let me know what you think. The difference of the, uh, between open weight and closed weight is your ability to get in under the hood and track the inputs. So this, this may, the earlier comment about the, the LLMs being commoditized, this could be a whole other dimension of that. That is either going to force a significant change in the, the category leaders of, of Open AI and Anthropic, or it may just be all the, you know, the, the newer models that are coming in, they just may win simply on the compliance issue. You can get under the hood and, uh, and track that provenance. That's, and I thought about that to write this, but that is an interesting place.

[Thania] It might have value and, and, and, and people might pay a premium for services that they know have that type of, uh, governance associated with them because it just,  it is scary if you think about, you know, making a decision for a multi-billion dollar decision for a business is always a scary proposition. There's risk associated with that. And you're making these bets on information, hopefully not just, you have good advisors, hopefully, but, um, it's not just the loudest person in the room driving the decision. You're actually, and this is what we do. We want to give you information. We want to make sure that we can reduce the risk of you making a choice. That's been our job with insights always. Um, and then you make that choice and it goes South. You know, you obviously as a company are going to be not really happy and want to understand where the breakdown happened.

And so I don't know that I blame businesses for being, um, a little bit cautious in some cases to the point of like, we shall not use that until we feel comfortable with it. We still have people in that bucket, believe it or not. The AI train is going fast, but some people have chosen to just take a little bit of a pause moment. Maybe, maybe their, uh, caution and it's going to pay off in some meaningful way. Nobody has, I don't know if you, maybe there is, or there isn't a story where something has gone off the rails so badly that it's given everybody pause. But like, I do think that we have to be careful.

[Lenny] Yep. Absolutely. Well, I always refer back to new Coke right now dating. But I think that's just the best example I could ever think of of, yeah, y'all really screwed up with the, uh, so yeah, interesting, interesting stuff. Tanya, we're coming up near the top of the hour. I want to be conscious of your time as well as the listeners. Is there anything that you wanted to make sure that we touched on that we have not touched on?

[Thania] Oh, Lenny, this has been wonderful. And we probably could go for, you know, longer if, if we wanted to. But we're just up to us, right? I don't know that there's anything specific other than, you know, I do think there's an, there's an encouragement that we, we need to lift as an industry, each other up in terms of sharing what we're learning. And, and I don't know, I know that there's, there's goals in associations like the insights association and facilitating that. I know that Greenbook has a wonderful resource library to share information and, and you do a great job of keeping the industry up to date.

I think we need to do a lot of that. You know, conferences are still places where you go learn, but I don't, I would love to see more forums of discussion, you know, and debate because we don't ever get into those in an open way and maybe in small pockets, but it's important that we share right now. And that's one thing that the Institute allows us to do a lot of is bring people to a conversation that we can, you know, impart learning, yes, but also learn something back.

And that sharing is going to be very important because it's, it's a rising tide mentality. We, we have to move and yes, we have to take care for the viability of our organizations, but there's always an element of common understanding that helps all of us. So finding more of those places and seeking them out, I highly encourage anybody listening, like go inform yourself, go look at your blogs and your excellent articles and things that are being written out there, plentiful on LinkedIn, pay attention to what's happening because some people have chosen to just sit back and go, well, I'll figure it out. It's like, engage. We all benefit from that. That's my only ask if there is one of people who have, who are in positions to bring value into the conversation.

[Lenny] Yep. I could not, could not agree more. And you know what, if you think that's overwhelming, you can use AI to set up an agent that can curate and bring that information and make it more comfortable. I do too. I mean, how the hell do you think I keep up with everything going on?

[Thania] Like full-time job even with that. So yeah, it's, I think it's exciting. Change makes me energized. There's always a better way to do something. And so we always seek optimization in life and this is not an exception. So let's keep going on that, on that path.

[Lenny] There you go. Well, on those words of wisdom, there was nothing else to add because that just kind of brings it all, all together. So thank you, Thania, for your time. Where can people find you?

[Thania] Well, I have a LinkedIn profile that I'm actively posting some things here and there and you know burke.com has always been a great resource for anybody wanting to know what the latest and greatest is. So there's that. Do you want me to share my email address? I’m happy to.

[Lenny] That's up to you. That's up to you.

[Thania] Start with LinkedIn. I think that's a great place to connect. I'm happy to have a conversation with anybody who reaches out and just has curiosity for what we're doing. I'm sure that there's stories to swap with lots of people out there. So that's probably the best place to go.

[Lenny] Okay, great. All right. Thank you so much for your time. Thank you to our listeners. Thank you to Emma, who is our producer and keeps all the balls turning, all the wheels spinning. I think I mixed my analogies there. Thanks to our sponsors and to everybody else who helps to make this happen. And that's it for this edition of the Greenbook podcast.