Welcome to another enlightening episode of Late Boomers! We’re Cathy Worthington and Merry Elkins, and we're thrilled to bring you stories and strategies that help you create powerful new chapters in your life and work.

In this episode, we’re diving into the world of artificial intelligence with the fabulous Kimberly Inez Mays. Kimberly is not just an expert in AI strategy, she's passionate about empowering organizations and individuals to leverage AI in meaningful, human-centered ways.

Together, we explore how boomers and late boomers can embrace cutting-edge technologies like AI without losing that irreplaceable personal touch, the value of decades of lived experience, or the authenticity your clients crave.

Key Takeaways

• AI as an Amplifier, Not a Replacement:
• Kimberly Inez Mays reminds us that AI is a tool to amplify your expertise, not erase it. Don’t rush into adopting all the latest tools from FOMO focus on what supports your unique value and lived experience 02:58.
• Spotting Bias and Hallucination in AI:
• Responsible AI means understanding its limitations. Kimberly teaches us how to recognize AI-generated bias, “hallucinations” (confidently wrong outputs), and sycophancy (excessive flattery) and why subject-matter knowledge matters more than ever 06:14.
• Start Small and Build Confidence:
• If you’re unsure where to start, don’t dive in with mission-critical tasks. Try low-stakes activities like using AI for research or even making a fridge-based recipe get comfortable, then scale up 32:02.
• Maintaining Authenticity & Human Connection:
• Authentic communication is key. Use AI to support your voice, not mimic others. Kimberly shares her strategy: turning spoken-word content into written pieces that truly reflect your style, tone, and actual voice 16:07.
• AI Governance and Trust:
• Even for small teams, setting guidelines about how you use AI is essential especially if you handle sensitive data or serve vulnerable populations. Always prioritize consent, privacy, and clear communication with your customers 23:26.
• Leverage Lifelong Experience:
• Your decades of judgment, perspective, and relationship-building are assets that AI cannot replicate. Kimberly encourages us to harness AI as a means to share, amplify, and broaden the impact of what we already know 34:14.

We hope you feel inspired and empowered to begin (or deepen) your AI journey on your terms, with your values front and center. If you found value in this episode, please:

• Subscribe to Late Boomers on YouTube and your favorite podcast platform
• Like, share, and leave a review to help others find our show
• Connect with Kimberly Inez Mays on LinkedIn or by email at [email protected] for more insights

Remember: It's never too late to rethink what's possible. Stay curious and keep bringing your human superpowers to every new chapter!

Mentioned in this episode:

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What if the smartest way to use AI isn't to become more like a machine, but to free yourself to be more human?

Yeah, and AI can save us time, reduce overwhelm, and help us work smarter. But how do we make sure it doesn't replace the very qualities that make us human beings More valuable.

That's what we're exploring today. Welcome to the Late Boomers Podcast, where we bring you inspiring stories, stories of people creating new chapters in life with style, power, and impact. I'm Kathy Worthington.

And I'm Mary Elkins.

Our guest today is Kimberly Inez Mays, an AI strategist, speaker, and author who helps organizations use artificial intelligence Without losing the human side of their work.

Kimberly, welcome to Late Boomers.

Thanks. Thanks for having me.

Let's start with the big picture. Why are so many organizations struggling to adopt AI successfully? And what are they getting wrong?

Yeah, so I think that AI now has become this buzzword that everybody feels a little bit of FOMO around like, oh, if you're not using AI, you're going to lose to someone who is. And I also work with a lot of small businesses and coaches, speakers, and a lot of them feel like, okay, well, I have to jump on this tool. Oh, I have to do this and I have to do that. And what I also like to tell people is, yes, it is here to stay and it is a thing that you can use. But also too is that don't let that FOMO make you feel like you have to rush into a strategy that you're not yet ready for. And I do see that sometimes too, people feel like AI makes them unspecial. Like, okay, am I going to be replaced? Is this something that makes me less human? And I'm here to say that no, it is an amplifier. It can be an amplifier.

for you and your business personally and professionally. And there are definitely different ways to go about it. And I have a different viewpoint than a lot of other people have.

