Deborah Yates, Chief People Officer at Coles Group

Siobhan Savage: Hello, Deb, how are you? Welcome to Skills Connect. Thank you. Welcome, everyone. We'll just give it a little second to allow folks to just enter in. Welcome to Skills Connect. This is the podcast where we have conversations with bold and responsible change makers, including Deb. I'm Shavan Savage. I'm the CEO and Co - founder of Reejig, and today I am joined by the wonderful Deb Yates.

Who is the founder? DYH Advisory, an experienced global C - suite executive and one of the most respected voices in people and culture transformation. And I personally know that firsthand, Deb has a career spanning senior leadership roles, including chief people Officer at Lendlease and KPMG. Deb has spent decades helping organizations aligned their people strategies with their business success.

Her expertise in culture transformation chain, senior leadership team, and her senior leadership team dynamics and C - suite coaching has made her a sought after advisor for companies navigating complex chains. Deb partners with organizations to deliver strategic people solutions that drive real impact.

And I'm so excited to say that Deb is here and Deb has been a two time reg customer. And is also an advisor now for rej and helping chief people, officers and CHROs globally really figure out how to operate in this crazy once in a generation change to work. But Deb, it's an absolute privilege to have you here.

Thank you for joining us.

Deb Yates: Oh, it's lovely to be here.

Siobhan Savage: So, I've given you a pretty decent,

Who is that woman? She

Deb Yates: sounds fabulous.

Siobhan Savage: It's great. It's great. The team do a good job. One of the things, that you have witnessed firsthand is how AI is reshaping fundamentally all of the foundations of work. In your view, what do you think is the biggest evolution? C - suite leaders must make today to stay ahead, not just in tech adoption, but in rethinking how work actually gets done itself.

Deb Yates: Yeah, I think it's a great question. I actually think it's leadership capability. If you think about how we've been developing leaders, we've been doing it in a really similar way for a very long time, and the world is just fundamentally different and changing at such a pace we'd never seen before. And I've been talking about this shift of,.

nice to kind leadership and I actually came across this book called More Human. And if people haven't read it, I actually think it is, a really interesting model to think about how leadership and AI interface and how you get the best out of your leaders. And it's very simple. It's talks about three things, awareness.

Wisdom and compassion. So people, leaders bring awareness, which is context, and the AI is gonna bring content at speed, at pace.  . Leaders will bring wisdom, which is. Asking the right questions and AI will give answers, and then leaders will question the answers. That is wisdom and compassion is the heart.

leaders need to bring the heart, and the algorithm will come from AI and AI bots. And so starting to rethink what are the leadership skills that we need so that we just don't think of this AI workforce as something separate, but actually the magic will happen when you. Really harness the interface together so that leveraging one off the other humans aren't wasting time doing things that AI can do faster, more at scale or more accurately.

And also we're not asking or relying on technology to do something that humans are better off doing and that we just need humans to do. And I worry a little that our. Our leadership development programs have not been modernized and are not keeping up, and therefore not developing leaders that, and the skills that leaders will need.

And the one final thing that this, really struck me when I was reading this book,. Was the importance of clarity and with the, I don't know about you, but when I ask people, when I meet people, I often go, how are I, is my first question. And the most common response I get is crazy busy. I am crazy busy.

You said it to me, right? How are you? I'm crazy busy. And one of the things that struck me out of this is, what if you could slow your brain down so you had real clarity? So that actually you are crazy efficient. Yeah. Not crazy busy. And Yeah. And even in, and it sounds a little novel, but I think it's, I would pitch it, I'm a believer.

Having tried it now is just the power of meditation to free your mind.  . Because, so some stuff is gonna come at us at such speed. How do we create the space so that we are making. Good decisions at FA that, yeah. And fast, but not a, I think there's a risk we become a ping pong ball.

And that actually, that's not the fa we know that path is not the fastest way. Yeah, actually that part is the fastest way.  . So to create that clarity. So I, if I, when I'm talking about the change that needs to be made to in, to really get the best out of, what's coming. I think leadership capability is, that is a big gap right now.

And we cannot, we must not continue to develop our leaders in the same way as we've done previously.

