If you’ve spent any time in talent acquisition recently, you’ll know the pressure is on.

AI is reshaping roles. Entry-level jobs are changing. And recruiters are being asked to deliver faster, cheaper, better — without a roadmap.

But what if that pressure is actually an opportunity?

Sam Schlimper, Randstad Enterprise Managing Director Advisory, believes now is the moment for TA to step up — and shift from support function to strategic partner. With decades of experience across agency, RPO and executive search, Sam brings a unique systems-thinking lens to the AI debate. And in this episode of TA Disruptors, she shares what it really takes to future-proof your recruitment strategy.

Join Sam and host Robert Newry they unpack...

🐝 Rethinking early careers: Why it’s time to stop hiring for jobs that don’t exist — and start hiring “scouts” instead of “executors”

🧠 Systems thinking in TA: How to break free from the cookie-cutter hiring brief and influence the business upstream

⚖️ Bias and process design: Why equity starts with better design — and how TA can lead the change

📊 Strategic metrics: How to reframe what ‘good’ looks like and reset expectations on candidate quality

🤖 Making AI work with humans: Why the most powerful tech still needs a human in the loop

This episode is packed with sharp insights and practical takeaways for anyone looking to drive change across their hiring strategy — from early careers to executive search.

Listen now 👇

Transcript:

Robert: Welcome to the TA Disruptors podcast. I'm Robert Newry, co-founder and chief explorer at Arctic Shores,  the task-based psychometric company that uncovers potential and helps companies see more in people.  

And in this fourth series of our podcast, we are focused on exploring, building and transforming TA in the age of AI.  And in today's episode,  we're going to explore the strategic impact of AI  across the whole of the recruitment process. And I have a phenomenal senior leader at one of the largest global talent solution providers to give her perspectives and insights. Sam Schlimper is an industry veteran, currently managing director at Randstad Enterprise,  and advising some of the biggest organisations in the world on their talent strategy.  

Prior to being at Randstad, Sam held senior TA roles in the financial services sector,  including Barclays Bank and Standard Bank. Sam has a passion for innovation and transformation.  And your expertise is bringing together people, process, data and technology.  An expertise that I am sure is in high demand as AI disrupts every aspect of the way that we work.  Welcome, Sam. 

Sam: Thank you. It's great to be here.  

Robert: So let's start with what are your clients experiencing with the AI enabled candidate?

Sam: I think everything and anything.  And I think that's probably the space we're in is that  we've got clients who've got really sophisticated candidates who are using all kinds of AI and then we've got clients who haven't experienced that yet and anything in between.  I think what they are looking for is some form of what should we be thinking about and how should we be thinking about that.

And even though AI has actually been with us for a very long time, with the kind of chat GPTs of the world and genesis of AI coming online,  more and more organizations are looking for  how do they harness that potential in the right way and get not just kind of efficiencies and effectiveness, but really what's a quality output? What should they be thinking about? How would they be thinking about it? So I we've got clients across that entire spectrum asking questions. 

Robert: Yes. And I think that's part of the challenge of where we are at the moment. You've got some people  that  are going,  actually,  is this a big issue? The candidates have now got Ai in their fingertips on their  phones that is way above the technology that they used to have before and in many ways actually more sophisticated than what we have  as  recruiters in our hands. But there are others that are seeing a huge increase in volumes, there are challenges around integrity. have you got cases where, you know,  that is something that has been a real problem? 

Sam: Definitely. And we have organisations who've come up very strongly and said, this is our belief and this is why, attached to their values, their culture, their strategy. And then we have organizations who are mute and then people don't know what to do about that. So, candidates going, going... shouldn't I, what's my expectation here? I actually had a really interesting conversation on Friday with, or Thursday with a person and consultant, we were talking about this, is it that a candidate comes in and if they don't use AI, you're sort of cutting off a limb because it enhances you in a great way?  

Or is it that actually it's more like a tennis racket that was,  and actually what, because what we still want to understand, and I think where most of our organisations still are. And actually, most candidates still are is, I want you to see me  and who I am as a human. And the organization wants to see  who you are as a human and what you bring, plus how AI enhances that. But what we don't want to do is cut straight to the,  what are you in an enhanced AI state? So I would say that in 99 % of clients and in candidates, we are saying, I want to be seen. I want to be seen for my humanity and I want to be seen how I'm using AI because it's a skill that I have and a skill that I want to grow, but still we want to be seen as humans and what that brings to an organisation. 

