Nicky Lowe [00:00:06]:
Hi, it’s Nicky Lowe and welcome to the Wisdom for Working Mums podcast show. I’m your host and for nearly 2 decades now I’ve been an executive coach and leadership development consultant, and on this show I share evidence-based insights from my coaching, leadership, and psychological expertise and inspiring interviews that help women like you to combine your work, life, and motherhood in a more successful and sustainable way. Join Join me and my special guests as we delve into leadership and lifestyle topics for women, empowering you to thrive one conversation at a time. I’m so happy that you’re here, and let’s get on with today’s episode. You can’t go anywhere these days without hearing about AI, and there’s an interesting theme that I’m seeing in my coaching practice. Women are often more hesitant to use AI than men. And it’s not just something I’m noticing anecdotally. There’s growing evidence of a gender gap emerging in AI adoption, with women adopting it at lower rates than men.

Nicky Lowe [00:01:12]:
And it’s not because we’re anti-AI, but we’re actually pro-integrity. It’s because we care about doing things properly. We care about ethics. We care about accuracy. We care about impact. And if we’re not sure if it’s safe or aligned, Or right, we hesitate. And that’s what I’m exploring with my guests today, Andrew Wyatt-Sames and Lucy Pitt. About 2 years ago, I attended an AI workshop that Andrew was giving.

Nicky Lowe [00:01:41]:
And at the time, AI was still a fairly new term. And I went in curious and quite sceptical, but I left completely mind-blown. Even though I started my career in the tech industry, I’m a pretty late adopter when it comes to tech. I only just started using Uber about a year ago, I’m embarrassed to say. But what Andrew shared didn’t just feel interesting, it fundamentally has changed how I work. I ended up doing an AI immersion program with Andrew and my guest Lucy, learning how to use AI to work smarter and not harder. And it is hard to quantify exactly how much those insights have saved me. But I can honestly say it’s been life-changing.

Nicky Lowe [00:02:30]:
I’ve got more capacity, more headspace, and more energy for the things that really matter. So today we’re diving into why women are falling behind on AI and how to use it with confidence and care with some real practical, real-life examples you can use at both work and home. And I’m especially looking forward to this conversation because I really appreciate Andrew and Lucy’s perspective. I’m all about more human leadership and they approach AI from the human side first, not the technology side, although you’ll quickly hear they absolutely understand the tech too. So Andrew is an AI integration consultant with a background in organizational psychology and over a decade in the leadership development and culture transformation space. And that’s how I know Andrew and alongside Lucy, he’s co-founded Uptake AI, helping organizations adopt AI in ways that enhance performance and resilience while keeping people at the heart of change. And Lucy is a strategic innovator and entrepreneur with a strong track record in business growth and transformation. She’s brilliant at translating fast-moving developments into generative AI, into practical, high-impact tools, aligning people, process, and technology so AI feels accessible, usable, and genuinely supportive.

Nicky Lowe [00:03:54]:
So whether you’re AI curious, quietly avoiding it, or even actively opposed to it, I think you’re going to love what Andrew and Lucy have to share. So I won’t keep you any longer. Let’s welcome them. So welcome, Andrew and Lucy. It’s great to have you on the podcast.

Andrew Wyatt-Sames [00:04:10]:
Thank you.

Nicky Lowe [00:04:12]:
So we’re going at this from a particular angle because I think everybody’s talking about AI and has been for a little while now, but I’ve obviously known you and your work for a good few years, and you’ve been in this space and have gone in, you know, you’re experts in this space. And I think what we wanted to talk about is, for my audience, is women specifically with AI. So I’d love to hear your perspective on what are you both noticing about how women are using, adopting, or interacting in this space?

Lucy Pitt [00:04:44]:
Well, let’s start with the research, because I’m a psychologist, I can’t help myself. So women are less likely to use AI than men. So, there’s some sort of fresh research out early 2026 that they are 25% less likely to use it. And typically, that’s because they’re worried about ethics, accuracy, and even job displacement more than men. So, that’s what the research is saying.

Andrew Wyatt-Sames [00:05:07]:
Just, I guess, more risk-adverse and less willing to experiment without the guardrails or without the kind of structured training in comparison to men? A fear of getting it wrong, maybe. It’s a really interesting conversation. I do think the needle is moving, but there’s still a gap.

Lucy Pitt [00:05:32]:
Yeah, and women in AI, like, if you think about AI professionals, 22% of women, of AI professionals, are female, so that’s probably not helping either.

Nicky Lowe [00:05:42]:
Oh, wow, I didn’t realize that. And so when you say it Is that in the AI tech companies themselves?

Lucy Pitt [00:05:50]:
Yeah. Yeah.

Andrew Wyatt-Sames [00:05:51]:
Wow.

Lucy Pitt [00:05:51]:
So, AI professionals across the board. So, probably not helping.

Andrew Wyatt-Sames [00:05:58]:
Yeah. And I guess if I consider myself, you know, when I think about my mindset, I would’ve classed myself as the most technologically challenged in a group. And also, I was always struggled with change because I’ve got my format. And so, I guess, you know, I would very much say, if I can embrace it, because I don’t class myself as technical, then absolutely, please, any listeners, you can too.

Nicky Lowe [00:06:32]:
Yeah. So, what are the worries that you hear? You’ve touched on some of them, like a kind of a, I suppose, a big picture. So you’re going out there talking to organizations and engaging in these conversations. What are some of the conversations you’re hearing from women?

Andrew Wyatt-Sames [00:06:50]:
I think we’ve got to start with the C word, haven’t we, Andrew?

Lucy Pitt [00:06:54]:
Yeah, so because we run immersion programs where we help people to build fluency, and it kind of helps with the fluency bit and the culture bit and the team bit and all that. And it’s usually a female person who brings up the cheating word. And we noticed it really early on, and it is quite a pattern.

Nicky Lowe [00:07:12]:
Yeah, cheating. And it’s interesting because I had that feel when I first got introduced to it through yourselves. I like, oh, it feels like I’m almost, yeah, cheating, cutting corners, not doing a full job.

Andrew Wyatt-Sames [00:07:29]:
Yeah, I class it as the good girl mindset. And it is present. It’s always the females that talk about fear of getting it wrong and also not being seen to have done it the hard way. And I like to just ask out of humor and curiosity, Do you use a washing machine, out of interest?

Lucy Pitt [00:08:05]:
You don’t think a car’s cheating if it drives you to the shops, do you? We accept physical shortcuts and machines, but there’s something about the cognitive and the effort. And I’m definitely not an expert in this space. I mean, I’ve done a bit of inclusion work in my career as a psychologist, You trace it back to being kids. Boys are rewarded for being the genius, girls are rewarded for being the hard worker. That plays out in adult life, and we even see that— that’s my answer to why we see that, I think.