Siobhan Savage: If we develop them in the same way that we've always done, we'll develop the same outcomes that we've always had. And in this world, nothing's gonna change if we don't change up the way that we're first principally thinking or approaching solutions.

And in. The current age now, I was on a, I was on a big meeting earlier on and we were talking Josh Berson and I about just how using the old frameworks doesn't work anymore in job architecture. And if you do that, you're building the same, it's you're not actually reinventing.

So I think it's a really interesting point that no one's brought up on the series yet is actually about leadership and the folks that are creating the strategies that are delivering what everyone's gonna do. It's a really, it's actually really interesting. One of the things for folks as well listening that you might not know or you do know or you don't know about, Deb and I, so the reason Deb so special to Reejig and personally to me is, Deb come really early on the Reejig journey was the second customer.

She was seeing exactly where we were trying to bring it to and we were still building at the time. It was all very new. And as we kept going through when you were at KPMG, but then when you moved into Lendlease, we started to notice shifts where we were going to Deb, and I'll never forget, there was a couple of, I remember having dinner with you with the team and we started to think about AI and what we could do and how we could evolve things.

And then I also remember. Bringing you data that wasn't great on your, I think it was your top, it was 20% of your top, workforce. And I remember the data quality wasn't great and the data quality wasn't great because we didn't have great data from you guys. There was a big gap and you were part of that early.

That was good few years ago, that early evolution of, Hey, hold on a second. Why do we not know this data? How do we not have that data? And then it led down this whole rabbit hole of where we ended up coming out, which is what we ended up solving together. Right. And I think that whole context is really important for folks because.

we hear so much about the skills for strategies, and you and I started out on that directive, but what we ended up finding was that organizations actually need to even rethink that. In this new era, that skills are definitely important and people have skills, but the work itself, is becoming that critical infrastructure to enable this new AI part workforce.

So. How do you think organizations, when you went on that journey with us, you were seeing firsthand, but given that experience that you've had and also the world that you now I know, how would you say to your peers, your friends, folks on the on listening right now?

What was that realization for you? Because I would love that context for folks to have because it was a very important moment of our journey.

Deb Yates: Yeah, it was a real aha moment, I think for both of us because we had invested a lot of time and energy trying to map the skills, trying to map the capabilities, and it's a logical place to start because that's where most businesses are on that journey.

but the, and I think there are a couple of things. One, we were working in a distributed. Large business. So the language that people used was not, that didn't mean the same thing everywhere, and so that's why the data wasn't good. We, I think sometimes understanding why you think you have all this data, you do all your quality check of your data and then it still isn't right.

Why is that often the language that's being used means something different to different people. And that I think was a real tipping point from a skills capability perspective.  . But the most interesting thing for me when we got to tasks was the aha moment around when you break the work down into tasks, what you enable is this,.

if you think about a job of a bunch of dots and made up of all the different tasks, then the tasks go out and come back. So you stop talking about jobs that are redundant and you start talking about the task and then new dots come back and you have a new job. Yep. And that's. That's way more enabling in a number of areas, right?

It's, you can talk to the business about tasks, so it's a much easier conversation to talk to the business around the tasks that make up jobs than it is to have a conversation around capabilities. It's just an easier conversation. It's an easier conversation to have with your people because it's less about total redundancies and more about how jobs change and that, I think that's just a far more, people can be more curious.

About that. And I think that, the task is the task. The job is the job. Yeah. So the language is clearer and more repeatable. The challenge, I think, is that it can be so overwhelming if you think about the number of tasks that are in the number of jobs you can, I think you can run the risk of going, even for me, I was, oh, what's.

Surely it's not worth it. It can't be that different that I'm gonna get the ROI to map all of these things. That's where I got to, and that was the conversation I think we had. I'm it. And also, all my tasks cannot be that different to everybody else's tasks. If you think about the tasks that a HR person does in their job, or the tasks that a finance person does in their job, where's the value add in Me going and deciphering all of that for my business and then another person doing it that.

Ran the risk. I thought of all those beautiful competency frameworks that HR people spent years and years working on, and then sat in the cupboard and no one ever looked at. Yeah. And we should never do that again. Yeah. Do what? We should not do that again. And so then when there was this idea of the ontology and the.

