Speaker 1: (01:11)
Welcome to Customer Transformation Live. Buckle up as we tap into transformative conversations, real world case studies and innovative solutions that are shaping the future of customer engagement. Your journey to customer transformation starts now.
Speaker 2: (01:39)
I love your intro music.
Speaker 1: (01:40)
Oh, yes, , we're here. Hello everyone. I'm Chris Hood. I am your host. I'm a digital strategist and author, and we are joined by one of my most favorite people in the entire digital space. Kate, welcome. Would you share a little bit about yourself?
Speaker 2: (01:59)
Hi, thank you so much. And I just wanna make sure my, my connection is stable. The internet is giving me a little warning here. Are you stable? Technology? I'm not stable. I mean, , what a joke. . Um, I'm Kate Bradley, chart and I'm the co-founder and c e o of lately ai. But I have a, a weird background as a rock and roll dj, as I'm sure we'll talk about before. And, uh, marketing agency owner, I was even a line cook. You know, all the fun pty jobs that you can imagine that, you know, seem to be lawless. Those are the things that tracked me. , strangely enough.
Speaker 1: (02:38)
No rules.
Speaker 2: (02:40)
No rules or, or rules at least that are, you know, broken and, and not even made to be, but designed by design. Right.
Speaker 1: (02:48)
I think no rules fits right into the AI space right now. Like, it's crazy. It's the wild, wild west.
Speaker 2: (02:55)
It sure is. Um, it's so fun to be witnessing it from this particular chair because, you know, generative AI was born in 2014, which was also the year that we launched lately, right? So we've been sitting here for a little while, and part of it, not even knowing that we were in the AI space, we didn't even know, I don't know if I mentioned this to you previously, but like, we didn't actually know that we had built AI when we first started, and a mentor kinda came along and said, Hey, let me introduce you to the folks at I B M Watson. 'cause that was cool back in 2017. And, um, you know, we kind of got started that way, but it, it was, um, wild. It's been a wild ride, Chris, that's for sure.
Speaker 1: (03:39)
Yeah. And, and say that again. When did you found lately?
Speaker 2: (03:43)
2014. Right? So we're the OGs
Speaker 1: (03:46)
2014. So all those individuals out there that think AI started in 2023, get a call a day from somebody who claims to be an AI expert who just started learning chat G P T a couple months ago. So I just wanted to clarify how long you've been in the space.
Speaker 2: (04:05)
Yeah, I mean, it's so interesting. I just was, um, doing a presentation for inbound on the history of Generat AI specifically. And for me, it was just interesting to not only understand for myself because I did understand already, but like to be able to translate it for others and to really kind of drill down, you know, why now is the time? Like what got us here? Right? And part of that is data and patterns like AI can't exist unless those two things are in place and in place in large quantities, right? And the, um, sort of events in the mid nineties really started to set us up for this, right? So, um, we had the switch to the internet. I mean, the internet was born. We had the switch from paper to digital. Oh my God. I mean, Chris, don't tell anybody, but I have two file cabinets sitting over there.
Speaker 2: (05:01)
. I still get my, my bank statements in, in paper, even though I'm an AI tech founder. Um, we had the birth of Amazon and Google and like all these places to now vomit as much, you know, digital data as we could out into the universe. And then, um, kinda matching up like this Confluence events. So now we're able to study the patterns, right? We, we now have enough information so that we can see, um, without an, without error being in the, the midst that things are likely to do, you know, X, Y, Z, right? So I love the, um, I'm just tangenting a bit, but like, I love the the cell phone, the Siri, right? So I was talking to someone about an example recently. My husband and I were at the mall and, uh, he dropped me off so I could go run an erring 'cause he doesn't wanna go into the mall, but he was starving, so he was looking for like McDonald's or something, and he came upon Shake Shack and it was forcing him in order to make the order, he had to like, go through all this stuff on their iPad and it would've taken two seconds to say, Hey, I would like a Arnold, Arnold Palmer and a hamburger.