Andrew Wyatt-Sames [00:08:40]:
Yeah, and I also think it comes back to a lack of knowledge and confidence, of course, around AI literacy and how to get the best out of tools like Copilot or ChatGPT. Of course, they’re the kind of the biggest brands that we hear about, but you’ve got Google’s Gemini and Anthropic’s Claude as well as the main players. But often people have had a go or they’ve seen some content or copy that’s been written, produced by AI, and think, “That’s slop.” that crap, or they’ve received something from somebody and they know there’s no way they would have, you know, could, would have, or could have done this. And so, their mindset is kind of reinforced early based on the bad practice of others. And it’s overcoming that.

Lucy Pitt [00:09:44]:
I was talking to a female professional the other day and she said, like having a conversation with ChatGPT, it sounds like an overconfident male colleague. And I was like, yeah, I never thought about it like that. You know, so there’s this sort of instinctive, like, I don’t like the content, I don’t trust it, you know, slop, slop, slop. So, you know, I thought that was rather amusing.

Andrew Wyatt-Sames [00:10:04]:
Gosh, but can you imagine if ChatGPT or Copilot had, you know, when you’re talking to it and you put it on the conversational mode so you can literally work through certain scenarios, problems, ideas, But if the voice back was, “Oh, I’m not sure, are you really sure about that?” rather than, “That’s an amazing idea, Lucy, you’re amazing,” which of course we know sometimes the models can be your biggest cheerleader.

Nicky Lowe [00:10:33]:
So, you’ve already talked about a number of different things, and I don’t want to assume anybody listening there— we might have people listening that are like, “Yeah, get all of that, get all of the names that you’ve mentioned around Claude and so forth, and the conversational piece that you just talked about.” But if we assume there might be some listening that’s like, okay, slow down a bit, like, tell me a bit more. What kind of scene setting can you give for somebody that may not yet have engaged in a meaningful way with AI?

Lucy Pitt [00:11:01]:
If you haven’t engaged in a meaningful way, get on with it. Like, you haven’t got to become an evangelist, you haven’t got to become— you haven’t got to fall in love with it. You have to engage in a way. So if you’ve never touched it, I bet you have, because if you’ve, you know, if you’ve, right, I’m going to say this and it’ll probably kick off in the background. If you said Alexa, okay, it’s fine. You know, if you use that or if you use Siri or something, whoops, if you use something like that, you’ve already used it. But get on, have a go on ChatGPT, use it for really low stakes. So things like write an email, do a sort of shopping list or just anything, just get going with it and just start to build a relationship with it.

Lucy Pitt [00:11:40]:
It’s going to help a lot.

Andrew Wyatt-Sames [00:11:41]:
Yeah, because you can sign up for a free account if you’re going to experiment and trial from a kind of personal perspective before the workplace. Of course, certain organizations have got their approved tools of use. And as Andrew said, have a go, have a play. The biggest top tip we can share for people to get started because there’s a lot of fear around, “How do I prompt?” Prompt is the term given for what I tell it, what I need. Prompt, as a terminology, feels and sounds a bit technical, and it also, to me, implies something really quick, which is not the case at all. The biggest tip is, Share the problem. What are you trying to achieve? What’s the task? What do you want it to consider, to know? What’s the format? The more you can share, and of course, that’s easier if you are talking to it versus typing, but the more you can share, the more accurate and the more it’s going to understand. So, the best way is, imagine you have an assistant, who has every PhD known to man, Nobel Prize-winning in terms of intellect, can do anything, but they know nothing about you, nothing about your projects, nothing about your file names, or acronyms, or how you like things, all of that.

Andrew Wyatt-Sames [00:13:18]:
How much information, and detail, and direction would you need to give that person to complete the task.

Nicky Lowe [00:13:25]:
Yeah, and I always remember, Andrea, it still sticks with me. I first got introduced to AI through yourself. We were at an event together where you were speaking, and you stood up and you gave this really great example, which I thought brought this alive. And you were saying that your kids had got quite frustrated with you because you’d started to talk to people like they were an AI prompt. And I think you gave the example of going out for a meal before you were going to the theatre, Yeah, something like that. And it was a great example about giving context and how you did it. I don’t know if you can remember and recreate that, but I thought that would be really great.

Lucy Pitt [00:14:03]:
So we walked into a restaurant, this was when I was really like getting super obsessed, I’ve eased off a little bit since then. We went into a restaurant and we were like, hi, there’s 5 of us, we have a dog, we are going here at this point, I’ve noticed that your opening times are this, We would like that, we’d probably have one drink, we probably won’t have a starter. You know, kind of gave this whole contextual briefing and kind of said to the poor waiting staff, you know, we would like a meal, we would like to leave in 47 minutes’ time, is this achievable, yes or no? And so I painted this context objective and necessary detail thing that I do to the model. And my wife kind of looked at me and went, you sound like an absolute idiot. Because she loves to give me feedback on free event. But I actually thought that was quite, it was clear communication. I mean, a bit robotic, but yeah, yeah, I started prompting people and that was the point at which I knew I needed to ease off a bit.

Andrew Wyatt-Sames [00:14:55]:
But that’s the key. Sorry, that’s the key, isn’t it? It’s clear communication, it’s clear delegation.

Lucy Pitt [00:15:03]:
I’ve got another one, Nicky, I’ve got another one. So my car’s getting sorted out and I noticed that the dealership probably wouldn’t connect the dots with another piece of work that was getting done. So I phoned up the car dealership, and I was like, hi, my name’s Andrew, I have a car, this is the specification, it’s coming in on this date, here’s the context, and I basically briefed it, and then I said to the poor soul on the end of the phone, could you just play that back to me so I know you understand the task? And she was like, excuse me? So I was talking to her like I do talk to a model, because that’s one of our big things, is like, when you spit out all the context in there and the objective, always say to it, before you write reams of stuff, can you just play it back to me? And I was like, I’m really sorry, sorry, I’m in work mode. What I meant was, just want to make sure that I’ve communicated clearly. Is there anything else you’d like to know from me? And then she was fine.

Nicky Lowe [00:15:50]:
But there’s little nuggets like that that I’ve learned from you guys, which is so powerful about, as you say, playback. What have you just heard and how have you interpreted that? And what, looking back, have I missed from it? And you talked there, Lucy, about the conversational piece. So You said, obviously, talking to it is a lot better than typing. And like, it took me a while to realise that, oh, actually, I can talk to it. So, for somebody that may not have used that functionality, can you just— it’s so simple, but actually, it’s that kind of stuff that’s easy to miss. Absolutely.