A map that you could start with That's interesting to me. And that's what I say to the CPOs. 'cause one of the most common pieces of feedback I get is, it just sounds too big. How do you climb this mountain? Yeah. Where do you start? And so you start with something, a map that you can al that you already have, and you go, yes, no, yes, no, yes, no, yes.

No. Rather than creating from scratch yourself. So I think it, this, my, the way my brain thinks about these little dots going out and coming back together and creating new tasks, that's a. And a much in more interesting way to talk to your, the business, to talk to your people and to think about how work will change.

And the other thing it enables is solving, it's not just about efficiency, it's about growth. Where's the,  . Where are the challenges? Where are, where's the rub in those little tasks and dots? Where do they make you, where do they help you solve client challenges? And where do they hinder?

And so how do you change that? And that's far more interesting, I think, for businesses.

Siobhan Savage: Yeah. And it's so true. 'cause even I remember that conversation and it was, there has to be commonality between what a HR business partner is doing in your company versus somewhere else. And then what we ended up doing, I honestly that it feels so long ago now, from that happening.

But I remember looking at that going, how do we solve that? Julie? And then what we ended up finding was, yes, I head to our business partner or a finance person or project director. Industry specific is very similar. If you start going across industry, they have different regulation requirements, they have different things.

So that was why we ended up splitting it out into industry ontologies rather than one big, ontology. Because we were, actually, and what we're seeing now in our data, it's between 80 and 97% approval rating that we get. From the business when we give them the data from our customers, and a lot of our customers at the start were, we need to go and validate this.

And we got, we wanna check with the business 'cause HR don't know, is that actually the work that's being done? So that was really interesting. And I think I. Even, when you think about the mountain to climb thing, people go, but, I can't even get them to tell me the skill of something.

And now you're adding tasks to the mix.

Deb Yates: Yeah.

Siobhan Savage: And that's the, that's what we've heard from customers. But what ends up happening very quickly is we just go, we'll, just give me one of your jobs and I'll just show you the data. You can go and take that off and have a look and see what you had.

And they come straight back and they're, this is more data than we've ever seen before. And that's because we did all of that effort for creating that work ontology. But you were essentially part of that. And then AI became a thing where, yeah, we're having dinner and we're seeing this whole chat GBT thing explode.

And then I built a model. So I remember talking to you, said, I'm gonna build you a model that's gonna tell you all of the skills and the impact to your workforce base in ai. And it was crap. It didn't work. And the reason it didn't work was because, and we couldn't even ship it was because AI does not automate skills.

It automates the task. And that was the realization of, actually this is not valuable data because it's gonna tell you a whole pal nonsense when you actually need to know at a task level. So it was another round of, Hey, I think we're onto something Deb. This is actually becoming even more important now.

Not just about solving what we were trying to then became this much bigger thing around. If we really wanna embrace AI and create this new world, we need to know the task now. And the business wants this data. That was where you start getting CFOs, you start getting all of the CIOs all saying you have access to what data can we, I see that.

So that was a big, and I know this is a long winded thing, but this was real time, what was happening for us, in terms of working with you and actually realizing, oh God, this is not working. We need to fix this. How do we fix it?

Deb Yates: And I think the couple of things that you said there, one is that, the language that you talk to about tasks is business language.

It's not something theoretical that they have to get their head around which skills and capabilities can sometimes be. And that's a key enabler and just the magic of something that's already 80 or 90% there when you get it. One of the key pieces, someone asked me the other day, what would be your key piece of advice to be able to,.

Not get overwhelmed by this, and I said, only be different where it makes a difference.  . You are not that unique. What we do is not that unique. I love that there will be some bits that are really unique, but only be different where it makes a difference. Otherwise, take what's already been created and run.

That is the advantage, and that's the advantage that you now provide versus what we started with, right. Which is, yep, a hundred percent. Having to figure it all out at every time, that's so overwhelming. So that would be my piece of advice. Only be different where it makes a difference.

Otherwise you are not creating the value that your business and your people deserve.

