Smarter AI Playbook with Brendan Witcher | Building AI Boston

At the heart of an industrial revolution is an innovation that changes everything. Building AI Boston sees artificial intelligence as a renaissance. From the heart of innovation and the mecha of tech learning, we bring you AI for real people to a conversation for everyone. Our guest today is Brendan Witcher. Brendan is a trusted strategic advisor to well over half of US Fortune 100 companies, including eight of the top 10 that sit at the forefront of driving innovation and digital transformation. He is globally recognized as a leading authority on consumer behavior, market developments, technology trends, and solution providers in the digital engagement space. And today we discuss where AI fits into his philosophy for businesses of any size. Welcome to the show, Brendan. Well, thank you for having me. I'm really happy to be here. Thank you. And you know, your insights are sought out by Bloomberg Time Magazine, the Wall Street Journal. So we're really honored that you're with us. And you just rolled off of an important keynote. Can you tell me what you were up to? Is recently is this week? Yeah, yeah. I just got done with the event here in Boston, the E-tail conference. They have a couple of them around the country, but E-tail East is the official title of it, I believe. And yeah, I just did the keynote there. It was a wonderful session. We talked a lot about the drivers of unstructured inputs into AI and how that's changing the capabilities of organizations today to better win, serve, and retain customers. So it was a lot of fun. Got a lot of great feedback from the session. Of course, it was a four day event. So, you know, throughout the event after that keynote, I had lots of opportunities to have conversation with folks about what they're doing and what they're working on. So pretty interesting things going on. Not all, you know, not everything is clear path yet. We're certainly in a test and learn phase for a lot of organizations, but it's exciting. It's an exciting time. Well, it's exciting that you're right there in the midst of that ecosystem. As Cara knows, Cara's got her feet on the ground in Boston and it's a super exciting ecosystem when it comes to AI. I would also say though, it's kind of at the heart of the fever dream, the intensity behind what's happening because you sit right there in the, you know, the commerce sector, which is what I think most people fear the most is. I'm going to miss out on something. I'm a small business. Where do I stand as a human being? So you, my friend, are a very important part of that conversation with your past and your history. And trust me right now, we are not going to ask you to look into a crystal ball. We know that's not part of your philosophy. And I really want to start a little bit back and like give us some of your past. You really have an interesting work history that informs your philosophy. A lot of people running around trying to future fit their companies, but you have some important strategy that we're going to break down. Take us into your past and maybe answer some of that as it relates to AI. Yeah, absolutely. So as an, you know, for those of you that don't maybe know what an industry analyst is, you know, a lot of people don't, you know, my job is to basically think all day. That's really what it is. Right. I get paid to use my brain to think about what's going on, what's happening, look at the trends that are happening and what does it mean for organizations today. You know, when you say the word commerce, a lot of people I think might immediately go to the e-commerce idea, but it's really about consumers buying things. It can be online offline, you know, through apps, through call centers, you know, wherever. And it's not just products, it's services as well. It's anything we're willing to pay money for. Now, I don't really look too much at B to B because it's not my background. I do know a little bit about what's going on there because a lot of times B to B or B to C will influence the other. But B to C is my primary focus. I do look at international B to C as well. But U.S. is where all the fun stuff is really happening. If you take China and Alibaba out of it because they're pretty cool. But, you know, other than that, really it's the U.S. is where a lot of this sits and Boston to your point earlier is where a lot of this stuff is being developed and being worked on. And so there's some pretty exciting startups here in the area and some long time players in AI. But that's, you know, that's what I currently do is I help organizations understand how technologies are going to affect their ability to win, serve and retain customers. I'm not really looking at the features and functionalities of every single technology out there. And, you know, if somebody were to ask me like, tell me about APIs, they'd be like, I don't even know what that stands for. Right? Like it's not really my thing. Right? I'm not a technologist. I'm a strategist. So I care about how AI is going to actually change your business. I don't care about how you're going to hook it up to the hamster