Speaking Your Language
Speaking Your Language is a Configur podcast about implementing AI in your business to deliver real results.
Host Marco Oliver, CEO of Configur, brings over eight years of experience in the AI space. Each episode, he sits down with AI specialists, sector experts and clients to unpack their experience of AI transformation, what worked, what didn't, and how to get an actual return on AI investment.
This isn't a show about tools. Marco digs into what Configur preaches in practice: getting to the heart of the problem before reaching for the technology. Done right, that approach reduces AI spend rather than inflating it, because it addresses the core pillars that decide whether transformation succeeds. People. Data. Use cases and USP. Security and governance. Measuring implementation.
It's a no-nonsense conversation built to help small and medium businesses work out how to implement AI the right way.
Less hype, more help. The no-nonsense podcast for AI in business.
Speaking Your Language
Episode 1 - People: The forgotten AI transformation step that can lead to success or failure
Use Left/Right to seek, Home/End to jump to start or end. Hold shift to jump forward or backward.
Most AI projects don't fail on the technology. They fail because people are not involved in the journey.
In this episode, we're joined by Simon Drinkwater, founder of Vantor Advisory and a Prosci-certified change practitioner with over 28 years in people strategy and organisational change. He founded Vantor Advisory to serve as a trusted conscience for SME leaders under pressure to modernise. His focus is on making sure innovation strengthens leadership capability rather than layering technology on top of existing dysfunction.
We get into why people are the load-bearing pillar of any AI rollout. We discuss the reason for taking your team on the journey rather than dropping tools on them: a clear strategy before any software, an honest narrative about what AI will and won't do, and naming the places where you choose not to use it at all. Set those expectations early, and you avoid the fear, the quiet resistance, and the stalled implementations that sink most projects.
This one is for any leader who wants the transformation to actually stick.
Less hype, more help. The no-nonsense podcast for AI in business.
Big thanks to Nxt Gen AI for sponsoring the series. They're hosting an event at the ICC Wales this June, where Marco is also speaking.
Use code configur for 10% off tickets → https://nxtgenai.co.uk/Landing
Follow Configur
Website: https://www.configur.ai/
LinkedIn: https://www.linkedin.com/company/configur
Instagram: https://www.instagram.com/configur_hq/
Facebook: https://www.facebook.com/configurhq/
TikTok: https://www.tiktok.com/@configur_hq
Follow Marco
LinkedIn: https://www.linkedin.com/in/configur-marco/
Learn about Vantor Advisory
Webiste: https://vantoradvisory.com/
LinkedIn: https://www.linkedin.com/company/vantor-advisory/
Follow Simon
https://www.linkedin.com/in/simondrinkwater1/
Welcome to Speaking Your Language, the AI podcast that is focused on how you really implement AI into your business. No hype, no noise, no jargon. And today's special guest is Simon Drinkwater of Vantor Advisory. And the reason he is here is because this first episode is focused on the people. And people is a massive, massive part of business implementation of AI. I'm going to let Simon introduce himself and tell you why. So over to you, Simon.
SPEAKER_02Hi. So yes, I'm Simon Drinkwater. My business is called Vantor Advisory. And our focus is always on the people aspect and the organizational aspect of adopting AI. Many people think about you start with the tech. From my perspective, is very much you start with the organization as a whole, which includes the people, and then you work your way down. So I spend my time trying to look forward, if you like, into the future and think, you know, what's technology doing? And then bringing it back to the sort of the reality of well, what does that mean today? And I'll always start with a leader, uh, make sure they understand what uh AI is about and what they're how it could help their business. And then we can dive our way down deeper and deeper, ultimately down to the workforce. Great.
SPEAKER_01Well, I'm glad to have you on because we've worked together for a long time. We have. And uh I think we've we've swum in very similar ponds, but people often get confused, don't they, when um talking to people in AI because everybody has different focuses in different areas. So let's really get into. I'm a business owner. Let's start there, right? I'm a business owner and I come to you, so I'm gonna say, I'm looking to bring an AI into the business. Where do I start? What's your go-to for that?