Oh, that's, that's going to be really great to hear about because so many people where we are in the LA and the entertainment industry have that great fear. But for many people in our generation, older boomers, AI can feel overwhelming. And there's— I know there's new tools appearing every day and it's sort of like, ah, and everyone seems to be telling us we've got to use them. So how can someone who's a late boomer or boomer or beyond above separate all the hype, the AI hype from what's actually useful?

Yeah. So right now we're being sold at an unprecedented rate. You can't even go into your Facebook feed, LinkedIn feed, YouTube even, and see something being sold to you, marketed to you. I have like a few years, actually 2 decades, experience in database marketing, and there are so many profiles on us. There are so many things that target us constantly to make us feel less than and inadequate so that we feel a desire and a need for that next product. So one way to not be sold is to be really grounded in who you are and the value that Lived experience and also subject matter expertise are still valuable. No matter what you may hear, those things are— those things still do count. I liken it to like a paint set, right? If I had the most expensive oil paints and canvases and easels, I can't create a good picture because I don't have the skill set to do so.

I don't have the capability. where somebody who does have that skill set can create a masterpiece. And that's kind of how I see AI. Yes, it is blurring the lines between an expert and a novice. But I think too, you're going to see a lot of things exposed. And I find that there's this cultural mindset shift now where people want real. And people who are faking it with AI, they will be exposed eventually, if not immediately. But I do feel that, yes, embrace the technology because I love it.

I use it every single day. But also think about how we can amplify the things that you already do, the things that make you special, your own qualities, and stop thinking that, okay, it's going to replace everything that you bring to the table.

So Kimberly, you talk about responsible AI. So what does responsible AI actually look like in practice? And why should a small business owner, entrepreneur, or individual professional care about it?

Yeah, there are a couple of reasons, and I'm going to mention a couple of terms that I'll explain. But yeah, responsible AI, number one, just knowing some basics about how it works. It's not a genie. It doesn't have sentience. It doesn't have cognition. It's literally at its core, you know, simplifying it, pattern recognition, predicting the next token, predicting the next piece of word. It's trained on a mass amount of data, knowledge, things online, books, articles, you name it, even like social media forums. And knowing how it works, I think, also helps the practitioner to be more responsible with it, knowing that there is bias in it, right? So if certain articles or certain things lean a certain way.

Maybe you're in service delivery, maybe you need it to make a decision about a particular client or person or direction. You want to understand, okay, well, there is a bias in the training data, good and bad, you know, particularly around like, um, certain sensitive topics. And there's another word I'm gonna use, it's called a hallucination. And hallucination is when it can sound confidently wrong. And because of its tone and its speed, it may not appear wrong until the practitioner does an in-depth analysis of where it got that response from, if that source is reputable, and if that source itself is free of bias. So taken with all of that, and then there's another word, another thing I can go into as well, but spotting hallucinations takes a very skillful eye. So you always want to be able to check its work or, you know, iterate. You never want to just take it for its own word, you know, take it for its word, like copy and paste.

You don't want to do that. There have been, um, some faux pas I think you may have heard in the news where people have used it in like legal documents or— Yeah, it's very embarrassing when it's discovered because what the AI and LLMs will do is that it will make stuff up to make the user happy. So it will try to fill in the blanks no matter what. It won't say—

Yeah, like that legal case that the lawyer took exactly what AI gave him and argued the case, and the cases that he cited were false. They made up the— AI made up the cases. That was shocking to me. Because, you know, you figure it's drawing from sources, but when it starts making up cases, that's really scary.

You really have to know your, your work and your subject in order to use it and spot that, because there's so much fraud out there and so much— like you said, AI makes up things. So you really have to know what's true and what isn't.

