34 | Dajana Achelpohl’s Framework for AI-Ready Teams

What does it really take to get teams excited about AI? Audrey Chia speaks with Dajana Achelpohl, former Google and PayPal leader turned founder of AI Changemaker, about the real challenges behind AI adoption. Dajana breaks down her AI Building Blocks exercise — a hands-on approach to helping teams identify use cases, overcome fear, and start using AI with confidence. She also shares how leaders can bridge the gap between strategy and implementation, and why starting small with real problems can lead to lasting change.

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Transcript

Audrey Chia: 0:00

Hello and welcome back to the AI Market Playbook, where we cover actionable frameworks to help you leverage AI and marketing strategies in your business. I'm Audrey Chair Host, and today I have with me Diana Achelpohl, the founder of AI Change Maker. So Diana is an expert in AI strategy and change management. With nearly 20 years of experience leading teams at Google and PayPal now, she's really passionate about building AI strategies that create tangible people first results for organizations focusing really on practical hands-on learning. Diana is also the creator of frameworks like the AI building Blocks exercise, which helps teams get started with AI in a way that makes sense for them. Diana, we are so happy to have you on the show. Welcome.

Dajana Achelpohl: 0:44

Thank you so much for having me. Delighted to be here.

Audrey Chia: 0:47

Awesome. I would love to know a bit more about your interesting journey, right? You talked about being at Google and PayPal and now you are the founder of AI Changemaker. Tell us more about how you got started, and how you ended up here today.

Dajana Achelpohl: 0:59

Absolutely. It's been quite a journey. Yeah. As you mentioned, so I spent nearly 20 years leading sales, marketing and operation teams in, PayPal and, and then in Google. So I'm very much not common from, from a technical background as such. And, I guess working in big tech, I've been exposed to AI for a long time. More, more traditional AI before we had an ai, and was always amazed by the, by the possibilities, but it was always hard to get access to it'cause you needed the engineering team to partner with you. To get anything going, any automations, et cetera. So I was super excited when Gen ai, burst onto the scenes. I thought this was gonna be my time where I could do so many exciting things myself, without having to rely on those really scarce engineering resources and then to my shock and horror. I couldn't make it work. So I was really in, in a position where I was very eager to use more ai, to see those results, and I just couldn't do it. And there was various reasons for that, right? So. First of all, I actually found it difficult to figure out what exactly could we use AI for. Then there was a question of how can we integrate it into our work? How can we measure success? And then to my big surprise, my team actually wasn't that excited about it. There was a lot of reluctance in the team as well. So where I'm now with ai, changemaker really comes from my own experie. Experience. So I was a leader with a team wanting to make AI work and I couldn't. So when I was at that point, I thought very briefly about giving up where we just leave this whole AI thing, but then decided to like really dig into it. So I learned a lot. when it comes to ai, how does it work? I also got back to my roots on change management to figure out whether the team resistance come from. And then eventually I did learn at some of a somewhat of a sweet spot where we, found the right problem, the right tool and the right mindset in the team. And only then really did we see results from ai. and what I'm trying to do now with AI Changemaker is I guess help people get there quicker so that they don't have to go through, through all the, the ups and downs that I had to go through. To get to that point.

Audrey Chia: 3:05

Well, I, I think there's such a brilliant introduction and there's so much to unpack, right? Maybe let's talk about that resistance that people face, like what you say, right? A, a huge part of being a change maker is also a change. And I think with, you know, gen AI especially, it is a huge change for many people. So what are some of the common objections that people face, or why are organizations limiting themselves or reluctant to change?

