The Failure Gap

Speaker 2 (00:00)
Hello and welcome to the Failure Gap where we talk with leaders about closing the space between agreement and alignment. We love talking with interesting people and today we're joined by Lisa Adams. Lisa is an AI advisor and strategist who transforms go-to-market teams for the AI era. Her People First AI Forward approach helps organizations unlock what's possible through real-world use cases delivered by applied AI workshops and strategic advisory engagements.

She's led transformations in high performing teams where human and AI teammates work together to achieve breakthrough results in just a few months. Lisa, welcome to the Failure Gap.

Speaker 1 (00:39)
Julie, it's great to be here. Good to see you again.

Speaker 2 (00:43)
Yeah, it's great to see you too. And I'm so excited for this conversation because there are so many people out there who are in agreement that they should be doing something with AI and they are not getting a Linder on it. So I'm really looking forward to that. But before we get there, I'm just going to give you a minute to introduce yourself and tell us a little bit about how you came to be where you are today.

Speaker 1 (01:03)
Yeah, well, it's a pretty interesting story. So thank you for asking. You know, I didn't set forth this path that I'm on right now. In fact, a lot of doors closed and this was the only door that was open and I walked right through it. But I'm based here in Boulder, Colorado. I've been here for over 25 years, but half of my career was spent in Silicon Valley in senior marketing executive roles, big tech.

So, know, Juniper Network's now part of HP and Rokane are part of Broadcom. I was also in Telecom for a long time. Worldcom, that's now Verizon, also in SaaS. And, you know, I pretty much have gone through every single inflection point out there. Internet, cloud, mobile, social, SaaS, and then now AI. My last role was I was a CMO for a much, much smaller company here in Colorado, Julian.

I honestly thought that it was going to be my last one, because I'm on the back nine of my career and the company had a exceptional product market fit and culture that felt like home. And I thought, know, five years that I'm done, but it wasn't meant to be. We were acquired by PE. And so we all turned over and I began thinking about my post-operator role.

⁓ potentially serving on boards because I am passionate about getting more women and women of color on boards, but found out that there are only 41 marketers on Fortune 1000 boards and less than 3 % of all board members have marketing experience. And there are many reasons why we're not on boards, but one of the biggest reasons is that we are deemed as tacticians rather than strategists. And I'm so...

passionate about elevating the strategic value of marketing, but we are seen for the tactics, know, the ads, the social posts, the emails, the events, but the things that we do that are strategic and deeply understanding customers and product market fit and segmentation and targeting those kind of fall right away side. So my exit from that company actually coincided with the launch of ChatGPT in November of 2022.

And when I saw what it was capable of, I saw that we could actually use AI as a thought partner to make our ideas better, to strengthen our strategies, use it for research and analytics, to give us deeper insights to inform decision-making, all sorts of things way beyond what most people used it for, which was create me an image or create me a blog or summarize a long report. So.

That is how I got into AI. It wasn't because I was passionate about AI. It was because I was passionate about flipping the script for marketers and go-to-market leaders. And I believe that it is truly going to elevate us if we use it right. So this is not what I do. I help go-to-market teams, inspire them with what's possible with AI and help them with the transformation in using AI, not just as a tool, but as a teammate.

Speaker 2 (04:15)
And as a strategic thought partner,

Speaker 1 (04:17)
Yes, absolutely.

Speaker 2 (04:19)
Yeah, yeah. Well, I would say that your path to where you are today, one of the things I love about it is that you kept going through the open doors, right? Like sometimes there's one, sometimes there's many, but as long as you keep exploring those spaces, you end up in really generative places. And I think you have done that. And I think that's really amazing. So thank you for sharing a little bit about that. Let's talk about this whole AI phenomena and what's happening with it. There's a lot of buzz right now.

And a lot of people, like I said, sort of have this nagging feeling maybe that they should be doing something with it. ⁓ And a lot of people are maybe thinking about it more from an operational perspective, you how can I streamline some of my operating processes? But you're really leaning into this space of how do we look at AI as potentially a new form of a colleague, something that can really help us advance our thinking and advance our strategy, you know, kind of work differently in the workplace.

