The CTO Trap

Welcome to Applied AI Australia. I'm Raman Rodriguez. This show cuts through the noise and delivers only on what matters, growth, margins, and time. Each week, I translate AI into practical outcomes leaders can actually use. Today, we're in conversation with David Nord, CEO and founder of Pathfinder. Today, we're going to expose the dangerous illusion gripping corporate Australia. Right now, execs are pouring millions of dollars into AI and handing their company's future to their CTO, a consultant, and even a tech vendor. But the truth is, AI investment failures aren't technical. They are leadership failures. You can't scale what leadership doesn't use, and you can't govern what leadership doesn't understand. In this episode, we're going to unpack the CTO trap, and we'll end with a 48 hour challenge so every leader can take action. Because real transformation doesn't start in tech, it starts at the top. Let's get into it. David, thanks for coming on the show. Uh, no worries. Thank you for having me. No problem. So, obviously, Pathfinder, you've had some extraordinary growth over the last couple of years. Well done. Thank you very much. It's been uh pretty hectic like learning as much about entrepreneurship as AI during that time. Um, whilst AI itself has just been getting more and more capable. Um, and people also being more and more confused of where to start and overwhelmed. So yeah, it's been it's been really good. Yeah. So a bit of a candid chat that we want to unpack today. The numbers are saying over 80% of AI investments in Australia are currently failing and you know in enterprise Australia that's north of $25 million, $28 million to be precise. I don't believe it's a problem with the models or the technology. I think it's something a lot more basic than that. It starts with the executive. What's your view on that? I think a lot of it also comes down to like our understanding of this technology and the role it plays has has really shifted over the last few years. Um the there's no like early on the models were they weren't nearly as capable as they are now. Um so there's all sorts of ways of measuring this. Um there's all sorts of evaluations and benchmarks but the models that we have now they're drastically different to the ones we're using two years ago. I think like that term of most companies things are failing with AI. A lot of that comes from things aren't going from pilot to production, it's not going live, that type of thing. Um, but there's many reasons why things haven't been going live. But what we've also realized is that if you do actually just use what's available, um, and use it in its simplest form, don't try to over complicate it. Don't do um a massive amount of um customization. Don't try build something like like um autonomous agent and all these things. Just actually start by becoming power users of of a model. There's tremendous value to be found just in using a tool like chat the enterprise or claude off the shelf. But it's not used at all well um if your executive team aren't using it um themselves first. So that that's we find is the biggest unlock. So let's talk about all these surveys and these reports coming out. State of AI what 70 80% of organizations in Australia are deploying autonomous agent agentic AI I call [ __ ] on that because from everyone I speak to I would say less than one in 10 are doing that and some of the execs I speak to some of them don't even know you can upload a PDF into chat GBT. And that's no disrespect but if you think about execs you think about boards their prime job is to govern manage risk. How do you know what that looks like when you actually don't know what you're managing? No one's saying that people need to turn into being coders or developers, but you need to have a fundamental understanding of what you're investing millions of dollars into. So, a lot of the reports um it's really important with any report that anybody reads that they um look at the the survey data um the methodology, all of that. Um there's one report um like from MI MIT that came out um six months or so ago saying 80% of like all um AI initiatives are failing. Um and when you look at actually the the survey data in that it like the methodology of doing it was was incredibly flawed. Um and even a term like uh have you deployed agents which they're getting a um from a survey um well first let's agree on what the definition of an agent is um and which there isn't um there isn't a standard um industry definition for that but the the biggest thing with this technology is that it it is unlike um any other technology that we've ever seen and how it it isn't predictable. There are ways to kind of contain it and limit the answers that it gives, but we've never had a technology that's so good at so many different things. And that is very very challenging for a board or any leadership team to kind of figure out how do they wrestle it because your computer only being your let's say you use Microsoft Teams. Um you don't have to train people up that much on how to use Microsoft Teams because you can only use it certain ways. I can't ask it to write a document or to or to do research for me or to do all of these other things for me. Um because it just simply can't do that. I can't check if it does it well or not because it can't do it. Um and that's the big challenge with AI is that like if you can't get a predictable output each time, but we know that it's very um good at what it um we know that there's tons of value that it can bring, but it's so broad. How do we um how does a board then kind of limit its use? um govern it, derisk it and things like that. All of that is a completely futile argument um or conversation if you have no clue um like if you haven't actually used it yourself or you know how how it works um and you haven't applied it for yourself and that's usually what