Robert: Yes, and I hear that a lot that we've got to figure out how do we enable candidates to use  AI while it's still at the same time not overlaying their capabilities with something that isn't them. And so what's your advice to your clients then? Because you've got, you you come from the financial services sector and a lot of the regulatory authorities are saying we've got to deter and detect  AI. AI is bad because it impacts the integrity of the process. So candidates should not be using it and organisations should make that clear that they can't use it. So what's your take on advice? 

Sam: I think my advice is clarity. And again, this goes back to what does your organisation stand for? An explanation as to why. Interestingly enough, the AI Act is explainability and transparency,  the same applies and actually always has with candidates. So what are you expecting of them? Why are you expecting? But where do you want them to use it? Where do you not want them to use it? And why and what's your explanation to people? That's the advice. I don't think there's a wrong or right. The world will use AI though. And so our advice is also this is going to happen. So therefore, let's not pretend it's not. Let's not know how fast, how slow, we don't know what reputational things will come out and of course, our clients want to protect their reputation. 

I think it's really interesting when we talk to clients about the stories that you hear on AI and probably Microsoft is the one that people still bring up around, the bias, because bias often comes out interesting enough, what were the learnings from that is not what we focus on. We focus on that was the bias actually if we focus on... or 

Robert: Amazon?  

Sam: Sorry, yes. And thank you. And I think that's really important is what learnings  do we have from this? How do we keep that in a safe  way? And how do we learn as we go without having reputational damage? We see some of our clients going the whole hog. So we've seen one of our financial services firms actually do as much automation and as much AI as they can in the entire recruitment process. And then we've seen them come back a little bit because the feedback they got, and this is really important, was, that feels a little wrong to us.  as candidates and as  people hiring  want more human in the loop here.  And so they almost chose the route of let's push the boundaries and then let's get the feedback as to where that feels good and where that doesn't, what the experience is and how that's affecting outcomes.  

I think that's the first advice is  what does it, and the other thing is what are you measuring?  So how are you measuring things along the way?  This is not one  sort of holistic, there are measures to be put along. What is the measurement? What's the impact? How do you feel about that impact?  What's the unintended consequences of an impact? What we encourage our clients to be is to be scientists, like scientists deal with things, right? Scientists don't go into the lab and go, here we go, off you go, we're running with it. 

Robert: evidence-based, isn't it? 

Sam: It is, and it's feedback loops. It's not a once and done. And so that's, think, where we are with AI. So we see clients taking AI in different parts of the process. We tend to see clients still being a little bit nervous about that front end matching and making decisions, of course, because there should be a human in the loop with those things. I will be a little controversial here, Roberts, and say…

One of the things I think this gives us a fantastic opportunity to do  is think about what we're putting in at the beginning of the process. And the reason I say that is we have bias inherently  in all of our processes. 

Robert: Yes, we always have. Yes. 

Sam: And that is true. And I think what people are worried about is when you put AI, then you create that in a sort of prolific way throughout your entire. Exactly. It's just repeated at scale and it can be exponential. But what I think it gives us the fantastic opportunity to do is really think about that top of the funnel. What is it that we understand creates performance? And I don't think we've spent, I mean your world is  purely based on this right? We have not spent enough time doing that.

We've almost kind of gone, okay, well, if we get that kind of right, we'll sort it out as we go. This, think, will force us ultimately in the right way to really think about how are we thinking about potential? What does that mean?  In a world, how does the world of work change? I think that top end of the funnel will become highly focused because now we're going to automate and put AI down the funnel. 

Robert: Yes. Well, I like that. And I think it's an important point that you've got two big elements in what we need to think about here is this transparency, how is AI being used? And then we have to come back and think about actually the world of work is going to change and therefore we have to think about what performance in the future is going to look like. And  I will come back to that because I think that's a really important point. But the first bit around  back in the process then again and how AI is being used, one of the things that I feel it would be great to get your perspective on this too, that is one of the challenges around this, is what I talk about as the  moral contract that exists between candidate and recruiter. And the moral contract used to be,  I put a lot of effort in to fill in an application form, I will go through this recruitment process and whatever hoops and hurdles that you ask me to do. In return, I expect you to give proper thought and respect to whatever effort you asked me to put into.  

So if we are going down the route of AI and automation because we just have to because the volume of  applications and even if we're transparent in saying to people we're using AI in the process,  do you worry at all or what's your advice to your clients about that moral contract? Because if candidates think you're using AI, then they go, well, I'll just use AI and it's just a battle of AI versus AI now. 