wheel to make your business go. So that's that's kind of where I look at you mentioned my background before what I do now. You know, of course I've worked in retail. I sat in the seat. It's nice to be able to come from a practitioner background because I kind of know the pain points of the real world that people live in. I know like not everything can be rainbows and unicorns. And sometimes you have to like deal with the politics and the cultural barriers of your organization and the, you know, all the sorts of things. And I have out in different areas. So I was in strategy over guitar center. I was in marketing and merchandising and area and David. You know, before that, I was a restaurant tour. So I know a little bit about the service industry too. So, you know, so I kind of bring that all together to have my view and philosophy about what is actually going to move the needle for organizations. You know, I'm going to stop talking here in a second, but the reality is a set, you know, a lot of people talk about AI and it's all good. It's all fun. But it's really hard sometimes to differentiate like, well, what's going to what makes a difference and what's just interesting, right. And that's in the work that I do with organizations. What I'm trying to help them focus on is, but what's going to move the needle for you? Now let's take it out of AI for just a second, right. If I ask consumers, like, you care about sustainability, like 90, 96% of people are going to say yes to that, you know, question. Obviously. But if I asked them, well, once the last time you checked a sustainability page before you made a purchase, it's like, you know, half a percent, you know, it's closer to zero, right. And so like I care about that. I care about like what what do consumers do because of their values and beliefs and what really drives their behavior. So when it comes to AI, I'm always looking at, you know, what's what's interesting or going to make headlines in the Wall Street Journal or CNBC versus what's actually going to make the consumer go, you know what, I think I'm going to buy from this company this time. I'm going to I'm going to move my purchases over here because this experience works for me. And when you were talking about so what we were talking about, detail and your key note. So when you say unstructured inputs, right. Tell the audience what that means because that's one of the things we like to do to is kind of break it down like, you know, we don't assume everyone knows the tech like you don't know what API means. So tell us what I know you do. What does that what does structure? I love that you are like thinking that I do, but I really don't like the great matter can only hold so much. There's so much work in strategy. But somebody knows it. And that's what matters. So what what do you mean by like unstructured inputs and how does that really to kind of like e commerce or like the commerce universe. What does that mean? Yeah, so so the reality is is that you know unstructured data. AI was built for unstructured data. I think what most people don't realize is that structured data and unstructured data are two different things structure data. We've been and I'll get to the definitions in a minute. So the data is more about machine learning, you know, I used to be an old sequel programmer and do all the, you know, database stuff and things like that. So think about like the product you last purchased the skew number of that product or the day of the week that you bought it or the price that you paid or the page that you bought it on. The kind of shipping that you used, you know, all sorts of things. So you tell because most people understand buying and retail for thing. You know, all of those things are structured. They go into your database in a very specific way. Right. In your database, it's not going to say, you know, it'll have the data purchase as an example. It'll say, oh, nine, oh, seven, twenty twenty five, right as an example. That data is very structured. It's two, two, and then four digits, right. And it has a very sort of format to it that that technologies can read really easily because it's always the same format, right. Sort of thing. If I buy, you know, Nike Panda dunks. Every customer that buys Nike Panda dunks are buying Nike Panda dunks. It is a, it is a structured piece of information, right that has no variance to it. And it's a very different thing, right. In the database and the taxonomy of that organization. Those Panda dunks are named a certain way and they have a certain skew number and every purchase ties to that name and skew number. So you can actually run a report as an example of saying how many people bought this and would go in and look at that and say, what did I do now. Now, unstructured data is a little different. Imagine if your database didn't have those those elements pulled into the database. And then you have a lot of data that you have. You have a lot of data that you have. And then you have a lot of data that you have. And then you have a lot of data that you have. And then you have a lot of data that you have. And then you have a lot of data