the biggest unlock is is when people start using it themselves first. It helps you understand the risks and things that um it may or may not have. Yeah, I completely agree with everything you're saying. The general rebuttal I have from a CEO or an executive, I've got a CTO for that. So my question is, are you going to give your CTO full control of some of your biggest organizational levers in the next 5 years? CTO is a completely high value roles, right? But this isn't a technology transformation. It's a business transformation and people are at the heart of it. And to your point about, you know, getting people to actually understand what the value it is. I firmly believe AI adoption stalls and people feel like it's getting pushed on them and they don't understand the value it brings. If the CEO is understanding the importance and the value it brings, from the CEO to the B to the doormand, everyone's going to start to see that value of practical use cases. So one of the biggest things with this technology is is that um uh every leader has a particular role to play on a sea suite with with this technology. So um the CEO and the board uh their first question is what does this actually mean for our business model our long-term survival if you're in um if you're in a services industry at the moment um the board and the the um seuite should ab and the CEO should absolutely be talking about like how do we um leverage this technology how do we how do we evolve our business model to leverage this technology instead of competing against it um u a CIO, CTO, they're all uh they're in charge of making sure it's secure and compliant. You shouldn't be outsourcing your your company's destiny uh to that group. It's an it's an unfair expectation on a CIO to not only um understand the technology, figure out which uh vendor provider they should select, how to deploy it, um how to evolve the business model for it, like it's it's completely unrealistic to do that. they're there to make sure it's secure and compliant. Um the um your chief people officer is um hugely important in this as well because they they're looking at the um the future of work um the future of role descriptions um also it's a huge change management and adoption challenge and cultural challenge um as as part of this as well. Also, one of the weirdest things about this technology, and it's being demonstrated more and more as the models keep getting better, is even if your tech team does no work, zero work, literally doesn't lift a finger. Um, this is hugely hugely valuable for a typical business office worker, like hugely valuable. We've never if you deployed just let's just say a CRM like Salesforce, you did nothing to it and you just gave it to people in the company, it is worthless. It's useless. um it has to be configured for your workflows and all of that. Um AI is this technology where if you just gave people chat GPT um and you showed them how to use it like it's hugely valuable like um and so we don't really have a technical challenge anymore. We have an an adoption challenge um which is um which is one of the biggest things. Yeah. Yeah. It's not a tech problem. So going back to capability, how much is enough, right? like you know how much does an executive need to know. A good example is I had that a little while ago with a logistics client and they didn't want to get into the detail. Three four months on they came and told me they solved a million dollar business problem and it wasn't with a multi-million dollar AI stack was essentially just using claude to upload some of their financial data. They spotted a trend. They spotted a double up in some contracts and were able to wipe it. Now that isn't complicated but for a human to pick that it's pretty hard right and the power with AI is its reasoning. You can see things in large amounts of quantity and context that we may not necessarily see. But the cool thing about that story is it wasn't a super technical agentic AI agent. It was literally Claude uploading a file. So how much do you think the executive needs to know? What does capability look like? They don't need to know a lot. Uh there's a few small things. Um okay. So the two biggest things, one is inspiration and the other is capability. So actually knowing what to use it for is a huge um is a huge gap. Like that's people they hear AI all the time. Um but they're not really sure what to use it for. And also they often think it's for other people not for them. So for an exec exec should be using it. The first thing they'll go is like great but but what should I be using it for? And then the second thing is how to use it. Okay. So what should an exec be using it for? The number one thing an exec should be using it for is to make better decisions like the example that you gave. So an execute get far less excited about it optimizing their inbox and um taking meeting minutes and all that. Those things have a role to play. But we we also know that like some of the best execs in history um are people who are very very disorganized. Like you look at people like Richard Branson and all of that. Um so just being better organized of course of course it will help. Um but that's not that's not where the gold lies for an exec. The gold lies in actually um using it to improve all the decisions that they make and something as simple as we're deciding which vendor to give this contract to. I'm think it's based on all the evidence this vendor looks like the best one. Can you critically evaluate these contracts and and see what you think and come up with a framework that's not making the decision for you, but it's it's helping you make a better decision. The problem with that example is it falls over if you don't know which model to use. And so what execs simply need to know is that there's two types of models. Those that think and those that that don't. And um any exec