Andrew Wyatt-Sames [00:16:24]:
And it helps you to just converse more naturally. There is a little bit of— it’s a polarised kind of statement to say, Talk to it like it is a human colleague. Some people don’t like that, and that’s why we think, you know, do continue to say your please and thank yous, because why change a habit of being nice? But it helps you to just kind of think out loud and get out the challenge, the problem, the thing that you want the assistants for. When we type, I think we type in structures, and perhaps it’s slower, and obviously, it does take more time. And so, when I learned that if you’re working off a PC, there is the button on the keypad, which is Windows, it’s either a diagram of Microsoft Windows, or it says W-I-N, When you press that together with the letter H, it brings up the Dictaphone of the device, not the AI tool. So you could use it if you’re in Word, if you wanted to, or whatever you were on. So that’s how you just talk away, and it’s wonderful because you see it translate live. And then when you’ve finished, as Andrew’s just demonstrated, you might say, “Sorry, I’ve just garbled on.

Andrew Wyatt-Sames [00:17:57]:
Can you just kind of play back to me what I’m trying to do here? I just want to make sure.” you understand.

Lucy Pitt [00:18:03]:
It’s funny, like, we say it makes it more naturalistic, but there is an exception. So, if I walk through the kitchen of my house and I hear my wife talking, I know she’s talking to AI because she sounds like a Buckingham Palace switchboard operator. She’s like, “Hello, ChatGPT.” She puts on this really weird posh voice. I’m like, “She’s talking to you again.” She’s like, “Yeah, how’d you know?” I’m like, “Just a guess.” It should make us more kind of fluent and get everything out of your head into the model. The more you get out of your head into the model, the easier it gets. So, if you haven’t had a go on ChatGPT, or if work has provided Copilot or anything, just have a go. Dead, dead simple. And by the way, if you’re a leader, you know, and I’m assuming a very high caliber of listenership for your podcast, Nicky, you can’t not do that.

Lucy Pitt [00:18:47]:
So, you actually do need to crack on. I’m not saying lead or leave, but get on with it.

Andrew Wyatt-Sames [00:18:52]:
Yeah, I was just gonna say, and that gives me the idea that, for women and women in leadership. Sometimes, in meetings or situations, the female voice might be overshadowed by— or more dominated by male voices in the room. And sometimes, that can be frustrating, can be intimidating. And I love the idea of using tools like ChatGPT as a coach, effectively a bit of a coach in your pocket. If you know you’re about to approach a certain situation, not only to help you craft an email and make it a little bit more polished, the use cases are absolutely endless and problem-solving and, you know, a coach. I’m just about to go into a meeting and I’m, I’m worried that my voice doesn’t get across. I’ve got some points. Can we just kind of work through some ideas of how I could join the meeting or be more vocal, whatever it is? And you’ll be amazed at what you can do.

Nicky Lowe [00:20:08]:
Absolutely. And I think it might be useful, because you’ve just said, Andrew, about get on with it, because if you’re not, you’re almost— there’s an impact. Can we just talk about what that impact is? So almost highlight, because People might go, yeah, this is all great, but I’m doing fine. I don’t need that AI stuff. And I’m sure there’s nobody at that kind of extreme, but almost if we’re being tentative with it, what’s the cost of being tentative?

Lucy Pitt [00:20:34]:
There’s one or two paradigms that get in the way for leaders, you know, male or female. The first is the kind of let’s wait for the technology to mature, let everyone else make all the mistakes, and then I’ll get on with it. And the other thing is like, you know, if you often we get to leadership positions with the kind of red, amber, green mentality, like, is it red, is it amber, is it green? I can’t tolerate any ambiguity. Kill it, kill it, kill it if it’s not going to deliver. So that sort of hits us if we are in an executive position. So those are the paradigms we need to tackle. So embracing a bit of ambiguity, you know, about AI and moving from a kind of execution mindset to an experimentation mindset, that’s what you’ve got to do. And so I would say that the risk of not getting involved is not twigging that you need to implement— if you are in a leadership position, you’ve got to start thinking about how you implement a learning culture, a culture of experimentation, a culture of inclusion.

Lucy Pitt [00:21:30]:
The inclusion bit, we had this great conversation with a team where this young lad was saying, I’ve been using ChatGPT for 2 years to cover my dyslexia. And our advice was, don’t talk about covering your dyslexia, talk about it like superpowering your dyslexia. And even— and we facilitate that conversation with the team. So I think engaging with it means that you end up like, you get the performance benefits, right? Because you’ll be modeling it and your team will be— will therefore be doing it. But you’ll also start to dial into the cultural and capability stuff that needs to be true to really become an AI-powered organization or an AI-powered team or an AI-powered person.

Andrew Wyatt-Sames [00:22:09]:
Yeah, and let’s face it, Workplaces are evolving and business structures are evolving and will change, and leaders need to be on top of the opportunity and the dynamic around that. We’re starting to work with organizations that are actively supporting business heads of department around AI literacy to improve processes, to see how things better land, lie, are structured through the lens of AI, see what that change is going to require, to then feed back to the business in terms of what skills need to be in place, what people we need to hire in order for that to be true. And I think, therefore, if leaders aren’t getting on board, there’s as much that they’ll get left behind in terms of their own capacity and capability, but equally left behind in terms of their needs and their requirements and what’s happening in their business. AI, when it comes to the leadership table, is a team sport, it isn’t IT, you know, it isn’t just delegated to that one person, it impacts absolutely everybody. So, from a leader perspective, absolutely, there’s a second important kind of narrative here, got to get on board.

Lucy Pitt [00:23:49]:
That sounded well posh when you said that.

Andrew Wyatt-Sames [00:23:52]:
Thank you. Maybe I’ve put my palace voice on.

Nicky Lowe [00:23:59]:
Putting this through there. Sounds good, Lucy. But I, I think there’s brilliant stuff that you said in there about actually the— if we’re not engaging with it, it impacts us in terms of our strategic thinking around this, but equally our personal productivity and capability. And I think there’s two— those are two powerful sides for any leader, but I think there’s some particular nuance for women, you know. How many senior women I work with that are at full capacity. Because often, you know, in terms of my audience, they’ve, they’ve got the dual shift, you know, they’re— they’ve got a huge demand and responsibility they’re carrying in the workplace, and then they’re carrying potentially most of the mental and domestic load at home. And as you say, trying to have gravitas and impact around the leadership table if you’re not engaging with this what you can bring to it.

Andrew Wyatt-Sames [00:24:54]:
And perhaps sometimes there is a fear of opening up, if there isn’t psychological safety at the top table, in terms of some of their thoughts or some of their ideas, they kind of want to sense-check it first. That’s another fantastic kind of use case to get second eyes and ears on something to help build the confidence to then kind of present it, if you like. And I think not just in business as well, personal life, you know, scenarios with family or whatever it is that adds to the mental load.