that you have. And then you have a lot of data that you have. And then you have a lot of data that you have. And then you have a lot of data that you have. And then you have a lot of data that you have. And then you have a lot of data that you have. And then you have a lot of data that you have. And you have a lot of data that you have. And you have a lot of data that you have. And you have a lot of data. And you have a lot of data. and a product that structured data can say, okay, I know this customer who's also in the database, right? A name, first name, last name, those are structured elements. They're not gonna contain numbers typically, right? They're gonna be all alpha characters. In unstructured world, we're dealing with things like photos or natural language processing or even biometrics or weather or whatever. These sorts of things are very unstructured. They don't go into a database in a very certain way. So this gets back to our point earlier, right? Which is machine learning does fine with structured data. It says great with structured data. In fact, it's very good at it. I mean, remember the whole big data era, you know, and then we moved to small data, right? But the whole big data thing was all about like using machine learning to do that. AI is really about, if you'll notice, that prompts are in a natural language that is unstructured data. That's what you actually, PT is an example, right? If you go put something in, you're not saying, you're not key word jockeying that. The way that you do on a Google thing, right? You're saying, I really wanna see blah, blah, blah, blah. I wanna know about, you know, blah, blah, blah. Do it in this tone and tenor, you know, make it sound like Ryan Reynolds is saying this and blah, blah, blah. All that kind of stuff, it needs to kind of assess the words make it sound like Ryan Reynolds. All those words together mean something, right? It means separate things, right? And so AI was really, I'll say it again, AI was built for this era. It was absolutely built for this era. And I think what people don't realize is that we've had structured and unstructured data for a really long time. I mean, it's all been coming into the system. But my good friend who passed away unfortunately, Mark Hurd, who was the CEO of Oracle, you know, I was in a conference with him in about 2014, 2015. And he was on stage in front of a big audience and he said, you know, we have all this data and most of it's useless. And he was talking about unstructured data. And later I had, you know, dinner with him and we were talking about it. And I said, you know, I didn't wanna correct you in front of anybody, but I disagree with you, right? I don't think it's useless. We just don't know how to use it yet or we don't have the tools to use it yet. And now we do the era to be able to use that. Yeah, it's interesting that a lot of our perception of AI is kind of invisible. I mean, even when you go to order a pizza, you don't really understand that app of it is a person in half of it is AI and maybe AI is eclipsing that experience. But, you know, it's just part of the fabric and we're just becoming aware of it. I always tell people, you know, if you're freaking out about things, remember you're a big part of the voting scheme and where you put your dollar is how you vote, friends. Like this is still, consumers are still driving in the conversation, would you agree with that? Or is that part of... Yeah, but I think most people don't realize how much they want AI. Like, let's take your pizza analogy, great setup for me, by the way. Let's take your pizza analogy. I'm from Chicago, so, you know, I love pizza, but this has nothing to describe. Deep dish. Deep dish all the way, baby. We are just all the way. All the way. All the way. But dominoes in Australia, as an example, was using computer vision, right, with a camera that went over the top of a pizza to make sure that the ingredients were spread out properly when the person was making it, right, as an example. Now, you may say, well, okay, that's a cool use of AI. No one's really scared of that kind of AI, right? Like, we want our pizzas, I don't want pepper, I don't want a big bunch of pepperoni over here and a bunch of sausage over here, like, you know, and like my green peppers to be like all bunched up, you know, places. I want them to be spread out. I want it to be balanced, right? And so they were using computer vision to get the person would put the pizza under there and the AI would say, okay, it's a nice balanced pizza, right? It's got the right amount of ingredients, it's got the right balance, you know, we're building a consistency, because that's what consumers want, right? There's a reason that Starbucks and McDonald's are as big as they are, because we want consistency. Right. So dominoes knew that they have thousands and thousands of employees making pizzas. How do we create consistency? The use of AI is a great way to do that. Comparatively, if you don't mind me saying, like, this is why when people talk about AI, they talk a lot of times about, they're scared of it, they're not going to use it, they don't want to use