just needs to get into the habit of just living using a reasoning model and not a um just an instant base model that will solve 99% of of any of the issues that that you have. Um and now even the agentic capability is just all it's starting to just be built into the reasoning process. Anyways, it doesn't need to be built for you by a tech partner. Yeah, just on the reasoning part that is a critical part of it because tiding your inbox and managing meeting impact, you know, is great, but it's not going to fundamentally change your P&L, right? One of the things I often think about and speak about is the problem that executives are facing. There's going to be a business that would have experienced a very similar problem somewhere in the world at a point in time, right? these large language models can reason and pull pits of information together that we can't see. So the real hard problems that the organization and the leaders can't seem to work out themselves are taking it to it giving its hardest problem providing all the context and getting the AI to pressure test and come up with new ways of thinking and solving organizational problems and opportunities. Yeah, that's um that's a really really good way to use it. And um you'll give it a whole lot of information. It'll come back with a response um that'll make you think about it in a different way. It'll make you have more questions and then you keep just going back and forth with it. And that's where this whole term of uh vibing um comes from is this approach of like I give you some direction, you produce a result and then um I look I look at your response and then I ask you again. Um and um there there's some small things though that people can do that will make just a a huge difference to the um the result that they get and and one of them is simple is literally just asking the AI to ask you a few questions before it produces an answer. So if I said hey what should I I'm trying to optimize my marketing for this year. Um what are ways that I should what are ways I could do that? That's going to give an answer. But if I said what are ways I I can do that but ask ask me five questions before answering. It's going to say, "Okay, great. Where do you see where do you feel is the um is the problem at the moment? Um what are you trying what customer group are you trying to optimize for?" All of that. Those types of things that you would typically um be instructed to like prompt learn prompting and prompt structures and all of that. Much quicker hack is just simply saying, "Hey, just ask me a couple questions before you answer." Yeah. But even something simple is uh just voice. When I was walking over here, the prep I had is I told them about the podcast I've got going on. I was someone probably thought I was in the phone. I was talking to chat GBT voice prepared me pressure test me and I do that not just for you but all sorts of meetings I go into and I often walk in the most prepared person in the room because it can give me a level of synthesis and data in a form that I like and can take in. The um yeah definitely the voice is really powerful um on car drives as well. So yeah, that's more on um like the voice mode instead of just dictating ends where you're having a conversation with it. Um but it's a really productive way um to spend an hour if you've got a an hour commute somewhere. Um one of the best things you can do is just open chat GPD, flick it to um voice mode and just just have a conversation with it. Um it's really really powerful. It'll take you like nobody with everything AI related. Um there've been so much talk of AI, so much noise for the last few years that nobody's ever going to believe this unless you you have to try it for yourself. Um but the first time you use voice, you will um you will get like um some really big insight and unlock. One of the one of the things with voice is there is a trade-off. Um and that is its reasoning ability. So when you typically when you're using voice it's not as smart a model um because when we're conversing with somebody uh we don't expect them we're not willing to typically wait for 10 seconds 30 seconds 2 minutes for them to research their answer before responding. And so there's there are ways you can prove that but your your role of like actually giving more context and prompting is actually much more important um when you do things over voice mode. So actually, and this is where um the tools AI in general um the more of a power user you are, the the much better results you're going to get from it. Um and so on voice mode, typically this is where you would um learn to say things. Oh, can you make sure you do a web search before you answer? Whereas, uh when you're using a thinking model, um on text, you don't have to say that because it'll just know for this type of thing, I'm going to do a web search first. Um but this is this is kind of edge cases. Um um even if on on voice it's also sometimes you're not trying to solve something. You're just actually um you're just brainstorming. You're just trying to get more information. It's not it's you sometimes not not as big a reasoning task. Yeah. And with the reasoning ability that's particularly on the voice mode, you know, sometimes it's not, but I think I use that a lot when I'm driving, but particularly when I'm just walking, talking, trying to work something out. So it's very interesting. There are hundred different ways to cut the cake there. But if we go back to the CEO, the CEO largely they've got to that position because they've done a bunch of different roles, but their role is to be a generalist, right? They need to know a little bit about everything and specialize in some cases where possible. The great thing about if you move into something like Notebook LM, you can essentially be anything to anyone in a short period of time. So for me, one of the first things