Sam: So I think, interesting enough, and again, I was trying to think, he posted this, think  my colleague, Len Cathy, posted this. The issue has never been about the tools we use or how we use it. The issue is ethics and morality. No matter what you're doing, that still stands. And so  our advice to clients is that's exactly what you have to go back to. What are your ethics and morality? What is the contract?  Why is that your contract? We've said transparency, there's also explainability, right? And that would be, I was on a panel with a law firm that other day and we're saying  that's going to become even more important. 

Now, interestingly enough, an AI can say, well, these were the steps that I took you asked me to do this, these were the things you asked me to look at, these were how you think they were performance indicators, I took these seven steps, so AI actually has more explainability than what sometimes we have today, so that's going to be a really interesting thing as we go, it can show you its steps if it's been set up in the right way, but it's our steps, to your point. We are still guiding the steps, so again going back to we need to be really clear about what the steps are,  what is our social contract, and our ethical and moral compass.  

One of the things that we see organisations do incredibly well and the big organisations that we work with the world, and I can name this because they are publicly out there. So if you think about the IBMs of the world and their CHI Ro-nickel,  they were the first to set up a governance around AI with a people element. Because often it goes product first, what's happening with our customer, how are we putting that into whatever our business strategy is there's a people element for your employee that needs to be thought about whether that be a current or possible employee coming in that is then brought into that governance and ethics and moral there's a, we've seen organisations step that up well and then make decisions off the back of that as a principle rather than a technology's come in or there's a use case the first thing that comes in is what's the morality, what's the ethics around that, and how does that sit with us? So I think that's a great point. 

Robert: It is, and it's a really important one that I think we have to kind of explore a bit more, this point, but it's one thing to have governance. It's another to say that we need to have human oversight. Totally in agreement with all of that. Then there is the understanding and the discipline about how we make sure that that explainability is as we think it is. Because for me, and it's be interesting to explore your thoughts on the difference  from the EU AI Act between automation and AI. 

Because in my mind, automation is where, to your earlier point, somebody in the organisation has set those seven elements and criteria against which a computer algorithm has then determined a score. That is very different from saying, here's a job description putting that into  an AI large language model and it's scoring it and then post-hoc explaining how it came to that decision but that wasn't set by a human and is that the kind of governance that you're seeing? 

Sam: It’s a beautiful thing. It's where are you putting humans in the loop and for what? So is it your design? Is it that an to your point that generative areas design something and now you're checking and validating that. Those two things can both be true, but you have to be really clear about that.  I also think one of the infancy areas that we're looking at is  when you think about work and let's say  recruiting is a piece of work to get done. We don't think of it like that today. So we think about, what the outcomes I'm trying to do, what are the tasks I'm trying to achieve, what are the skills that, and then what part of that should be automated or got AI, what part of that should be human and what are the skills that are required to do that and therefore which humans are best to do that. 

We do a lot of that with organisations around redesigning work to then make those decisions rather than  there's this new shiny object  and I can use it.  And I'm not saying people shouldn't experiment with those things, but before you put something in place, you want to be thoughtful about your design. You're designing a system of work of which humans automation and AI are all part of that. You need to be thoughtful about  what you are designing in that and why.  And so I think the design of work is super important. I also think it has an implication and there's a fear around this and excitement around the skill of recruiters.

Robert: Yes. What are they? What value and what skill are they bringing?  

Sam: And you brought up an amazing word. The way we measure recruiters today,  is that the value we want them to add or is that because there's a process that they are driving today and that's a of  KPI widget based productivity set versus a value set. Those things are fundamentally going to change. And we need to be thoughtful around how we move people through that in a positive way too. 

Robert: Yes, there's a couple of things to unpick around that are worth exploring a little bit more.  One is the your point about with, you you talk about a system of work and  understanding how that system of work is going to change in an AI world.  The same can be true of a system of recruitment. And I talk a lot about the golden thread that needs to be between the output, this is what performance looks like,  and then we need to design back and that kind of systems thinking around that to.

The application and who we want to attract. And there has to be a golden thread all the way through. But so often, and maybe you find this too, I find that golden thread has been sliced so many times because somebody has come along and said, oh, look, this is a  lovely piece of AI technology. My new ATS provider has said, oh, I've got this new feature. We can screen CVs now, resumes for you.  And and they go, let's, you know, hit switch it on.  And then suddenly a golden thread is because how does that relate to performance?  Therefore  part of the value, I think, of recruiters now is  how  we need as recruiters, we need to understand that golden thread.