SPEAKER_02So my starting point is always them, the the leader, if you like. So the person who ultimately is gonna be making the decisions around, well, where do we go on this journey? How do we go about it? Do we need to invest? Do I need to change the shape of things? So I'm always gonna start with the business leader and ask them questions about themselves. What do they understand AI is? What do they think are the challenges they're gonna face? What do they think the opportunities are going to be? Um, and that gives me a good sense of you know where they're at. Now, one hand, if they're really sort of up to date, up to speed, they've got their their fingerprints all over it, then we can dive deeper quickly into more about, well, so where we're gonna, where's this gonna go within your organization? If they're in a place where like, I don't really understand AI, don't really understand where people fit, where data fits, where governance fits, then it's a different conversation. Yeah. And every leader in every business is gonna be unique.
SPEAKER_01Yeah. And I and I think the first thing we can say to anybody that's in that position where they're unaware of what's going on, um, the reason that we do a lot of talks, for example, uh and are doing this podcast, is to just say, just start listening to what people are saying about this. And also I think the thing that people forget is you can learn so much from AI just from a large language model like ChatGPT, Gemini, Copilot. You ask it about itself, right?
SPEAKER_02Well, it it it there was a um years ago in one of my in a company I worked in, they talked about restless curiosity. And and that's really what you've got to think about for you for yourself as a leader and then with your people. You know, you need to be really curious about well, what is AI? What can it do? What are the risks? What are the upsides? Um, how can it help me in my job today? How could it help my team? Yeah. You know, this but there's there's so many questions. And as you say, yeah, you could use Chat GPT or whatever to sort of try and get some answers to those. But bottom line is you've got to go on a journey of discovery. Um and you know, that's for me, that's the exciting bit.
SPEAKER_01Yeah. And, you know, I think when we're talking about business leaders coming and speaking to you, that's typically sort of SME size, I would imagine. More, more.
SPEAKER_02Yes, and no. Um, so I've, you know, uh yes, of course, SMEs probably what I would say would be my target audience. But in reality, I've had a lot of conversations with public sector senior leaders as well. And equally in in sort of private sector, you know, there's in some ways, I would say that, you know, all of this is sector or business size agnostic. I agree. You know, it's it still boils back to, you know, you only know what you know. Um, I think the more interesting bit gets probably when you start talking about different organizational sizes, is how quickly are they going to move?
SPEAKER_01Yeah. And I and the reason I asked that question is I think sometimes in larger organizations, you can have a disconnect because there's transformation experts that are tasked with implementing AI, but they don't necessarily get a steer from senior leaders uh on why or what direction. They just say we need AI in the business. And that can sometimes happen at an SME level. And they say, we need AI because everyone else is using it.
SPEAKER_02So I can give you an example, but Craig, going back about 10 months or so, I had a reach out from uh a member of an HR team of a global financial services business. And um, she was like, I'm just looking for someone to help us um with AI in the HR space. Uh and I asked a couple of questions. I said, okay, fine. So, you know, this has obviously come from the top of the organization. And it's like, yeah, the the CEO just said to all the directors, we need AI in our business. Go do it. Yeah. And then I found they went a few questions later, it's like they'd brought somebody into marketing, somebody into sales. They were looking for someone to come and help in AI in AHR. IT weren't fully on board. It was, you know, it was a great case example of like, this isn't the way to go about this, guys.
SPEAKER_01I mean, we we see a disconnect now when, especially in much larger organizations where, you know, technical teams, data teams, they're off doing a million things of AI. And the operational teams are kind of like, well, okay, we'll fend for ourselves ultimately. And they're trying to find their way in the space. And it it does stem from a top-down strategic uh strategic report approach, right?