Dajana Achelpohl: 3:29

Yeah. Big, big question and, and there's, there's so much in there, right? I think on the individual level, there's obviously like real fear associated with gen ai. What does that mean for my role? What does that mean for the skills that I have? So I think a lot of people, I. That there is that genuine fear that AI is actually coming after your job, after your livelihood, and that there is big change afoot. And I think that is something that organizations need to acknowledge. That's not something that you can just brush over and ignore. It's nearly like the elephant in the room when you're introducing ai. Especially considering that a lot of organizations introduce AI with efficiency in in mind, so of course for, for people that that means that they're even more worried. I think even without that existential fear that people have, most people, me included, I don't know about, you actually don't like change. Right. We, we like things the, the way they are. And AI is a big, big change. It's not just another IT tool that you're bringing in and that you're learning how to use. It really changes how you work, what you do, how you do it, what you are good at. So it's, it's much more existential than I think, than a lot of other things. So that's really what I see on the individual basis. And then talking about organizations. Again, coming back to that point of AI being in a, in a separate category, nearly right, this is not like bringing any other IT tools on board. So I think a lot of organizations are really underestimating what is required. So what I see in my experience, I guess is, is three different types of organizations. The ones that are saying, we don't know about this AI thing, we might just wait and see if this is actually something and we are just gonna continue as is. And there is no AI use in our company, which is of course not true. We, you and I know that shadow AI is, is a big thing, right? And your teams will use AI anyway, so that's, that's one type. Then there is also the organizations which, Are going, okay, AI is the next thing. Let's do something. We're gonna buy an AI tool. That's often something like Microsoft copilot, if they are operating in that environment, and that's it, right? They're putting this new tool in front of their teams and then they're expecting for magic to happen and for people to use it. And let me tell you that, that most likely won't work. And then thirdly, there's companies that are stuck in that pilot phase. So they do have ai, they do have pilots, but they have real trouble of scaling it and really making a go at it. In Ireland where I'm based, there was a recent study that showed that only 6% of companies have really scaled ai and that is. Tiny considering all the hype about AI that, that we hear. So I think we are still at really at the beginning of all of this and there's so much potential. and still we are not late, right? Because I think sometimes organizations or even individuals feel, oh, I'm late to this. the train has left the station. I don't think that's the case. There's a lot of fear, a lot of change that people and organizations need to go through, but I think there's still so much opportunity.

Audrey Chia: 6:29

I think it's very interesting because, on LinkedIn or on in certain spaces, you would see everyone leveraging AI or being like, you know, advocates of using it. But there are many organizations and individuals out there who have barely used chair GPT Yes. Barely understand the functions and even really, like, haven't made the time or choose not to, explore AI because of like what you said, the fear, right. of being replaced.

Dajana Achelpohl: 6:54

Absolutely, and that was actually one of my, Biggest surprises when, when I left my, my tech bubble. So when I, when I left Google and started doing this, I had been under the assumption that most people were much further along in, in their AI journey. And of course, me having been in that environment where everybody is, is. Maybe a bit more, used to using tech, et cetera. I was really surprised.'cause it's really, like you say, a lot of people are not using any AI or using AI for very, very limited use cases. And they have one, maybe two tools, which, which they like and they use them and, and that's it. And there's so much more people could do and should do.

Audrey Chia: 7:29

To that point. Right. I'm so curious, since you said your team was reluctant to, you know, make that change, and of course at an organizational level, there are different types of organizations with different needs, but specifically at your previous organization with your team, how did you convince them? To start, you know, adopting ai'cause that is such a big task.

Dajana Achelpohl: 7:48

Yeah, it, it is. And I guess what, what I'm going back to also in my approach now is that you're gonna have different types of people in, in your team and that have different reasons or different levels of where they are with ai. And I think you need to bring them all. To that same sort of level where we can all get behind ai. I find that personal productivity, so finding something that is a real pain point I. For people or for teams and that AI can help with is often what will really make the difference and where people then see the potential and are also seeing this as something that will actually help them and not as something that will come after their job or that that will be a danger to them. For my team, which I was just talking about, was actually something fairly small. We had a weekly report, which we had to sort of provide, to, to another sort of partner team, and it took every member of, of the team, this was quite a big team, about an hour and a half every week. To compile this report and we brought AI in and we brought that down to 20 minutes for everybody in that team. So that means now everybody on that team has an extra hour and 10 minutes a week to do something else, to do something that they actually want to do because nobody liked doing that report. and that was fairly small, you know, but it was really that that one point where people went, oh, okay, now I know why this is something that can actually be good for me. So I think often I. It's about finding that real life pain point that individuals or teams have and starting there, and I think then people really see that what's possible and get excited about it.

