LH131 AI for People People with Erica Farmer

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We're using a methodology that's out of date. We're treating people like tech users. We're not treating people like people and empathising. Around what's actually going on for them personally. That's why this is different.

Welcome to The Learning Hack, a podcast about the people and technologies that are creating the future of learning.

I'm John Helmer.

Now guess what? Learning is cool. Learning is cool. Learning is cool.

Learning is cool.

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Welcome to a brand new season of The Learning Hack. My guest today is one of the most prominent figures in the UK, among the many who have come forward in recent years to help people be more effective in their use of AI.

Hack Facts.

Erica Farmer is an AI and future skills specialist, speaker, and author. She's co-founder of Quantum Rise Talent Group, host of the podcast AI for the Average Joe, And in May this year, she published AI for People Professionals, a book endorsed by several past guests of this show and read by me. Before any of that, she spent more than 25 years in corporate learning, running talent, leadership, and apprenticeship programs, organizations from Virgin Care to the Mission Group. Yes, she's actually done the job she's now helping people to do better. Advice about AI has a short shelf life, though, and Erika knows it better than most. Her answer was to anchor the book not in tools so much, but in questions people professionals have always asked about change. What's the change we want to see? Who's sponsoring it? Where is the gap? Where's the risks? Where's the opportunity? Those questions matter because the numbers suggest the profession is, well, a bit stuck.

Could L&D step up a little bit? I think L&D is taking a bit more of a submissive stance on this right now.

CIPD research says 2/3 of HR professionals put AI at the top of their development priorities, but only a third of organizations offer any AI training. Fewer than 1 in 5 say their leaders are equipped to lead in an AI-enabled environment. And Don Taylor's Global Sentiment Survey this year, which we did a program about, reports that AI is adding to L&D stress, not relieving it. So who's letting the side down? Erica's answer was not the one I expected. She argues that organizations are rolling out AI in the way that they rolled out every HR system for it with a project plan and a town hall, treating people as tech users rather than as people. She has pointed things to say about leaders who will not put down or change the way they've always worked, and about an L&D profession she thinks is waiting to be told what to do. We also talk about writing a book with AI in the middle of a backlash against AI, why the machine tends to make you work its way rather than yours, and what happens to motivation when people are handed a tool and no reason to use it. Plus, one company that gives every employee an hour a week just to play with it. Here's Erica Farmer.

So, Erica, welcome to The Learning Hack.

Thank you so much for the invite. It's been a bit of a long time coming, isn't it, since we originally talked about coming on to this. So I really appreciate the fact we're here.

Oh yes.

Well, it started well in advance. So Erika, you've written a very necessary and timely book for people professionals, which has strong backing from the UK L&D commentariat. I'll put it that way. I mean, several people in that group have been on this podcast in the past. So really they kind of qualify as friends of the podcast. The book addresses people professionals as one audience, but are HR and L&D in the same place on AI in adoption, attitude, and skills? If it's different, how does it break down?

I think that's a great question and a great question to start with, John, as well. So, I'd say they're in very different places. There's, of course, the crossover, and a lot of it all comes down to mindset and also environment and context. So, if you're L&D, as an independent, for example, and you specialize in things that you are starting to potentially see AI as a threat to, like coaching, facilitation, content design, instructional design, I'm definitely sensing a real threat response from that kind of community, of course, because it's linked directly to their success and income. Why wouldn't you be threatened by that?

Yeah.

Compared to perhaps corporate L&D and bigger teams, maybe have more time and headspace, resource, and budget to trial and pilot and see what works and get stakeholder backing and talk to their HR and all that kind of stuff.

Hmm.

With an HR perspective, I'm seeing, up until quite recently, actually, a hesitation, a waiting, what's gonna happen? What does it mean for us? Who's leading on it from a corporate perspective? You know, is it an IT thing? Is it a people thing? I've seen that change probably in the last month, where HR, particularly in corporate, and if they're self-employed consultants, are starting to get their hands over what that means in regards to being a people agenda, and actually leading from the front. So, taking that place in, I guess, the organizational hierarchy to actually say, this is ours, and this is what we're gonna be delivering. It's dependent on where you are and who you speak to, and of course, the organization that you work in and the leadership. The great organizations I'm starting to see transform are where HR have kind of gone, this is mine, this is a people agenda. You know, I'm gonna need L&D support from that, for example, from a skills perspective, but That's the stuff that I'm starting to see changes and the grassroots of transformation in. Could L&D step up a little bit? I think L&D is taking a bit more of a submissive stance on this right now. Of course, there's exceptions, but I think it's a nice place for L&D to play with. Just don't sit and wait for your HR friends to tell you what to do.

Do either of those 2 groups have particular skills that are useful? Or, you know, the other side of that question, is there anything about either of those 2 groups that makes it really difficult for them?

Perception of where you sit in the organization could be a big blocker. I know David James talks about this quite a lot, you know, like HR sees it submissive to the C-suite, or to the COO, or CEO, and then L&D sees itself submissive against HR. I think we need to throw all that out the window really, and really understand what it is that we bring to the party, particularly with AI. We talk about mindset, and agility, and the ability to change, and understand, and support leaders and people. That's exactly what this stuff is, but it's on steroids.