Siobhan Savage: Yeah, I agree. And I would also say, look, reflecting on that experience, I remember at one point I was, I have spent 40 plus million dollars on this. And I think I've got it wrong. I remember sitting going, I think I've got this whole thing wrong.

And then I was, oh God. And then getting out the other side of that, oh God, the shame of making that mistake and then actually going, but I think I'm right. No, I've got the solution. I think I'm right. And then getting to the point where I was so confident that, what the best.

Ideas come from failure. And if I, and us now, me as a company, me as a leader, us as an industry, now we have to get comfortable with failure because this whole thing is so different and no new. We talk about, being, this being a once in a generation change to work. We all on this call are once in a generation, leaders this will never happen again at this scale.

Yeah. And this is the opportunity that we have now to be this once in a generation leader and lead really boldly and be really responsible. And we're gonna make so many mistakes on the road to getting to that outcome. And that was one of the things that I looked back on now and I was, at the time, that felt heart wrenching for me, that I was, oh god.

Then actually it was the best thing that could have ever happened. 'cause if I didn't have all those mistakes and you were giving me feedback, I would never have went deeply and thought about things and went, find a solution. Find a solution. Keep that consistent coming back on. I think it might be this.

Keep trying. So I think that's gonna be really important and is, you have the privilege of getting to coach some of the leading, C - suite CEOs, folks mindset. In this moment is critically important as well as, I think, we talk a lot about being bold and reinventing your company, but being really responsible and not harvesting people out of jobs.

What do you think the mindset needs to be right now for leaders to navigate this new AI transformation in a world where if you read certain things, you will think that the world's gonna end? Because of what AI is gonna do to everyone's job. So what's that whispering in the ear that you would do at that exec level to make those good decisions?

I'd love to know that.

Deb Yates: I think one of the first things I would say is that actually, I don't think life exists at the edges that. It's gonna be really awful or it's gonna fix everything. The, I, so I think just coming back to the middle, I. And language is really important.

So it's not going to replace all jobs, and it's not gonna be the panacea to everything. Actually. It's gonna be somewhere in the middle. And so that language and the le, the language that leaders use is mission critical.  . But my, the, one of the, I think one of the. Challenges people have is where to start.

it just feels, 'cause you're trying to run your business, you're trying to be competitive and at the moment it's a lot about efficiency. There's a real focus on efficiency. Costs are high. It's, and so a couple of things from my perspective, it and is the most important word you have in your vocabulary, efficiency and growth.

That is, when you're thinking about something and has to be there and. Very simply go where the noise is my advice. Yeah. Understand your customer, think about where the noise is in the system, go solve that. That is going to be an efficiency and growth story and you will get some wins and some belief.

you are the way you just described, the learning you had there. For me, I never lost faith. It was just messy. And when you're doing something new, it is gonna be messy. So when it's gonna be messy, go where noise is. Solve some of that noise and that just won't solve it for your customers.

That will solve it for your people. I heard this saying that I think is brilliant. Go where your people are burned out or bored out.  . Go where they can't keep up with the pace and scale or go where the work is. So mind numbing  . And focus there and once again, you'll get efficiency and growth.

So yeah, those mindsets I think are mission critical, but there is a capability build around ethical capability that I, you've heard me, this is my pet.

Ethical capability, and I do think it's a capability that you can build. I don't think people are just born ethically ethical or not. There is a decision making framework, a capability that you can build from the ground up where people consider different lenses, consider different impact groups, have an empty chair in the room of people who aren't represented in the decision that you are taking.

But that is a capability that. Leaders have to be building. 'cause CEOs cannot be everywhere in every decision. CPOs cannot be everywhere in every decision.  . So how do you build that capability that people are asking the question? Just because we can, should we? Yeah. Point, what point problem is this going to solve?

Yeah. So. So if I had to say, bring it down to three things, would be always have an, and when you, so it's this and, yeah. It's not a binary choice? I'm not sure. It's always a binary choice.  . Go where the noise is and you'll know where people are burned out or bored out.

An ethical capability. Ethical capability that is, you will not waste money there.