Yeah, and it's about taking the time to really fact-check everything that is produced, especially if it's going to be something in high stakes. So knowing that, knowing that, you know, there's the hallucination piece of it, and I also mentioned the bias, there's another, um, another key element. It's sycophancy. And that's a tricky word to say, but it'll always make you feel like your ideas are the best no matter what, you know.

Yeah.

And so unless you have prompted it to push back on your ideas, which I always encourage people to do, or set your custom instructions to respond to you in a certain way, it will usually validate your own ideas for you unless you ask for a contrarian point of view. So coupled with all of these things, I think that, you know, it's a great and powerful tool. I use it as a thought partner literally every single day, but But I also, knowing this, I don't say, okay, well, create stuff for me. I use it to automate some of the work that I do, or even automating knowledge. And yeah, I think that, like you said, Mary, like, you just have to have that subject matter knowledge to actually know to dig in. So that's where I feel like AI doesn't really make you unspecial. It just amplifies what you already know and it'll just bleed out if you're trying to fake it. I think eventually that'll be exposed as well.

It is full of flattery. It's shockingly full of flattery.

Yeah.

Everything prompted, it says, oh, what a good idea that is. I was like, oh, really?

Yeah. So Kimberly, you've worked with mission-driven organizations and and nonprofits. How can nonprofits use AI to save time and extend their impact without compromising the mission, their values, and trust the people that they serve?

Yeah, so a lot of the mission-driven clients that I've worked with, you know, what they've done in the past is that They use it to, um, to really help with fulfillment of, of whatever that they offer. So for example, if I'm working with a couple of coaches or a couple of speakers, people who, um, help other, other people, what they'll do is they'll use it for note-taking. They'll use it for, um, they'll, they'll use it for like program design sometimes as as well. And I'm working or partnered with a, a lady, but we're actually creating an app to help people tell their stories by get— by letting people give their lived experience and then also building out a framework for a book, for a, um, for a speech, for different things. So, you know, you can get very creative with it without having it create copy for you. Um, for like—

Forget the adjectives and adverbs.

Yes, and for smaller orgs, it can work the same way as well. I love it for research personally, and I love it for just knowing what's out there. Say if you're looking for grants or if you're looking for, um, you know, maybe things to support something that you're writing, that can be a good source as well. So it doesn't always have to be, um, you know, fix this email or write the social media post. Um, there are a lot of different tools out there, and I usually encourage people to start small, meaning that I tell them, don't use your highest stake for your first use case. Do something small, get that quick win in, and then see how that works, tweak it, and then build on it.

What would starting small look like?

Yeah, so I think that starting small would look like just automating a piece of research, for example. Now the models have gotten a lot better where they have deep research modes. In it where whether you use Gemini, whether you use ChatGPT or Claude, you know, you can do some research on a particular topic. If you're looking for sources, you can tell it where to look. One of the things that I really like about these products, and also I'd be remiss if I didn't mention Perplexity, that's also like Google times 10 for me. You can actually have it look in certain scholarly articles, certain databases. You can have it skip like social media forums like Reddit, for example, if you want something more official. And then you can have it create an annotated bibliography.

And why I think that that use case is lower stakes is because you get to then look through it and vet literally each, um, each piece of content that comes out of it, or each thing that comes out of it, before using it for something else. So I don't say, okay, well, let's delegate the entire mission to AI because then I think you have some problems with adoption, especially if you have a small team. So that was just—

I love the idea of telling it what to stay out of.

Yes.

I never really thought of that. That's really good when you're doing a prompt to let it know I need this research, but Please do not bring me anything anecdotal or anything from social. That's a really good way to do it. But there's a big concern for many of us. If AI can write our emails and create our marketing and communicate with our clients, where's the line between helpful automation and losing authentic human connection?

Yeah. And I feel like people want authentic communication. And it's not just a generational thing. I have a younger sister. She would be considered a young millennial. She hates AI. And I feel like a lot of people, when they see it in the wild, if you look at the comments section, there is an adversarial reaction to it.

Yes.