Audrey Chia: 9:18

Yeah, and maybe like that's the first step in getting buy-in, right? Yes. When somebody realizes like, Hey, this is actually very useful, I can save more time, and then they start being curious and they start wanting to experiment and explore. Yes. I think as an individual, that's how they grow. Right. But I'm also wondering, because that's on an individual level, getting individuals too. You know, try something new and perhaps learn something new. But what about management, right? Because it has to be bottom up and maybe even top down. So how would you recommend, you know, teams having those conversations? I do know management that can be very resistant to change. and of course, because. They are so used to the status quo. Right. so when AI is here now they have to rethink how they build their clients, how their organization operates. So many big conversations to be had. How would you recommend a team navigate that?

Dajana Achelpohl: 10:07

Yes. so I have actually in, in my work, seen many instances where you might have actually gotten the workforce, the team's excited, but leadership is. It's not there. And that of course is a problem.'cause like you said, it needs to be top down but also bottom up. So what I find with, with a lot of leaders is that they actually know very little about ai. So they are talk in the talk about ai, but they actually haven't experienced AI themselves. And I do think that even for leadership teams, it's quite powerful again, to actually show them what AI. Can do and also have a conversation with them about obviously the possibilities, why you should be interested in AI and should encourage in your organization to talk about competitive advantage. The stat that I said earlier, only 6% have really gotten to the scalable phase, so this is still an advantage that you can grasp now. So I think there's something about getting that possibility and paint that picture. I also think sometimes that depending on what industry you are in, some leaders might feel that this is not for us because they might be in an industry that traditionally is not associated to it, or that they might not see themselves in that sense. So again, even showing that AI isn't this. Pie in the sky. Really complicated thing, but it's something very tangible. And I find having, I have workshops with leadership teams sometimes where we really look at what their business is, what they do, and where there could be things where AI could help. I'm a big believer that you should start with a problem and not with a solution, which is. Ai. I dunno if you know that, saying that if you have a hammer, everything looks like a nail. I sometimes think leadership teams. Think, okay, we need to use ai. We need to use AI for everything now. So you have the AI hammer and everything looks like an ai, AI problem. IE in the right. I much prefer starting the other way around where we look at something like, what is a concern in your organization? And then introduce AI as a solution. And I find when you talk with leadership teams about that, that's also then when they see the possibilities. And then also get excited. I also get them to actually use a bit of AI themselves. Again, often they, they have never used it, not even used chat, GPT. and I think that there's this whole, I have this idea of AI ready leadership where if you want to lead ai, you need to be ready for it. And part of that needs to be that you're using AI yourself.

Audrey Chia: 12:33

Yeah. And I think this actually transcends across different functions. Right. I had a personal experience where I was just sharing a couple of use cases with a friend of mine who have, has not used AI before, and he's in the finance space and after just introducing a couple of functions, he's now using it to build up full workflows. And he's finding his own use cases? Yes. And then it opens up, you know, new doors, right.

Dajana Achelpohl: 12:56

And I think it's, that's so true, right? You really need to get, once people have have seen the light, they, some of them get so excited and like you say, then come up with, with their own, wonderful ideas where, where to use ai. And that's really what, what you want to do. And that's really where I see my role, right? I want to get people to the level where. They understand enough about AI that they can try it out. They're excited enough about it if it's a leadership team, that they understand that they will have to have some change management in place. This won't just happen by itself. And then also that you need a form of AI strategy, so you need that problem, you need to measure, et cetera. And then, then often it's, that's a good place to put people in and then, then they're off right in, in their own. Of ai.

Audrey Chia: 13:39

Yeah. And you also mentioned the term change management. I don't think this is a concept that a lot of people are familiar with. So tell us more about change management and if you have any like frameworks. How can someone, you know, understand this in a simple way and maybe start implementing it in their organizations?