Lucy Pitt [00:25:38]:
Yeah. And, you know, so I live in a very woke household. So, you know, my wife is an advocate for end sexism, end sexism end sexism in schools, amongst other things. And I’ve got daughters who challenge me all the time. And I said I was coming on this podcast and my wife was like, do not be giving anybody any extra burdens. We’ve already got enough on our plate, thank you very much. And I’m like, with that in mind, the one wonderful thing about AI is that when you’re feeling burdened and somebody goes, here’s a new thing you’ve got to figure out and learn, it does actually save you time. It’s not just this new thing you’ve got to learn to add to all your burdens.

Lucy Pitt [00:26:15]:
It actually does take stuff off your plate, which is wonderful. And so that’s what you’ll discover if you’re a non-user. You know, you can do things like chuck the URL of your website or of your business into ChatGPT or Claude or whatever and go, can you do a SWOT and a PESTEL analysis on my company? It’ll go boom, there you go. And you’re like, that would’ve taken me hours. You know, so those kind of things, when you get time back, you’re like, wow, there is a virtuous circle if you’re asking the right questions. And so that’s the, let’s do my little bit, you know, not, not trying to burden anyone.

Nicky Lowe [00:26:46]:
And I, I will forever be grateful for you, to both of you, because the amount of time that you’ve saved me by helping me become more of an earlier adopter than I would have been is just mind-blowing. And we talked, we talked about that inclusion piece around somebody that was dyslexic. I have found that as a perimenopausal woman, the thinking partner of AI has just— when I’m like, oh God, I can’t get my brain quite started, and it’s just a springboard. It doesn’t replace my thinking, it becomes my thinking partner and helps me springboard my thinking or accelerate my thinking. So both professionally and personally. So on that note, if somebody is thinking about, okay, you talk about saving time, you gave a really great example there, Andrea, of somebody that might have a website and you review it. Where have you seen people use this? So, if somebody’s like dabbling and like, I’m not quite sure, what might be some examples, either professional or personally, you’ve seen?

Andrew Wyatt-Sames [00:27:48]:
Well, personal, a use case that came up in a meeting that we were at this week, where this lady I was talking to said that she couldn’t find a wedding dress, that she just knew the style and type that she wanted, so she drew her own. Own outline. She took a photo of it on ChatGPT, and she said, this is the style dress I’m looking for. Some of the designers that I know do similar things are XYZ. Can you find me shops in London, or wherever it was that she was located, that have currently have dresses like this? And she said it did it, and she has her dress. I thought that was amazing.

Nicky Lowe [00:28:32]:
Wow. And the creativity to add into that, because I’ve never tried drawing anything and getting kind of AI to look at that.

Andrew Wyatt-Sames [00:28:39]:
Yeah, and I’ve just noticed the improvement of image generation is absolutely phenomenal. I’ve been looking at the designs for my engagement ring, and some of the things that have come out are just absolutely brilliant. Occasionally, it’s really warped, and it actually, on one of the images, had a prong going into my finger. But loads of use cases. I’ll list some on the personal level. I love the idea for birthday presents or Christmas presents when you’re really struggling to, you know, tell the model, “I need to buy a present for my nephew. He’s 15 years old. He absolutely loves golf, anything to do with golf.

Andrew Wyatt-Sames [00:29:28]:
Could you have a look at sites, whether that’s Amazon or any online shopping “site based in the UK that could give me some ideas for presents up to £50,” for example. You know, I think that’s a really great idea. What about you, Andrew?

Lucy Pitt [00:29:46]:
In our household, we always go, “Oh no, it’s cousin so-and-so’s birthday today. We totally forgot.” So, nip into Google Gemini image creation and say, “Do me a virtual birthday card.” You know, here’s a picture of the kid. Put a funny little logo in there, did this, that, and the other, get a lovely virtual birthday card, chuck it onto WhatsApp, breathe a sigh of relief, tell them the Amazon package is on the way.

Nicky Lowe [00:30:08]:
Yeah. That’s a clever one. I’ve never thought about designing my own card in that way.

Andrew Wyatt-Sames [00:30:12]:
Oh yes, I did my Christmas card in the style of Bridgerton this year, which just went down very well. And we’ve got to mention, haven’t we? It’s been very popular, the weekly meal planner.

Lucy Pitt [00:30:29]:
Yeah, this is a bugbear of mine because Lucy and I will do big presentations to big audiences and I’ll talk about big strategic, you know, AI, AI, and Lucy will casually mention the meal planner and people will come up afterwards and go, yeah, get lost, Andrew. Lucy, tell me about the meal planner.

Andrew Wyatt-Sames [00:30:43]:
I get people writing to me, you’ve changed my life. Like the Sunday afternoon fear and, oh God, what are we going to eat this week has gone and You know, it could be as simple as taking a picture of your fridge or your cupboard to say, “What can we do with this? Give me some ideas.” To, “Andrew likes this kind of food. My daughter is, you know, intolerant here, and my husband is a fatty and likes loads, has to have big portions. We only want to be cooking for 25 minutes each night, make sure that it’s a healthy balance, da-da-da-da.” “do me a meal plan,” and it’ll then literally give you ideas and a meal plan. Then you can go a step further, “Great, can you now give me a shopping list that I need for the week, and could you list it according to our location? I shop at Tesco’s.” And then, when you understand and you’ve got the process once, you can then say to the model, “Could you give me the configuration now, because I’m going to build a GPT, so I can do this every week?” And they literally then just push a button, takes all of the stress out. And equally, some people have done that with their children for a bit of fun, so that the kids feel that they’re kind of planning parts of the meals or what have you. But it’s about removing micro-frictions in life, whether that is at home or whether that’s in the workplace. You know, people think of AI and talk about innovation and how it’s going to automate everything.

Andrew Wyatt-Sames [00:32:17]:
The real impact comes from the kind of compound effect of micro-innovations. Something that might take me an hour that I can now do in 10 minutes, something that might take me a day that I can now do in an hour or two. When you add up, you know, the collective wins, then we’ve, you know, we’re winning.

Nicky Lowe [00:32:37]:
And that’s what I want anybody who’s listening to this to hear. If you are not engaging with it in this way and you are feeling that, you know, I am overwhelmed and I don’t know how I’m going to get through everything that’s on my professional and personal list. This is why you have to, you know, not only does it— for my— it’s helped my sanity, my well-being, but in terms of my productivity and elevating me to be more strategic in my business, because I’ve effectively got all of these, as you say, GPTs with like little admins. And we can come on to that if somebody’s not aware of what we mean by that, that are working on my behalf, that are doing things for me and elevating me into a different space. Um, absolutely, I’ve got it from food, but I’ve also had like health tests where I’ve run my health test through it and gone, what do you think based on the— this profile would be a good diet for me? Through to, you know, give me the— give me the 7-day plan. Um, I’m— everything from— yeah, just phenomenal. And I, I love what you were saying about the design. I’ve— I had an operation at the beginning of the year and I’ve been sat at home a lot and dangerous to me because I’m like, don’t like the design of this room anymore, or that fireplace just isn’t working for me.