Yeah.

So, what I say, particularly to HR, who don't know where their place is with this right now, is double down on what you're great at. Double down on communication, influencing, negotiation, thinking, and representing what perhaps the other part of the C-suite might not have considered. That's your organizational conscience. We need that more than ever right now, Particularly around senior decision-making.

When we first set up this interview, we talked about before we turned on the tape, so to speak. I said that in the light of AI's rapid development, I wanted to record as close to transmission date as I practically could. I mean, we're not that close to transmission date, but a lot closer than it was when we first talked about it. Because in my view, advice about AI keeps like fish. And you do say in the book, it's a moving target between chapter 1 and chapter 10. A lot of things came on stream that weren't there before. Multimodal models, Copilot mainstreaming, and agentic AI all arrived. Your answer was to anchor the book in timeless questions rather than tools. However, does this limit its usefulness in some ways for people who hear any number of exhortations and encouraging messages about AI in the course of a normal day, but just want a bit more procedural knowledge perhaps, if you like? Maybe a bit more step-by-step handholding?

I think it's a great question. And I remember having that conversation with you, like, how relevant is this going to be? And I had exactly the same challenge from Kogan Page. How are you going to write a book about AI when it's changing so quickly? And I had some fantastic conversations with Laura Overton and Andy Lancaster about this. And I remember Andy saying to me, what's your premise? What's your principle across the whole thing? And that's how I came up with the Change Architect. You know, the change architect is the golden thread that runs all through this, no matter what your job title is. That could be people, principles, agenda, tools, technology, organizational strategy. I think what we've got now is an intelligence that can help us. It can be that in-the-moment coach, trainer, tutor. You know, Claude can help you learn the latest version of Claude Cowork.

Mm-hmm.

You don't need somebody to write a book on that or deliver a training course to you. Where I wanted to really add value was those key principles and those really practical actions and questions, which, you know, when you go through the book, that you've got the little tick boxes that I've put through. That's really those timeless questions that you call that. Those are the things that are proven. They're part of our toolkit as people professionals, whether that's working with change champions, whether that's asking questions like, what What is the change that we're looking to see right now? What's the end in mind? What are we going after? Who's sponsoring it? What does it mean? Where's the gap? Where's the risk? Where's the opportunity? All of that will always apply because AI will be changing so much. But what we do know is that kind of risk and opportunity, that gap's getting bigger and bigger and bigger right now.

Mm-hmm.

And that's gonna take both technical understanding and tool usage, as well as that cognitive advantage that we have to really understand Intuit, build context, communicate. And by the way, you can't overcommunicate right now in any role when it comes to AI. You know, bringing those 2 things together in that together-with collaboration rather than either-or black-or-white thinking that I'm seeing quite a lot of.

AI is, you know, there's a precedent for it as a change thing. We can look back to, you know, if you're kind of as old as me, you remember the introduction of the internet. And we do see things that kind of chime. that rhyme, that are very similar to that kind of progress of change and adoption. But in other ways, it is quite unique. One of those ways is I found as a writer is working with it as a writer. And so one thing that fascinated me, quite selfishly I suppose, about the book was your description of working on it with AI to write a book and as a neurodivergent writer as well.

Yeah.

A lot of us suspect we might be slightly neurodivergent. I think it almost goes with the job description of being a writer, that you're slightly neurodivergent, because it's an odd thing to do. It's an odd way to think. But can you talk a bit about that and how you found it working on both those streams really? What it's like to work with AI as a writer and the neurodivergent stuff as well?

Yeah, absolutely. And pure transparency, I didn't use AI to write the book as literally as that sounds. And, you know, Cogan Page would come after me very quickly if they got any hint of me scraping the internet in a large language model and calling that a book, right?

Yeah.

I tend to use AI as a thought partner for ideation and also for pointing out my blind spots. So I'll create, I'll draft something with AI, I will what I call Ericarize it, Yeah. I will think of things in a very different way, which I think that's probably where the neurodivergence piece comes in, both diagnosed ADHD and autistic. So, I've got a natural pull with those 2 conditions, if you know anything about them anyway.

Yeah.

But also, how do I serve the reader or the audience in ways that don't fit my own preferences? Because I would be a hypocrite if I was to go on to people about using AI for bias checking, for example, if I didn't do that myself.

Yeah.

And when I say things like bias checking, I'm not talking about English as a second language or he/she or protected characteristics. I'm talking about how we all like to consume information in different ways.

Yeah.

So having something that's closer to an intelligence than the traditional technology gave me another brain to bounce ideas off, to help me come up with metaphors, to illustrate key points, to challenge my argument and opinions on things based on wider research, to give it the persona of the, you know, the council of elders. What happens if the best people in HR in the world were writing this book? What would they expect to see and why?

Hmm.

So, I could make sure that I was holding myself to a standard where I was creating a blueprint for HR professionals, which was practical and easy to use, rather than a piece of slop. That if it did get printed, which it probably wouldn't even get through my development editor if that was the case, I would get a really bad name to it and it wouldn't sell anything and it would do me more damage than it would good. So, for me, using AI as a collaborative thought partner, but taking full transparency and full ownership for that was a no-brainer when it came to writing a book about AI.