Sam: 100%. I couldn't agree with you more. And I think it's interesting, right, because there's upstream and downstream and you have many stakeholders. That's what is really exciting  about recruitment and really complicated  because it's not that there's one element to that, there are many,  but to your point, there's this golden thread. 

So I think one of the skills that recruiters will move into, yes, there's relationship and yes, there's  understanding and seeing people and being able to understand the nuances of people,  really important. And I don't think that will go away,  but it is the systems thinking.  I,  I, again, I don't know what your experience of this,  even before AI, I think AI is just going to heighten it. And I think it does. This is another example. We just spoke about  connecting to performance. Here's another heightened.

What I've seen before with recruitment processes is SLAs where it's handed from one thing to another. It also causes the same issue, right? Because you are chopping between things that sometimes  you can't then see this golden thread  and it also creates an inconsistent, sometimes you need to move people's faster and sometimes they need to go slower and that system doesn't allow for that. You need a dynamic system that changes based on things like supply and demand.

Based on what's happening now and what, and that dynamic system doesn't necessarily take place in some of the processes I've seen. AI will actually be able to help that dynamism and actually go, oh, this person needs to move faster because they've got something else going on. And if we don't do that, we're going to lose out here. But look, there's these three other people here that could,  how do we work that system differently? That's going to be helped. But I don't think we've, I haven't heard people talking about this. I've heard them more about like you said, what can I put in here  at this point in time? So I  personally have a  bugbear against SLA's  because I think it creates a fragmented system.  

And so  I think it can be helpful if we again, we're thoughtful about its design rather than we just plop it into a point because. 

Robert: Because somebody said I need to improve my time to hire. 

Sam: Yeah, which is probably the fastest  and time to hire is important.

It's not the biggest importance, right? Quality of hire has been this elusive thing. the most, yes. Yes, like how do we measure this quality of how do I know? But actually we can really start moving towards that quality  perspective. 

Robert: Yes. And so the challenge,  and it'd be interesting how you would advise,  you know, senior TA leaders to deal with this because you've got directives coming down from  senior leadership two directors I'm hearing all the time. One is we need to use AI, we need to be more efficient  and actually recruitment is one area where  we want to experiment with. So you're getting pressure of use AI, use AI. And then equally, TA teams are seeing their budgets  slashed. In many cases, my clients have made between 20 and 40 % of their budgets have been reduced in the last couple of years. 

So, you've got TA leaders sitting there going, well on the one hand, my senior leadership is telling me I need to adopt AI, I've got less budget so I'm going to have to do more with less.  And then on the other hand,  I have to  experiment and think about how I do this without completely  breaking recruitment.  

So there's a tension in there between I've got to get my SLAs done and I agree sometimes that they're  counterproductive,  but at the same time under huge pressure to transform and change. how do they, you know, square that circle as it were? 

Sam: And I listen, I feel that I have a level of empathy because it is a  circle square and both of those things are true and all of that is needed. So that is the reality and that is what they're being asked to do. I do think often and again in many organisations  there is little time spent on innovation and I'm not actually going to call transformation because I think lots of time is spent on transformation whether in the right place or not  let's just park that because I feel people when they say the word transformation it feels a little bit like strategic workforce planning and everyone sort of loses the will to live because it's my constant transformation and actually we've never really landed anything I think is what often feels so.

But I do think there's innovation and experimentation, which is super important. How is it built into the work system? That's the question for me. So you have to build it in as it happens.  And it is part of what you do as your job. It is not something that is nice to have. I feel the same about learning.  Learning is not a nice to have. Learning new things is part of your job. If you're going to be great at any job, you have to constantly learn and unlearn.

So it's not a extracurricular activity that happens between the hours of three or four or what everyone puts in on their Friday afternoon and then never gets to because they've still got all the  things, tasks in their inbox.  So I feel like this is not an extracurricular. It needs to be built into the way you work. Of course, there's  what we call business as usual, which is  how do I be as efficient as possible? Make sure I'm not,  there are no extra slush funds sitting around. I haven't come across a team anymore that's like, oh yes, I've got this thing stashed in the back for,

Just that's not happening. So you have to be thinking about that. How am I going to be as competitive,  as  productive,  as commercial  whilst doing the right things? And I think that is a tension.  And I think that's a leadership moment. 