it. I say to them, you know, are you the same person that was complaining about everybody uses their mobile devices? Nobody socializes anymore and blah, blah, blah. Oh, by the way, hold on, I need to check in on my airplane on my mobile device and have my QR code so I can get on my airplane. It's like, you know, when we talk about technology, yes, there's good sides to it and there's bad sides to it. I don't think that I think what we can't do is to lump them all together and just either throw them away or adopt them. I think what he is for people to realize that AI is going to help them in business, it's going to help them in their personal lives, it's going to be able to help them in the way they manufacture or manage their careers, right? That's sort of thing. But of course, there's other sides to those things. So I just think we need to separate the conversation a little more often. Mm, and I've heard you even used the analogy if you've ever visited, you know, Amazon as a site, you know, what would it be like if it didn't collect your cookies? Imagine the head banging you'd go through when now it's very intuitive. I'm just citing that one as a, for instance, I've heard that from you, so I still let from your analogies. Yeah, exactly. I mean, you know, here's what I would encourage you all to do. If you don't think you like companies understanding you or using AA to get you, here's what I would encourage you to do. Go to your web browser, clear all your cookies, clear your browser history, close out your computer, go back online and start shopping. And the last time I did that, the first product that recommended me was a pair of Daisy Duke shorts. Like if you remember back in the day, you got that look like. Oh, God. And if you can, you just, just from this headshot, you know that's not an appropriate run for me. So, I love it. Love it. Absolutely not. So it is getting hotter. This is what I mean. We say we don't want things, but then we do want them when we experience the other side of it, right? You know, how many of you would continue flying with an airline that said, you know what, we're so old school and classic, we were going to get back to the good old days, paper tickets for all, right? Sort of thing. How many of you would continue flying with that airline? Maybe what, 5%? You know, that's it. So we have to be careful about like raising the red flag and creating all this fun and like this whole like, you know, it's all wrong, you know, sort of thing. What in fact, we're probably going to demand it, use it and demand it going forward. Even at the most basic level. Yeah. Well, I think a lot of people rightly so are concerned about job losses, at least, AI and that's a huge concern. Do you see this disruption is good news for the entrepreneur and small business owner? And if so, what should they be focusing on? I think it is, it's, I'm going to be very industry analyst with my question here. I'm sorry about that. There's no one waiting answer that. So I'm going to kind of like part, I'm going to, again, like I said, I'm going to parse this a little bit. I think for the entrepreneur business professional who can think outside the box, it's going to be a very good thing. For the industry professional that can't, I think it's going to be a very bad thing. I was just recently, don't tell anyone that knows me that I did this, but I went to McDonald's recently and I try not to do that. I like McDonald's, but you know, I went to McDonald's recently and I ordered on my app, right? Sort of thing. Yeah, I have the app. That's how often I go to McDonald's. I'm just revealing like a terrible. I am. Shame, shame. We're not everything that I was nudging. Walk of shame, right? The walk of shame. No, come on. I love McDonald's. I do work with them. So they're good. So, you know, what's interesting is I was looking at the app recently. I just, I have it on my phone right here. I was just looking at it. There's a, where is that thing? There's a thing that I downloaded where my app code was called voice, voice code. It wasn't, it wasn't like code. It was voice code. And it reminded me that we're probably not too far off until that voice coming out of that speaker is not going to be a person. It's going to be a lot. We're going to use natural language processing to ask the question of are using your app today. And if I say yes, it'll say, you know, what is your code? And I'll say it. And the whole time I won't be interacting with a human being, right? I'll be acting with, I'll be interacting with somebody, somebody who's an automated assistant, sort of thing. You know, because then that allows that person to then go, you know, dunk some fries in the oil or do whatever they do, right? Sort of thing. So this is the kind of things that we're seeing is like, are you the kind of entrepreneur that can think that way? That can be creative about using innovations to end AI to solve the business problems? Or are you going to be so stuck in your ways on, you know, like everything got to be anti-AI so I'm going to not do anything? I'm going to share with you the risk of that because here's, here's to me probably