Nicky Lowe [00:33:51]:
I’ve not got, I’ve not got the right like knickknacks on it. It’s not, it doesn’t feel in balance, but I haven’t got a good designer eye, like I don’t know what I’m doing. And taking pictures and interacting with it and then saying show me, and it’ll, and, and list where I can find these things on the internet. And I’m like, that capability has just gone through the roof. I feel sorry for kind of interior designers now because it’s it must be fundamentally changing their business, but being able to, to get that real-time feedback.

Andrew Wyatt-Sames [00:34:22]:
And it’s experiment.

Lucy Pitt [00:34:25]:
Sorry, there’s something in your approach, Nicky, which I’m always looking for, which is that I wonder if it could— I wonder if it could do that, I wonder if it could do that. And so if you’re constantly asking that question, you get really incredible returns from it just, just by being curious. And the fact you had an operation meant you had time to to reflect and think, and you know, that’s the stuff. That’s the stuff that gets you the goodness, is that time to, not getting operations, obviously, but having time to step back and think about things and work and your environment and stuff like that. That’s where you get the goodness.

Andrew Wyatt-Sames [00:34:56]:
But it’s also the learning from experimenting and having play, because you realize, you know, you’ve taken a photo of your fireplace, and it’s come up with some creative suggestions. It’s also come up with some lists of where you could buy those things. As Andrew was saying, that kind of open mind of, “I wonder if,” that learning from that is, “Oh, actually, I need to redesign the shop outfit,” or, “I need to have a look at what ideas we could do to make this area of the business more appealing or more safe,” or whatever it is. “I wonder if I take a picture of that, it’s got some ideas around that.” And that’s where, naturally, more and more use cases that are relevant to you come about.

Nicky Lowe [00:35:42]:
Yeah, and it’s things like the cognitive load. I’ll give you another example. I was writing a sympathy card for friends of ours that have just lost— my friend’s just lost her mother-in-law. Never met her, but they’re, you know, they’re a family that we’re really good friends with, and so I wanted to send a card, and I was thinking, how do I write a message that’s appropriate for them as a family that we know really well, but I never knew the person. And I would have spent time agonizing over that because that’s really important to get the right message for it to land. So we talk about it takes away the humanness, but for me it was like, no, I want to land this in a really human and appropriate way. And I would have spent a lot of time overthinking that, and I kind of put that into ChatGPT and it gave me like 4 options. I was like, well, I like a bit of that and a bit of that, and it cut the time down.

Nicky Lowe [00:36:32]:
So For me, I am aware that people go, oh yeah, but we’re, you know, we’re becoming robots and they’re going to take over the world. And I think there is a, you know, we’re not kind of doing the toxic positivity, everything in AI is just perfect and don’t worry about that. But there is this— it’s not, for me, it’s not taking away my humanness.

Lucy Pitt [00:36:52]:
And you’ve sort of— when I was prepping for this, I was kind of thinking, right, don’t burden people, don’t burden people. But, you know, is it possible to use AI to help, you know, help with that sort of thing. And you sort of— you’ve nudged me into thinking about, um, you know, the way women communicate, you know, because the, you know, the evidence suggests that women can sometimes, or female people can sometimes, use kind of hedging language or strategic softening in their communications. And you can, you know— and so I worked in HR, and I know this, right? You write a mass email to 100 managers going Give me the stuff. If it’s more assertive, you get more stuff, so that actually helps you. There’s less chasing. So one idea might be to take your writing, your email request or whatever you’re about to send, drop it into a model, Copilot, whatever, and say, can you audit this for strategic softening and for hedging language and give me some feedback? And then perhaps even rewrite it for me. So it’s a combination of human and AI..

Lucy Pitt [00:37:52]:
And hopefully, you know, little ideas like that will actually start to chip away at the workplace burden as well.

Nicky Lowe [00:37:59]:
And I often get a lot of my clients to do that, actually, exactly what you’ve said. Yeah, let’s run it through, play around with being more assertive, less professional, more professional, like just experiment. And it expands your flexibility and language because you’re absolutely right, you know, those minimizers, or I just want a little bit of your time, or sorry to bother you, can I just, you know, they slip in without our conscious awareness. And having that thinking partner that goes, “Hang on a second, that’s okay, but it could have this impact. What about…” And you can start to experiment and expand your capability in that area.

Lucy Pitt [00:38:34]:
And you can extend that, right? So, you can take a transcript of a one-to-one meeting or a team meeting and analyze it for interruptions, and then put it in front of the team and say, “Oh, I’ve analyzed our team meeting, by the way, folks, and it looks like there’s some interruption patterns.” So, you’re not going, “You’re a sexist because you’re interrupting the the females, you’re just going, I’ve just done this piece of analysis because I was worried about interruptions. Here it is. You can put it in front of the team. So there’s loads of things you can do to start to chip away at that burden without creating a new burden.

Nicky Lowe [00:39:07]:
So, like, there are millions of different ways, isn’t there? And I think that if anybody’s listening to this, the overriding piece is just start experimenting with it and don’t limit the areas in which you can experiment with it. However, a big concern of people’s is like ethics, confidentiality. What can you tell somebody that is like, actually, I want to do this with care and consideration, but I want to feel confident in what data I can put into it?

Andrew Wyatt-Sames [00:39:38]:
Good question. Yeah, and I guess it comes down to the use cases. So if we’re talking about using it within an organization, then it does need to comply and abide with the organization’s kind of policy and ruling around that. Many have got that in place, although a lot don’t. But each model, whether that’s ChatGPT or Copilot, do have the functionality within data controls to be able to turn the model off. For training, which gives you a level of security in terms of what I’m doing in my account doesn’t go out to the world to kind of train the large language model. But I guess on an individual level, then it comes down to risk appetite and the— what it is that you need to do. If there is an analysis, for example, in terms of customer data, 9 times out of 10, you don’t need the personal information because you’ve got customer identifiers, you know, IDs or what have you.

Andrew Wyatt-Sames [00:40:54]:
And so, if data is kind of sanitized before, then we reduce risk in certain ways. But you’re right, it does involve the critical thinking piece and it does involve the kind of stop and think. Just because I can, should I? And that comes down to the, you know, an element of kind of moral compass as well as then guidance from the organization in terms of what can I do, what can’t I do. And if it’s your personal account, then again, that comes down to your sense and level of ethical and your ethical stance.

