Revenue Remix - Inspiring Visionary Leaders

AI Upskilling Done Right: How to Equip Your Team for Tomorrow’s Challenges

• summer poletti

Share episode

In this special episode of C-Suite Sidekick, host Summer Poletti welcomes Tara Bonhorst, founder of Do That Dave, to discuss one of today’s most pressing topics: the role of AI in the future workplace. They dive into the stats that show why AI skills are becoming non-negotiable for job seekers, and the impact of “BYO AI”—employees bringing their own tools into work environments without company oversight.

Together, Summer and Tara explore why training in AI is crucial, the pitfalls businesses face when they don’t take control of upskilling, and how to foster a culture of continuous learning without overwhelming your team. Tara also shares practical advice for business leaders on the basics every employee should know about AI, from safety and ethical use to essential skills like prompt engineering and tool selection.

Whether you're a CEO wondering how to integrate AI into your team or a professional looking to stay relevant, this conversation will inspire you to think strategically about AI in your workplace.

Tune in to learn:

  • Why “BYO AI” is on the rise and how it could impact your company.
  • The 3 pillars of essential AI training every team needs.
  • How to create a culture of continuous learning that’s both fun and productive.
  • The real risks of ignoring AI in your business—and how to manage them safely.

Don't miss this insightful conversation on preparing your team for the future of work. Available now on Apple Podcasts, Spotify, and all major platforms.

summer:

Welcome back to the C Suite Sidekick. This is your host Summer Paletti and today I am really happy I have a guest. So we're going to do a full size pod today, but first a little bit of background and then I'll let her introduce herself. As I was researching for my beginner AI podcast, I found a stat that I found a little alarming. 70 percent of business leaders say that they won't consider hiring someone who doesn't have AI skills and 25 percent of companies say that they are AI upskilling. So it's a fairly alarming gap that, inspired me. To do that podcast so that people can start upscaling themselves. But then the challenge is if you're upskilling yourself or you're relying on employees to upskill themselves, does it really align with your company's vision or things like that? So it's important to think about taking on the upskilling as an organization, and that brings us to our guest that we have joining us today, Tara, please introduce yourself.

tara:

Thanks so much for having me. Uh, my name's Tara Bonhorst and I founded Do That, Dave. Uh, we create, uh, online learning, uh, environments where people can come and discover AI and explore different tools and skills and. We have, really both training options. You can come to us and, upskill yourself. We have self paced online courses where, you could learn, basic AI literacy skills like prompting and creating deliverables. And then we also, do work with organizations who want to provide training for their whole team. Those stats that you cited, some are really, you know, that's what we're seeing across the board, I think, you know, that's a common stat right now that only 25 percent of companies are planning to offer training in generative AI this year. But, you know, at the same time, we know. That people are using AI tools at work, whether their organization knows it or is aware of it or not, uh, Microsoft and LinkedIn released their annual work trend index in May and found that, um you know, 75 percent of knowledge workers. are using AI at work. And that seems pretty high. But it's, it's, we know that there's people using them at work, but then 78 percent of those people who are using them are bringing their own tools. It's not, you know, tools that have been vetted by the organization and there's been guidance around how to use them. They're just. Bring it in themselves. They're calling this BYO AI. Bring your own AI. Um, and it's even more common at small and medium sized companies. So, yes,

summer:

that's funny. I like BYO AI. I haven't heard that yet. Um, what it reminds me of is like, it's just a tech wild, wild west. What tools are they using? What guardrails? Um, how are they using? Um, what's the security related concerns? Like, I feel like if the employer puts it on the employees to skill themselves, you kind of lose control of how the tools are being used. And I feel like that's a risk the employer would be best. To not take. Um, but I also like that you have a self taught course. I didn't realize that. So people can upskill themselves if their employer is kind of forbidding it and they don't want to make themselves unemployable in the market. So it's all good.

tara:

Yeah, exactly. When you're not tackling this head on as an organization, you don't know what people are using, how they're using it, what they're doing, whether or not. They're doing it responsibly. We'll talk about that a little more. Um, but yeah, I think that if, if your company's not going to offer it, it's definitely something you should try to take on yourselves. But I mean, I think companies are absolutely should be doing it. And I've got a few theories about why they're not.

summer:

I would love to hear those.

tara:

Yeah, so, um, especially in terms of what companies are thinking about why they aren't offering this training. I think there's, you know, there's a ton of uncertainty about the future right now, and that's at the root of a lot of this. You know, these AI tools, they came out kind of really suddenly, it really caught a lot of people by surprise. And now they're already changing so fast, you know, every week there's another model, another feature and other bells and whistles coming out. And so I think it's seeming to a lot of companies like investing in a lot of training at this point would be a waste of resources. Right. They're going to get their workforce trained up on the latest and greatest thing, but it's only the latest and greatest for about a week now. And I think then that really flows into this, you know, idea of just not knowing where to start. There's so much going on in the AI space right now. There's. People offering training, there's a lot of consultants out there who want to work on implementation. There's all these developers who are putting out their products. So they're putting kind of their own spin on education and what you need to know. And that really, you know, they're going to set that up to serve them and their solution and, and highlight that, which is fair. But so it's, it's really though, it's hard to know where to look. with all these, this messaging coming at you from every direction. So I think that leads, a lot of organizations to like a little bit of paralysis, I know I need to do something. I have no idea what to do or where to start. And I like to think that, that it's more that than this idea of, Of being willfully ignorant of what's going on. And I, there are some organizations that are doing that too. I think they're putting the blinders on and they're thinking, well, if we just kind of pretend we don't know or ignore the fact that their employees are using AI tools for a lot of their tasks, maybe they can try to avoid some of the blame if things go wrong. I don't think they don't want to be. Liable for these outputs, you know, if something goes wrong with AI, or if there's a data breach or, you know, the things we're hearing about now, sharing sensitive information, with AI models and compromising like companies. proprietary information and stuff like that. So maybe they're like, well, we didn't, we never said they could use AI tools. We never showed them how, so that's on them. And unfortunately, I think there's a little bit of that going on too, but I'm hoping it's more of a case where people just need a little guidance on where to start with this. Yeah.

summer:

So I have two thoughts. First is yes. On that second one, unless you're in technology CEOs. are not usually the most tech savvy person in the room. Um, so there might be a little bit of they don't know what they don't know. Um, this seems like a passing trend. We have other things to worry about. There could be some of that. And then when we're putting on our blinders, just, I, I spent enough time in HR to know that that is the wrong approach. So if anyone listening, if you're thinking of, I'll ignore the fact that they're using AI, and then if something happens, I'm not liable. That's not how this works.

tara:

Exactly.

summer:

If you knew about something and you didn't train them and you didn't put guardrails, and then there was a security breach because. They uploaded sensitive information because you didn't tell them not to. Um, that's a hundred percent on the employer. If the employer isn't setting up the employee for success, um, the employer will lose that lawsuit all day long, every day.

tara:

Exactly. Yeah. And, um, yeah, I think you, you kind of raised an interesting point too, in terms of, you know, In, in bigger organizations where they do have these silos, where there's HR versus IT, you know, I think there's some, a little bit of a hot potato thing going on where nobody's quite sure who's supposed to take the lead. You know, HR is usually in charge of learning and development, but IT is in charge of tech stuff. I think going forward, We're all going to be doing the tech stuff. That's the difference here with AI. It's bringing the capability to use these tools, like so much closer to the people who are using them and it's really blurring the lines. So, you know, I think there's a lot of sorting out to do. If you're in a bigger organization too, where there's these lines and sometimes territory, territorial lines between these, you know, different stakeholders.

summer:

Yep. Oh boy. We do not have time for office politics right now, but yeah.