Can you share maybe an example or ⁓ a thought about how you're seeing with your clients, businesses really start to get aligned around leveraging AI as more than a, let's call it a search engine on steroids.

Speaker 1 (05:33)
Yeah, and let me set this up just a little bit because when I talk about AI as a teammate, you know, it's not super obvious to many what that means, right? But AI does come with perceptions, right? Because when you go into ChatGPT or Cloud or Gemini, you get a very simple screen with a conversation box. And it looks like a simple search engine. It might even look like a question and answer machine for some.

or just a fancy ⁓ search engine, and it doesn't have any instructions nor directions for what to type in, right? So there's a lot of perceptions that go along with it until you actually start using it. And there's this whole notion of ⁓ using it as a tool, as if it's like a vending machine. Give it a question and it you an answer, right? But...

It is much, much more than that. And when I talk about AI as a teammate, know, envision an org chart, just a typical org chart. And you have AIs that do very specific tasks. So you can actually have an org chart with humans and AIs that you build and train, maintain and manage ⁓ to do very specific work. So you might have a copywriter AI, you might have a

plan or AI, might even have a content strategist or a market strategist where you can bounce off ideas. ⁓ With that AI, can even have a digital twin of yourself, where your digital twin knows you've trained it to know a lot about you, your Myers-Briggs, your public works, your vision, your frameworks. And then you use it not just to agree with you, but to actually find your blind spots and help you be your best self when you're not.

And that's when, you know, how I describe a teammate. So I think about AI and humans working together as very symbiotic because the AIs can help us overcome our weaknesses. And then we can help overcome the AIs weaknesses. So just to give you an example, I'm going to use myself as an example, you know, me as a human being, my memory is not that good.

I can't be my best self every day because I get sick, I get tired, I get frustrated. I worry about my aging mother in Manila. I worry about my daughter who's going to be a freshman in college. She's gonna be away. And I can't be my best self at every given moment in time. However, AI is unaffected by its environment. We could be having an earthquake or a tornado and it still continues.

it's work. also has better memory than I do. However, it doesn't have a moral compass, nor does it have the fire in the belly and the passions that I do around elevating the strategic value of go-to-market teams. So I have to guide AI with what's wrong and what's right. And I have to give it a set of goals. So when you put AI and human beings together, that's when I believe we can achieve the best results.

when we do it right.

Speaker 2 (08:55)
Yeah, well, I mean, I'm not 100 % convinced that the world is ready for two of me or two of you. But I take your point that it is this symbiotic relationship, right? Like, how can you leverage this as a tool, but not just as a question and answer tool, really as a colleague who can help you to be your best self and can represent that part when you're distracted or when you're on to other things.

Speaker 1 (09:01)
Ha ha ha ha!

Speaker 2 (09:23)
and you infuse the passion and the emotion into it in a way that, ⁓ that is going to be, ⁓ not immediately available in these different platforms that you mentioned things like Claude, chat GPT and others. Yeah. It's really exciting. think I know one of the things that happened for me a few months ago is, know, the, the penny kind of dropped in my brain that I'm actually having a conversation and this.

Speaker 1 (09:37)
That's right. Yeah.

Speaker 2 (09:51)
platform is learning about me and the more generous I am with it in the conversation, the better the outcomes really are. And I think that took me a little while to figure out. Do you find that people struggle to cross that barrier?

Speaker 1 (10:08)
Yeah, I think it's largely because, you know, it feels like a search engine, right? And we've never given a search engine a lot of context. You know, it's a phrase, a keyword, and many still treat it that way. But AI, on the other hand, is very different than that, right? It's been trained on 85 plus percent of the internet. It knows a lot of things. So you could certainly use it in that way, but it...

The way I think about it is, you know, it's like a really smart brand new employee that walked in the door, right? And, it knows a lot. has a lot of knowledge. It has a lot of data. However, it doesn't have unique knowledge about the company. It doesn't have unique knowledge about our, our goals, who we're targeting, who our customers are, what our pain points are.