Lucy Pitt [00:41:36]:
So a couple of mantras, you know, is don’t chuck your sensitive data into a public model, you know, and a good way of thinking about that is if you wouldn’t leave it printed out on the bus seat, don’t put it in. And if you don’t understand your company policy on what data you should be putting in or not, go and find out and keep asking until someone gives you the answer. Because if you don’t, if you’re not sure, it’s going to inhibit your performance. So find out where the data goes and just be constantly critical, like Lucy’s saying. It’s a new AI model, or, oh, there’s a little connector, some sort of widget that somebody over in Portugal’s written. If I use that, what does that mean in terms of where the data’s going? So just like, protect it. You wouldn’t leave it on a bus, don’t chuck it in.

Nicky Lowe [00:42:23]:
Yeah. And one of the things that I think you said to me very early on, Andrew, when I did your immersion, because I think we all came into that immersion, didn’t we? I think we were one of the first groups that worked with you. We were all like, oh, but data integrity. And you were like, well, how do you work with— like, it’s got the same set— a lot of these have got the same setup as like Outlook or the same kind of security provision behind the scenes. You probably would explain it far better than I can.

Lucy Pitt [00:42:54]:
Well, it’s like there’s this weird paradox, right, or tension where people go, don’t put any data in. And then on the other hand, they go, you can’t trust anything it says. So I was sort of thinking like the secret formula for Coca-Cola, if I chuck that into ChatGPT, is somebody going to go, that is the secret formula? That’s the sort of the weirdness of it. But yeah, there’s a public narrative about ChatGPT, and there are sort of horror stories where somebody in XYZ computer company put their code in and their IP got squished out. And I don’t know anyone who’s actually had any real horror stories. We’ve been in the game for a couple of years, You know, the controls are usually decent. And if you look at ChatGPT, it’s some like geeky for a second, SOC 2 compliant, GDPR compliance. Basically, it complies with the same stuff that LinkedIn does or Salesforce does.

Lucy Pitt [00:43:43]:
It’s just there’s this public narrative about the horror stories about it. But do the work, do the research. You know, if you’re going to use a model, make sure you know how it works.

Andrew Wyatt-Sames [00:43:51]:
But, you know, ultimately they’re cloud-based. Products, just like Microsoft is, and the things that go up into SharePoint. So, there’s an element of comfort and security in, “We’ve turned the model off for training,” but anything, the majority of setups that we have anywhere that are cloud-based, have the ability to be hacked. So, there is little difference in a way from what we already do to now what we want to do with the likes of ChatGPT. But Andrew’s right, the scaremongering is there, and it’s often on the back of competition and their kind of race to get to who knows what and where, but one wants to obviously dig the other. But it is an important thing, and bottom line is, stop and think, do I need to for the outcome that I want?

Lucy Pitt [00:45:08]:
And also, beware, these models are incredibly good at triangulating. So, if you chuck in one spreadsheet with a bunch of stuff on it, and then later down the road, chuck in another spreadsheet, and you’ve sort of sanitized it and cleaned it all up, the models are brilliant at connecting the dots. So, you’ve really got to think kind of systemically and really, really carefully. Minimum viable data, always be thinking, what’s the minimum viable stuff I could put in to get the sense out of the model? Think like that and you’ll be fine.

Andrew Wyatt-Sames [00:45:36]:
That’s really cool.

Nicky Lowe [00:45:36]:
That’s a really good one. I was going to ask, yeah, so, if somebody’s thinking about engaging with different tools. Some of this might be driven by what does your organization say. It might be Copilot because they’re Microsoft users, but for general guidance, is there a guidance that this tool is better for this, or is it personal preference?

Lucy Pitt [00:46:02]:
The way I think about this is like when I was a kid, I used to go to slot machine fairground type places, and there was this this, um, game which was like a mechanical horse race, and you put a coin in and you’d watch these metal horses, it’s all edging in front of each other. That’s how— that’s what they’re like, you know. Claude, Gemini, ChatGPT, Copilot, there’s sort of 5 big ones. They all kind of hedge and edge in front of each other from time to time. And I’ll take on that question is just pick one and go deep with it and keep abreast of the others. Like, have one paid account with maybe ChatGPT or Claude or Gemini, whichever if you get to choose, that is, but just flirt with the others and have free accounts, and you’ll always just keep an eye on what they’re doing. So, think like T-shaped or 80/20, you know, that sort of thing.

Andrew Wyatt-Sames [00:46:46]:
That really works for us. And I think just then, just to add to that, ChatGPT has the most best all-round functionality. So, if there was one that I would put to the top, it’s ChatGPT. However, Google’s Gemini is better at image creation. However, Anthropic’s Claude has got phenomenal at data building and data analysis. So there is also an element of what’s the primary kind of use case. If it’s an all-rounder, then it’s ChatGPT for me.

Lucy Pitt [00:47:29]:
I know I would describe myself as very AI fluent, right? So I kind of love all the models, and I think they’ve got different personalities, different uses. For me, it’s worth £100 a month to have 5 subscriptions because of the productivity benefit that I get. So if you’re sort of starting your journey, I would say don’t do that. But the more fluent you get, you’re like, it’s worth £20 a month for Claude because I can write something in— well, you know, I can research something in Perplexity, draft it in ChatGPT, stress test it in Claude, red team it in Gemini, and then I’ve got this amazing document and the whole thing only took me 10 minutes, but it takes a while to get there. And so I would say go 80/20 until you’re ready and then start to bolt on some paid subscriptions.

Nicky Lowe [00:48:11]:
And I think that’s like the optimized usage approach, isn’t it? So you’ve taught me that Perplexity is great for doing research. It gives you more grounded, evidence-based. So when you said red TeamDIP, did you say? Never heard that term before.

Lucy Pitt [00:48:27]:
What does that mean? It’s basically, one of the challenges you’ve got if you write something in a model, it’s like, how good is it? Objectivity is a nightmare with these tools. So, there are two things that I do to address that. Well, three things that I do. The first thing I do is triangulate, right? So, you write something in one model, you go to another model, and you say, “Give me some tough love on this.” And then you go to another model, but tough love is still like, you don’t know what the mix is. Where’s the toughness? Where’s the love? It’s still not objective. Red team is like an instruction to the model to say, “Give this a kicking. Whatever I’ve written, just find all the problems with it.” And so it will do, but we’re still missing the objectivity because we don’t know how tough it’s being. So, my third method for really getting objectivity is to say, build a framework that you would use to analyze the quality of this and give me some behaviorally anchored rating scale.

Lucy Pitt [00:49:25]:
So, like, actually spell out what bad and good looks like across the whole of this thing and then score my output. And so you can impose objectivity and impose a framework which actually bypasses that problem of the models not really knowing what they’re doing. If this is too geeky, just, like, hit the buzzer. Hang on.