tara:

Yeah. You've got to get everybody all hands on deck for this. Yeah. Well, I mean, this

summer:

is where I come in as like, find somebody, make them responsible. What comes to mind is IT. Implement the tool and then HR come in and train people how to use the tool. But the CEO has to take charge here.

tara:

Yeah, we've got you got to find a single point of contact of responsibility. But then delegate from there. And yeah, I think, you know, that is an interesting, um, you know, a blended approach. And it's not necessarily 2 departments you see working together a lot. I don't think HR and it, but. It's a, it's a whole new world out there.

summer:

Yeah. If HR is meeting with IT, somebody just got their pink slip.

tara:

No, that's, we're just going to have to adjust for sure. But, you know, I think there's, there's some topics. That I think any team could agree on, both IT, HR, executive suite. There's three really core areas that any sort of like workforce training that you want to do has to cover. The first one is just really basic AI literacy. You know, what is AI? How do these models work? What is it actually capable of versus what are like the known limitations? I think, with any emerging technology, there's going to be a lot of misconceptions out there. There's a good portion of the population who thinks that AI is just chat GPT. And that's all they've been exposed to so far. It's not even on their radar, some of the other stuff it can do. And then there's a good chunk of the population who thinks that, well, AI is gonna just, it can do everything for me now. And it's going to replace us actually because we don't need humans anymore and that's not true either. I think that's a good

summer:

fear to tackle when going into an AI adoption or training is empathy for employees. Who are going to feel okay, we're putting this in because you're going to fire me later. Um, you know, I remember when software went from on prem to cloud and there was a little bit of that, like, Oh, am I implementing my replacement right here? Um, so I, I think that AI basic literacy, you covered some things that are super important to make sure that you discuss with your folks. That's an elephant in the room.

tara:

Yeah. And I actually think that once people learn more about it, they get more comfortable with it and they see, Oh, this isn't just really something that can replace me, and this is something that can augment what I'm doing or something that can free me up to do the things that I'm best at and leave behind some of the busy work and the, you know, emails and meeting notes and agendas and all the low hanging fruit that's out there that can actually make you better as an employee.

summer:

Yeah. It's what Jenny says. Automate the mundane so that you focus on the extraordinary. Exactly.

tara:

All the stuff that really needs the human attention. That's where our focus should be, so. Yeah, so we've got literacy, what's next? Um, so, you know basic skills of how to use, AI tools like prompting, I think is, that was kind of the first big skill to emerge and everyone was all, fired up about prompt engineering and, how to get the perfect prompt, you know, here's 1000 prompts that you need in your life forever that are going to change your whole world. I think that was really common in the early days, but really it's, Not so much that you need to know exactly how to structure a prompt or how to, you know, put together the killer prompt or whatever, because these tools are actually getting a lot better at, responding to like conversational prompts and just really, the goal here is just be able to talk to the model. And I like to say that, you know, using AI is less about tech skills and a lot more about communication skills. If you can clearly state, you know, what you need and what you want the output to look like, You're well over halfway there. And then I think another one of the big skills is actually knowing when to stop using AI. You know, when you get to a certain point in a task and you're kind of fighting back and forth with, with your AI assistant there to get it just perfect, instead of just, you know, pulling it out and finishing the job yourself, Especially when, you're worried about efficiency and, you know, ROI on these tools, you don't want your employees to be using it to try to get from like 95 to 100%, right? You use it to get from 0 to 90 or 95. Yes. And then you're the human in the loop and you have to land the plane, as they say. Nice. Gotta know when to stop and also, there's this jump right now to think that like you have to do everything with AI.

tara (2):

You know,

tara:

AI everything all the time, but it's not always the right tool for the job.

tara (2):

So

tara:

that's something else we talk about too, is like, how do you think about what tools you need? When is like, can you get pretty far with a free tool? When should you invest in something more specialized for what you're doing?

tara (2):