Yes. You mentioned the S-word. Yes. Slop. As you'll know, there's an AI backlash underway. Anyone who, like me, has grown up kids, especially kids in the creative industries, will know all about that. Admitting that you wrote your book with AI as a helper is no biggie in the context that we're talking about, because I think people who work at all with it understand that it's not necessarily just about drafting everything. It's fantastic as a research tool.

Absolutely.

Bias checking, fact checking. and so on. Elsewhere in the forest, it's like saying that you print your own banknotes. There are example of this, 2 book awards in July and January of '26 generated media controversy over the role of AI in writing fiction.

Yeah.

We've had a lot of pushback on SLOP. I have a friend who's a creative writing teacher at a university. He's taking early retirement, because he's fed up of sitting in tribunals trying to work out whether people had used AI to write their work or not. And we've recently had various examples of people, tutors who've decided to take all their exams face-to-face, paper and pen, because they just can't work out a way of dealing with it. So it's causing societal problems. Talking more broadly perhaps, have you been affected by the backlash in your work and how would you advise that people deal with that? You've been very transparent about your use of it and detailed and nuanced. Your use is nuanced and expert. I've read your stuff and I don't see a lot of slop there. I have to say, regrettably, when I scan through LinkedIn nowadays, I find that people that I like and admire who've been on the podcast perhaps, who I enjoy talking to, Suddenly I'm not getting their voice, I'm getting Claude's voice. And if you work with it closely, you know the tells, you know how hard it is to get them out when you redraft something. So I actually find I'm drafting less and less with it. But how should people deal with that when feelings run so high?

Don, it's a great question. And I'm right in the middle of having this conversation with— I was literally on a call with Liggy Webb earlier this morning talking about something very similar and some of the stuff that Liggy's seeing as well, particularly from human skills perspective, we are in a bit of a backlash with it. You're absolutely right. I'm lucky that I find myself in a very, and I'm very grateful for this, a position where people come and ask me how to do things differently rather than come to me to say it's a load of tosh or whatever it is. Don't get me wrong, I do feel like I'm the first over the hill getting the arrows sometimes, particularly in virtual sessions. And when somebody will really in the chat go off about environmental impact or entry-level jobs and the stuff that AI is eating up right now. Quite recently, you mentioned about, you know, if you've got kids, particularly in the creative industries. My last 2 sessions that I've run in person, I've had people say that, yeah, I use AI for work, but I can't use it at home because my kids crucify me. Are you using AI? You shouldn't be using AI. Look at the environmental impact, et cetera. And we talk a lot about things like misinformation and critical thinking skills and skepticism. Which I think is really important to understand what that means. So, let's take that back to when we do jump to the environmental conversation or the entry-level jobs conversation. It's all valid in opinions, and it's driving for a lot of people how they feel about stuff, which at times I think is a red herring for fear. You know, I think it's easy to blame AI for a lot of things. If you look at the data, some of the stuff I've read recently, particularly around the use of energy with AI is if you create a poster or a meme or a graphic on ChatGPT, it uses about the same amount of energy as it would if you had your laptop sat open for a minute, which I think is quite an interesting comparison because I don't know about you, but particularly when I was in corporate, I would leave my laptop open probably all day and I'd be in and out of meetings and offices and stuff, and I wouldn't think twice about it.

Yeah.

And I'm not saying one's better than the other and we should do one over the other, but I think it's good to put it into perspective in regards to environmental impact. Because if you don't put numbers and data and research behind it, we fill in the gaps and there's a massive narrative that happens around. The other one was, it's going to take all our jobs. There's going to be more jobs displaced than there is new opportunities. Actually, the World Economic Forum's just told us in their research impact on AI labor market that by 2030, there's going to be a massive net gain in opportunities due to AI. 4 million off the top of my head. I might need to double-check that.

Hmm.

So it's all very well to get into the media and to suck up like the sponge, the negative narrative. We love that. We love that on the algorithm. We love a bit of doom scrolling. We love to feel that we're educated and empowered because somebody said something about the amount of water used in a data center. And don't get me wrong, Jon, I'm not throwing the baby out with the bathwater. I'm not undermining any of this stuff because there is a massive environmental impact. Where I struggle is where we're calling that out when we've also got issues around flying and eating meat and sustainability of how we run workplaces and the other tech that we leave on standby. AI is quite demonized at the moment.

Hmm.

And I've read cases where in states in America, They've had to make choices around, does that town get energy overnight or do we put that energy into the data center we're about to build? There's lots of difficult choices right now. There's not a magic wand or a black and white answer. So I think it's easy to get on the anti-AI piece. What I'm not hearing when people say that is this is the information and data that sits behind that.

Yeah. Like everything else, it's got massively polarized. I mean, I listen to arguments on both sides and I think a lot of the points you're making there are true. There's a lot of nuance in that. And really it's kind of foolish to blame AI as technology. We should look at the companies who are selling it and there's a difference between them. They're not all as bad as each other, I have to say. And you're right, it's in the context, a lot of different choices. My kids are kind of bash me over the head for using AI, they'll bash me over the head for ordering stuff on Amazon rather than going to a shop. But it's just a shame that it gets kind of caught up in this polarised debate.