SPEAKER_02It does. Is it starts there? Um, but again, I think you also sometimes have to appreciate. And I've been fortunate in my career to work in different organizations and backgrounds. And the more the last one before I sort of set up Bantu Advisory was a Microsoft partner. Now, in there, you've got a lot of techies and you know, people really interested in technology, et cetera, et cetera. And yeah, they would rush off ahead, you know, learning, you know, in their own time, they'd be playing with technology. That's just what they like doing. Well, other people in other departments don't do that. So you are creating this bigger disconnect immediately of people who are interested and capable and people who don't really know and sort of, you know, at a different point. So it comes back to leadership. We've got to guide that and help try and shepherd the whole business and all the people within the business on that journey at the same time.
SPEAKER_01And I think also there's a a sector uh challenge. So if you look at, you know, a lot of work we do with is in construction, for example. You know, business leaders who are doing these things, a lot of them are getting themselves really clued up. And actually, you know, some people say to me, Oh, you work in construction. Oh, I'm not surprised. Well, actually, no, a lot of the business leaders in there are very clued up on what they need to do. They just don't have technical teams as broadly as like, you know, for example, um in law firms and things where they're technically on computers all the time, so they have bigger tech teams.
SPEAKER_02But yeah, but but you also really, you know, there is a lot of sort of um uh evidence coming out through sort of research and surveys and stuff, which generally does say that, you know, the leaders of a business tend to be ahead of the curve in learning and understanding AI, you know, because they've got access to licenses quicker and they've got a chance to play. And let's be candid, they probably have got that learning mindset. That's why they're in the roles they're in. But then the workforce perhaps haven't been given access to some of these opportunities and are getting left behind. Whether it's construction or another sector, is there's a lot of similarities there that leaders are the ones who are pushing forward. But they've got to remember they've got a whole bunch of people behind them, they've got to take with them.
SPEAKER_01That's and that's a very good segue, actually, because I think if you don't bring people along on the journey, you've got a couple of friction points and challenges there. Um, one is the sort of you know, shadow use it just happens in the business and it kind of comes in and merges in, you don't even realize it's happening. And the other part is uh fear, worry. So, what as a business leader, somebody that's trying to bring AI in, what's your first step? You you've now understood it, yeah, at least. What's the first step of actually practically implementing it from a people's perspective and what to think about?
SPEAKER_02So I will very much talk to them about that you're we're gonna go on a change journey here, right? We're gonna have to take your people on a journey. And they are gonna go through a range of emotions and and as you've alluded to. And so one of them is having a little bit of a think about you know, what's the culture of your organization right now? What type of people have you got? Are they risk averse? Are they the type that perhaps don't like learning? Are they very set in their ways? Um, so you know, you're gonna start a conversation with the workforce. Yeah. And you're gonna try and build levels of trust and reduce anxiety, you know, and and there's nothing wrong equally with being vulnerable and saying, look, we don't know everything, guys. We know we need to bring AI into our organization because we can certainly see there are opportunities, but we we realize it's gonna be difficult for you, you know, it could be a bit of a bit unsettling. Yeah. So so I think that's really my next point is look, you're gonna start a conversation with the workforce um because they can also help you as well and they'll help you accelerate quicker.
SPEAKER_01I agree. I think we always, you know, we always say the people that are in your business are the most important part of making AI implementation successful. And if you don't set the narrative from a strategic level, they don't get on board. And if they don't get on board, you have massive blockers.
SPEAKER_02Well, they're the most important thing in anything. AI, forget it. I mean, this is a bit I think I find I sometimes smile wryly about, which is we keep talking about kind of, oh, you know, people, we need people on board because that's how we move AI forward. That's never been different. It just happens now that the thing we're all talking about is AI. It was always the same when you're into implementing things, be it systems, new policies, practices, whatever, you know, solutions, et cetera. So yeah, it's so you know, you're gonna take them on this journey, you're gonna bring them on board, and then you're gonna start getting into the conversation right, right, you know, how can we help you become more skilled? How are we gonna, you know, what's the impact on your role? What's the impact on your team, et cetera? So, you know, we're starting to work our way down from that leadership level, and we're sort of raising awareness through the organization as we go. Yeah. Um, and then, yeah, all being well and good, we get the benefit on the way.