Speaker 2: (06:11)
But like, those choices weren't available . And he was annoyed. And so he's texting me like how much he hates this experience. And then he says, I'm driving around now. And I'm like, okay, I am. I started with I'm, and then Siri knew from some patterns in the previous life, other lives that she'd seen shake Zack Drive I'm, and so she knew to recommend me not going and to, and, um, some other want, what was it not going and want were the three suggestions, right? And so she knew that I was gonna choose one of those things, which I was, I'm going to be outside is what I'm gonna say. But it only had to come from not only enough data, but enough of the same variants. And that's the other key thing. Like this particular variant had to ex exist multiple times before for her to make those recommendations for me. And that's the thing that I think people sort of forget about AI now is because maybe they don't understand that all this data has to be in place and the patterns and the variance, all, all for the AI to make a reasonable recommendation or slash prediction, um, that's why there's sometimes this disappointment, right? Because it is not magic. Yeah.
Speaker 1: (07:27)
You know what's interesting is I was having a conversation with somebody just, uh, last month, and they were explaining how they were going to be investing in AI and doing all these incredible things for their customers who are going to go through this process. And I started to dive into it, like, why are you doing it? What's the purpose of it? And they said, well, we have this complex onboarding process. We have a form, and what we wanna do is that when they answer the form a certain way, we want the AI to then an ask another question, . And I'm like, you realize that the forms that are out there today can do that , you don't, you don't need the AI to help you with this. And there is a disconnect between understanding what AI's intention, purpose, you know, the data that's behind it is capable of doing mm-hmm.
Speaker 2: (08:25)
Speaker 1: (08:25)
Versus reality, right? Yeah. There's a disconnect here, and I know you are spending a lot of time trying to educate people as well as sell people on your business practices.
Speaker 2: (08:40)
Yeah. And you know, it's funny, that hasn't changed by the way, in, in nearly nine years in somewhere or the other. And, and, um, it's just so funny. Like right now we're, we're educating and, and selling against magic, right? Which is to your point, point, um, that misalignment of the definition, specifically the, which is sort of derailing expectations. I mean, I'm gonna blame that on Hollywood, Chris altogether because like , the understanding of, or the definition of AI came to all of us from the movies. That was our first understanding of it, right? And it has been pretty much ever since. So we really think that sentient beans exist that, that are, you know, ro whether it's robots or, um, you know, R two, D two, you know, you name it, Terminator, et cetera. Um, so that's a, a real bummer is because people want that, of course.
Speaker 2: (09:31)
I mean, you know, we want it to exist. We've fallen in love with these things. Um, but the fact that it doesn't is, you know, it's not even close is, is like, you know, it's that, that that tree, right? If this, then that. Like, that's the only thing that AI is capable of doing right now. And it's really mis mistitled anyways. It's not artificial intelligence in any way. It's really just automation, to be honest still, right? Um, the, I like to think of, I like, I, I use a lot of metaphors to help people kind of get there with me. Um, so, you know, one good one is if you think of, um, think about human beings. So when we're born, we pop out and we're, we're just these helpless blobs. We can't stand up, we can't feed ourselves, we can't defend ourselves. All the things that every mammal needs to do in the world and everyone else can. You know, a deer is born, stands up and can start eating and run if necessary, right? Um, we are reliant, we're helpless, we're reliant on other humans to survive and thrive. Now, if AI itself was a human being, you would think of it as like three months old, right? Pretty helpless, pretty reliant on other humans to survive and thrive.
Speaker 1: (10:52)
You know, uh, I would agree Hollywood is probably to blame. But aren't we supposed to blame rock and roll
Speaker 2: (10:59)
? Well, what's, we have to
Speaker 1: (11:01)
Always rock and roll's problem. Uh, and I'm going to take that obviously back to your early days. There's clearly a segue in here. You started off, one of your roles in your career was as a dj you spent a lot of time in the music space. And that has contributed really into what Lately is doing. Can you make those connections for the audience?
Speaker 2: (11:28)
Yeah, for sure. Um, and thanks. You know, who would've thought my, my, I'm certainly my parents, never would've imagined. But, um, you know, with radio I was so interested, Chris, in the Theater of the Mind, which is of course why I like podcasts generally as well. Um, but you know, the theater of the Mind is the act of human imagination playing a role in the listening or, or the reading. It goes in, not, not in video, because in video they give you the whole piece of the story. So you don't have to imagine anything. But when you're listening or when you're reading, you do, and your brain, um, kind of puts itself into the mix to sort of fill in the blanks, right? And that's why you get off when you see a movie. And it does, it's not as good as the book, right?