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To focus a bit more on individual use of AI, because I want to move on to the organizational context. But first of all, I'm interested in the question of how people should deal with the challenge of reconciling their own working styles and practices with the way that works best for AI.

Yeah.

We talked again before we turned the tape on about the difference between people who are really good at improvising and thinking on their feet and people who need to prepare a lot. And anybody who's worked in an organization knows that people don't all work the same way. I've been a marketing person for a lot of my career. I've worked with salespeople, chalk and cheese in working style.

Yeah.

Some people are very meticulous, love systems, like to have things really well organized. Other people just Wing it. One of the things I've noticed about working with AI is that, as you say, Claude is great about teaching you how to use Claude. The downside is that you end up working the way that it wants you to and not the way that suits your own strengths and preferences. I'm spending an unreasonable amount of time in my view sorting out kind of file naming protocols and folders and trying to work out where all the data's going to sit to make it all work for the AI. And when you do get it sorted out, it works very nicely, but then things change.

Right.

At one point I had to kind of chuck away all my project instructions, the documents I prepared for Claude Cowork, and go back and write a high-level thing that said, okay, this is the system, this is the workflow, be prepared for the fact that halfway through a given episode edit, Helmer's going to chuck it against the wall and go off and pursue some kind of—

Surely not.

Chimera that looks like it's creatively exciting. So there is system, but the human element of this is that sometimes we just don't want to work to the system. I mean, this is a very long Kind of preamble to the question. The question really is that people are different, have different work styles. Is there a danger with, a threat with AI that the only way to do it is the way that it wants you to do it?

The way that Claude wants it to be done.

And the output of that could be that rather than changing the way that people work, we change the people who are doing the work and a certain type of person only is able to work in an organization. I mean, that's apocalyptic, Yeah. But what do you think about that issue?

I think it's a very valid view. My understanding of Claude is, so how people tend to use something like Claude, you've got Chat, which is the large language model. You've then got Cowork, which is so much more. That's where we talk about agentic, right? Or we're starting to get into that field. And what a lot of people don't understand, so I've worked with a number of organizations over the last couple of weeks who want Claude training. And they've been using Claude for 6 months, 12 months. And we always do a bit of a self-assessment, a pre-link that goes to them in the joining instructions, and they self-assess their AI literacy, et cetera, et cetera. And people, A, always overinflate. It's that analogy that you've got a bunch of people in the room, and you ask them, who's an above-average driver? Most of the people in the room will put their hand up. That's statistically impossible. It's the same premise. And we don't know what good looks like yet with AI. And we We probably never will, 'cause it keeps changing. What I'm finding is Claude Cowork in itself needs to pull from the LLM, which is what people are used to in themselves. So, the training data that Claude already has, but you need to set up something like a skill or a project to give it all the information it needs.

Yeah.

So, it needs its purpose. So, it needs a purpose document. It needs your SharePoint or wherever you're pointing that to, to your backend knowledge. If that needs renaming or reworking or sorting out, that's a data cleanse problem. That's not an AI problem, with all due respect. I'm not saying that was your problem, but that's what I'm seeing. And you also need to give it the behavior and the rules of how to act. And we don't see people understand that because it's new, and not a lot of us understand that right now. So, it's what we call RAG. It's looking at the LLM, but the specific information you give it around purpose, the organizational information that it would never get anywhere else, 'cause that's not on the World Wide Web, unless you've trained it specifically, and the other context that sits around it. So, when you're setting up something like Claude Cowork, you need to do a piece of work to make sure that that workflow and Claude has everything it does need to give you. And some of that might be, There will be time that John decides that he no longer wants to do A, and he throws it against the wall, and he does B instead.

Yeah.

As long as you tell Claude things like that, because it will never know that information. It can't read our minds, it can't assume. And I think that's where people fall over in both generative and agentic. We think we're just plugged into the matrix, and it can read our mind, and we're not there yet. No, I'm joking, but we're not there. This is where I always challenge people on AI literacy, no matter what model they're working on. They think they know what good prompting is, and most people don't until you show them a framework that gets them a better answer and helps the model think more critically. But also, you need to do a bit of hard work. You need to know what your workflow looks like. And I say to a lot of people, if you were delegating that to a team member, what would be the instructions? What would be the information you need to give them? You have to think about it that way because you're looking at a team member Well, you're only giving it half the information and you're expecting it to give you a magic bullet. No wonder it's not doing what you want.

Yeah. That's such a good and cogent description, much better than the rather scattergun question I gave you. It's a great description of what it's like to move from just prompting an LLM to get answers to questions into a kind of co-work kind of mode. If you're not going to go as far as going towards code, No, not yet. Yeah, you're right. And it does cause you to— you have to be explicit about everything. And so much of the way we work is implicit in our personal style, in the way we interact with people, in our personality type, as far as that can be defined. But it does want you to kind of nail everything out and sort of over-document So to the extent that I'd find it's not saving me any time, which is what I want— Yeah. It's taking more time, but it is allowing me to do things much better, I find, which is strange. I found today I was doing a video edit and I was giving attribution to all the photographs that I'm putting in on my B-roll, which I've never done before. And I've always just kind of flown by the seat of my pants and just hoped that no one was going to pull me up on it. And it usually gets through the YouTube checks, but that's That to me is an example of how it improves quality, doesn't necessarily save you time. So is it helping my productivity? I don't really know.