SPEAKER_01Do you know what I think the big difference is now though, and the bigger challenge, and correct me if you think I'm wrong, but typically people might be able to use little tools on the side to help their day-to-day. Now, because AI is capable of so much, even just from a you know, a large language model, ChatGPT, Gemini, people can leverage it to do things that they probably shouldn't be doing externally to the system. Whereas before you would have just waited till a system was built internally or use a spreadsheet or all these different things. So, do you think there's there's that sort of problem of, well, it's here, people are using it, and we need to kind of get uh almost a grip around it.
SPEAKER_02Yeah, we absolutely you need to get a grip around it. I mean, look, you'll understand the data risks better than I will, and there's other cybersecurity risks, et cetera. But yeah, if I think about it from, well, how are we trying to take our people on this journey? Then you have to put some kind of governance around. You know, you have like like you do with any other part of running the business, there will be some kind of policy that you're gonna put in place and say, right, this is how you can use AI, this is how you can't use it, et cetera. Um, these are the tools you can use, here are the tools you can't use. So, you know, you've now made it clear to people what's acceptable and what's not. Um, and then you can start thinking about other things like, you know, well, can we bring some of our enthusiasts together to start really exploring the true potential of it? Maybe they've just had more time. They're you know, they're the ones who outside of work are playing, playing with AI on their own. And, you know, you've got to find those opportunities to bring the right people. They can perhaps accelerate you whilst you also want to support the people who are a little bit more nervous. Um, but they, you know, there's a there's a role for everybody, um, but you've got to do it in a sort of coordinated way.
SPEAKER_01Yeah, I agree.
SPEAKER_02Um, without getting too formal about it.
SPEAKER_01Yeah. So get the governance in place. Well, first of all, learn about yourself, get governance in place, help people in your organization understand how you want to leverage AI and how they're a part of that process and and and what the I suppose as well, what the motive of the organization is. Because I I'll be honest, a lot of people talk about, oh, people are gonna lose their jobs. I would say nearly every single person we work with has never had that motive. They're always about giving back time to people because we're all too busy. Yeah. That's that goes across the board, doesn't matter what what sector you're in.
SPEAKER_02Yeah, absolutely. And I and I talk about uh this thing called the what I effectually call the capacity conundrum. Yeah, you know, we've got to give people time and space to learn this new tool uh or tools. Um, but to do that, you know, you've got to sort of said free them up from whatever they're doing to day to day, because ultimately the tool will give capacity back. Yeah. It it's sort of, you know, it's so there's challenges there again that a business has to think about in terms of how do I give my people time to learn the tool so that we get the benefit later on. Um, but yeah, it capacity is a big part of a conversation for me around AI. Definitely.
SPEAKER_01And I think you're gonna have some quick wins, uh, you know, high impact, low risk, um, doing those kinds of processes. But the the bigger change comes when you start looking at your actual, you know, data workflows, automations, how you highlight all of that. You know, it's that whole end-to-end process, which is a bigger change piece.
SPEAKER_02Yeah, it is. And and again, look, if I think about it from the people side, and this is why I talk about it as very much a really long-term journey that's going to be continually, you know, the whole, your business is going to continually evolve. Because, you know, let's uh let's try and break this down to a you've got a small team and they're starting to find more effective ways of working and actually they're creating capacity. And then you're saying as an organization, well, we let's reuse that additional capacity they've created for more valuable work or whatever. Um, but let's just say we also realize that there's some new opportunities over here, then that's a different skill set or perhaps it's a change to someone's role. So, you know, you're now saying somebody, well, I'm just gonna drag you a little bit away from let's just say, I know, you're a marketing, I'm gonna drag you across over into another little space to do some other stuff. Now their roles evolved. But in another six months, they've applied AI in that space, the role evolves again. And roles will just keep evolving and evolving and evolving. So you'll hear people talk now and say the idea of a singular role will disappear. Yeah, you're just gonna evolve. But you've got to coordinate that amongst a sizable workforce, possibly.