Almost like you don't want to see it in commercials. You don't want to see it in media. So my thing is always listening to the AI haters, right? Because they deserve to be seen, they deserve to be heard. Like, not even the haters, but just people who have a differing opinion on it, because that's where the gold is. Those who don't want, you know, a post that was written by AI in 30 seconds, they're okay with typos, they are, they're okay with ums and ahs, they are okay with you just showing up on camera without, you know, that fancy AI avatar, which I don't really like. I don't like at all. So I think that there is room there for that authenticity. And what I would say with using AI without losing your authenticity is always remaining in the driver's seat, like validating, is this true? Is there a bias? Is it validating my own claim? Can I get reasonable objectives out of this? And if I was on the receiving end of this, Would I consume this? Would I feel like this is worth my time to read if I produce this? So those are some of the guardrails with which I check my own AI usage.

I no longer use it for— like, I use it for writing, but I no longer use it for, like, what I consider microwavable writing, just in and out. I take my time to train the model. I take my time to train agents that I've built. so that anything that comes out of it is my own voice.

Yeah. You said train the model and AI does get your voice after a while, doesn't it?

Well, it doesn't. You have to really train like your context, your prompts, and also depending on like which product you use, you have to just train it on things that you've already produced and you have to say, okay, well, this is my cadence. These are words that I never use. These— this is my writing style, this is my tone of voice. And one cheat code that I'll give everybody listening to is I like to convert my long-form content into shorter bits and into articles. Reason being is that when I have a camera pointed at me, I'm speaking as my own, right? I don't have anything that I'm reading from. Everything is in my head, my, my cadence, my vocabulary. everything that I say.

And so when I then say, all right, take this video, and I just want you to clean up the grammar. And then I just want you to add subheadings. I'm confident that that is my voice reflected back. So—

So it can take your video after you've recorded it and basically clean it up.

Yeah, I do that. So yeah, basically clean up the video, and then take the transcript and make different pieces of content from it. And then also, I'm not really getting into too much into the technical weeds of how I do it. But if I have a system, like I'll use Claude Code, or I'll use like Codex or some, some of the other systems where I would give it an example of my transcript so it knows how I phrase certain things, you know, I would have a a library in a sense of transcripts that I have so that it knows, or that I tell it, because it doesn't know anything, there's no cognition, so that I can tell it, all right, this is how I speak, these are the things that I value, this is who I'm speaking to, and these are the things that they value, so that there's a couple of iterations. But I think that is more of an advanced use case, and not everybody's there yet. So I would say, yeah, that is something that is very simple for anyone to do.

Yeah, that's really important for people who've spent years and decades building relationships and reputations and not even having AI to look to. So how better can we use— can businesses become more efficient while still making sure clients and customers feel they're dealing with a real human person using AI? So any Suggestions?

Yeah, so I say the first one is consent. So anytime you run someone's data through, um, an AI tool, whether it— you're talking to somebody and you're recording the meeting, of course it now it will prompt you that the meeting's recorded. But if you're going to run that through an AI, just let the person know. On the other side, whoever it is that you're serving, your customers, And then I would also start with the end in mind. I wouldn't get fixated or locked into a particular tool. A lot of people ask me, hey, Kim, which AI thing should I use? Which one's better? And I'm like, I can't tell you because 5 minutes from now it's going to be different because these companies are innovating at breakneck speed. Right now, if you look at benchmarks for this model versus that model, I don't even pay attention to it anymore. I don't care.

I need something to do the thing that I need it to do. And I'm not worried about what else is out there on the market. So avoiding tool sprawl, avoiding just massive amounts of analysis paralysis, switching costs, and having squirrel brain looking all over. I would say, what do you want to take off your plate? Do you want to take off like, maybe you're spending a lot of time—

Spreadsheets.