Productivity should be the goal. And going back to what you said there, John, around how we typically work, intuitively, assumptively, this kind of stuff, that works for a certain group of the population, which we'll call neurotypical. That That doesn't work for us neurodivergents. This is why we all have war wounds in corporate when people and managers think we can read between the lines and infer stuff and use corporate terms.

Yeah.

And then you wonder why you're getting a ticking off in the manager's office because you haven't delivered something that you never had an explicit conversation. So I argue that point a little bit because, and not just from a neurodivergent perspective, but we tend to think we are better as humans and typically, do you know what? I'm struggling to see that sometimes. An example is, I'm very lucky, I have an electric car. I have a Ford Mustang Mach-E, and it comes with what's called Blue Cruise technology, where Ford have mapped out all of the motorways in the UK. You put your Blue Cruise on, you pay your £17 a month, and the car drives for you. You don't have to touch any pedals, any steering wheel, nothing. It's kind of pretty much as autonomous as we can get right now. As long as you're looking through and there's sensors looking at your eyes and you don't fall asleep, you're good. And it stays far enough away from the car in front, it brakes at the right time, it knows what the weather condition's like. But when I have people sit next to me and they see that I'm sat there with my crossed arms driving my car, well, I'm not driving the car, car's driving itself. People are like, oh my God, you know, you should be— my mum's like, why are you not touching the steering wheel? Do you know what? That car statistically is a far better driver than I will ever be as a human being because of delayed response times and distractions and all All the things that we know cause arguments. So when I hear this kind of narrative as like, but the way we do it already works, or we are better than it, I tend to struggle with that a little bit, if I'm honest.

Well, I sort of agree with that, but, and you're absolutely right about autonomous vehicles. The stats are that humans are really pretty shoddy drivers. kill 10,000 people a year on UK roads and EVs are much better. On the other hand, I don't think it works kind of across the piece. And thank you very much for making me feel that my years working in PR made me more neurotypical because it's all about nuance and not believing anything that anyone in a corporate role says to you at face value. So now this is really interesting because it's kind of, you know, I don't want to get into all that rubbish about right brain, left brain, but we're obviously very different personality types. And for me, as a basically creative background person who's made a living out of nuance and not saying exactly what they mean in marketing, it's a real contrast because it's sort of a— a nightmare having to work with AI in the way that you have to be absolutely explicit and in some ways honest with it. But then one of the things that occurs to me is just how, not biased, but how specific it is. I use this example all the time. I used an AI, an LLM to help compile my shopping list once.

Yeah.

It kept leaving out coriander because it didn't understand it. It had to be cilantro.

Oh, okay.

And it's similarly with the tone of voice thing when it drafts things. Again and again, being reminded that this place comes not only from the US, it comes from a part of the US called California.

Yeah, Silicon Valley.

Absolutely. Yeah. I mean, these products are culturally specific in an interesting way. CIPD research tells us that 67% of HR professionals name AI as their top development priority.

Yeah.

Yet only 33% of the organizations offer AI training and just 19% say their leaders are equipped to lead in an AI-enabled environment. So, makes you wonder who's letting the side down. Is this about individual capability, prompting judgment, quality checking, or is it about organizational readiness, governance, data, leadership, which is the binding constraint that's stopping this happening?

It's a great question, John, and my answer's not going to be one or the other. What I'm seeing, particularly from an organizational readiness leadership training perspective, not so much of a training perspective, maybe a training perspective, I'll see where I go with this, is that we are doing what we've always done, right? When we've rolled out workflow system, a new HR information system, a new telephony system, whatever it might be. You know, we set up a program of work, we've got work streams, we've got leadership sponsor, we've got the CEO that does the town hall that goes, hey, yeah, we're all gonna use AI, right? Brilliant. Love it. Okay, great. Right, I've done my bit. We roll out an L&D program, you know, we activate the managers or we engage managers. We probably don't activate them. And we go through our waterfall project plan, and we go, yay, grow, whatever our hard launch day is, 3 months down the road, or whatever it is. And I did that in corporate for years, running the L&D workflows and project plan as part of that. And one thing I always saw was, no matter what you say, people feel done to from a change program, because it's about work. It's not about them.

Mm-hmm.

And the other piece is we never quite get the full benefit realization out of the product or the system that we've deployed, because we get to hard launch day on the basic requirements, and we all pat ourselves on the back, and we move on to something else, because we're too busy. We don't do the reflective piece. We don't go full circle, background, continuous improvement, et cetera. This is different. This has already moved and changed at a velocity that's unheard of. It acts more like another form of intelligence than it does a vending machine or a software deployment or an answer machine or Google or whatever it is, although we're still trying to use intelligence as Google search, for example. And we need our leaders in particular to be fully activated engaged. So, that means they are practitioner, communicator, and strategist rather than just strategist. You know, I don't need to learn that part of the system because I don't do it in my role, is my typical experience.

Yeah.