Dajana Achelpohl: 13:55

Absolutely. So I think, change management obviously is, is not an AI specific concept, right? It's been around for a long time and people that are into change management would argue that any change that, that you do needs change management. I think AI particularly is unforgiving if you're not doing it because as, as we said earlier, right, this change won't just happen by itself. So a very useful framework for, for change management that, I think, it's coincidentally really great for AI is, there's, it's called atkar. So it's, it's part of the Prosci change management approach and in Atkar you cover five steps of change management. The first one is I. Attention, which would be to make it really clear for yourself and for everyone who works in the organization. Why so why are we bringing AI on board in, in this case, right? So we, we need to actually, I. Not just say we're bringing AI on. We need to say, we're bringing in AI because this is what we want to achieve and this is how we are thinking about it. The second one then is about desire, the D. So you need to show employees in your team what is in it for them. Why should they be excited about bringing AI on? And with ai that's obviously, again, showing them now you can actually do things that you enjoy doing and AI could do all those tedious things you, you don't want to do. Then K is knowledge. I think something really, really important with, ai, that we give people the knowledge and I think not just the knowledge to press a button in an AI tool, but the knowledge to understand how does AI work, and how can you integrate it. And in the next step, we should really give people a safe space to experiment. with AI so that they can really make those mistakes, try out things and experience them. And then the last point is recognition, or are where we don't just do this as a once and done, but this is ongoing, right? So we continue to talk about ai. We recognize people that use AI well. we celebrate success, but we also talk about failure and what we learned about it. So one of these change management frameworks like art care really. Covers that, that whole journey, of a change. And then also make sure that it sticks.

Audrey Chia: 15:59

It's interesting, it's like a lot of people think that change is something you just do organically, right? But it seems like there are many steps in which you can take, right? So that you are facilitating the change, in a more structured way. And I think it actually helps that people have that safe space to experiment. Yes. And also interestingly, like what you said, get recognized, I don't think that concept is something that. A lot of, you know, organizations have recognizing people for their use of ai and I think that could be a very interesting incentive or a motivator for a team.

Dajana Achelpohl: 16:31

Yes, absolutely. And I'm also a big fan of, of having AI champs in, in teams or, whatever you want to call them, AI ambassadors. So people in the team that, really are bringing this forward and my experience. Team members also. Always believe it more when it comes from a team member, right? It's much better than just, just the top down. And then as you said, if there's recognition that goes with that, then that will be something that people will be keen on doing. I.

Audrey Chia: 16:56

Have you seen, for example, a difference in bigger organizations trying to adopt AI versus like your mid, medium sized businesses versus like small businesses? Have you, are, are there any like big differences between the organizations as a whole in their pace and speed and openness to adopting ai?

Dajana Achelpohl: 17:14

I think most bigger organizations that I've worked with, are completely resigned to the fact that AI is the future and that, that they will need to be part of it. And they're figuring out the how. That's then where, where change management, for example, can, can come in, but they have acknowledged that this is something that they need to do. Medium-sized businesses, then I feel that there is a range there. There's some that are really excited about AI and very keen to do things very fast and maybe sometimes forget to bring their teams along. Then there's others who feel that it's not for them, like we said earlier. So where then I would, for example, talk to one person in, in the leadership team who says, I think we really need ai, but nobody else. Think so. Can you come in and, and talk to us about this and show us what's there? So a, a range of the really excited, the more reluctant and everything in between. And then smaller businesses. I find that small businesses often really feel that AI isn't for them, which is so surprising'cause I feel it's, it's such a great tool to give a, an even playing field. Right. I've talked to a lot of small businesses who feel that this is something for the big guys. And, and not for us. And obviously, it's, it's amazing for them and many then once they start thinking about it, see that this is a huge opportunity for them to actually compete with bigger companies.

Audrey Chia: 18:29

Wow. I I, I, it's so surprising that you see smaller businesses are, you know, don't think that that's the right fit. When I feel that AI has made so many things so much more accessible for the smaller players. Right.