Speaker 2: (12:13)
'cause you've had some ownership in the storyline of the movie. Now, a good author or a good dj, a good, if you're wielding the mic or wielding the pen, you know, this, you allow for this kind of se quo to help drive the story forward. And, um, that was exciting to me. And so I was a fiction writing major, and I another, you know, major that people thought would be useless. Look who's laughing now. Um, and I was, uh, , I, I took what I, I'd written hundred hundreds of commercials and took what I learned about writing and radio and translated it into, um, a spreadsheet system for Walmart that got them 130% r o i year over year for three years with what became the prototype for what is now lately. So my, my uber power in radio was turning listeners into fans or customers into evangelists, right?
Speaker 2: (13:09)
And that's the holy grail. That's what you want. Make the sale, generate the lead, but make the megaphone to get the flywheel, you know, going. And I was interested in how we could do that in writing as well, right? And that's what we've focused on focused, uh, lately, is, um, not just generating content for content's sake, because I mean, who, who cares? Thanks so much chat Bt who, you know, we're friends, but like, come on. Now, everybody can vomit more content out into the planet than ever before. Which means that our challenge, Chris, is harder than, it's the same as it's always been, but it's harder, which is cutting through the noise. How do we cut through the noise? Right? And that was the same kind of challenge in radio as well. And, um, it's going deeper, right? So the way we, um, lately sort of come at it is with a continuous performance learning loop, right? So the content that we're recommending for you, that we're generating for you is always tied to your analytics. So it's always relevant to you as opposed to whip it outta thin air and hope and pray, right? And that's the difference between great results and galactic results, right? And that's where we, um, are really proud to be in, in that space of like, listen, we get that, that the fear of the blank page is big. And we were selling that for a long time until everybody else was . Right?
Speaker 2: (14:39)
Now we sell like results .
Speaker 1: (14:41)
Yeah. The other piece of this, which I think is interesting, it, it brings things I think full circle is when we think about chat G P T, which everybody is starting to use, and they're generating masses amounts of content. Mm-hmm. I mean, I just watched a video today where somebody was able to generate, you know, over 2000 pieces of content, blog articles for their website in like 23 minutes by just automating the process and keywords. What's missing out of that? And, and what you touched on from your DJing days is the unique voice that brands have. And when you use these other tools that are out there, you, your voice is lost. Your distinctive nature of your organization that your customers are aligned to is missing. And what you're attempting to do or what you do, I I should not say attempting to do this is what you do is be able to leverage that data to bring your voice to the forefront in the conversation again, which is different than pretty much every other AI platform that is out there.
Speaker 2: (15:52)
Yeah. And I think people don't understand that too, because, you know, you can prompt the voice, you can prompt anything to be like, Hey, make me sound like a rock and roll DJ from the eighties who wears, I don't know, converse and is in love with, um, Andy Summers. I may or may not by talking about myself. Um, and the AI can do that, but it's pulling from gen uh, generic data set to do that. So it can't ever sound like me. It's, IM, it's impossible and it can't ever know my voice and it can't ever know what my unique audience would like to click. Like, comment and share what they would engage with. 'cause it's, it's impossible. There's no data behind it, right? Um, so that's like sort of the, it's not, we're not dismissing the greatness of it you and I in any way, right?
Speaker 2: (16:42)
But we're, we're asking what everyone else is now asking too. Like what's the next step? Okay. The shock and awe is, is happening now. We're all, like, we're amazed and less amazed. We get that. It's, it's here now, now how do we get it to genuinely do the things that we wanna do and do them well, and take us as not only humans, but as businesses of course, to, to the next level, right? And make it so that we're not all on the same playing field, which is where we all are now. Right? Everybody just got CliffNotes. That's what I like to think about, right? Remember CliffNotes, Chris, did you ever, did you cheat? I did. never never. But now we all can cheat is the deal, right? Like we all have the same answers to the essays and we know what they are. And, and, um, it's so funny to me that writing is such this, this pain point still, like, it's like as humans we're, we've, we've demoted ourselves to emojis and like, we're gonna be going back to grunting , we're coming full service, right? true. Remember Caveman with a Ringo star, God , what a
Speaker 1: (17:50)
Film. That's so true. You know, again, I think about just this voice, you know, obviously there's other tools out there now you can go clone your own voice, uh, you know, the audio version of your voice and
Speaker 2: (18:03)
Yeah. Read
Speaker 1: (18:04)
Entire, you know, eBooks and, uh, do the book in a clone voice of yourself. And we go back to Hollywood, this is already happening. James Earl Jones has given the rights to his voice for Darth Vader, so it will be forever Darth Vader as James Earl Jones's voice. Um, but there's still data behind that and there's still this fear that, well, once somebody has access to my data, I lose that voice. Somebody else can now copy it, somebody else can use it, somebody else can replicate it. As you said, I could go to Chachi BT and say, you know, write me a sonnet in the William Shakespeare style about a McDonald's cheeseburger. Like right
Speaker 2: (18:47)
,
Speaker 1: (18:47)
It's gonna happen. Right? Um, but there's still this, you know, slight subtlety between, you know, this open data that sources that are all over the place versus your company's data, right? That I'm sure people are concerned about and want to protect and want to ensure that that is still in their voice when they are hitting social media. How do you navigate that conversation?