Siobhan Savage: It's such a, the ethical one I'm thinking about while you're saying that, and I have heard you talk in your businesses about this as well as, just being with you a lot as well, and I think. Just because something can be automated and how far do you go?

at what point do we stop and a allow, there's multiple different things that can happen here. You displace a whole pile of people, is the biggest risk. The second biggest risk is that you, if you go and cut too deep around ai, who is skilling up the people coming up the ranks? Yeah. There's that risk around going too far and not having that coach.

skill, learning experience, hands on. And then, the ethical components on the data and what you're doing. There's so many layers to, we can merge all of our data in together and create super bots. Should we though, what? It's that whole, and your framework for decision making I think is such a good.

Point in all of those scenarios. I think imagine a world where you've got a compass and you've got some frameworks for, well, just because we can, should we, and help me work through that decision of how do I deploy that as a product? How do I think about, advising companies.

it's really, it's one thing that folks don't talk a lot about. I have to be honest. I'm in a lot of these conversations and there's not a lot of that. That's why we've pushed bold and responsible. Yeah. I'm not getting brought in, I'm not gonna work for a customer that only wants to, take people out of jobs.

I want you to think about reinvention of work, and I want you to think about your AI strategy, but let's understand the impact workforce and give you time to then re - skill and pivot that. My two products are aligned exactly to do that one serves for each reason. And I think that's why that, I feel deeply about what you're saying because I'm, I agree.

I totally agree and I think. More CEO pressure is happening now as well. Look what happened in America with certain people taking things into their hands and what hap, around what happens in a world where we go too far into automation and people decide that they don't that CEO for making those decisions.

and there's a whole path of risk association as well. So it's not only the right thing to do for CEOs, but it's also. Also good for them to think this so that the ripple effect isn't, greater than what it should be. Yeah.

Deb Yates: And I also think if you come back to thinking about efficiency and growth  .

Well, the people might be working on something different or working in a different way. And that's why I think you need that. That's why this notion of, a model of how people. Interact with AI and where AI adds value and where people add value, we need to be clearer on that and that augmentation of it working together is where the clarity comes.

And so I think that, and if it's not, it can't just be about efficiency. It has to be efficiency and growth. You need both.  . Yeah. And there's going to be impact. It cannot be all rainbows and unicorns. There will be impact to roles and there will be impact to people. But, anybody, my team that have worked for me know, one of my key mantra is, better to be in control of your own destiny.

Yeah. So lean in now. Lean in now. It's gonna happen regardless. So lean in. Now with curiosity and let's be purposeful in how we do it and let's have a conversation because it's going to happen anyway, rather us be in control.

Siobhan Savage: Yeah. And I can legitimately say I've heard you say that because when things are happening around you, it's, let's be in control.

Right. Yeah. And I think, on that point as well, you've steered major transformations, major redesigns at global scale. We're not talking, this is your first role. You've done this career wide. And when leaders try to reinvent work and integrate ai, where do you think they're most often stumbling?

how, what are they stumbling on and how can you help avoid that? What are the things that you would tell them to do?

Deb Yates: I actually think one of the places people stumble is they don't actually reinvent the work. They try to force fit. Any technology to the way we've always worked or, and the way we've done things.

and you, I think you ex you can extract a certain amount of efficiency from that, but you don't, you don't get the growth potential. You don't get the efficiency potential. So I think it being a mindset of being open to, well, why do we do it that way? Do we have to do it that way? What if we did it?

What if we didn't do it that way? What if we did it a different way?  . And one of my key learnings has been actually mixing the team up with folks who've never done it before. So, the simple example is in recruitment, maybe having some customer service folks and you mix your team up so that you have people who they've grown up focusing on customer.

Yep. And you've got people who've grown up focusing on recruitment. But the customer, people that don't know how, they've never done it that way. So they're your great two year olds. Why do we have to do it that way? Yeah. How does that serve the customer? Yeah. How is that making it better?

That's how you reinvent the work. So one of the biggest pitfalls is actually the work doesn't get reinvented. We paste, we spend millions of dollars pasting this technology on the work, and we try to do it the same way and then wonder why our customers don't feel that it's any better. Our people are frustrated by it and we're not getting the efficiency and the growth.