Dajana Achelpohl: 18:42

Yeah, I think it again, comes back to, me coming from, from the tech background and now you and I obviously doing a lot with AI and just being in, in our own little bubble in terms of usage and, and what we know and what we see. I just think a lot of people aren't there and a lot of small businesses also aren't there. So obviously it's becoming more and more, but I still, meet plenty who just feel that it's not for them.

Audrey Chia: 19:05

Interesting. Let's also talk about perhaps how, you know, non-technical leaders, right? Maybe in the smaller teams or medium sized teams can take a bit more of a practical approach to adopting ai. Because I think like what you mentioned, there are teams that A, just adopt certain tools and then. They just assume that it would work magic for them. And there are teams that think that AI is a solution to everything. Right. so how would you recommend like a non-technical leader, right, to figure out, you know, how best to integrate ai. Do you have a specific framework for that? I.

Dajana Achelpohl: 19:35

Yeah. So, what I can show if you'd like is this AI Building blocks framework, that I have and that, that I use when, when I, do workshops with teams. But I think it's something that anybody can use. It's very easy. Wow. So, I can show that.

Audrey Chia: 19:49

Yeah, that would be amazing.

Dajana Achelpohl: 19:51

Now let me see how I do this here. Now, can you see the screen?

Audrey Chia: 19:57

Yes.

Dajana Achelpohl: 19:58

Perfect. You can see AI building blocks. Yes. Wonderful. Then let me, quickly talk through this AI building block exercise. So as we said earlier, To get AI going in a team, you really don't just need the tool. What you really want to get to is to change the mindset of the people, right? So you want to have the skills to explore, adapt, and lead the AI driven change. And this is really where this exercise comes in. So it combines elements of AI literacy and AI ready mindset and change management so that you can help yourself and your team, not just to use ai, but to actually make it work. So, where I always recommend to start with this exercise is to ask the people in the team to pick a color. So just classify yourself. Where do you fall in? Have you never used ai? Have you tried ai but you were not too impressed? Do you use AI from time to time? Or are you an AI expert? Right, based on whatever colors people pick. Then we try to sort of put teams together that have elements of each of these levels of expertise. So you don't want people in one team that have or never used ai and you don't want a team full of experts. The idea is that they help each other here. So once you have your teams, then we will go through a couple of, building blocks.'cause I think of these as as very simple building blocks that all add onto each other. We won't go through all of them now, but these are the ones that I, usually cover. Starting with finding the right problem, then talking to AI like a pro, which includes basic prompting, fact checking AI using AI safely and ethically. And lastly, how do we make AI stick? So I would always recommend to go through a really easy exercise, and first of all, to ask the team to pick their problem. What is the one real problem that they have in their team that they want to solve with ai? I'm always asking them to write it down in one simple sentence. We want AI to do X so we can achieve y. Once, the team or the smaller sub-teams that we have divided the group into have agreed on that. The next thing then is that we are talking about what is a good problem for ai. So this is then where we are starting to learn. What can AI do, what can't it do? So very much, this exercise is built on, on learning in the moment and on learning on something that's really real for the group. So we are talking about how vague or broad goals are not good, for ai, how decisions without clear data, are probably not gonna work. That we don't want to use sensitive or confidential tasks here, and that AI still isn't as good as us humans and creative or strategic thinking. Then once we have discussed this with the team, we are asking them to adjust their problem and then we get started actually with ai. And an important thing here to me is that we always use whatever tool is already available. So most, organizations that I work with either have Microsoft, copilot, Google Gemini, or chat GPT. already in their organization. And that's the tool that I want people to work with. so no need for any new fancy tools. Then we ask AI to help us with a problem, and then 10 minutes later we come back and share the results. And that's then really when we start talking about prompting, where people go, oh, the results weren't as good. Then we can talk about why the results weren't understood. So all through this exercise, we are really block by block building all of these skills. I know we don't have as much time to go through the whole thing, but I'm sure you get the picture. An important point that I always mention. Is that those AI building blocks are really just the foundation, right? And that we should add on our, add on our unique human skills. All these not so basic blocks. If we stick with the building blocks, if we really want to build something. Amazing. And I think that's really key that we leave the team with that idea of AI skills, plus the skills that they already have to achieve something amazing at the end. Then I would always recommend that they don't just leave it at that exercise, but that they actually create a step-by-step plan how they want to implement the solution to their problem. And again, I suggest they just use, chat, GBT, Gemini, copilot, whatever they have. Already available to do that. And I find then that that, gives us something to start with and something where we have now a real problem that we are solving and those skills to do it. So yeah, I find that that is usually something that works quite well and I think it's something that's really doable for anybody, to run with their teams.