Speaker 2: (19:16)
Yeah, I mean, you know, first we're just trying to educate, as you mentioned before, and, and give people a list of questions that they can ask when they're shopping. Like, you know, what, what to look for, what to look out for, and to, um, just make sure, I mean, there's a lot of quote AI tasks, the task force being built right now. Um, and the, the questions can range anything from like, like you're saying, like, is my doublet, is my data staying private? Right? Or is it going being tossed out into a public data set for all to use, which is why Silver Sarah Silverman is, you know, um, , are my results 100% proprietary? Or like, are there copyright issues? You know, um, is the bias of all the internet being pulled into my results, is there external bias or is it similar?
Speaker 2: (20:10)
Just a mirror of like, what, you know, what we already do, what, who I already am? So these are some of the, some of the questions to ask. Um, you know, the, the big one around the data, for us, it's easy. Like you do need a huge amount of data in order for your results to be good, but equally you need, um, quality data. And that's where we put our emphasis on. So like, I don't have as much data as open ai. I mean, that's impossible, right? But I do have nine years of it, so I have a pretty good junk. But more importantly, in our case, I have have data that is it, it's garbage in, garbage out with ai, right? And so because we've been training it on me essentially, and our brand and all of our customers who are pretty top tier writers, we're able to put you inside, inside of our kind of closed world and keep everything closed, you know?
Speaker 2: (21:06)
Um, so that's been a bit of a win for us. Now, other options, right? I know that, um, I think it was OpenAI or somebody was built, they're able to close, like PWC was telling me that they're working with a, you know, closed data set, which is great. I mean, so that's a great option. Um, there's still no relevant kind of analytics tied to anything that's being produced, you know, so you still have all these hurdles to overcome. But I think of it, Chris, like, you know, you were thinking, you were saying the music industry, like the Beastie Boys, right? They sampled everybody, you know, and then people got and cotton onto it, but then they got over that hump eventually also. So I think there will be a medium, just like with all other art, where we figure out how to walk an, walk a line where there's like public and private, there's some kind of barcode on your writing, just like there is with audio and video, and you get, um, a third party like there is in radio to go and track that for you and send you a paycheck every six months.
Speaker 1: (22:12)
, you know, we maybe another way to look at this, we've been talking in broad sense about how people have looked at technology and how that has changed customer transformation. And again, premier episode of customer transformation live, who this is it? eight? Yes. Um, the premise of customer transformation is that your customers are the ones that are evolving. They are the ones that are going to be transforming first and afterwards the businesses, all of our companies and brands have to figure out how to adapt and transform to meet those customer needs. And we can go all the way back, as you said, if we look at, uh, the iPhone and, and apps, there's an app for that, and everybody needed to rush out and build an app. Now there's AI for that , and everybody's rushing out to get ai, right?
Speaker 2: (23:03)
That's true.
Speaker 1: (23:04)
But the fact is, is that customers expectations are the ones that typically transform first, and then we just have to figure out how to meet those needs, goals, and aspirations. How have you looked at this? Because clearly between 2014 and today, customer needs expectations, understanding has shifted drastically, and you've had to adjust your business
Speaker 2: (23:33)
For sure. I I actually just got the nicest compliment this morning from a Fortune 100 company that I can't say, but she said, um, you made AI feel accessible, right? And I think that's the most important thing. And it's partly these metaphors that we're talking about just to get people, the fear factor is relevant. I'm not disregarding it, you know, but it's not here yet. , right? And we're quite, we're some, we're sometime from it. Um, so trying to find more and more metaphors to share with people is, you know, one of the things we're doing also just asking questions like, you know, what are you talking about internally? What are the concerns? They're usually concerns. We've, we already know, you know, we don't hear a lot of unique ones lately. Uh, pun, no pun intended there, but, um, , I think also it, it goes two ways, right?