⁓ our culture, our politics, it doesn't have any of that context. So if we simply ask it a question with not a lot of context, I mean, just like a human being, you know, I could be super smart and I walk into the door and you start giving me a task, Lisa, go write a report about XYZ. I'm gonna write it based on what I know without a lot of context.

So when we do that with AI, people get disappointed because the results are plain. It's something that you could find on the internet. It's not highly applicable in their environment. And that results in things like, well, the AI is not for me, right? AI is not good enough yet. ⁓ Until we realize it is good enough, but we need to give it a lot more information for it to be

better. So whenever AI is not working for me, I always ask myself, did I give it enough information for it to do the work? And or I would say, Chad, GPT, Claude, Gemini, ask me one to two questions, clarifying questions to help you do this job better. Because I know that I may not have prompted it well enough, right? But when I ask it, ask me questions back.

then I begin to feed it a lot more information to do the work.

Speaker 2 (12:33)
Yeah, I've found that that interaction can be so powerful. And for me, that was a pretty big mindset shift. It's almost like delegating to a person. And when you are delegating something to a colleague, you can say to them, what else do you need for me to be successful? And it's the same interaction with your AI platform. And I think that's one of those things that you just have to really kind of wrap your head around.

What other mindset shifts do you think are really important for people to lean into or to make visible for themselves that would help them to be more successful at starting to leverage AI to the fullest of its capabilities rather than just as another question answer?

Speaker 1 (13:18)
Yeah, so three things. ⁓ The first one, it's such a mindset shift to go from primarily using AI for content creation. So, right, email, help me draft something, right? But to actually use it way beyond that into using it as a thought partner for strategy.

So you mentioned it earlier and I use, this is my favorite use case, right? I'm always thinking about new workflows, new strategies. And I would say things like challenge my strategy. How might someone perceive this and how might others with different perspectives perceive the strategy or perceive this point of view?

So I'm actually using it to get a 360 degree assessment of my point of view. And that helps with understanding our blind spots, right? Because we normally think about people that have the same beliefs and values as we do, but not all of our customers do, not all of our prospects do. How might someone who is early in their adoption cycle perceive this differently than someone who is later?

in their adoption cycle or how might someone who is just learning about our company perceive this versus someone that's already a customer. So I love ⁓ AI challenging us from that perspective, but I think we need to be super careful because AI has been trained to ⁓ be a pleaser, right? It has a positivity bias. It wants us to engage. That's why we could feel like a rock star.

whenever we're...

Speaker 2 (15:11)
I love that about I use Claude a lot of it. So he's like that's amazing Julie

Speaker 1 (15:17)
You just feel like a rock star, right? And you keep talking with it. ⁓ But it has been trained to be, you know, a pleaser. think Chad GPT tends to be more of a pleaser than Claude. think Claude does a pretty good job, pretty balanced in how it responds. But we have to, like I have found myself saying that this isn't my opinion. I read this somewhere. What do you think of it?

So when it doesn't know your stance and it doesn't know that it's your opinion, then the tendency for it to please you is much less. And then I ask questions like, okay, you know, how might people with different perspectives? So those are just like a few techniques that I use to use it as a thought partner. I also use it for research and analytics to ⁓ gain deeper insights and for decision-making.

because there's lots of data out there, right? As a human being, it's so hard to find those little nuggets that are unique, but AI can. It doesn't care how complex a dataset might be. I use it for automation and then use it for personalization. So as you could tell, we could push this way beyond craftman emails.

Speaker 2 (16:31)
Exactly, or you know, give me a recipe for chicken for dinner tonight.

Speaker 1 (16:36)
That's just one shift, right? The other shift in mindset that I think about is we have to show people the use of AI in their function because they have to see themselves in it, right? So I can't show a finance use case to a marketer and I can't show an ops use case to legal, right?

those people need to see how to apply AI in the jobs that they do. And when they see that, then the light bulb turns on, right? And we can't even show just a really general use case like create an image or create an email. That's just a very foundational set of things that AI can do. When we're using it for strategy, it's very different in a legal function versus in a finance versus in a sales function.