And

tara:

that's kind of like, it's a skill in and of itself is picking the right tool. And knowing when to use it. So it's a new, new skillset, I think, versus, before you're at work and you're like, okay, here's the tools you're going to use. We're using Salesforce, we're using Outlook and that's it. So even if you don't get to any of these other topics in your training, I think at a baseline, every organization is probably really should be focused on AI safety. If as a leader, you just don't have the time or the budget to get to anything else, you have to be teaching safe use and responsible use, if your employees are going to be using AI, whether it's. BYO, AI, or the ones they're providing, you know, they need to understand what the risks are. And this is getting better all the time too. And there's a lot of options for enterprise solutions that have better, guardrails and safeguards for companies data, but there is a real potential for data privacy breaches. If somebody on your team inadvertently provides or purposefully provides sensitive information to your team, about your customers to an AI model. I just saw a headline this week. Um, somebody who was working in a healthcare organization, accidentally put patient information into chat GPT. I know. And now, um, you know, I don't know as there's, there was a breach of that information particularly, but now the organization has put a two year moratorium on using any AI tools. So for two years, nobody there. Can be working with this, trying it out, you know, and maybe they can go back and change that later. But that was their initial reaction. Just be like, well, somebody messed it up once, now we're out. And when you're working with healthcare information, that's really, I mean, it's a fair response, there's a lot of like ethical and legal

summer:

Yeah, for sure. It took a long time to get to where there was a software that would screen your emails. I work in financial services, so there's a software that screens your emails and looks for like, does this look like a social security number and then it encrypts it or it tells you that you can't send it or something like that. So this. This just makes me think like we need that for AI tools, but we're just not there yet. Like the, the tools are progressing so much faster than the safeguards. It's a little scary.

tara:

True. And yeah, that's, that's a great idea. We should call open AI right now. Get them on the phone.

summer:

Are you sure you want to upload this?

tara:

It's just, yeah. And I think that, when there's enterprise solutions, if you know, you've got a big organization and you're going out and getting like your custom AI model built, they've got their own, secure data storage. And you can be reasonably assured that, the information you provide the model isn't going to get out, but that is absolutely not the case with anything like commercially available. To the end users, ChatGPT, Claude, Gemini, you know, anything like that. Really, if you put something in there, it could get out there. It's definitely not certain, you know, it's not certainly going to get out if you share it, but the risk is there. It's not just, you know, sensitive, privacy information. There's also, Just confidential company information about your strategy. Or, things that you wouldn't want your competitors to know about. Like, that's the sort of thing that I worry more about, like, kind of getting into the model, you know, say you're putting together like an RFP. And you upload a bunch of, strategy docs and internal. Stuff to, produce your response. And then that starts to get into the training data. And all of a sudden, you know, when your competitors are asking for help with RFPs, it's sounding a lot like your RFP. And so, I think there's some real risks. Even if the risk of leaking information is small, I don't think it's worth it. So a good training program is always going to make sure people understand what is sensitive information and also why can't you share it? Because if you just tell them, well, no, you can't, I mean like, well, why not? What's the big deal? Understanding and thinking through like some of the ways it could get out there is, you want to use these tools. With your company information. Awesome. I'm sold. What's next? Well, so training plan, you know, like we were talking about earlier, it's hard to know where to start right now with building a training plan. And so what I always recommend is just start with the basics and build a foundation of like basic AI literacy. Have fun. Everybody in your organization take the same basic AI literacy course, and then create either a real or a digital space where they can talk about what they're learning and share their outcomes. Swap tips and talk about, you know, the roadblocks they hit. It could be a message board. You could set up a Slack channel for that. Some sort of way that people can, can share what they're doing. I'm a big fan of having just kind of like a study group or, you know, an AI working group in your company where you meet weekly for a short amount of time. You talk about, you know, what's being covered in, the coursework that you're all working through. Um, and yeah, that doesn't have to be a big, long, PhD level AI course or anything. It's just, just cover basic AI literacy concepts. Like, what it is, how it works, some basic skills, and then that, you know, those safety issues and the risks and risk mitigation. So I usually start there, just have everybody take the same, same course. So everybody's talking the same language. Everybody has the same definitions and then yeah, create that space to explore and work together. And this is really about setting aside some time. You know, I see a lot of businesses right now, they want people to jump in maybe and start using these AI tools to like be productive right away. And really, I think it's better to do a low risk environment, something that's do a project that's not work related, that, you know, people can think outside the box a little bit, not have this stress of like, I gotta finish this project right now. It's something more, expansive that they can kind of discover ways to use AI in their own work and like get those basic skills before they're doing something where, you know, there's a real work outcome attached to it. Yeah. That makes sense. I like that. And yeah. And then from, from there, like once everybody has the foundation, then I think, having like that working group kind of go past just the initial training point and start to, you know, experiment. With some, some lower risk tasks, you know, things like, answering emails, even that's like a good place to start. That might not seem like much, but have everybody like one email this week instead of spending, you know, 20, 30 minutes. Like I, sometimes I do, I'm guilty of like really. Yes. Spending a lot of time picking my words and email, like have them just try an AI draft first something really simple like that, or use AI to create your meeting agendas and then have an AI meeting assistant join you and do the notes. And, you know, it's really, it's okay to not be jumping in, Both feet first or head first into the pool when, you know, you can start with some small things. And from there, I think the nature of the tools is like, once you get it going for you, working with one thing that's small, but that saves you a lot of time, you start looking for the other opportunities naturally and they start to come and then you get more of like, you get an AI, not as. It was like strategy, I guess. Yeah, you're kind of growing your strategy from, from the ground up while you're getting information about what people are actually using it for. What are people benefiting from? What's saving the most time? From there, then you can start to think about what comes next in terms of the more advanced stuff, like automation, building agents, you know, all the really fancy stuff that you hear about, it's all right. If you're not there right now, start back at the beginning. That's that's what we always recommend.

summer:

I am ordinarily a strategy first person. However, this is so new and it's moving so quickly. I could see if you wait to put together a strategy, you're losing a lot of time. Um, I, I just, I love that approach. It's great.

tara:

Yeah, I think, I like to have a strategy too. I like to have a plan. I think that's pretty normal. I don't know if this is the moment where we get to have those, those plans and those strategies. There

summer:

are sometimes those moments. I mean, in my work, it's, um, we need to improve revenue right away. Uh, what levers can we pull right now in order to shake the money tree? Um, and we'll worry about strategy later. Um, I almost think that that applies here. Like, we don't have time to put together a full strategy. Like, let's just get in and learn and we'll see opportunities. Right? I love it. I wouldn't have guessed that that's the way you were going to go, but I love it.

tara:

Well, I think too, you can get, you run the risk of kind of getting yourself locked in. If you pick a strategy and then the very next day, it's like, well, there's a whole new thing that came out and just. trashed our strategy.

summer:

Yeah, exactly. So, other than spending too much time, uh, planning and not enough time doing, what other pitfalls should we try to avoid? That's

tara:

a great question. I think one of the biggest things I see right now is organizations are skipping the basics. They're trying to dive right into the more advanced stuff. Like automation, agents, even chatbots, uh, you know, customer facing chatbots, we saw that a lot in the very beginning people rushed out with the customer facing chatbots and they were giving very, very odd and, you know, undesirable responses to customers. I don't know if you remember the Watsonville Chevrolet. Bot. That was a really early one. Um, they didn't have the right guardrails. And so people were going and using it just like chat GPT. Like they'd go to Watsonville Chevrolet and be like, make me a Python code for, um, you know, differential, like all this, you know, really technical stuff. Or, and then I think they got, um, the chat bot to. Like offer up a deal to sell a truck for a dollar. And just like, there was some argument about whether or not that was a binding offer, you know, if you skip like learning what these underlying tools are and what they're doing, I think you'll end up spending a ton of money on tools that you don't even know whether or not. You need them