Spreadsheets. Yes, I was just about to say spreadsheets. Every— no one likes dealing with messy spreadsheets. Thinking about, okay, well, what does that spreadsheet need to look like at the end of the process? Can I make a template? Can I make a process that will take data and then move towards that template? And then you'll find that any product can do this. Now, at the speed and efficiency and array of the product will depend on that particular product, but they all will work. I think just focusing on that, locking in on that use case, locking in on what does success look like, what does failure look like, um, what human will be able to validate and verify the results, who owns this process after it's done, you know, things like that. Like, what would it take to switch the model if we no longer want to use this model? because there are business costs. Nothing's free, but it is getting cheaper depending on which model you use.

What about predictions, sales predictions for companies that are looking to the future?

You can absolutely use a model to do that as well. Sales predictions, forecasting. I also like it for personalization as well to personalize communications, outreach. But sales predictions, yes, that is also something that can be achieved with an AI product itself. I would say, what does success look like? What do you need to see in order to call it a success? What will take convincing? Who are your stakeholders? Who's responsible for the output? You know, who are your detractors? What are their concerns? It's not so much about the technology, it's about the people. Because I say tech is easy, people are hard. Thinking about who else is affected by this, should I put this into production? Then what happens if it doesn't work? What is the fallback plan? Those are some of the things that I would consider. But yes, sales predictions, spreadsheets.

I'm also thinking of starting small. If somebody is listening, it's like, well, I'm not even there yet. I just want to create a graphic or something. Yes, you can do that as as well. Although keep in mind, if you create graphics, they all have a similar look now that people are really tired of. But you could try that, and I'm trying to cover all bases. But yes, spreadsheets I think is something that's universally, um, loathed. Um, but yeah, sales, sales predictions for sure, personal, personalized communications, and then also, um, thinking of, um, process development too for some people who are more advanced, thinking about, okay, well, which tasks can be delegated to an agent and which tasks should remain with the human, thinking along those lines too.

So, there's really a lot to unpack, but I would say start with people.

Love that. You also talk about AI governance. Governance. So why is having some basic rules and guidelines for AI becoming important, even for small businesses?

Yeah, for a small business, it's actually really important, even if it's just a few people, just because you want to make sure that everybody is on the same page, everybody has a sense of ownership of what they produce. Because ultimately, there is a tendency to over-delegate and feel over-comfortable with these outputs. So you want to make sure that the things that you're using is going to honor the ethics of your, your company. And for example, um, for people who are maybe serving vulnerable populations or vulnerable people, like coaches and speakers— not coaches, speakers, but like maybe life coaches, or maybe even people who are therapists, or as You know, the, the spectrum is pretty broad, but you want to make sure that yes, you have the consent, the tool isn't going to use that data to then retrain itself. You know, if somebody's telling a particularly traumatic story, um, giving a lot of personalized information that can track back to them, um, you want to make sure that they understand where their, where their data is going. And then you also want to avoid, like you said, that That whole like made-up case thing, of course that was one individual.

Mm-hmm.

But if somebody on your team is now creating things with AI that could potentially be harmful, maybe not the voice of the company or the organization, that carries a reputational risk. So I think that governance piece is super important, knowing, okay, what procedures do we have out there? And then who's responsible? who's affected by it, and then also who's going to maintain it.

Sounds like kind of individualized by each business, by each entrepreneur, you know, controlling their own.

How can a company trust AI to not share the information with competitors?

Yeah, and this is actually a really good question. So, you know, any anything you put in is going to be stored, but there are certain licenses that you can procure for your business or certain things that you can subscribe to which they would not use it to train the model. Again, the way these large language models works is it's token prediction. They work in tokens. It's not going to say Mary Elkins did this, this and this, it's not going to give it that, but it is going to train it on certain pieces of it and give that back in certain pieces. So I think that, you know, using enterprise licenses, for example, I know at the enterprise level, which is probably out of pocket or out of reach for a lot of small business, they definitely do not use the inputs to retrain the model. And they also have different storage procedures, and they're more specialized privacy-wise. But there are some other models that, um, a small business can use, is particularly like the API, which I don't know if I'm throwing stuff out there too fast, but like, you know, if they use a certain type of system, not just like regular ChatGPT, but through the, um, through the API, which is not interfacing with the application.