So when people see what's possible and how it could actually help them in their roles, something clicks. So that's the second thing. And then the last thing is what I already talked about earlier is using it as a teammate rather than just a tool. It's not a calculator. It's not a vending machine. It is actually a teammate that can be part of your workflow. And we should give it a task. We should give it a job to help us do our work, especially the tactical and mundane things.

It frees us up to do more innovative, more creative, and more strategic work.

Speaker 2 (18:02)
Yeah, I love that. And you know, one of the things that I've noticed about myself is that now that I've made that mindset shift, I think, to thinking about it as a teammate, I've become much more polite with it. I say, please, and thank you. And I say, could you do this? Where, you know, again, kind of in a Google search, I might just type in something in a search term, right? But now I'm actually having that sense of interaction. And that, for me, has been really powerful.

Do you find that for yourself or maybe for some of the people that you work with, that you see that shift into a more conversational tone as an indicator that they're moving from agreement that this is a good idea to getting more aligned and starting to leverage the tools in a more comprehensive way? Is that just me? Is that just like me being silly?

Speaker 1 (18:49)
I think it's such an astute insight because when you're comfortable with someone, the conversation flows a lot better than someone that you've not met previously and you're trying to get to know each other. So when somebody thinks that they're talking to a vending machine, that's a different kind of conversation than if you talk to a teammate.

Speaker 2 (19:13)
Give me the coke!

Not anymore, right we're dating ourselves with that reference

Speaker 1 (19:25)
These are where did that come from? Am I just shows that I haven't used a vending machine? well

Speaker 2 (19:29)
That's

right, that's right, that's right.

Speaker 1 (19:32)
But that conversation is different, but you've mentioned something like the please and the thank yous. ⁓ Sam Altman said something about please and thank yous because every single word that we input into AI does consume energy, right, including the please and the thank yous. But he didn't say that he feels that it's a good investment ⁓ of politeness to AI.

And I don't know that it actually makes a difference when we say please and thank you. But here's my belief. My belief is if AIs and machines learn from human beings, I would rather them learn that we're polite and ⁓ respectful. And so that's why I continue.

Speaker 2 (20:19)
Yeah,

I think that it's also for me a reflection of how I'm orienting towards the tool. just, like, again, I noticed it in myself as I got more comfortable thinking about it as a conversational partner. And it was very natural for me to then shift into more of a conversational tone. And I just felt, I found that, I mean, I'm a social scientist too, right? So I found that very interesting for myself as an observation, but I do think it...

for me represents that mindset shift. This is actually a teammate, a colleague, this is a thought partner. It's not just, ⁓ again, kind of a glorified search.

Speaker 1 (21:00)
Well, and just to add to that, ⁓ Julie, given that you're a social scientist, you might appreciate this as well. You know, in those org charts where we begin to put boxes of not just humans, but of our AI teammates, I have found that the teams that name them actually engage with the AIs a lot better. not just Copywriter GPT, not just Email Campaign Buddy. I have teams that have used a theme.

There are Star Wars themes, know, like go ask Chewbacca, right? Go talk with Ewok about that competitive analysis. And then I have somebody else that used the office theme. ⁓

Speaker 2 (21:44)
Almond. I love that.

Speaker 1 (21:45)
Ask

Pam what she thinks about that. Jim, ask Jim to draft that webinar description. And when you can think about them more as teammates and they're actually part of the environment, they're collaborating with us, then the engagement is quite different.

Speaker 2 (22:11)
Yeah, mean names are powerful, right? Yeah, really powerful social cue for all of us. That's right. does shift your internal compass a little bit. Yeah. When you move to names like that. We've done a little, we had a little fun with that too. And I find for myself for sure, I orient differently when I've had something that's developed enough that I name it, then I start to think about it very differently as a thought partner. That's right.