that we're seeing is AI is actually creating new skill sets for people they never had before. not just improving but actually creating it. Give me 20 minutes and I can be an expert pretty much on anything to anyone just by popping something to notebook LM turning into a podcast and synthesizing and that's cool but when you apply it to a real problem or a real opportunity within organization it does wonders. So the number one way I use AI is full learning like by by miles like this is I use it for this all the time. Now the crazy thing about this is is that a tool like Notebook LM is so powerful and everybody already has it uh for free because everybody has Gmail accounts. Um and so that's one of the crazy things about this technology. Uh and I think this is also why there is some resistance to this tech because in some ways it's almost too good to be true. Like if you're a if you're a CIO and you're used to paying millions of dollars for um a tech implementation just in license fees and also in implementation costs and all that to have tools that are anywhere from free to $25 a month that um are so incredibly powerful. It's not like I think the resistance comes from an irrational place just because it's so weird. It's almost like an input output error. It's just like I'm not processing this. How can something be this good? You just need to know how to use it. there is a small learning curve um that's required of all of this whole technology that makes a huge huge huge difference. Yeah. And its most basic forms. One of the fundamental problems in a big business enterprise for middle level and senior level is finding information, right? Because you know you should know something but it's in 10 different places and you spend your day chasing your tail and putting out fires. something as simple as getting those bits of information and data and centralizing Notebook LM. What we did was instead of ping three different people to find out information about a product, audience, whatever it is, put into notebook LM, it knows everything about a product or vertical within your business. And if you put that down to their impact in terms of time spent and output, it's amazing. It gives a clue just how transformational this technology is going to be over the next 5 years. But one one of the big things with AI is doing things in um reimagining how you do things instead of just optimizing how you used to do it. Now one example of that is think of a tool like uh Copilot that you can point to a SharePoint folder and create an agent that points to a shareoint folder. That's fantastic. It's really helpful. Um but let's say you're in sales and you want to have sales best practice known by everybody. And this is where um CRM have tried to do this for ages. If a deal's been won, um they mark the reasons why. All of that usually terribly adopted. Terribly. I've never seen a world adopted at all. Um and then you might have um like a deal review or win review meeting that people turn up to um or they don't mean it gets moved. It doesn't really happen that often um to try capture that information. But one much simpler way is you would just literally have a channel have a team's chat and just say whenever you have a um a successful deal has been closed. I just want you to put in there as like a voice note just ramble in there what was successful, what was unsuccessful, what were the key things that that win this deal. And you can with co-pilot you can actually point an agent to a team's chat. Um, and now all of a sudden, I mean, that's taken the person 1 to 3 minutes any time of day. Nobody ever has to read that channel. The only thing that needs to read it is um this AI agent that again is all part of a co-pilot license. It'll synthesize all the results um for you. Creative ways to do things. Yeah. Just one more example, then we'll kick on to the capability just comes to mind because you're thinking about salespeople. I was working with an organization. They ran a large call center, right? And with the sales team, there was high performers, there was low performers, and there was the mediocre. And that's the classic case in any sales team. But the question the sales team is always asking is why? Why is Joe a 10 out of 10 is why is Billy a two out of three? And they've got the same amount of hours in the day, trained on the same skills, but big difference. So what we did was got all their call recordings and uploaded into the LLM. And over a period of time, what they quickly realized it was Jerry's prospecting of the type of clients he was speaking to, even though he had the same amount of time on the phone. This problem had been going on for years, costing millions of dollars, and they couldn't work it out. But very quickly, the LLM was able to point it out. You know, very practical, very simple, but very useful. There's um there's so many things like that. Um, one of the big things with this is, uh, there's a lot of things that AI can do that yes, you could have done those things in the past. It would have been harder and taken longer. Um, but it's often it's in the moment. Like if you're a, in that example, if you're a sales leader, sales manager, you go, geez, why is this one person like just crushing it compared to the others? Like what are they doing that the others aren't? Um, usually when you come up with that thought, like that's your focus and you want to pull the thread on on it at that point in time. Um, where like there's this term inspiration is is perishable, which is important. Um, and very true. But in the in the old world, if you wanted to deep dive and try to find out why one sales rep is is not performing compared to another, having that as a whole project, um you're gonna you're going to go on to something else next week that is going to dominate your thought space and your mind and all of that at that point. But the ability