So that would be the number one nugget from my perspective. Are you, my question would be, are you really inventing the way that you, what's different?  .

Siobhan Savage: , it's back to that day zero. What would you do if, you were building it from scratch, what would you design?

forget everything. Yeah.

Deb Yates: Yeah. I think, I actually don't think I'll challenge a little bit of that because I think if you say, forget everything, people get frightened. Right? So I'm not saying forget everything. True. I'm just saying once again, if you go where the noise is, what if you did that bit differently?

Yep. So what's the bit that your customers are frustrated about? Okay, let's not do that the same way. What are the bit that your candidates are frustrated? What if, where the issue? What if the way we organized work, what if it's not them? How cool to solve that. And so that's, I think that would be my biggest aha that you actually, you fall into the trap of not reinventing anything but pasting something on.

And then the other thing I would say is, it's gonna be messy, so look for the times that it goes, right? 'cause even if it goes right nine outta 10 times and the one outta 10 dozen people go, see, I told you I knew it would never work. And I have faced this a lot in the early days of Reig.

Right. I told you, Deb, I knew it would never work. Yeah. What about the, and it, and when you first start, it might be the five times it goes, right? And then the six times that it goes, right. And then the eight and then the nine. So the lens with which you look through and it's, and it's not that you're ignoring the ways that you can continue to evolve and improve because we did that and we do that, but you do that and you keep moving forward.

And you look through a lens of, okay, sure that I hear you. That's the issue. Tell me the way, where, what is it? What is it improving?  . What are we hearing that's going so that mindset, we talked about the Hill once again. My team, we know, I reckon you can look at a mountain and go, holy crap, how am I gonna climb that?

Or you can climb to the top, look down and go, holy crap, how did we get here? Yeah, I'm definitely the latter. I'm the latter. And I think I'm having that moment right now. I'm, how did

Siobhan Savage: we get here? How do you on a call with me?

Deb Yates: So that would be my big learning.

Siobhan Savage: No, I love it. I love it. And I think as well, just the whole way that the world, no one knows. The AI companies still are trying to figure out what's the potential and what's the impact of this moment. Right? And I think talking a lot about capturing that moment of, what does this mean for us?

But it actually creates that safety that everyone's trying to figure it out. You're not late. You'll be late if you leave it too long, but if you are. Trying to figure it out. What way to go about it. At least you're in the race. No, you're in and you're learning. I think the thing that we have found, even from building the ontology to then there's a difference between telling people to build where to build the agents, then building the agent, and then what happens next.

So there's this whole thing of going through. We're the only ones because we went first to market that have had that whole experience. And by the way, the product that I built back then is not the same product, not because I've learned so much through that whole thing. Right. And I think that's where, if you think about it, even in the transformation, the stuff you go into, and a lot of folks do have that, oh no, we need to do that because we need to do that.

'cause we've always done that and it's really important. And it's, but why? That whole, why are we doing that? What, for what? What's the purpose? I do love that. And I think that's good advice regardless of whether you're reinventing your company or just looking at your own process of what you do every day in your job, right?

Yeah. With AI moving faster than most organizations can keep up. So I can't keep even keep up with the announcements anymore from all of the big AI providers. Open AI did, I think 12, 13 releases in the last, 10 days. So it's, I it's very difficult to keep up. How do you personally approach the balance between bold reinvention.

And protecting your people's potential through that change. Because I would imagine that all of the employees that have worked for you around you, with you in the same company, would be getting a lot of stuff through social media, a lot through their friends, a lot, through their mom, a lot, through a whole pile of people actually.

wondering, what's this gonna mean for my job? How can I do this? So how would you think about that in the sense of. Protecting the employee in that moment. How do you communicate it? What is there, what level of transparency,

Deb Yates: where would you go on that?

Yeah, and actually I had a question there. I was on a panel event the other day and I had a question around. How do you en enable curiosity in your people? And I think you have to start to, create development opportunity. You don't have to create it from scratch. I actually think the answer here is partnering with other people.