SPEAKER_01Yeah, I mean, there's been some, you know, quotes that people have said, like, um, I I mean several people have said this, but uh people won't lose their jobs to AI, but they will lose their jobs if they're not able to adapt to an AI implementation workforce. And I think that the biggest challenge, you know, we're we're talking about, I'll come on to the younger generation in a second, because I do think that's a potential impact. But um what they're not talking about is, you know, older generation that aren't necessarily tech as tech savvy as um, you know, people between the ages sort of 20 to 35, because they've grown up with tech, right? You know, they've they've had the tech in their lives. So that adaption curve is a lot harder, I think, in in under people of that.
SPEAKER_02Yeah, well, it's interesting, isn't it? Because you could again look at it another way, which is you know, AI is by all accounts at a base level very straightforward to use. You know, they say talk to it, have a conversation with it. Well, I'd like to think probably the older generation are quite good at that. You know, they they're they that's what they've been brought up with. Um the bit that's scary is when you start saying it's technology, it's artificial intelligence. I had a great chat with someone the other day who said maybe we've given it the wrong name. It should not be called artificial intelligence. Um and I if he doesn't mind me using it, I'll use his phrase, he said, just call it easy magic. And if I said to you, do you know what? Do you know if I said to my mum who's 80-year-old, I can give you eight some easy magic to make that little task a little bit easier for you. Do you want that? Do you want to have a go?
SPEAKER_00Yeah.
SPEAKER_02They're putting go, yeah. If I said to her, do you want to use artificial intelligence? But what? Yeah. You know, so there's um, I think the generation one is a really interesting one. I come back to it's about whether you have a curiosity to learn and try different things.
SPEAKER_01I think you're right, because obviously older generation has so much more experience, knowledge that's built up in certain industries. A big challenge, like you say, is yes, you can chat to it, but actually you have this force that's coming the other way, which is well, okay, well, that's just very small part of what AI does.
SPEAKER_00Yeah.
SPEAKER_01You know, again, it's prompted it to give you back certain results. The knowledge part is being democratized by AI. They're saying we have the knowledge on all these things. And what's coming through in the uh sort of the younger generation is, well, now I if I can do that, it's the it's the logical operational thinking to go, I can do that with that and I connect it to that, and then I can connect it to that. Yeah, they're calling it almost, you know, the maestro level. Um, and I think that's what they that's what the old generation is. It's the understanding of process, technology process. And that this is a generalization, by the way. I should say that. This is not about uh saying this is everybody, this is this is uh uh you know a macro view, yeah, not a micro view of of what the what they're saying is the problem. So, how do you feel about that? What do you think?
SPEAKER_02Well, um what would you say? It's a it's a general view. I I can agree with that and I can disagree with it. Probably the bit that I think's more interesting when you get to the generational conversation is um again, I'm gonna make a big sweep in generalization, the younger generation don't necessarily know how to operate in an or within a um within a company. Correctly. You know, there are rightly or wrongly sort of ways of doing things, ways of operating. And the real challenge for any business is to to get the take the the bet the upside of both. You know, the the people who have been in the workforce for longer, who have all this experience, they understand the context of of things, they they have judgment. Um, to then the younger generation who probably have a different level of enthusiasm, they're you know, they they perhaps are getting, as you say, the flow of it all a bit better, or they certainly pick it up quicker. And and the real challenge for a business for me is how do you bring all of that together? And you don't end up with these silos. Yeah, you know, and um I think that's uh that's where a big challenge is gonna come.