for anybody when the when the thought arrives actually pull the thread on that go, I wonder, oh, what does best practice say or what's a way of now like um incentivizing people that are quite different? And it's it's as if you've got the world's greatest sales coach that all of is set standing right next to you and when you want to like dive into things you can with them straight away. So I think the speed of being able to act on these types of light bulb moments is really important. Um and uh that's a that's a huge unlock. And while we're talking about middle level leadership there that goes all the way to the CEO's office. If you think about emerge and acquisition, how much time and due diligence is spent on that? You know hours and hours upon days. Now going on to obviously capability is key for the executive right and the organization. We spoke about it before in terms of what does good look like but how would you define an executive that is capable with AI generative AI. So the number one is just become a um a power user of chat GBT. Even if it's not the tool that your company is going to be using as a sanctioned endorsed like companywide tool as a leader it should be the tool you should be using as a starting point because it's what most of the world uses and so your customers are using this. Your your grads that have been using it all through university using this. So that's the number one thing on that is just purely out of proliferation out of the volume and particularly your customer base. It's a great daily driver. Now um like where you start is very different to where you end up with multiple models and tools like that's where you end up. Now one of the mistakes that people make is they go ah I use this tool it actually has access to all of it has access to chat GPT and Claude and Gemini and all that. It's actually no, you're talking about the model itself. There's much more to a model than just the model like um and it's become more and more complicated. So you have the model itself, but now you have how much thinking you actually allocate to it. This is very new. This is a year old like 03 which was the real breakthrough um open AI reasoning model um um is not that old and then we had DeepSeek which is a real breakthrough um with R1 with reasoning. We're talking about things that are just over a year old. Being able to um like as soon as you go off of chat GPT and you use GPT 5.2 that's part of another tool, there is somebody from it that has decided how much it thinks. Now, the more it thinks, the more they pay for it. And so therefore, they're incentivized to not let it think that much. When you're just using the chat GPT license by yourself, you it's an all you can eat buffet. You can set that um reasoning as high as you want. No, I agree with what you're saying. the chat GBT point. I think mine would be very similar to that would largely be though if you think about it from a leader perspective, what is on your desk at the moment? What are you working through? What are you struggling with? What you want to do that you don't have time to do? And just play with it. Similar to your point, become the power user. Then you'll truly understand how to approach it. Because if you're thinking about looking at your strategy and thinking about how AI can help, sometimes you can't spot how AI can help if you don't understand what it can actually do and the potential it can actually generate because often it sort of does feel like magic. It does feel like it's too good to be true. But the reality it is here with some limitations, but you need to understand what that looks like. Get it to do a career reflection. Like that's that's the number one way. There's not a single leader on the planet that is that isn't wondering, geez, I want to be spending more time with my family or I was burnt out last year, I don't want to be as burnt out this year. Am I like not feeling like they could be doing managing their day differently? Every single leader on the planet um feels like they're dropping the ball in some areas and that they're doing okay in other areas all the way through to complete burnout. Um, and the right thing to do would be to get like a really good leadership coach. There's a couple of problems with that. Let's say you could afford one. Well, first you have to find them. And that's really hard to do. It's going to be unique for every single person, different personality. The second thing is um they're only available one hour a month or long you you do that. Now, I'm not saying don't get a leadership coach 100%. But what everybody can do immediately is actually use a tool. And in this case, I'd actually recommend Claude by Miles. If you were to just say, "Hey, help me do a career reflection." Um, it's got you're not going to get a great result. Just the prompt will need to be a little bit different. I'm using Claude for the first time. I'm a leader. I've heard that this might be able to help me reflect on my career, but I'm not sure how to do it. Can you can you interview me and help come up with an approach of how I could use Claude to help me reflect on my career? Now, that's the first prompt at basically telling Claude, "Teach me how to use Claude." Um but after that you will you'll go down a rabbit hole and the value that you get out of it is remarkable. The other fundamental one that I get a lot David is who I need AI capability in my organization right so do I get one of the big fours in do I get one of the boutiques in do I need to have you know in-house help do I need to hire a new team you know one of the big things I'm a believer of is you're using AI to solve a problem and application so harness your own guns I think some of the best capability is sitting right in front of you you just need to empower them to be using it and solving the problem what's your view is the first person and they call