Audrey Chia: 24:20

I really love the fact that you managed to simplify such concepts and create a beautiful visual analogy to help people understand, you know, it's like building a, a beautiful Lego house together, but it's a matter of like understanding how you piece different pieces and understand the different functions, the prompts, and even tools available so that. You use it to solve that problem or create something better or new?

Dajana Achelpohl: 24:47

How, absolutely.

Audrey Chia: 24:48

How do people respond after you have your whole such sessions? Like are they, do they respond to AI in a different way? Do they have a different perspective? What have you seen?

Dajana Achelpohl: 24:57

It's actually, it's, it's lovely to see, I, I have to say, and when I ran this the first few times, you know, you're always a bit worried if this will actually work, but people are generally excited, right? And they feel that they have a new skill.'cause I think with all of the fear that we talked about earlier, that people might have, if you give them the skills and also if you tell them at the same time. Everything else that, you know, won't be obsolete.'cause there is certain things that AI is not good at. This is where you are good at and something that you should do more of. It gives people like a really new perspective and energy And, I usually, when I do these workshops, I, I check back in with the teams after a month. And after three months, et cetera, to see where they have gone with, with the problem that they have identified, et cetera. And I often find that this is a really good catalyst just to get them thinking more about ai. So it works really well. And

Audrey Chia: 25:43

I would love to also know what are some potential use cases for companies? So assuming, right, you get a team's buy-in and they're excited, and you really wanna start implementing, what are some like examples of actual use cases? That, you know, most companies can already start, thinking of when it comes to implementing ai.

Dajana Achelpohl: 26:02

So I think coming back to that personal efficiency, productivity or team productivity team, topic, right? I think there's this easily 20% of, of time spent currently in most teams on things that are just that tedious, repetitive work, right? I think even tackling that first. It's very powerful. And then you can, of course, then move on from, depending on, on whatever industry, the, the teams work in right to, to then find more things. But I think that the productivity element is really, really powerful. It's also something that you can usually measure. In time, and it's something where you then have that ai ready mindset in the organization. It can be small things, right? it can be how, how they do reporting, how they analyze data, how they keep notes, et cetera. That there's so many things that many teams spend a lot of time on. Nobody wants to do it, but it needs to be done. So, so let's get AI on board and let's get started there.

Audrey Chia: 26:58

Yeah, and I think the productivity and the time savings that you get from using AI adds up. I would say that I have saved at least 70% of the time that it takes to create any piece of content with ai. But it wasn't also instant, instantaneous. It took time right to yes, build that muscle, understand the tool, understand the nuances of working with a specific. M how it responds. Sometimes a bit lazy. How do you prompt it again?

Dajana Achelpohl: 27:24

Yes. Yeah. You won't

Audrey Chia: 27:27

Skillset. Yeah.

Dajana Achelpohl: 27:27

Yeah. It is a skillset and it's a muscle that, that you need to practice and you won't get everybody in in the team who's gonna be that enthusiastic. But even if you have a few people, right? Those AI champions who keep this going and if they are supported by leadership, they get the recognition for it. The whole team is brought along. I think there's, there's so much that's, that's possible. And AI is gonna be like an expectation, right? There's gonna be an expectation that people know how, how to use AI in the not too distant future. We might be further away from it that than we sometimes think, but I think most people do see the potential there. And once they have that little. Starting point and an in, they get really excited about it.

Audrey Chia: 28:08

Now, this is gonna be a bit of a bigger question, but what do you think the future of work could be like, you know, with ai?