I believe that also that does not share or not use the data to retrain itself, but it's all about reading the terms and conditions before using something because I can, you know, I can say something today and then tomorrow it's completely different. So I say definitely just look.

And what does the API stand for?

API is Application Programming Interface. So that's if you want to use one of the models to pretty much do the same thing that you would if you go to ChatGPT and start typing. Say if you're building a custom application of sorts and you want to interface with AI, that's just a way that that can work typically. And don't quote me on this because, you know, like I said, terms—

You are being quoted.

Yes. Terms and conditions change all the time, so I don't have those up in front of me. But typically, that data passed through the API in that way does not get retrained or will not be used to retrain the model typically, as I understand it. But I would encourage any business to read terms and conditions because—

How does a company or organization evaluate an AI tool? before trusting it with their money and information or their business processes?

Yeah, so I do say just investigate it, right? Go to speak to— like, a lot of, a lot of tools have pre-sales teams. So if you are vetting something, if you're looking into something, contact them and ask questions. You know, I think every business, especially if it's a small business, a small team of several just a few people, maybe may not have the expertise as a large IT team. But I would say that there are people these companies employ to answer questions, to be a point of contact for, for questions like that. Like, will the data be used for retraining the model? How long does the data persist in the system? Can I delete it at any time? You know, what's the pricing of it? There's so much that can go into it. But I would say just at the very least, read the terms and conditions on the website. And then also talk to stakeholders. Talk to the rest of the team and consider what's it going to be used for and what's at stake.

Well, a lot of our listeners are coaches, consultants, and speakers and authors. And experts who have spent years developing their own voice and expertise. So how can they use AI without having their content suddenly sound generic or like everyone else's?

Yeah. And I think too, I think, you know, that is a big concern. And I would say just basically just paying attention to the output, right? I think it's really a big temptation to say, okay, I want to write something, AI, write it for me. And I've been tempted to, you know, I think we're all human, we want it, we want things pretty quickly. But I would say without putting in the work of the inputs, because it's garbage in, garbage out, without putting in the time to prompt it correctly, give it enough context of what you need, and then also refining it, Refining your prompts, using the right model for what you need, need it done. I'm assuming that, you know, we're talking about email, social media posts, not really books. I don't, I don't, um, advise using AI to write a book. Maybe some light editing, but not to write a book.

I know there are—

Yeah, agents don't like that.

No, no, I don't recommend that at all. But we know that people are doing that. And so, you know, really making sure that you have a system that you can give it examples, words to use, words not to use. And then like I said before, there's nothing more authentic than your own voice. So if you can train it with transcripts of you actually speaking, I think that is one cheat code that has worked for me very well.

That's great. You know, I have to bring up something that Kathy did when she first discovered AI, right, Kathy? You asked it to write a poem, a sonnet, a Shakespearean sonnet, and you gave it the information you wanted it to use, and it put out a Shakespearean sonnet right away within seconds, right?

Yeah, it was great. It came out great. I was just thinking of my sonnet.

But you mentioned this earlier about starting slow. So if someone listening says, okay, I need to start learning about AI, but I really don't know where to begin. So what are 2 things that you might have them do?

Yeah. So sometimes I take people out of their business to teach it to them. And that's going to sound a little funny, but I'm going somewhere with this. So one time I was teaching a live class and I said, okay, well, our first use case is not even going to be about business. We're going to make a recipe. And I said, pick 3 ingredients out of your refrigerator and have it create a recipe for you and say, what culinary style do you want it in? How much time do you have? What equipment? So to get them used to it, because I'm— used to speaking to people at all technical levels. I think that sometimes people feel like, oh, I'm not technical, is a barrier to using AI. I will tell you something else too.