the consultant. The first thing um every leader has to realize is that everybody is figuring this out and people haven't figured this out and that it's your responsibility to figure out it for your company. Now the issue that you have if you go to a consulting firm is they're also figuring out who they put on it and then what else they have what else that person has on their plate. I think AI is quite the specialist field and I I say everything from your search engine optimization agencies. I don't know if they're the right people to be going to for like generative um optimization services. They're all advertising it as well. I I think it's so niche. Um I would want to be going to a company that that's all that they do is they're figuring out how to have their search results show up in AI. try to find a group that that's all that they do is specialize in in AI advice or adoption or something like that. Number one thing though is um they need to demonstrate that they're a practitioner. Like you should treat it as a huge red flag, massive red flag. If you go to a big four consulting firm about AI and they issue you a PowerPoint proposal, like this is a huge red flag. There is no reason why you should be getting a PowerPoint proposal back. That's a slow manual process. And also if you are all in on AI, you know how incompatible PowerPoints and slides and all of that are are with AI. And so people in in that field, we flipped to um ages ago to micro sites and PDFs, but that are generated through um through this highly visual code and all of that type of thing. And that's where that's really easy. So I would the first thing I would ask anybody who's pitching you the AI services number one thing number one thing is say oh I'd love to know how you used AI to prepare for this meeting and if they don't if they don't get super excited to show you oh it's amazing I never get asked that and they flip their laptop around and they go I use chat GBD for this but and that look you can just get so far with this um and then I did that like then it's a huge red flag. What would you say for the executive listening to the call today is the 48 hour action that they can can implement the next one to two days? Grab Chat GPT. Um, get a paid license and the first thing you do is can you interview me and help me find all the ways that chat GPT could help me reflect on my career and come up with a 100 day career plan. Just that process will make a huge difference um of unlocking what's possible. The second thing is then actually still using that process to then say um uh can you interview me? Can you ask me 10 questions? Really important to prompt it um to ask you those questions and help me come up with all the ways I could use AI in my role. And so start using AI to to learn AI. Now there's one bonus thing. Uh start having fun with it at home. So, uh, put it on your, uh, put the mobile app on your phone. Um, get it to create, um, a quiz with your kids on their favorite topic. Get them to choose the topic. Put it on voice mode and say, um, want to play Who Wants to be a Millionaire? Get your kids to choose the topic. Um, and done this. My son loves poison dot frogs. And so, playing Who Wants to Be a Millionaire about Poison Dart Frogs. Now, what's happening through this is not only is it fun and engaging, and thank goodness we've got a technology that is like that, um, but you're also learning about lots of things. What have you just learned? You've learned how good it is at personalization. You've learned how good it is at voice mode. You've learned how responsive it is. Um, so you're actually learning about AI. You're not just learning about the app. Um, and kind of the fun you're having. So, those fundamentals, have fun at home and and do some career reflection would be would be two big ones. Love it. I think for me what comes to mind is first of all if you don't have it installed in your mobile phone, have the damn app, have it downloaded because that's where when you're on the move thinking download it. And if I had to give you one other thing after that would be it's very simple. So we're not talking about API, you know, connection. It's nothing. You just authorized your Gmail and calendar through chat GPT into it. Click deep research and ask it to do a bit of a audit into what you're spending your time on and where your blockers and opportunities are. and you will be amazed the amount of insights that it will pull and then from there the use case will be unlimited. Yeah, that that's huge. Um, another one that's really powerful with that feature is um get it to do an account briefing on one of your top uh customers or suppliers or something like that because even though you might have an ERP or some contract management system, whatever, all of that information has already landed up in your inbox somehow. they've they've sent you the contract to sign all of those types of things. And so you've got a full history of and interactions including all the people you've interacted with there, all the contracts you've signed, everything. It's all there in your inbox. Um and so that's one of the ones that uh usually causes a jaw drop moment. We could go for days. So how does the audience get in touch with you, mate? Yeah. Um definitely LinkedIn. Yeah. Great. All right. Well, lots of gold here today. You know, have to contact David. Awesome. Thanks, man. We'll catch you next time. If this was useful, make sure you subscribe. We publish regularly. One podcast, one newsletter each week. All you need to stay informed and execution ready. If you want to understand where your AI reading sits, head over to appliedustralia.com.au/schoolcard and take the 5minute assessment. Now remember, you can't control the speed of change, but you can control a frict. Thank you. My name's Ramon Rodriguez. This is Applied AI. Thanks for listening and I'll catch you soon.