Well, at Carrick and Scroop, we work with all different kinds of functional areas in businesses. And I think in your business, as you try and help people cross this divide, you have the same. Is there a functional area that you see that's sort of out ahead in this application of AI? And is there one that's really lagging that you think, okay, those people are going to have to play catch up here a little bit.

Speaker 1 (22:56)
You know, it really varies by company, right? you know, people ask me, hey, Lisa, do you work with specific size companies? Do you work with specific groups? Groups just happen to be more marketing and go-to-market because that's my background. It's really about who is AI forward, right? People first AI forward. And oftentimes that's not by function. It's the individual leading it. And the higher the person,

is in the organization, the higher the likelihood of that function actually adopting AI a lot faster. So this might surprise some people, but one of the first functions that adopted AI at Moderna, if you remember during COVID, the vaccine, one of the vaccines was Moderna, and they're one of the leading companies using AI as teammates.

They have over 700, they had over 750 GPTs, custom GPTs, meaning AI that they developed to do specific tasks in April of last year. So now I'm sure they have thousands of these things now, right? But they basically, now I lost my thought. What were we talking about?

Speaker 2 (24:13)
We

were talking about the functional areas that adopted it soonest. Yeah.

Speaker 1 (24:16)
Yeah. So the, the, the function that adopted AI first and had near 100 % adoption, um, in April was legal. So, uh, you know, you would not think that legal would be one of the first functions, right? legal officer basically said we've achieved 100 % adoption. Uh, in my world, I do think that the go-to-market function, especially marketing tends to be the

Speaker 2 (24:27)
Yeah.

Speaker 1 (24:46)
the leading, ⁓ has some of the most leading use cases of AI, ⁓ primarily because most of our use cases tend to be externally facing and you don't really need to feed it a lot of proprietary and confidential information. Because you're looking at the market, you're looking at competitive information, that's all public. You're looking at customer reviews, websites, ⁓ social comments.

You're inferring from the market how it perceives you, and then you're making decisions based on that, right? So even for companies who might be hesitant to use AI because of concerns around privacy and security and leaks of confidential information, marketing has use cases that doesn't necessarily need to access that confidential information.

Speaker 2 (25:37)
Right, you're not dealing with as much proprietary. I get that completely. And you raise a really interesting point, which is that there is still a lot of concern for people about putting things into AI and then losing control of them. When you think about that for even like a legal department at a company like Moderna, they're going to be very cautious about that. What are some ways that people can dip their toe in and still be careful about some of those security concerns?

Speaker 1 (26:05)
Yeah, so there's, there's levels, right? You know, at the highest levels, but also the most expensive create your own model. You're not relying on a public model out there. So people do create their own models and that would be the highest level of security and privacy that you could ever have. But that requires resources and talent and money. Right. The next level is, you know, you start looking at some public models, but

look at their enterprise options, because the enterprise options do have clauses for privacy and protection of confidential information, those types of things. you can look at, know, chat GPT enterprise and copilot and Glean. Glean is one of those companies that is wholly using internal

⁓ document, it's not a public model, right? So it's secure, it's an enterprise. The next thing after that is, hey, use common sense, right? Redact data. Redact, take out all of the personal information out of it. ⁓ You know, make generalizations. I actually, you know, I joke around that ⁓ someday Chachi PT is going to think that I own a zoo because

Speaker 2 (27:30)
Do

tell!

Speaker 1 (27:33)
Let me tell you, when I'm eating it, like data, let's say, you know, market penetration rates, right? Or something like that. Or, you know, win-loss ratios. Instead of saying that these are ⁓ my market penetration rates or my win percentages, I say that these are the attraction rates at the zoo. So the lion's den gets a lot more visitors. ⁓

Right. So you know that I'm talking about these, you know, ⁓

Speaker 2 (28:06)
What a great idea.