Nicky Lowe [00:49:46]:
Too geeky. This is why I want people to hear this, though, on here. It’s not— you’re not just talking about AI from a concept perspective. You haven’t just jumped on the bandwagon, and that’s what I really appreciate. Whenever I speak to you, I learn something deeper and deeper about AI, about how to avoid the pitfalls, how to optimize the benefits. And so I am sure anybody that’s listening might be going, not quite sure, but this— they will get the essence of like, you really think about this stuff.

Lucy Pitt [00:50:16]:
Have a go at it. I’m a practitioner, so I was in a coaching conversation. I still do a bit of old-fashioned coaching. I was in a coaching conversation with the CEO the other day, and he was talking about a colleague not delivering. And so I conjured up instantly a competency framework in front of him on ChatGPT and said, just score the person out, you know, so you can really quickly get that kind of objective thing that you need in the moment. And that’s— yes, but anyway, right, I’m going to stop talking now.

Andrew Wyatt-Sames [00:50:47]:
I love, um, also from a kind of new eyes, second thinking, double-checking kind of, um, layer to, to the work is if you can build personas. And I do know, um, across various different clients that we’ve come across individuals that have then gone on and built a GPT or an agent that is to behave in the way of their boss, for example. So, then when they’ve written something, they put it through this GPT to say, “What would Bob think about this? How could I get it so that he approves it?” or whatever it might be. And so, again, with what Andrew was just saying, Putting your piece of work through various different models to kind of quality control it, sense-check it, kind of kick the tires. Another layer is to build this kind of synthetic advisory board or your executive board. There are nuances that need to be considered for that to be successful and for that to be to work appropriately, but it can be a really good way to get different perspectives and feedback on what you’re doing.

Nicky Lowe [00:52:11]:
Love that. And can we just quickly share then? I’m conscious of time, but I think this specific GPT thing, one, it has revolutionised how I do my work, but I wouldn’t have been aware of it if I hadn’t have heard it from you. So I would have just been using the generic ChatGPT. I probably wouldn’t have had the paid version and known that even that functionality existed. So, would you mind just, like, in layman’s terms, explaining what it means to build a specific GPT?

Lucy Pitt [00:52:45]:
I’ll have a crack. So, a GPT is almost like storing a really good prompt. So, if you do something on a regular basis, like preparing for a team meeting or writing sort of strategic communications or whatever it is you do, If you find yourself repeating that action a lot and re-prompting it, then my advice is to build a GPT. And you can do that by saying, “Could you just capture everything we’ve done in this chat and write it out as one long prompt?” And then what you can do in ChatGPT or in Google, it’s called a Gem, there’s always a name for it. There’s a little thing where you can build a widget where you basically store a prompt for long-term use. And every time you open that widget, you know how it’s going to behave. You know, so if it’s a strategic communications widget, it will go, I need to address this audience, I need to use this tone of voice, I need to include people.

Andrew Wyatt-Sames [00:53:36]:
It’s like a set of instructions. This is what I do, and the dos and don’ts. So, as Andrew says, you don’t have to keep repeating yourself when you go back into ChatGPT to go, I now want to write an email and I need this and I need that. It knows that that is its remit and its task, and so that’s where you can build GPTs Here’s one for my email assistant. Here’s one for my report writing. Here’s a proposal writer, because it has a process, and it’s the guardrails in which, and the rules in which, it adheres to.

Lucy Pitt [00:54:13]:
Think of it like a colleague who’s an expert in a domain and a process, right? You know, that’s the way. And when you get fancy with this, you can have a chain of them. So, you can be in a chat in ChatGPT, and you go, “Strategic thinker, in you come. Here’s my problem. What’s your thinking?” And you go, “Thanks, go.” Email writer, how do I write this up? Brilliant. Now persona, come in and tell me how this is going to land.

Nicky Lowe [00:54:34]:
Brilliant.

Lucy Pitt [00:54:34]:
And so you can just imagine like having this limitless group of employees outside your office and just calling in one at a time to work on a project and then say, be gone and bring the next one in.

Nicky Lowe [00:54:45]:
That’s how we use them. Brilliant. And also what I didn’t know until you taught me is you can load documents in there. So I’ve got like when I’m writing the podcast notes for this podcast, for example, I’ve got a my PodcastGPT, and it’s got my brand voice, my brand tone, the guidelines. You can load that all in. And so it’s got that stored in its memory. So it’s using that as its reference point. And as you say, it just shortcuts everything.

Nicky Lowe [00:55:11]:
So I am sure people listening will go, oh my God, we need to know more about what you do and how we can learn more from you. Can you explain a bit about how your business works, what are the services you offer, and also what are the services you don’t offer?

Andrew Wyatt-Sames [00:55:26]:
Because we’re talking to individuals here, and I know you’ve got particular ways in which you work. Yeah. Sadly, we don’t support individuals per se.

Lucy Pitt [00:55:38]:
Unless you’re a CEO and you’ve got money, and then we will.

Andrew Wyatt-Sames [00:55:42]:
We mostly support teams and organizations. We run executive workshops and leadership workshops, HR and people team workshops, to get them a certain point of AI literacy, but to get them aligned on what it is, what it isn’t, what it means to the organization, what are the priorities. And ultimately, AI is not a separate strategy. It’s not a standalone thread. It impacts and has the opportunity to support every area of the business, which is why we You know, say it is a team sport, and so we need to generate that alignment. We need an organizational stance, we need a responsible use framework for our dos and don’ts and our stop and thinks, and we need to all be on the same page in order for any future pilots or projects to succeed, so we don’t have that as a barrier. We run AI literacy programs that could be for, individual teams, whether that’s a marketing team or a sales team or even finance team, we have had, or multidisciplinary, to build champions in organizations, and their programs are typically delivered over Zoom. You know, we meet organizations where they are at, but it’s our responsibility, knowing what success looks like, to say, “We can do this,” but my concern is it won’t land, because you’ve got the equation for success, 75% is psychology, it’s people, it’s change, it’s culture, it’s capability, only 25% is the technology.

Andrew Wyatt-Sames [00:57:31]:
So, if we don’t have certain things in place, we can give everyone the shiniest tools in the world, But it ain’t gonna stick, it ain’t gonna land. So, you know, governance, we support organizations with, as well as data now. So, the whole shebang, we’re obviously a great crack to work with, and we have a team of ready, willing, and able specialists to support whatever people need.

Lucy Pitt [00:58:01]:
Something to think about, right? There’s so much disruption, and we get that there’s AI fatigue, right? And it’s exhausting. People will be saying things like, Well, software as a service is doomed, or, you know, in a year’s time, you’ll be able to talk to your phone and it’ll build your enterprise, you know. Oh, you know, all that stuff is bonkers. But to super underline what Lucy’s saying, the enduring competitive advantage you will get is if you focus on the AI fluency, right, and capability, because that’s the bit that sticks. The tools will come and go, the technology will come and go, it’s all going to change. The one thing that ain’t going to change is an organization with a learning mindset and a learning culture, because it will adapt to all of this. If you’ve got a learning culture and an AI-fluent organization, you will thrive, and you will smash the heck out of all your competitors. We got through the whole thing without swearing, by the way, I just want to point that out.