Dajana Achelpohl: 28:15

Yeah. Who knows? There's, and so many different versions of, of what people are. Right. To me, like I said earlier, I think there is gonna be an element where being AI literate, having AI skills is gonna be like baseline. It's gonna be an expectation that everybody knows that. That then also means that other skills are gonna be more important. Right. Think about people being able to explore new ideas quickly. Being able to adapt quickly, being able to like, come up with new ideas. Maybe with the help of ai, I think there are certain skills that people need to, lean into more and learn more of. I hope that we are gonna see companies going out of that pilot phase for ai that we really see it. See scale for AI and that this is something where we have that scenario where we're working alongside ai. AI is doing what it does really well. Humans are doing what we do really, really well. And overall we do more things and more good things. I think obviously AI ethics, are gonna be a huge thing. AI governance. I am based in the eu. We obviously have the EU AI Act. come in our way. There's gonna be a lot of questions around how do you regulate ai, how do you use it in the right way without stifling innovation competition? So I think that there's, there's a lot of big questions, but I'm really encouraged by the amount of people that are using AI for really, really generally good use cases and, and to better the work life and life overall for, for all of us. So, I have, I have great hope that this is what AI is gonna mean for all of us. Better, a better situation. Yeah.

Audrey Chia: 29:53

I think what would be interesting, at least from a marketing or creative point of view is I think as I. More and more people are gonna use ai. It's gonna force brands to become more creative because you will need to stand out in the sea of noise. Yes, in the sea of content and in the future. Content will be hyper personalized. You're gonna see a lot more of it, and it will be less and less, I guess. Apparent it's AI generated because extra as G PT evolves, you can really tell that its writing style is gradually getting a lot better. Yes. But in the past year, so that will be really exciting to see. But with that, Diana, maybe to end things off, what are some of your favorite tools or tips, you know, when it comes to using AI that you can share with our listeners?

Dajana Achelpohl: 30:39

Of course. so my, tech stack is actually not, not that fancy. but I do use, I use chat CPT of course loft costume, GPTs. I think that's, that's something that, that people should explore straight away after they, they have the basics least Gemini explored loft Perplexity. obviously, I do use notebook LM a a lot. and I think it's actually a really undervalued resource, especially to, to keep up, to date with things, quickly. I, I use Fathom for meeting notes, et cetera. I'm a big Canva fan. My presentation earlier was, was Canva. I like Ideogram for images, and I know a lot of people think Ideogram isn't that great. I still love it. and I use Notion, so it's, it's fairly basic, but with time I really find that I can get them working with each other. It's, it really works for me and I'm always open to adding new things. I think one of the things with AI is there's so many tools, right? You, you could spend your whole day trying out new tools. Where do you start? Where, where do you stop? I try to practice what I preach and always have a problem first before I just jump on a tool. And I feel that that, helps me, but I still spend a good bit of time playing around with tools and some of them are so much fun. Which is great, and I would recommend that to anybody, right. Have that, that playfulness, that, that joy in it as, as well. It's amazing, what AI can do. So if you can keep that excitement and, and play around with it from time to time, that's actually great.

Audrey Chia: 32:08

I think it's also a beautiful day. We are in this, you know. Space and time where we actually get to experience Yes. Something so incredibly new, right? Yes. I don't think many people get to have this kind of exploration, in a new technology that really is a huge victory for so many of us. So I myself find so much joy, experimenting, and for you listeners, I hope that you guys will also find joy in that, like what Diana said. So Diana, where can our listeners find you and who should reach out to you?

Dajana Achelpohl: 32:38

Of course. So you can find me on LinkedIn and also my website, ai changemaker um.com. So if anybody's interested in talking about AI and change, how can you, Get started with ai, how can you get your company a bit more excited, about ai? reach out and I'd love to see how I can help.

Audrey Chia: 32:54

Awesome. Thank you so much, Diana, for sharing your lovely insights. It has been amazing. And thank you for tuning into the AI market, this podcast. If you are interested and wanna stay in touch, hit the bell for more actionable marketing insights. We will see you next week. Take care.