SPEAKER_01Well, let's talk about the younger generation in a bit more detail because I think the biggest challenge, and I and I worry about this for my daughters, their biggest challenge is how do you get the experience? And okay, it's not gonna mean that we're not saying AI is going to eradicate jobs at this point, but it probably will stop people hiring more junior roles in the capacities they were. So where do they get started? You know, there's a uh I think there was the last numbers that came out was around 800,000 graduates unemployed in the UK. You know, where'd you go with that?
SPEAKER_02Well, if I had the answer.
SPEAKER_01Well, absolutely. But what do you think? What do you think? Do you think we need to.
SPEAKER_02Well, look, I look your your kids are younger than mine. So mine are uh are sort of 19, 20, 21 years old. And one of them right now has been going through exactly that, applying for jobs, et cetera. Which when I think back to when I was his age, you know, I'd pick up some work quite quickly and easily, and now I'd get on the ladder and I'd start building my way. Um, the opportunities just are are far less less available. Um problem now is we're gonna probably start drifting back into what I call the education system now and and how we've got to, you know, it's this is a big systemic shift now. This isn't just about I'm gonna make some tweets to my organization, I'm gonna take some tweets to to one board, I'm gonna do this, that and the other. This is a much deeper thing around, you know, well, what does experience look like? Where do you get it from? Um, you know, I think the biggest challenge that a a business has right now, or one of the biggest challenges, certainly the large ones, is how do you redefine learning pathways and career pathways for your people? Yeah. You know, what is a career path now going to be anyway? Absolutely whether you're starting at 19, you've just got your foot in the door at least, well, you know, the next number of years, what's that look like?
SPEAKER_01Yeah. And I and I do do you think the responsibility resides with business owners? Because I think, you know, we're we're all, you know, generally on this movement of, oh, what can we do with AI? It's very exciting that we go. But we're kind of forgetting that whole pathway side because we think right now we're in that, you know, excitement period of getting stuff implemented and doing these things.
SPEAKER_02Well, I I I there's certainly a responsibility uh around leaders. Um, I mean, to come back to your point earlier, you said, you know, the people that will lose, you'll you'll lose your job to people that can use AI better than you. Well, there's only so many people that can use AI better than probably the people you've got. So, you know, as a business leader, you've got a choice. You can say, Do you know what? I'm gonna take a punt and go and see if I can find some more people that are better equipped than my people, or I'm gonna really put some energy into my people and make them better.
SPEAKER_00Yeah.
SPEAKER_02Um, and I think you have to go with the latter personally. I just, you know, this is just a simple supply and demand combination.
SPEAKER_01I think this is the problem. You could talk about it all day because then you could counteract it with, well, actually, they're the people of all the knowledge. So why would you get rid of them? And you can go round and round circles like that.
SPEAKER_02They have the context of your organization.
SPEAKER_01Absolutely. I think that's the big challenge. But let's let's get into some really focused use cases. Yeah. So what have you seen implemented well from a people perspective? Obviously, keep it anonymized and where have you seen it work well?
SPEAKER_02So really uh again, I I'll a different company I've come across in the financial services space, I had a long chat with them, who I think have have done this well, is the first thing they recognized that um they they had a CEO who was very much bought into the fact that AI was going to make a positive difference. So they had an energy from the top straight away. What then I I guess they started to realize though was, you know, this was going to be a long journey. So they accepted that point quite quickly. And then it's more about an iterative journey that they go on. So they started to ask their staff about how are you feeling about this? What's your level of capability? What's your competence? Um, so they started to get some some intelligence, if you like, about their workforce and where they were at. Um, and they built from there. And so it's been, you know, I spoke to them originally 10 months ago, I think. Um, and they'd already been on the journey for about 10 months prior to that. But but they were just sort of showing that it'd been an iterative journey. They still didn't have the answers. And they've come back to me recently and just said, actually, would you come back, perhaps look at doing another piece of work with us? But it's they recognize that this is just evolutionary. Yeah, this is no, there is no route map. There is no um clear set way that says this is the way to introduce AI. There's lots of things coming out now. It says, look, these are the sort of things you should be doing, thinking about. But that's a really good case study for me is they just they were taking their time, but they had alignment at the top of the organization to start with, and they were flowing it down and they were they were giving people space to to to sort of learn and grow, etc. And there has some governance in place as well.