They need to opportunity spot. They need to be vulnerable and be really clear because AI can enable senior leaders just as much as it can enable frontline, for example. And then, on top of all that stuff, forget the change in the pace and all the stuff that we're reading, and the managers, and the capability, and everything else. We've then got a workforce that have been told, in the last couple of years that AI's coming for their jobs, or someone who knows how to use AI is coming for their jobs, but we then tell them that they have to learn how to use AI. So, that in itself causes a tension and a friction, and that's where we're seeing a lot of kickback. So, number one, managers just aren't— sorry, leaders are just not up to it at the moment. And I'm working with a number of leadership teams that are really struggling to put down power and ego and resource. This is how I've built my leadership by doing this this way. And to be honest, I don't believe you, and I'm gonna keep doing this way because that's what I'm relying on. That's my comfort zone. That's my fixed mindset, whatever that might be. So, there's a big gap from the top that we're seeing right now, and I'm not seeing this across the board. There's some great leadership teams out there that get it. There's some leadership teams out there that are terrible. And then they're not even considering the support around the what's in it for me for the people that they're leading. You know, the engagement in regards to what's my intrinsic motivation to partner with AI to make my personal life a little bit easier? And then I'm gonna be less frictional to pick it up in my work life. And then I might toe the line a little bit more to do the use cases that you're talking about, and this prompting that you keep talking about, and stuff like that. We're using a methodology that's out of date. We're treating people like tech users. We're not treating people like people and empathizing. around what's actually going on for them personally. That's why this is different. Sorry, John, I completely went on my soapbox about that answer there, but it's what I'm absolutely passionate about. And I get very passionate and very frustrated when I come off calls and sessions sometimes where the leadership team are more interested in the CYA, the COVID their ass, than they are of the future of the organization or the opportunities for their people.

Yeah, no need to apologize. I mean, that's a really interesting response, I think. And it's making me think that there is a leadership, and we give it a fancy name, governments, but you just feel there's a certain amount of panic in upper management that this is something we have to deal with. We have to kind of get it done and maybe move on. But it does remind me of a few years ago where we had these digital transformation programs And you would talk to a business leader and they say, yeah, we've done our digital transformation very smugly and it was a huge success. And that's it. We can put it back in the box for a while. And this was a time even then when AI people who knew about this stuff like Donald Clark was starting to say, AI's coming down the track. You just don't know what's going to hit you. And it feels in a way there's the same kind of There's a lot of tech blindness in this in certain regrettably powerful parts of the organization that it's maybe a way of reducing headcount. First of all, we see that. Let's hire less entry-level people because we expect that the slack is going to be taken up by AI in some way. Yeah, I know. And it's not really kind of— you're right. People aren't really establishing win-wins here. How is this going to be good for the employees? Because you can't just kind of— and it's like leadership is moving into a very directive sort of mode where it's, this is the stuff, you've got to use it. And in a year's time, we can make you redundant once the AI is good enough.

Yeah. And not being explicit around what the plan is. If the plan isn't to get everybody made redundant, say that. If the plan is you are going to displace jobs, say that. You've got to lean into it, but there has to be a plan behind it. And that might feel really uncomfortable and difficult.

Yeah.

But rather that people can get ready, people can upskill, become digital ready, AI literate for either their next opportunity in the organization or somewhere else. You know, are you going to be an Amazon that kind of got rid of 14,000 people? And by the way, that was because of robotics in the new factory. Or are you going to be an IKEA Kia, where yes, you displace all of those entry-level jobs, but then you use the efficiencies and the billions of pounds you've saved off that to upskill all of those people to become design consultants to work over the phone with the Kia customers. That's a win-win. That's strategic thinking.

Yeah.

What you don't want to be even worse than Amazon is the company that fired all its customer services people and then found that they had to hire them back because they couldn't make AI to do it.

Yeah, absolutely.

Because that plays even worse to the share price.

Yeah. And imagine working in a culture where you've been hired back, where you were made redundant because of decisions the leadership made around AI and technology.

Yes.

Yeah.

I can't imagine.

But there'll be a lot of people in the learning industry who have had that experience, not because of tech, but just because if you're in a listed company, there's a round of redundancies at Christmas, and then they hire them all back in the new year to make the figures look good. I'm too cynical, aren't I, Erica?

Redundancies have always happened. Like, I was made redundant 3 times in my corporate career for lots of different reasons. And again, let's look at the data. So, and I know this is Anthropic who own Claude, so there's an element of potential skepticism there, but, you know, there's been no mass redundancies, mass redundancies due to AI since 2022. Now, And what happened before that? The pandemic. No wonder people are scared of redundancies, but let's not put it at the door of AI all the time that we seem to do. We make up this narrative because leadership, unfortunately, are not in the place when they're explicit around what their intentions are when it comes to AI and technology and the future of their organizations.

Yeah. And it's not necessarily showing up in the data, which is kind of surprising. So, we're in the last half of 2026 now. Let's try and cheer ourselves up maybe. In your work, do you see any organization that's genuinely redesigning structure around AI yet? Or is it still pilots and policies? I'm hoping there's going to be some good news here.