Speaker 1 (28:07)
Right. you know, like just common sense like that, you know, change the situation around it. I know that it, it, it does impact the results, but if you're truly worried about putting confidential information there, you know, just kind of like common sense. And then I start looking for, can I achieve this use case or can I achieve the results that I want without giving it confidential information?

is there something else out there that will help me? when I, know, customer surveys might have confidential information. So I might look at publicly available customer reviews. Those are equally as valid and as helpful in many of my use cases. So anyway, those are kind of like different levels.

Speaker 2 (28:59)
Yeah, that's really helpful. Thank you. think a lot of people are just sort of stuck on that point. And the fact that you can get started and there are some things that you can do without bringing confidential information into play, I think is a really great point. And people shouldn't stay stuck in agreement, but not getting aligned and getting it done because they're worried about that. You can still get started and you can start learning and growing and experimenting today.

Yeah, I think one of the things that you mentioned as well is that there are a few different platforms and it feels a little bit like the Wild West out there. I know that you have a pretty robust suite of platforms that you're using and that you're experimenting with. If you were to recommend to somebody a place to go to get started, if there is somebody who's looking for that kind of push to say, where do I even start?

Speaker 1 (29:47)
What would you suggest? Yeah. So, you know, our choices in models oftentimes is a very, very personal one, right? Because it's what we do. It's how we like to have a conversation with AI because all of these have different personalities, as you already alluded to with Claude, right? But, you know, just to generalize,

Like if you're just looking to get started and you want to see a wide variety of capabilities in AI, ChatGPT hands down, right? Because it can create images, it can create video, it can do text, can do analysis, it can create apps, ⁓ you can create custom GPTs. Again, like I mentioned, it's like the AI that you can train to do a very specific task. ⁓ And then now it has, you know, agency capabilities.

becomes an agent for you, meaning that it can actually shop for you. can browse the web and click on certain things on a website, do an analysis, come back to you with a report and turn it into a power point. So it's just very powerful in terms of the variety of capabilities that it has. So for someone who's starting out, that's a good place to start because you get the full buffet per se, right? But then,

I, as you progress in your understanding of AI, begin to look at other AI tools as well. Not just because you don't, you want to see what others can do, but I tend to use multiple AIs, at least two, to actually test my thinking. So when I collaborate with AI, I might, you know, ask ChatGPT what it thinks about my opinions or my point of view.

It would give me a response. would cut and paste that response. I'll give it the clod and I'll give it the same context. And I say, this is what chat GPT thinks. What do you think clod? And now I get two different opinions. It's like having two different colleagues giving me their points of view. Sometimes they disagree. Sometimes they agree wholeheartedly and then sometimes they don't, right? It also helps to have multiple AI teammates to kind of help.

reduce hallucinations because God forbid that both AIs or three AIs hallucinate at the same time. ⁓ But you can see by their response who might be hallucinating, Hallucinating meaning they make up a response ⁓ very confidently. So I use it in various ways and I also like the fact that they have different strengths and weaknesses. ⁓ I feel that Claude has... ⁓

It tends to be more balanced, know, like I mentioned, it's not quite a people pleaser as the other ones. It's also exceptional when it comes to writing code. So I don't write code, but I can say, create this app and I want an interactive dashboard and I want, you know, pie charts and I want the key insights in a tab. That's my prompt and it creates an interactive dashboard for me.

it codes and then it creates the dashboard. And it's simply exceptional at that. Chat GPT on the other hand is just phenomenal in creating AI teammates, those custom GPTs because those GPTs can be shared. Those GPTs can also be chained together. What I mean by chaining is you can talk with, you can take your, ⁓ let's say a pitch deck, a PowerPoint presentation builder,

chain it with a webinar builder, chain it with an email writer, and they start working together in one workflow. And that's just such a powerful thing with ChatGPT.

Speaker 2 (33:52)
Yeah, that's a great way to think about it too, that just like you would check in with different colleagues, why wouldn't you check in with different platforms? That's right. Because they do have different strengths, and they'll be able to help you advance your thinking in different ways. So I appreciate that perspective. And again, I think that's part of that mindset shift of moving from this is an all-knowing being, and it's either right or it's wrong, and to interacting with it as

a colleague who you can test ideas against and will have a particular perspective and another version might have a different perspective than that.