So these, learnings exist, right? But in starting to build the language and the knowledge and people are afraid of things that they don't understand or don't know, so how to build a base level understanding of. Of the opportunity and the impact. And I think you have to be honest about that. Things are going to change if things don't, it's not in the best interest of any company that it can't compete.

And that it can't be as efficient at its as its competitors. How you do that is within our gift.  . And so I think. Continuing to develop your people so that they have the value in that their skills are valuable in the marketplace. And what they, their awareness and their curiosity and not just in technical competence, but in this leadership competence I was talking about, so that they're ready and able to interface with ai.

They have the capability to ask the right questions, to question the answers that the AI gives them so that it actually. Improves where they're going. And I do think that our open conversations are really important. And that means, also sharing where we don't know the answers, where we're, we are not sure yet, but let's come on it together and the promise that we can make is we'll continue to talk.

Yeah, we will continue to let you, we will continue to have this two - way conversation. So I think that is really important and, to harp on, I think having an ethical framework that you can come back to make those decisions and not, I'm a big believer that you need to have a framework and principles in place before the Red Mist.

Cause to make those decisions in the thick of it.  . You wanna be able to come back to, some, and it'll be an ethical framework and it'll be principles about what you stand for. And then you ask the question, is this decision getting us closer to it or further away? We said these things were important to us.

If we make this call, does that get us closer to what we said is important to us or further away? And so you have to have decided those principles and the framework before you are in the thick of it so that you can go, okay, let's go back to what we said was important.

Siobhan Savage:  .

Deb Yates: I love this clarity levels.

Siobhan Savage: Yeah. And I think, honestly, I'm not, I'm gonna sound drama right now, but I'm, this is legit. I've thought every waking second that I have is thinking about this problem, right. And I think. I do see that there is a time coming very soon because it's not really generative ai, that's the problem.

It's generative AI and robotics. So digital factories at the same time, I'm seeing dark factories, which are basically wiping out whole populations of workforces, which will have five to six people because they're AI part from day zero. Right. And I think there is gonna be some level of impact here.

And how do our, we've got time to get ahead of this. But if we don't do something about it now, then we're gonna find ourselves in a really on, I don't even know. Yeah. What that world looks. But it's not a good world. And I think I love this whole leadership framework about ethical decision making.

'cause in that moment we actually, I feel we should publish one. In this world, this is how you should think. I think Ted, this would be a really good follow up. It's. How do you use this? To think about, how to operate in that world where we don't, when we, for the record, I believe that I'm building my own AI hard workforce.

I'm gonna build a billion dollar company with under a hundred people. So I am very pro ai, but I believe that I believe in zero waste of potential, and I believe in making sure that everyone has access to meaningful work. I believe that we have the data that's gonna tell us where and who will be impacted, and we've got time.

So what's the reason why we wouldn't do anything about it?, but that's an, and that's

Deb Yates: a, that's a brilliant example of, and right? Yeah. You are going to build this company leveraging the best of technology and you can, you wanna make sure that you can leverage the potential for people.

They don't have to, they don't, they can coexist. And I think the one thing I'd add to that is. There will be new roles, there will be new tasks, there will be we every, we understandably focus on what gets lost. But what about the new and interesting, it, this is, this interface between people and technology hasn't existed at this scale before.

There will be new jobs and new tasks and new roles and new skills that don't exist today that will be, available for people to do. So we must challenge ourselves to think about both, not just one.

Siobhan Savage: Bold and responsible, build and reinvent boldly but do so responsibly. I think that becomes, that should be the compass of decision making in terms of the workforce strategy that organizations are creating.

Deb, I could keep you here for days 'cause we could talk a lot about this. Deb, thank you so much for sharing your time. Perspective. Thank you for all of your leadership, your coaching, your really good feedback. Feedback is a gift, and it's best when it's clear and it's, this is not working. And why, and because then people can find solutions.

There's so much more we could explore, but for now, I'm just so grateful to have this moment in this conversation. You can find Deb, or we'll share Deb's, social media as well. You can follow, what she's getting up to and what she's involved in. Thank you to everyone who's dialed in. Thank you Deb, and have a great day everyone.

Deb Yates: Thank you. See you later.

Siobhan Savage: See you soon.