Yeah. Well, one of the best companies I've worked with is Simply Business, right? SaaS business-to-business platform, UK-US. Really understanding what that means, what their customers need, as well as other technologies being a tech platform business. What do our customers want more of? Where do do we add value in the human intervention? And they started this right back. I worked with them over a year ago when they were kind of— and the leadership was taking very clear accountability and real intentional steps around this. And one of those intentional steps was simple as, this is what we're going after. Because of that, we are giving everybody in our business, both UK and US, 1 hour per week carved out to go and learn and play with AI. And that will be on your development plan and your measurable results. We want to see you doing that, 1 hour per week. And a lot of people would put a pound or a dollar sign next to that and go, oh my God, that's gonna cost the business hundreds, thousands, whatever.

Mm-hmm.

But think about the impact on culture and innovation and decision-making, just by being really psychologically safe and explicitly clear about messaging like that. And because of that, they are looking now at what does the OD look like? What does that What does that mean? How do we do more tasks and roles that serve our customers, that are higher value, that are stretching our people and our strategic thinking and our organizational edge and our thought partnership? I could go on and on and on. Great case study.

And I hope they assess the outcomes and not just the activity. We've heard of companies that got into trouble with having leaderboards and token maxing and then finding out that they'd blown through their AI budget very quickly.

I mean, I'm sure they won't mind me sharing they're a Google Gemini company, so I don't think it's too much of the same challenges. But yeah, I get your point.

They've got a lot of tokens to burn through. So there's a big message in the book about alleviating stress, but feedback from Donald Taylor's GSS report is that AI is adding to the stress, not relieving it. How do we stop this exciting and increasingly smart synthetic work colleague? How do we stop it burning us all out as puny humans.

I love that you pointed that out.

I mean, I've experienced some of this. When I first really got into working with Copilot, I just thought, oh, this is fantastic. And I was within 3 or 4 days of quite intensive usage, and I was quite proud about the fact that I'd maxed out my tokens on the tier I was on. I started to get symptoms of burnout, and it suddenly occurred to me, you know, this is kind of wearing me out a bit, you know.

It's a great question. And we're seeing that precipice right now of pace versus quality, right? Like we do with everything. For me, this goes back to what's the problem we're looking to solve? Because you're right, all this instruction about getting onto generative AI, you've got to start using it, you've got to put it in your workflows. We're all figuring this out for the first time. There's no rulebook, no operations. There's no clear, you know, 5-year buildup or project plan or whatever it might be. So, people are left to their own devices. That's issue number one. And again, we all assume that we know what we're doing, that kind of inflated self-use piece. So there's a piece there. If you've got people who are within organizations, I know this is for the likes of you and I, Jon, you know, we don't report into a big management hierarchy and things like that. So it is slightly different.

Yeah.

But for people who are burning through tokens, creating a bunch of content, what's the purpose? Why are we doing this? We wouldn't do this normally. So why are we doing it this way? Is it because we're excited and we're playing and we're learning and we're piloting? Or is it because we're not stopping, thinking, pausing, and asking why? What is the impact? What's the value? Why are we doing this? Again, having a great conversation with Ligi Webb about this this morning. We've got to get off this automation train. We've got to really give people those critical thinking skills and a clear roadmap of what that means. So, the analogy is, I don't know about you, John, but when I learned to I think I passed on my second attempt and I was so excited. I lived in a little rural village in Beer in Devon, and it is called Beer, by the way, you heard right. And it gave me freedom.

I've heard of it, yes.

Driving gave me freedom. That was my intrinsic motivation. And for the first couple of days, I drove all over Devon. I didn't care. I just wanted to drive. I passed my test. I was free. I could do what I want. But then I learned that driving costs money. It costs petrol. I haven't got time to drive one around. And actually, I'm a little bit bored with that because it's not servicing me in what I want to achieve anymore. So then I started driving to my part-time job or to college or whatever it was. I had purpose and understanding of the benefit that driving gave me. We need to help people understand the purpose and the benefit of what it is in using AI. On the flip side of that, what I'm not seeing is across the board, that creative art of the possible use that really starts to unlock scalability and innovation. That's the stuff that we should be helping people to work through. And the grassroots early research is showing us the organizations that are starting to head towards their organizational goals and strategy around AI have supported their people to collaborate with AI as a real thought partner. And if you are motivating and you are using AI in a way that helps you achieve, and you're doing more of the job that you love and less of the job that you don't love, and perhaps it's saving you a bit of time so you can do the school run every day, or perhaps it's letting you, you know, whatever that benefit is, of course you're gonna be less stressed. Of course you're gonna be more motivated and happy. If you're sat there churning stuff out like a vending machine, or, you know, just searching stuff or rewriting emails or whatever it might be, You're going to struggle to connect your purpose to what you're doing, and that's inherently going to cause stress anyway, let alone the amount of slop that you're producing and probably getting poor feedback from your manager because of that. So, we have to ask our people, where's the accountability with this? Have we given them the driving license and the training with the instructor to go out and connect that purpose of driving and the benefit that it gives them? Or have we just gone, right, there you go, just keep driving whatever you want and do what you want, and, you know, I'll pull you over when you run out of road? of petrol because it's your fault and you should be accountable for it. I just don't think we've done enough to help people get what this is.

In some ways, the narrative you get on social media doesn't help. I'm fed up of watching AI experts get on LinkedIn and show you the latest video game they just one-shotted with Fable and created.

Yeah, I saw that.