the best advice I could give entrepreneurs today on this topic, which is I am not saying by an extra to the imagination that you should dehumanize very important customer moments. If there are things that you do that you think a personal touch is really, really, really important, do not automate them, right? But there are parts of the customer journey where it doesn't have to be so one on one, right? Calling a good example of this that we saw years ago is right. If I need to find out a store's, you know, business hours, what time are you open? Yeah, I really don't need to talk to an associate and develop a relationship for the answer to that question. I just want, I just want the answer, right? When we look at a customer journey, there's going to be plenty of moments where the customers like, I don't need you to like ask me how my day is going right here. I need to just know the information so I can get my kids to soccer practice and do whatever, right? Those are the moments you want to automate. Don't automate the human moments. Now here's the best part of that. And I tell a small and mid-size, even large companies this all the time is the more you shift those low, those low touch, those low impact moments to automation, you're actually freeing yourself up to do more of the high touch moments, right? Yes, yes. I was just working with a music industry company who the small business owner is only three people in the company. I was just talking to them and we were at a conference, we were chatting and he's like, you know, I really like to call my customers and say, how did you like that last product that I bought? I go, now imagine all the calls you take that you don't need to be taking, how many calls could you make that day if you weren't taking those low impact calls? And you can call instead of three or four people a day, now you can call 20 people a day, right? Like that's how you apply AI, right? You think you're applying the human touch, but you're really applying AI to another part and that's what's allowing you to do it. Starbucks did this with their DeepBroom program, right? Like if you listen to their earnings calls and they were talking about DeepBrew, their main priority was we want to take the mundane stuff out of the associates, you know, workflow so that they can do more focusing on how's your day going, Jeff and Jessica, you know, the same old, you want your usual, right? Um, those sorts of things become really important. So that's, that's how I would say the entrepreneurial world can either benefit or suffer from it. And the young, the younger generations also don't want to talk to people sometimes in some of these, in these, in these early stage like in some ways they prefer just to get that automated quick information and not have to have like a long conversation, right? Is that kind of what you're seeing out there? No. Okay, so we'll cut that. No, no, no, no, no, I like the question. No, no, don't cut it. Leave it, leave it. Okay, okay. Because here's, here's the important thing. Again, I'm giving you, I'm going all strategy, analysty strategy here is kind of straight, right? So here's the thing. You did something very interesting right there that I actually encourage my clients not to do. They do not aggregate the customer as if they are all one person. So you said younger generation wants this. That is an aggregated assumption, meaning all younger generation people want a certain experience. That is absolutely not true, right? If we ask, you know, if I asked a survey question said how many people want video in experience by your answer, you'd probably say 100% of the younger generation wants that. It's actually more like 60% right sort of thing. The key to understanding the consumer is knowing when do they want to talk to somebody? I mean, there's plenty of younger generation people that get frustrated because they can't look at someone on the phone for a very important moment, right? Sort of thing. And one of the challenges we have today is we really can't determine if a person is a younger generation or not when we need to engage them. So even knowing that fact is almost like you can't do anything about it anyway. So maybe you don't focus on that sort of thing. I really do encourage my, you know, the people that I work with to focus on more individualization rather than personalization in the way that you described it, which is to take an assumption or a persona, right? And then apply it blankly to everybody. I think that is a, and I see companies doing it all the time. I don't mean to insult anyone, but it's really a strategically lazy way of approaching a very important topic, which is customer experience. Yeah. It's more important to say, how do we learn if the customer wants to talk to someone at this time and at this moment? Do we give them a path to say, it's like the, let me use an analogy to explain it. If you go to an Amazon ghost or a fresh store that was using the automated checkout, right? Where you just go in, you scan your palm, you go in, you shop and you walk out the door, right? They didn't get rid of cash years. Like there were still, not in the ghost