Speaker 2: (24:25)
There's the whole ethical conversation, which is very important, but ethics rarely drives wallets to be, let's be frank, you know, um, so you, you have to have the conversation, but I always like to make sure that there's a dollar sign tied with it so that the people writing the checks are gonna be motivated by the, the ethics of it. So, um, one of those metaphors I love to tell Chris, and I love to tell them to our customers, um, specifically, especially when there's a lot of fear around AI, is the Betty Crocker story. So, uh, do like box cake in a box, right?
Speaker 1: (25:01)
Man, I I, I, I can tell you that I have a cousin who had one of the little Betty Crocker, you know, kitchens, and then
Speaker 2: (25:08)
Yeah, for
Speaker 1: (25:09)
Christmas, we would always go and make our own little cakes, you know? I mean, I think I was like eight years old, but so
Speaker 2: (25:14)
Cool. Of course, I
Speaker 1: (25:15)
Still love to bake today. So I've taken that experience from my linell, portable Betty Crocker experience, uh, all the way up to yes, the full mixes, the big boy mixes of today. So, yeah.
Speaker 2: (25:29)
What's your favorite flavor?
Speaker 1: (25:31)
Uh, uh, chocolate, probably. Yeah, me
Speaker 2: (25:33)
Too. I'm a, I'm a devil foods food. Devil's food cake. Yeah.
Speaker 1: (25:37)
I had a Devil's Food, uh, donut this morning.
Speaker 2: (25:40)
There you go. I mean, breakfast of Kinks . Well, so what, what Betty Crocker did back in the fifties was they invented cake in the box in case anyone doesn't know this story. And at the time, you just added water, and bam, he had a cake. And the housewives, who they were marketing to, thought this was weird. And it was weird. They didn't feel like they made a cake or baked anything. And so Betty Crocker pulled out the powdered eggs, and the new slogan became Just add an egg, and the sales skyrocketed. And the reason this is important is because around the whole conversation with AI in humans and collaboration, when you, when humans feel they have an ownership, this ties back to the theater of the mind and that role of, of in the journey there, right? When, when you have an ownership, it's a deeper feeling.
Speaker 2: (26:30)
Like this is how you create fans. This is why sales soar, right? One of the things that we've been doing since 2014 is building an AI platform from the ground up with human collaboration as part of the process, the whole, the whole way through, right? And again, yes, this was an ethical thing to do, but we saw the difference between great results and galactic results, by which I mean, 12000% increase engagement, 1000% increase in visibility, tripling sales leads, right? When you put the humans in the equation, and it, it, it's, and let me just tell clarify some of these reasons why. Um, it's because AI still has to be trained by humans. That's the first thing, right? So there's this symbiotic kind of relationship here, and only very skilled humans can train the ai. We have to be able to analyze what it puts out and, and course correct that as well, right?
Speaker 2: (27:28)
And so it'll start to learn and get smarter and smarter. The more and more we do this, which is why those results are so great. Harvard Business Review did a recent study that said, AI and humans together outpaces AI alone by two to seven x. There you go. R o i, it's all about r o i in the end, right? And who doesn't, who doesn't want that? So, um, it's a good way to sort of level those fears, cheer on the check writers, , you know, and then, and get people to understand that it's, it's the human collaboration in combination with that continuous performance learning loop. So always results tied to analytics. And then, um, also the securities of the privacy we talked about and the, and the, um, ownership of your results. Like, those are big four big wins that we're able to provide in this wild world, wild west of ai. .
Speaker 1: (28:30)
You know, you, you mentioned the emoji comment earlier where it seems like we're just going back to using , uh, to communicate. You're right. There's, there's an interesting element in here that I've talked to other people about in that the human that has to train the AI and even ask for what you want from the ai, you, you craft a prompt. Mm-hmm. requires a level of creativity. And also, uh, uh, on some level, there's some critical thinking involved in this. Yes. Like to really get into it and get legitimate responses. And when we talk about reverting back to emojis, we as a society are starting to lack basic critical thinking skills and creativity. And then it's just getting worse because we're allowing the AI to do it all. But that middleman, the human still has to, to be there. And I don't think people are fully grasping this.