Yeah. And I see loads of them again and again and you think, well, Well, can't you show us something useful? Can you show me how to get the frame rates of my video clips all the same and to do a rough cut for me in Final Cut Pro or whatever?

Yeah.

And my kind of instinct about that, and I don't know if it's I'm using it wrong, is that to actually get it to do these useful things and join up all the dots in your workflow, it takes kind of slow, meticulous, work and thought and a lot of back and forth and iteration and learning. And that's not what we're hearing. I don't think it helps people who are starting out on this to be given this message that 5 minutes, one prompt, I produced a video game or an app I can run on my phone. Well, yes, you can do that. I mean, the coding behind it might be rubbish, whatever, but how is it going to help you in a real-life work situation? That might be a bit more difficult and a bit—

And that's why it's important that we talk about it and share it and demo it and give people frameworks to cognitively go through that process. Prompting's a classic example. So, I share my prompting, I talk about it in the book.

Yeah.

And it's very, very simple and basic. And there's a lot of information, like very similar, that's out there. But whenever I share it with teams and people and leaders, it's very eye-opening for them in regards to the quality of the output that they're getting. So, if we're not, and you need good prompting to set up Claude to deliver in the right way as well, and co-work, you need to understand the fundamentals and basics. And that's what people, a lot of people are not doing. People think we've moved on from prompting. We haven't, not yet. It is that pure AI literacy is so important for people right now, to really start to build your layers of understanding of how this technology is gonna evolve. And if you've skipped the first couple of layers, and you're hoping that it's gonna plug in and read your mind, then you've got problems. Now, I don't mind people sharing things like they've just created a game on Fable, but actually— massive industry, and there'll be a lot of people that get a lot of benefit out of that. But that's not relevant for the average Joe like you and me. This is, again, where we need to be brave and kind and clear and overcommunicate within organizations, and vulnerable as a leadership team. This is how I'm using AI. This is the win that I got from it. This is where I got it wrong. And this was my learning out the back of it. And then I went and built my new functional strategy in partnership with it. And I'm actually really pleased. But I did a few things wrong, and this is what I've changed, and this is the feedback I got from it. And all of that great developmental process, that's what we need to be taking people on the journey for.

Yeah. I think your prompting advice is really good because my experience has been that Claude will teach you how to prompt properly by a process of doing really stupid things in response to your sloppily worded prompts and tearing your hair out of it. How stupid are I know that you do have to get more specific, as I said, more literal, more tied down, and to know the things that can go wrong if you say it wrong. But it's like the classic— I've said this on my science fiction podcast that I think people think of prompts as spells like in Harry Potter.

Yeah.

But in a way it is. It's like those fairy tales where the genie gives you 3 wishes, But you get it slightly wrong in a way that means that whole thing turns into disaster. And it's about how you ask the question. You can have anything you like as long as you ask the question in the right way. But if you ask the question in the wrong way, it's going to be kind of garbage in, garbage out.

Yeah.

Anyway, I feel like we could talk about this all day, but you've got things to do. Last question. I mentioned all the high-profile L&D names who have supported your book and been on my podcast. Well done. But who do you look to outside that perhaps charmed circle for inspiration in people industries maybe, but also elsewhere?

My AI girl crush is Dr. Philippa Hartmann. Dr. Philippa is the person that I go to when I want inspiration, or I've delivered a couple of practical learning design AI workshops at World of Learning, for example. And I'll go to Dr. Philippa and I'll say, say, you wrote a great post about XYZ, can I steal it and credit you for my presentation? And she always comes back and says, of course you can, Erica, no problem at all. Philippa's mindset, the abundance mindset, it's for the greater good. It's sharing. There's no ego, no preciousness there. I love what she puts out. And by default, people buy from her because she's amazing. She's approachable, she's credible. And I feel that she's one step ahead, certainly of me, certainly of a number of us who kind of do a bit of thinking around this stuff. But actually, when I want a non-AI view on things, when I want to come back down to earth and understand what it's like for us humans, speaking— I've already mentioned Liggy's name a couple of times.

Yeah.

Just had a great conversation with Laura Overton, Liggy Webb, Andy Lancaster, who are very human in their approach. I love Andy's view around you know, what will be the currency of community and spending time together and the purpose of that time together. And I've done a bit of work with Andy, and I just get inspired every time I hear him talk and hear him think and, you know, share all of that stuff. So yeah, I think Philippa, from a geeky AI OD, L&D, art of the possible perspective, I get inspiration from, but also the likes of Liggy, Laura, and Andy from that kind of the real core people-first stuff, Well, thanks for giving me ideas for who should be the next 2 people on the podcast. There you go.

Yes, Philippa, if you're out there listening to these glowing endorsements, drop us a line, let's book you in.

Love it.

And I think Liggy, we've already talked about that. So thanks a lot for that and telling us about the people who inspire you. I'm sure what you have to say will inspire even more people and you're inspiring people all the time. Thanks for the work you do, and thanks for the time you've taken to be on the podcast today.

Thanks, Jon. And I'm, yeah, I was very excited for this conversation. So thanks for having a great convo with me. I appreciate it. That's all for this time. Thanks to our guest and to our sponsors. We'll be back in your feed in 2 weeks' time. Meanwhile, stay classy, learning people.

Now I finally get it.

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