SPEAKER_01I think that I think that's a really good um. Example. What about bad implementations?
SPEAKER_02Um, well, a bad implementation probably wasn't even defined as an implementation. They just allowed AI in. Okay. And so, you know, so that's implementation suggests there was a control, some some control around it. The worst ones I've seen really is where, you know, they've just given licenses out. And now, you know, they're months and months down the road. And you sort ask the questions about have you got some governance in? What are people doing? And they haven't. Yeah. And it's like, well, what have you done to upskill your people? Well, they haven't. Um that that to me is, you know, and I've come across a few of those. And you're like, okay.
SPEAKER_01Well, I mean, at that point, you start having people put spreadsheets into uh cheap licenses of large language models, and they've got training turned on, and that's getting past there, you know. Then they say, Well, how likely is it that that's going to go into the system? You don't know. That's the problem with with training large language models, right? So if you've put in very sensitive data in, not only are you probably in breach of some major regulations like GDPR and all the different things, you just don't know what's going out there. That's your IP and information.
SPEAKER_02Absolutely.
SPEAKER_01Yeah.
SPEAKER_02So But but it is, I think that is the the worst case of implementation, really. Because I said a lot of organizations just, I don't really think, are on what I'd call our coordinated implementation pathways. It's a bit of this, it's a bit of that. Um, and that to me is the the bit, you know, you have to you accept this is a program that you're going on, or a change program, as I would say it is, and therefore you gotta have some control over it. Or at least some some you know, guiding it on the way. Absolutely.
SPEAKER_01So to summarize understand, yeah, start there, and then from there look at what kind of governance and things you would want and controls you'd want to put around in in place as a starting point, and then speak to the people and and help them understand one, what your motive and direction is, yeah, and then ask them what they're actually doing right now and and what their knowledge is of the space and how they could help.
SPEAKER_02Yeah, I think that's a very simple way of doing it, really, is that, you know, and remember, you can always come back and tweak the governance and tweak the policies later. But you you you just got to get that engagement, you've got to raise the awareness levels, get people to at least start to understand what's what's arrived or what is coming, if you like, within their organization and take them on the journey. Um and and they'll educate you as a leader, probably as much as you're gonna educate them. Absolutely. No one has all the answers, is a simple point.
SPEAKER_01No, and and that's it. Like you said earlier, it's accessible now. AI is making it easy for people to just even experiment, try things out, prototype and do those kinds of things. And you should be encouraging them to do that. So I think training, like you know, we mentioned training at a top level, but give your staff the right training as well and make sure that they're understanding what their capabilities are and and direction.
SPEAKER_02Yeah, exactly. You know, it's it's like, you know, going back to sort of her basic stuff and it's set somebody a bit of a vision or along an end point and then help them on that journey. Yeah. Um, so if you can set them some kind of vision which says, you know, think this is how work could be one day with us in this organization, um, and you're gonna help us get there, yeah, that's quite empowering. So I think that's a big part of it, really, is the role of the leader. Now, I I would always talk about this separately, the this whole thing as um the the AI sprint that needs a marathon plan. And the leader of the organization is basically gonna be the person that sets the pace for that run. And they're gonna make sure the organization is prepared before it gets to the start line. And when it's on the start line and it starts running, the leader is the one who's gonna help guide a good job. But it's gonna be a team effort to complete it. No one runs big diff di big marathons and endurance runs on their own. They have a team. Yeah.
SPEAKER_01And I think the processes are the same, whether you're a team of six people or a team of six thousand people, right? Yeah, I I I I think it fundamentally is. Yeah. There's always gonna be nuances, but yeah, fundamentally it's the same thing. And would you give somebody the responsibility of being an AI lead? Would that be something that you would sort encourage, or do you think it stays with leadership?