Speaker 2: (29:36)
No, I, I just, um, did some research and I can't remember the number, but it was something like, there's this massive skills vacuum, um, to what you're saying in, in analytics specifically. Um, and I think it's like 200% like of jobs are going unfulfilled in the skills arena and across every industry because they can't, because we're getting dumber, right? . That that's what's happening. And it's, it's that movie, you know, coming to, what is it? Um, what's the movie I'm thinking of for like, the humans all just buzz around and electronic
Speaker 1: (30:09)
Oh, uh, the Disney movie.
Speaker 2: (30:10)
Yeah.
Speaker 1: (30:11)
Uh, Wally.
Speaker 2: (30:12)
Yeah. Uh, yeah, like Wally. Yeah, exactly. Exactly. You know? Um, and that's kind of interesting. My, my, my friends, I have friends who have daughters who are 13, and I, these kids are so cool, they talk when they're talking, they do emoji signs as part of the conversation, which is also interesting. So like this, like someone's crying a tear. Well, just as they're talking. Um, and so it's so funny, like how it's being interwoven and how, you know, who's learning cursive writing, nobody. Um, you're talking to your phone talking the text instead of writing it. Like, it's so interesting that this basic form of communication, I'm, I'm wondering like, you know, how long will we just get to be like, you know, you put your brain on my brain and I guess our emotions will be, you know, transferred to each other. I don't know.
Speaker 2: (31:00)
But, um, I feel like the ability to communicate is the thing that sets us apart as human beings from every other animal, you know, on a, on a high level. And it's something that will always be challenging. And I don't mean just saying yes or no, but like, the whole point is getting people to do what you want them to do. It's the whole point of everything. Take out the trash, do your homework, make the sale, write this piece of copy for me, right? And I think people forget that that's the basic objective. And then behind it, like, kind of breaking that down. So like, in my world, 'cause I live in social media, organic social media land, everything is about clicks and shares, right? So I have to back into that as the objective, what will make people click or share my content, you know?
Speaker 2: (31:54)
And so just knowing that the reason we want the AI to do better is to get to, to do whatever the objective is and to make sure that that's how you're coming at it. Then I think when people are shopping, when they're, when you're asking them why AI for this task, and that is really just automation, they can come at it with, with true answers and understand, like, it should be questions like, well, we can't do this on our own. That's the, that's the reason, you know, we haven't been able to do this well on our own, we, and that, and then maybe they have a hiring problem. I don't know. Um, like I find that the answer of saving time is now becoming weak. I mean, that's a great answer. But like, the reason to do things should be more like, make money, save money, make money, you know? And these, these have been, even though it's valuable, right? These have been soft, soft goals, Chris, like when I ask a lot of our customers, what is your objective? And it's save time. And I'm like, Hmm, shouldn't it be more effective? ?
Speaker 1: (32:59)
Yeah. I'm going to, uh, look, I'm gonna go back to my book and, and I'm gonna promote this while I'm saying this. Uh, your objective, your only objective is to reach your customers saving time. Why do you wanna save time? You're saving time because you wanna communicate with your customers more effectively. Why do you wanna communicate with your, your customers more effectively? Because you wanna generate sales. It's, it always, no matter what goes back to your customer, you have to think about it in this way.
Speaker 2: (33:31)
So
Speaker 1: (33:31)
From a social media perspective, more eyeballs means potentially more loyalty, more clicks, more sales. It always goes back to your customers. And what's fascinating about this is when I talk to people about AI and why are you using ai? Same questions that you're asking. They say, you know, some type of internal, you know, whatever mandate. And I say, are you selling ai, ai? Are you generating AI for other ai? Right? Like, we're not building AI products to serve other AI products. You know, we don't have the terminators in the robots right now who are standing there saying, oh, let me see what social media is saying. And interacting back and forth with each other. No, there are real people, real humans, your potential customers who you are trying to engage with. There is no other higher priority. Right?
Speaker 2: (34:28)
And it's
Speaker 1: (34:28)
Absolutely amazing when I hear like what you're saying, oh, well, we want to do this, or we want to do that. Well, if you can't relate that whatever it is back to a customer value proposition, then there is no purpose. There is no reason to be investing in it.
Speaker 2: (34:46)
Agree. Yeah. Um, and by the way, we gotta acknowledge April over here. Who, who whipped out a, a sonnet on a Shakespeare style McDonald's
Speaker 1: (34:54)
Cheeseburger. Oh yes, thank you. April .
Speaker 2: (34:57)
Yes. We'll
Speaker 1: (34:58)
Laugh about a Shakespearean style, about a McDonald's cheeseburger on a golden stone.