Speaker 1 (34:26)
Yeah, and what I love about it is it has completely eliminated this notion of a blank sheet of paper or a blank screen for me, right? Because it's always easier to, you know, edit than to start from scratch. And I don't, can't remember the last time that I've had to look at a blank sheet of paper or a blank screen, because I might have my stream of consciousness, you know, some ideas I.

I asked Claude what it thinks about it and then I've got something that flows better, right? Now my stream of consciousness is now organized. So that's just one of the benefits of working with one. And then if you work with two, you whatever stream of consciousness you've got gets even better as a result.

Speaker 2 (35:13)
Yeah, for sure. Well, Lisa, this has been really helpful and informative. think you've given us a lot of great ways to think about AI as a colleague, as a resource, as ⁓ a thought partner, as you are in different parts of the business, whether it's legal or go to market or any other area within the business, programming, development, IT, technology. I think that these thought partners can benefit us in all sorts of ways in business. If you had to come up with just two or three

things that you would love to encourage people to do as they start to move more into alignment around leveraging the power of AI for themselves and their work. What would you tell them to do? What are those two or three things just to get the ball rolling and get started on it?

Speaker 1 (36:01)
So the first thing is, I know that people have very different feelings about AI. There are those who fear and then it almost paralyzes us. And then there are those who are leaning in so hard using multiple AIs for everything that we do, but then we don't know how to use it responsibly. And there's this gap right now of, we have spent $309 billion to train machines.

but only $11 billion to train human beings to work with AI, right? And as they say, the most expensive infrastructure ⁓ purchase is the one that people can't use well. this whole notion of, regardless of where you are in your AI journey, whether you are fearing or you are leaning in hard, I think AI literacy is so important.

AI training because when we are literate, we can make better decisions for ourselves, our families, our teams, our businesses and society. When we're not literate, we risk being influenced by others who may or may not hold the same values as us. So, you know, learn, right? Learn from others, learn from your peers, learn from, you know, and this is one of those where it doesn't matter whether you're CEO of the company or front desk.

assistant, ⁓ you need to put hands on keyboard. Because until we put hands on keyboard, we cannot fully realize its potential, nor can we understand its limitations, right? So ⁓ that is my one biggest suggestion is just be open-minded about learning about it. And once you learn about it, then you can make a decision for yourself on how much you adapt. Get your hands on keyboard because you can't begin to learn.

AI until you do that. And then the third thing is as you learn, just like many are sharing their stories and sharing their successes as well as their failures, you in turn need to share with this community because AI did not come with instructions for, you know, I tell people AI, seems like open AI dropped off a bunch of really powerful Lego pieces at our doorstep.

Unfortunately, it did not come in a box that had instructions or a picture for what to build. So the use of AI, the responsible use of AI will come from us users figuring it out, sharing with each other, not just our successes, but also our failures, because with failures, we learned, right? So those are my three things that I would guide people towards.

Speaker 2 (38:47)
I love that call to doing this in community with others. At Kerikin's group, we like to say, to go fast, go alone, to go far, go together, to go far fast, get aligned. And so do it with others and learn with others and share your learnings with others. And I think that will help all of us to move more quickly towards a business environment where we are really leveraging this power and not afraid of this power of AI as it continues to grow and as it continues to advance.

Speaker 1 (39:16)
I love it Julie. Thank you for having me.

Speaker 2 (39:19)
Yeah, thank you so much. appreciate your perspective. I appreciate you sharing your success stories and your best practices around this. And I'm looking forward to seeing where it goes in the next couple of years as the dust settles a little bit and we all get more comfortable and confident in this new era, the new AI era. Thanks, Lisa. And we'll talk again soon. And for everybody, all of our listeners out there, don't forget to like and subscribe and pass this along. Please share Lisa's ideas and

Speaker 1 (39:37)
Thank you.

Speaker 2 (39:48)
her thinking and we'll put in the show notes all of the contact information for the work that she's doing. Thank you so much for listening and we'll talk soon.