SPEAKER_02And depending how you define the role, I don't see anything wrong with that at all. I think, I mean, ultimately, accountability sits with the exact with the leadership team. Yeah, it has to. But if you want to put some control around it and and perhaps make sure you're picking up the opinions of your workforce, you're putting in the right training and basically you might need someone to sort of take a lead on that. Yeah. Um, you know, if you're gonna put a lead at somebody who's leading on something as important as marketing or sales or whatever else, if AI is that important to your business, yeah, why would you not put somebody leading it?
SPEAKER_01Yeah. And we're very lucky to have uh NextGen AI sponsoring this podcast, which is an event happening uh in June, and link will be in the description. But 10% off for anybody that's listening to this, and it's gonna bring all the all the you know business leaders together to hear from experts in the industry and how they can encourage and advise that. And I think that's a really good starting point to kind of go and do training is to go to these events, mingle with people, chat to people like you know ourselves who are doing this all day every day.
SPEAKER_02There are loads of uh uh resort, you know, loads of things online you can go to, there's loads of events you can pop to, you can just go onto YouTube and follow people who are just saying, This is how I use Code Pilot, that's how I use ChatGPT. But you just gotta be curious. And yeah, I come out to that point. You can't do that.
SPEAKER_01And I think follow people like yourself on LinkedIn, you're putting putting videos out all the time. They're just little nuggets of information they're gonna keep steering people.
SPEAKER_02Yeah, it's trying to, you know, it's only where I come at it. I what I'm trying to do is stimulate thought. As I said, it's you know, you can make a decision today as a leader about this is the path we're going on, but if you haven't perhaps gone a few steps down the path just to see what's there, yeah, you you don't know, you know, you might make a decision today that's gonna bite you on the bum down the road. Yeah. And that's very much how I see my role, really, is trying to be a few steps ahead to help leaders make decisions now as best they can that aren't going to backfire down the road. Yeah.
SPEAKER_01And we'll we'll include your details as well.
SPEAKER_02So and what's your website for the uh www.ventuaadvisory.com.
SPEAKER_01Brilliant, excellent. And I need to put it recently. Yeah, that's why you had to think about it. Um, okay, awesome. Let's let's just close off the uh I've it's been great chatting, Simon. This has been really interesting. Quick fire. If you can recommend one book, one tool, and one piece of advice, what would it be?
SPEAKER_02Well, one book I'm gonna cheat. Or podcast. You can use it. Thank you. Oh, there you go. So I was gonna say there's there's one that I was going to call the AI-driven leader, which you can find on Spotify. Uh, and I think remember rightly the the the guy who uh wrote his guy called Jeff Woods. Um, but that's a really good sort of starting point I suggest for any leader. Um that's one book, one podcast, one tool. Um well look, I'm gonna be uh this is not a plug or anything, but I I I just be fair right now, and people will probably shoot me down who are in better space than me. Copilot, I just works for me. But the reason it works for me is because I know it's it's in a secure environment. Um people I know will say Claude is probably better right now and Claude co-work and all this other good stuff. Great. But for me, that it worked, it does what I need it to do. Um what's the third one? One piece of advice. One piece of advice. Um I just be curious. Um I'm sure I probably nicked that from some Ted Lasso thing, but yeah. But it but it is, you know, be curious about this. Don't be afraid of AI, don't be afraid of the technology, um, but be curious and and embrace it because it didn't go anywhere.
SPEAKER_01I think that's great advice, though. It didn't go anywhere. That's exactly right. Yeah, be curious. I think it's a good way to put it. And who doesn't love Ted Lasso?
SPEAKER_02Well, I had to drop him in somewhere.
SPEAKER_01Yeah, absolutely. Well, thank you very much, Simon, and thank you all for listening. We'll be back with uh another episode. Thank you.