Speaker 2: (35:03)
So McDonald's cheeseburger, humble treat thy taste and charm forever can't be beat. That's just .
Speaker 1: (35:10)
I love it. We're going to post that somewhere.
Speaker 2: (35:12)
Who knew? That's so great. Oh my
Speaker 1: (35:14)
Gosh. Yeah. April, uh, just to call April out. Uh, I went to junior high with April.
Speaker 2: (35:20)
No way.
Speaker 1: (35:20)
Well, yeah. Appreciate her watching.
Speaker 2: (35:22)
Amazing. Um, boy, that's when someone knew you, huh?
Speaker 1: (35:25)
Yeah, exactly.
Speaker 2: (35:27)
You know, uh, and I was just thinking as you were talking, like what, you know, the summation of it to me of what you're saying is like putting yourself in someone else's shoes, right? That's, that's the challenge that we have. And it's something that's easy to forget. We, we forget all the time when we honk at somebody furiously, you know, on the road or we snap off a snappy text, you know, just forget to like think about what that other person is going through on the other, on the other side. And, um, so that's down to sympathy empathy in some cases, right? Just making sure that's part of your conversation. Um, I think that, you know, I don't mean to sound like blase about artificial intelligence in any way, but it really is. It's like the microwave. I mean, you know, I can pull out the pan and heat up the water and it'll take me 12 minutes, or I can nuke it for one minute and eventually I went over to that 'cause it's faster and I have other things to do. And certainly that's about saving time, but it's about saving time so I can get to do those other things that are more valuable that my, my brain, my time is needed to be doing. You know, that can't be replaced.
Speaker 1: (36:39)
Let's wrap up and give our listeners some advice. Like what are some of your golden rules of AI that you wanna leave with the audience?
Speaker 2: (36:50)
The number one rule is to actually give yourself as a human, more credit than you do. Um, the executive function is this part of your brain here that makes all these decisions that we make thousands of decisions, maybe even millions and milliseconds, right? That we're taking in, uh, everything around us and being able to make, to know, to take the next step, to say the next word, to drive the next, you know, two feet, right? And it's a very powerful function. And you can see if anybody has watched the Mandalorian when the, um, you know, murderous robot becomes a nurse , it's so meta on meta here, but like this, this piece of AI is like relearning how to pour a cup of tea. And you can see the challenges. It's all fictitious, but like, that's the executive function at, at play trying to take these things into, do these little tasks that you and I Chris take for granted every day.
Speaker 2: (37:44)
And they happen automatically. There'd be no way to list all of them out so that we could actually train, um, an artificial intelligence to do the, if this then, then that, because there's so many variants, right? The variables that come through. And that's the thing that I, I want people to take away and remember is like, um, you know, there's a reason if you're thinking, okay, AI drive a car, that it can't, because it would have to know all the different kinds of manual transmissions and all the different kinds of automatics and all the different possibilities of weather and birds flying by and dogs walking out and traffic lights being different shapes and like all these variants, right? And that's the thing that makes it not actually artificial intelligence that makes it automation. And that's why humans are still very much relevant in, in the leaders. You know, we're still the top dogs in the space because you can't replicate it, right? Yeah. So calm down, ,
Speaker 1: (38:49)
Calm down. I love it. Don't get fearful of it either. It's not gonna take over the world anytime soon.
Speaker 2: (38:55)
Yeah. And have fun. I mean the, the get those definitions, right? So understanding patterns, understanding data, understanding that predictions, there's no, um, you know, magical woman with a crystal ball telling you who's gonna win the W World Series. Like that's not what a prediction is in ai. It's more of like a recommendation. Yeah.
Speaker 1: (39:16)
Well, Kate, thank you so much for joining. We have the information and a little barcode up on the screen, so if you wanna check out lately ai, you can capture that or just go to lately.ai and find out all of the exciting things that are happening over there in Kate's world. I appreciate it so much. Thank you for joining us on our premier episode.
Speaker 2: (39:38)
What an honor. Thank you so much, Chris, and thanks everybody. Great to see you today,
Speaker 1: (39:43)
And we'll be back next week, every Wednesday at 10:00 PM Pacific time next week. We've got a great new show and we're gonna continue the conversation about customer transformation. So I look forward to sharing more insights with you from leaders in this space. Once again, thank you for watching and stay tuned for more.