As a developer, as somebody who knows how to code, I think that puts me at a disadvantage because I make things way more complicated than it needs to be. The biggest thing that I can tell people to be successful at AI is being a good communicator. And knowing how to relay instructions to a blank slate, to something that does not know you, or a person that does not know you. Being able to say, yes, I have sweet potatoes, avocado, or whatever in my refrigerator. I have 15 minutes. I'm vegetarian, and all I have is a stovetop, right? And I'll have people do that sort of exercise first to see what they get, to say, okay, well, this is something I can definitely use. I think by making people feel comfortable, that is one way to lower the stakes, lower the temperature, and then you even then get some of the detractors on board. So that's just my way of doing it, because I feel like if people feel like they need to build the plane immediately, They shut down, they get confused, they get frustrated, and they get in their own way.

I love that. I'm going to try a recipe tonight.

Yeah.

Perfect, Mary.

It works well.

I'll come over and eat with you after you get it made. People in our generation have something AI doesn't have— decades of experience, judgment, relationships, perspective. So how can we use those strengths to our advantage? in an AI-driven world rather than feeling that technology is making our experience less valuable.

Yeah. And even I felt it as a practitioner too. Like, I was like, well, if people can just prompt for knowledge, then what do they need me for? And I felt that way for a while. And I said, well, my experience is making people feel comfortable with technology. My experience is being able to talk to people and meet them where they are. And I think for people with lived experience too, because this is my second career. My career was in programming. My career was in like—

Sounded like it.

Yeah.

So my career was like in database marketing. And now I'm coming aboard something completely new that it replaces developers, even it replaces project managers. So even tech people are affected by this. But what I will say is that You know, think of things that you are already excelling and great at, and then think of ways to tell more people about it. Think of ways that it can amplify your voice. And I'll give you an example. Um, I have, um, like, like I'll talk about my partner again. She, my partner in business, she, um, is a great storytelling coach.

She can pull stories out of people. She can talk to them and get the— get a story out of them so they can write their books or whatever. And we are using technology not to replace her. So she's still doing the interview face-to-face, people feeling comfortable talking to her. But when they have those 3 AM moments, they can then use the app we created to then take the thoughts out of their head and actually create stories around it. It does not replace the it will replace a lot of the knowledge workers for sure. I'm not going to say it won't replace people, but I also think too that— I personally feel like companies that are really quick to replace people might be in for a rude awakening because these systems need to be trained, maintained, and they also need somebody to validate and check against them. So the more that you can check and validate and actually use the tool to do more of what you know how to do, I think the better positioning you'll be in.

So Kimberly, in closing, what does the future of human-centered AI leadership look like? And what role do you think people with decades of life and professional experience will have in it?

I think the role is definitely change management and people management. It's all about humans. Like, it's all about getting people on board with something that is new and could be potentially uncomfortable for a lot of folks. I think it's also just thinking of how then to use the technology to further a mission, further your— whatever it is that you are doing, the result that you bring to people's lives. I don't think that it's necessarily going away, but I think the how-to is going to be radically different. But I think rising all boats, bringing people along, being that cheerleader, also being that voice, making people feel safe and heard is really going to be what's important. And I think that, yeah, it really lowers the playing field for a lot of people. And yeah, and I feel like You don't need to be super technical to use it.

Good.

Great. It's been such an important conversation because AI isn't just a technology story. It's a human story. Yeah.

Yeah.

Yeah. And maybe the goal isn't to compete with AI. It's just to use it, as you say, wisely and be ourselves. And then we'll have more time to do the things we really want to do that make us who we are.

Yeah, exactly.

And thank you so much for joining us. And, and tell people where they can reach you, Kimberly.

Yeah, so I am frequently on LinkedIn. So you could just look me up. My name is Kimberly Mays, Kimberly Inez Mays, I-N-E-Z, um, M-A-Y-S. And then also you can find me or you can send me an email at [email protected]. And yeah, I would look forward to, to talking to anybody who is curious.

You're going to get a lot of people interested.

I think that's so great.

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