Andrew Wyatt-Sames [00:58:49]:
I think I might have had a little blip, but it’s difficult because organizations sometimes approach us and they’ve already run some pilots, or they’ve had company X come in and run some workshops, But we know that when it isn’t relevant to the sector and to the organization, so there’s an element of tailoredness, because it has to solve individuals’ pain points and teams’ pain points. Unfortunately, we know it doesn’t land. And we’ll go into an organization 6 months later from the distribution of Copilot, and we’ll go, how are you getting on? And there could be, you know, 100 people or so in a room, and we’ll run a live Menti, and we’ll get 12%, “Where’s the on button?” We’ll get 20% saying, “Oh, I have to keep remembering to try it.” And we’ll get 50% saying, “I use it a bit like Google.” 75% of organizations have tools that are adding near to zero value.

Lucy Pitt [00:59:56]:
My favorite one at the moment is like the UK government’s going, “We’re going to do free AI training by 2030.” You can just imagine, you know, leaders going, “Oh, I can breathe a sigh of relief. I’ve got 4 years to wait now. You know, I don’t have to do anything for 4 years.” We’re like, “Come on, the competitive advantage is insane. Just train your people up. They’ll get like a day a week back. Get on with it.” And they’re like, “No, I’m going to wait and see what the government does.” And then, oh dear.

Andrew Wyatt-Sames [01:00:19]:
Yeah, I’ll wait to see what the government does. But in the meantime, IT are doing loads of agent, agent stuff. So we’re doing AI, we’re doing it.

Lucy Pitt [01:00:28]:
We’ve done it. We’ve done AI. It’s all done. We can go to bed and sleep well at night.

Nicky Lowe [01:00:32]:
Yeah, it’s all done. And so where would you point people to? What’s your website? And I’ll put this all in the show notes.

Andrew Wyatt-Sames [01:00:40]:
So we are uptakeai.co.uk. We do also have an online learning platform to support larger organizations We’ve worked with organizations and teams from 10 up to an organization that has 50,000 or something like that, crazy, globally. And this was developed, it’s not about the platform, it’s not about the technology or anything like that, it’s our content, our framework, our approach to learning with AI.

Lucy Pitt [01:01:16]:
All the magic from our immersion programs, we studied how people learn, And we’ve designed it with that in mind. It’s not AI-powered learning. It’s not like an AI person going, “Oh, do this, do that.” It’s like classic, you know, learning, e-learning, but it bottles the magic and it’s sympathetic to the brain. It’s like brain-friendly AI learning.

Andrew Wyatt-Sames [01:01:34]:
Yeah. And that, I guess, to give people a flexible way, but a reliable and safe way to train their people when they, you know, can’t afford to put everybody through an immersion program because, you know, it is costly. Because guess what? Becoming AI literate doesn’t happen in a free workshop. You know, it’s a really overused word, isn’t it, journey? But it is a journey, because you win on some stuff initially, and then you get really frustrated on other things. You need to come back and learn from others, and experiment, and keep trying, and the penny kind of drops gradually. And that’s where success lies. So, yes, multiple different ways. uptakeai.co.uk.

Andrew Wyatt-Sames [01:02:23]:
Obviously, we’re on LinkedIn and happy to have conversations. And if we’re a fit, great. If we’re not, equally great.

Lucy Pitt [01:02:33]:
If you’re not a leader and you ain’t got no money, still follow us on LinkedIn because we give away loads of ideas as well.

Nicky Lowe [01:02:38]:
We do. So, if there’s just one thing that you would hope somebody listening to this conversation takes away, what would that be?

Lucy Pitt [01:02:46]:
You become competent by experimenting. So, if the thing that’s in your way is like, “I want to be good at this before, you know, I want to really nail it,” no, forget that. Experiment, treat failure as data, and have a go. Like, you know, smash through that good girl thing that Lucy sort of flagged at the beginning. You get good by experimenting.

Andrew Wyatt-Sames [01:03:05]:
That’s my mantra. True. As an example to finish on, put in, “I want to produce a market report on the— I want the latest insights on the housing market.” Okay? See what you get from that. Versus, “I’m responsible for business growth in a UK-based property development organization. I’m really interested in what’s happening in the market. I’m interested in the latest trends around construction, around X, around Y.” you know, much more detail. I’m going to use this report for an idea to extend our current business plan. This is what I’m doing and why.

Andrew Wyatt-Sames [01:03:49]:
And, you know, you kind of learn from not very much to, just like we said earlier, to somebody who can do anything and everything, but doesn’t know anything, how much would you give them, and then see the quality.

Lucy Pitt [01:04:04]:
That’s, you know, how you learn by going, You’re not saying, “Go and do that housing example.” What you’re saying is, you know, think about your role and your mission and the things that you care about, the problems you’d love to solve, explain all that to the model, and you’ll be amazed at the quality of what comes back.

Andrew Wyatt-Sames [01:04:21]:
Yeah. And I’ll share with you the Christmas card as well, Nicky, so if you want to put that up, have a play, have a crack, it’s really great fun.

Nicky Lowe [01:04:30]:
I will do, and I’ll put that in the show notes as an example, if you’re happy for me to share it.

Andrew Wyatt-Sames [01:04:35]:
I came up with so many different images. I was like, oh, but even if I printed, you know, lots of different ones, like the multi-pack if you like, but then mum gets that one, but then auntie gets that one, well, they won’t have seen the others, they’re so great. So the Christmas card had all of them on it. Like you think, look at me, look at me.

Nicky Lowe [01:04:57]:
Yeah, I’m gonna be taking inspiration for this year. Thank you both, not only for joining me for today, but actually what you’ve empowered me with, with my own AI journey. So thank you.

Andrew Wyatt-Sames [01:05:09]:
It’s an absolute pleasure. Yeah, welcome. We love, we love to talk. Thanks so much, Nicky, and you’re doing amazing things with this podcast. It’s a pleasure to be part of it and hope we’ve helped all the listeners.

Nicky Lowe [01:05:24]:
If you’ve enjoyed this episode of wisdom for working mums, I’d love for you to share it on social media or with the amazing women in your life. I’d also love to connect with you, so head over to illuminate-group.co.uk where you’ll find ways to stay in touch. And if this episode resonated with you, one of the best ways to support the show is by subscribing and leaving a review on iTunes. Your review helps other women discover this resource so together we can lift each other up as we rise. So thanks for listening. Until next time, take care.