tara (2):

and then

tara:

you spend a lot of time learning to use them. And it really, it didn't even advance your goals, especially with like all the, the startups out there right now trying to sell their solutions. You can easily get really excited about something, you know, like agents. I mean, of course we all want. To have these AI agents that can act and like they can research and respond and act on their own and do stuff. Oh, that sounds great, but If you're not ready for that, it's going to fail if you don't kind of have a foundation in AI in your, in your organization before you get started. It's, we're seeing that a lot. So

summer:

it feels like if the machine is the smartest one in the room, you are going to lose control pretty quickly.

tara:

Exactly. Oh yes. I love that. Yes. We don't

summer:

want Terminator here. Okay.

tara:

Yeah. We need to understand what's going on here first before we, before we let, yeah, let them take on any sort of responsibility. Yep. The other thing that kind of goes along with that, is just organizations are focusing their training on one specific AI tool.

tara (2):

You know,

tara:

they're teaching their people how to use the tool, not how to use AI. When you get kind of locked in to one solution, then you're missing out on what else. You could be doing and what else could be out there and you could also run the risk of you pick a tool And you know, it's just gone Tomorrow, the startup environment right now is like there's so many companies starting up the herd is gonna start to thin here There are gonna be companies that are going under and if you kind of set up all your workflows you around the tool that they offered, you're going to be out of luck when they shut down. So, and that's even with more, you know, higher profile, more popular stuff, you know, the fee, you could start to build a workflow around a particular feature and then it's gone, you know, even if you're using Salesforce and you're sticky, you've learned all about, you know, the AI tools. The Salesforce has, and they're doing a great job, I've seen some of their stuff in action, but, um, they can change their mind. Like, all of this is really in flux right now. And they're like, well, this feature isn't selling, so we're going to drop it.

tara (2):

And

tara:

you really liked it and now it's gone. And, you know, you're also missing out again on, on, there might be something better out there and cheaper. Then Salesforce that you're not going to know about if you just block yourself into learning one solution.

summer:

That's really clever. And I think the reason why it matters just from my non techie brain is the cost. of changing has been lowered. Like it's so much easier to switch tools now than it used to be. And, um, if you're training on only one tool, you're going to miss out especially with like, everybody's going to try to come out to be a chat GPT killer. Of course. Um, you know, it's easier to change than it used to be. And so just having a fundamental on. Like just AI skills is going to serve you better because, you know, you'd be more better equipped to, to

tara:

switch. Exactly. Yeah. I mean, you, you are ready to do that. If you know that like what's underneath the hood at Salesforce is not that much different than what you might be able to find somewhere else. And that's one of the reasons I think why all these, legacy business software providers like Salesforce have been in such a rush

tara (2):

to

tara:

get those AI tools built into their platforms. Because they know that if they don't, people are going to realize that like They might be able to do this on their own for less or use another tool that's actually, you know, cheaper or better. And I think that's why everybody really jumped on board right away. This is what you got to have is it's not just AI. It's our AI that you need. Right. But yeah, and I think, though, in order to get there, really, at the end of the day, you have to give your people some time and space to explore right now, not endless time and space to, you know, you know, make, you know, AI generated images of cats, which I know we're all guilty of maybe wasting a little time with AI sometimes and doing something fun, but it's really not a waste, I think doing something fun. It's like, it brings that, that kind of wonder. I've heard a lot of people in the space right now saying that bring the wonder first. And then the ROI will follow, you know, get people excited about using it, get them wanting to find different ways of doing this. Cause you know, we're, we're seeing that happen in, communities that, that you and I are involved with, like women in AI, when people get together and talk about using this stuff and show them what they've done, everybody else gets excited about it too. And they want to go try it. Yeah, so, but you have to have, like, actual time and structure in place. Mm hmm. To let your employees do that. Otherwise it's just, well, you'll never get out of that, you know, that grind we're all in, it's like, just get it done and don't think about, you know, can we, is there a way to get this done better or faster or more fun? You know, I'm really hoping to like, at the end of the day, I'd like AI to bring a little bit more fun back to the workplace. You know, I don't think people really talk about like, there's a lot of stress. This is a really, you know, stressful time in the workforce. So I think if you can just try to be a little creative and have a little more fun with some of these AI tools, I think that, you know, improves, improves your whole workforce culture and, you know, That's, that's more valuable than ROI in a lot of cases.