orbit in the fresh store, there were still cash years that if you wanted to work with someone, you could still check out. That's the reason targets still has people that will scan your items for you, right? Yeah. So if you want to have gone basically all in on self checkout, like the stop and shops, right? And them, they're struggling because not all customers want that. That is an assumption to make that people want the same thing. So I would say like it's not about using AI. Here's my strategic advice. Don't use AI to do deliver an experience to everybody just because you make an assumption or some, some, some survey says 70% of people want this in this age group. Use AI instead to understand what does this customer want regardless of their age group, right? That to me would be the most important thing to do. By the way, that earlier stat about 60% of young people want video and experience. After that, it goes down and then goes right back up. You know why? Because people can't read things. They really like video. It's right back at 60% in the older generation, right? And so data, you know, I say this as an industry analyst, be careful with data. You know, it's really easy to assume a story out of data points. And people use them all the time to justify a certain angle they want to go. I've generally found that most data, especially consumer data, can be fairly useless because consumers answer in a certain way. And then they really mean the other thing. And you never can really tell who's who in the customer journey anyway. So it's really hard to use data to create great experiences. It should bring up a really good point. And I think what the deeper thing is that we're also, we have such fear of missing out that we are so fast, fast, fast, fast trying to do. I have to think quicker. And I would say in this like fast food analogy, one thing I've noticed about your philosophy is you would say, no, dial that down. Let's dial that down because there are things. And I'm just going to pull right from what I've heard you say is that don't try to solve problems today that don't really matter. In other words, we don't know where things are going. Maybe robots are going to serve all our food. Maybe they're going to take a road or the drive through. Maybe they're going to make our pieces. But in an effort to just kind of get a grip, there is this moment where we just need to look at data and use it thoughtfully. And that's where I think your strategy is. So one of the most important components of this conversation is how can any business size use strategy in the most thoughtful way without trying to solve where are we going? What does our future look like? Is that basically what you mean by that? Yeah, a little bit. It's pretty close. I would say, I know there are some listeners that are going to hear me say, you need to slow down. And they're going to be like, this person is crazy. I'm never going to listen to him again. I get through that audience. But let me say something first before you hang up the phone on me here, which is when you hear that, you know, fail fast and if you're not failing enough, you're not trying hard enough, that kind of stuff. You know what that's coming from? That's coming from Facebook, Amazon, Walmart, these Bank of America, these huge companies that have the balance sheets of a small country. I mean, they can have a hundred million dollar failure and it's a rounding error on their P&L. I really do not advise small businesses, mid-side businesses to fail fast. You should aim to not fail at all because you really can't afford it. Amazon can have, you know, I'm under like 76 NDAs with Amazon. So I can't talk about what they're working on, but I will say this, like for everything they try, right, they may have like 10 things fail and they can weather that, right, that most organizations cannot weather that. So I would say, now I'm going to say, slow down, apply good strategies. Think about your business. Don't take Facebook strategy and apply to your business. If I can be blunt, you're not Facebook, right? You're not Amazon. I mean, I remember telling this luxury, this huge luxury retailer, everybody knows them. If you were lucky, you probably got something from them. I was telling them, you know, they're like, we want to be like Amazon. I go, you want to be nothing like Amazon, right? Because when people buy from Amazon, they'll say, oh, I'll just get that from Amazon. That just tells you everything you need to know about the relationship with Amazon that they have, which is like, I could care less about this product. I just wanted in my house, you know, that kind of idea, right? This was a luxury retailer that I think, I don't think you can go in and get anything from them for less than like five grand, right? Sort of thing. And they were like, we want to be like Amazon. I'm like, no, you don't, no, absolutely. You want people to say, yeah, I'll just get it from someone so, right? Like, that means they don't care about your product anymore. They're thinking of your product as commoditized and that's the worst thing we can do, right? Sort of thing. And so even at the