summer:

Yes. Cause I work with small business owners and, um, the CEOs must have the ROI, but they're all generally very protective of their culture. So that makes perfect sense. And I like where you put it, like the, the program. giving them time to explore. What popped into my head is like, this could be seen as another project that they don't have time for because they're so busy doing their regular work. So if they're not permitted time, then they're not going to explore it. They're not going to work with it. They're not going to see what's possible. Um, so I, I can see where that would be critical.

tara:

Yeah, not everybody is going to have the luxury of doing that, but, um, you know, giving them, yeah, giving them that time and not making it another chore is. If you can do it, if you can swing it, I think that's the way to go.

summer:

Yeah, no, I like that. You've given us a lot of food for thought. I'm gonna wrap it up and let you finish out the rest of your day. Before I close this out, I want to touch back on culture again. I was glad that you brought that up near the end of your tips because From my experience, I spent a few years coaching before I do what I do now, and I also spent time in corporate where coaches would get brought in sometimes, and I think that if you have a training program that you're going to install, um, you need to be careful with your culture. If you don't already have a culture of continuous learning, you need to work on fostering that. Because where this can go, unfortunately, is people resist it because they think they're being sent to training because they're being fixed. Or if you're not super clear on your intentions, people are going to think that you're. Going to replace them with AI bots and they're going to resist. So I think you gotta look at your culture first, wrap the AI training and anything else like you would with any new initiative around the culture and make sure that people understand why, uh, so that you don't get folks actively resisting.

tara:

Yeah, and I, I, you know, the continuous learning thing here is really key. AI isn't something you can learn in a day, you know, put it to work the next day and set it and forget it. It's really gonna be a continuous process of, exploring what they can do, pushing the limits of what they can do, kind of finding, you know, ways to keep up with the new tools that are coming out without kind of getting lost in the hype. So, do that, Dave. We think the best way to do that is to just get that foundation. basic knowledge and don't fall into the trap of these misconceptions about, you know, AI can do anything or AI is garbage and it can't do anything. You know, once you start to understand what it's doing and how it's, using What you already have to be more creative and work faster. You know, that's where you've got to start. And from there, I think just finding the time and the space to explore and use AI together. Is, the way that you can build this culture of incorporating AI into your organization and not just making it another chore, that people have to do learning about, you know, learning about AI. You can use that to help your, your whole team grow, just reach their full potential. I love

summer:

it. I love it. All right. Well, Tara, thank you for joining us. Um, where can people find you?

tara:

We are at do that Dave. com and we're also on LinkedIn. We've got the do that Dave page and you can look up me Tara Bonhorst on LinkedIn as well. We'd love to talk to any organization out there who's looking to. Get their team up skilled on a wonderful.

summer:

Well, I will link all that in the show notes and For anyone new I'm summer Paletti rhymes with spaghetti You can find me on LinkedIn or you can find me on the rise of us calm. Send it to anybody Who is beginning their AI journey or who maybe is in the middle of it and they're starting to have some of those trip ups that we saw. It's okay. You can still fix it. And if you enjoyed it, I would appreciate a review. So it helps me with my reach and we will see you next week. Thanks for tuning in.

People on this episode

Head Shot

Summer Poletti

Host