highest levels of organizations, this way of thinking happens, right? So I encourage you all to not adopt that no matter what company you're in or work for or own or whatever it is. Adopt the strategy of a, who is our customer? And what can we learn? What can we do? What are we capable of that is low enough risk where, you know, if it fails, we can get out of it, right? And it's not going to kill our balance sheet and it's not going to destroy the future of the company. But also that is backed by data and information and good advice and testing. You know, I cannot tell you how many times I see companies just do something. And I was like, that should have been tested. You know, there's a way to test that to get a sense for whether that's going to work before you go put all in on it. And I see too many people in this fail fast mentality, like we're going to skip testing. We're going to skip a pro forma and we're just going to launch, you know, and we're going to make headlines about how we move fast, right? And of course, they never make headlines because now they're on a business. So, like, I think I would say headlines for going bankrupt. Yeah, there you go. That's the headline you want. Then go for it. And Karen goes this well. I mean, Karen is an AI founder and she has a very smart team pushing forward to describe. Shameless plug cars come from some success herself this week. So, Brendan, any final words on, you know, the future where AI stands or small business owner advice, I know I'm kind of great in on that story this today, but, you know, what can someone learn from you? And also, how can they stay connected to what you're doing? Well, I am a serial networker on LinkedIn. So you can absolutely find me there. I love engaging with people on there. I'm constantly liking comments and commenting back and things like that. Nature posting what I see, posting what I like. You know, that's really my output for a lot of what I do. So thank you for letting people, allowing me to let people know how to reach me and to get in touch with me and to learn about that. And if you send me a connection request, I'll probably connect with you. Don't worry about it. It's like, I love connecting with people and learning from them. The other thing I would say is, you know, what I would say is the big takeaway for me is, first of all, let's have this conversation again and go a little deeper on AI. You know, at some point here, because I think there's so much to talk about, we just scratch the surface. I think what the most important advice I can give people is to don't be AI ignorant. Okay. And what I mean by that is you don't have to go get certified in deep AI structures and large language models and blah, blah, blah. But at the very least, you should get some education in yourself about what is AI? How does it work? You know, when people bring up, you know, things like large language models, you kind of understand what they're talking about. You know, subscribe to a lot of newsletters that talk about AI because they often have case studies in there that are interesting and how that might apply to your business sort of thing. But I say that that's what gets you comfortable with the AI conversation. I think what happens is a lot of people think, well, I don't want to, you know, I'm never going to become a programmer. So why do I need to learn about AI? And I think that is a mistake. That would be like 20 years ago, not 20 years ago, back in 2007, 18 years ago, you know, when the iPhone came out, you know, saying, well, I'm never going to program phones. So I'm never going to learn what mobile, you know, how mobile is going to impact my business like that would be foolish, right? And I'm giving you some advice here that it would be foolish to be completely ignorant of AI and understanding what it is and how it's going. You know, hopefully a little bit of the structured unstructured data conversation made you feel a little more comfortable and saying, oh, this isn't that hard to understand. That was pretty easy, actually, right? And all like that quite frankly, it just takes a little time to learn. Yeah. Well, Cara, don't you feel apart too coming? I really appreciate you telling us, goping that, Brendan, and we'd be happy to have you back to break it down deeper. It's a pleasure to talk to you, friend, and we know you're part of many good things. It's such a great turn that you come and shared with us today. Some of what's on the front here. So please come back. Yeah, absolutely. And thank you. Thank you. Thank you. Thank you. We will post in the notes how what exciting things we can share about Brendan in his future, what it how it could involve you. But he is not lying, man, go check him out on LinkedIn. He will friend you and you'll feel more connected than you've ever felt on a, I have to say, on a LinkedIn connection. Big return on investment. Yeah. All right. Well, stay tuned for part two, like and subscribe and thanks again. We'll see you soon. Thank you for joining us on Building AI Boston. Stay tuned for more enlightening episodes that put you at the forefront of the conversations, shaping our future.