Robert: It is. And I wonder, I wonder Sam, whether we need to petition our TA leaders  to  go to the board table and do what the CTO and the IT have done for many years, which is, and I love your point  about innovation and experimentation, because that drives learning.  But in TA, we've never gone to the board and said, OK, if I want to do all these things, I get all these strategic imperatives that you're giving me,  then I have to be able to innovate and experiment,  in which case I need a sum of money.

Because  you don't object to IT doing that IT have always had budgets for trying out new tech because they're saying that's the only way  we can keep on top of the change. So why would that not be  true for TA? That's true. 

Sam: And I think you often see, well, you're starting to see now, which is, you know, at a broader level, the CHRO and the CIO role coming together. 

Robert: Well, right. I it Moderna wasn't there that has...

Sam: Absolutely, that's done that. And we see that more and more because the point is AI is a technology and a colleague, it's interesting. It's both of those things. It's not just a tool. It is a colleague, which is  now no longer human. Therefore you have that crossover. So you do need to experiment. You always have, but even more so now.  And 100 percent, why would you not get your...  The other thing I think sometimes we've over leveraged hiring and under leveraged mobility and learning.  So I think we see that starting to change too is actually  the way we go about recruiting or hiring  should be internal as much as it is external. 

Some organisations have always had that, some really haven't.  And so that is, am constantly looking at who my people are, whether they be external to my organisation, whether they be  non-permanent, whether they be permanent in, and that is my workforce of the future, plus its synthetic friend.  How does that come together? I think that's a different skill set. I also think,  Robert, what's really interesting is structurally, It often tells me a million things in an organisation is where have you put recruiting? Mm-hmm. 

Robert: But in terms of organisational structure. terms of organisational structure. 

Sam: Where is it at the table? Is it purely a shared service transaction? Is it sitting in your strategy? Is it sitting in? And that is often a question I'll ask an organisation to say, and why have you housed it there? How do you think of it then? Do you think of it as a pure transaction that has to just happen,  then you won't be doing the other things and then you're going to miss out. 

And so it, and because it crosses those boundaries and I think that's what's really interesting about it too. So I'm not saying it shouldn't be in a GBS shades of,  but they're parts of it that shouldn't and it crosses over those. And so how you structurally think about how it's set up in your organisation to enable it to go to the board, to have the right conversation. 

Robert: I think that's  going to be so interesting as we sort go through all this change in the next couple of years is how organisations think about that and they think about recruitment.  Because it always makes me smile that there isn't from a publicly listed company an annual report that I read that doesn't start with, people are our most important asset. then you go, okay, so and how much have you invested in recruitment or is it a shared service that has, you know, got a shrinking budget?

Sam: Agreed. I and another structural which I'm not going to solve for but I often point out is where does it sit on your finance? it sit under investment? 

Robert: Yes or just cost. It's under cost. That's an interesting thing. 

Sam: So okay we have to make it a bit more strategic and how then are you advising your clients  on what to invest in and what not to invest in?  

Robert: It's a great question because it doesn't really have one answer. So, and I mean, that sounds really non-committal, but it's true. Again, one of the things that clients will often come to me and say is, okay, so what's  best practice? What are others doing?  And I understand why people are asking that. And I understand there's a need to know what's happening out there.  but I feel like companies are often obsessed with what others are doing rather what they should be doing. 

Sam: Because it's all situational and contextual and nuanced. 

Robert: It’s totally contextual,  aligned to your  DNA of your organisation and your strategy.  And just because you're in an industry of  financial services or other  does not mean you want to be doing what other financial services firms are doing. Yes, you might want to know, but  to what end?  I don't think organisations spend a great deal of time thinking about,  what do we want to be?  

And it tends to be and...what others doing,  great, but what do you want to be and why do you want to be that? Because if you focus there, that's what gives you that competitive edge. 

Robert: Yes. And that, of course, is  a good common sense around thst. I think part of the challenge is,  mean, particularly when I've spoken to the legal sector and the financial services sector,  you've got disruption that are going on in there sectors in their huge amount just think in financial services, you know, the revolutes the world  and and so if you  are not  keeping an eye on what's going on out there and how the newer organisations that coming into your sector  are organizing themselves and structuring themselves and the processes they're using and you're not attuned to those you're going to be in trouble but there of course they have a completely different contextual setup.  

So how, if you are,  you know, how do you go about then  talking to your clients about, because they worry about transformation and  in some cases you're going, oh my God, I've got just this enormous  organisation here. It's like shifting a tanker and yet I've got these fast moving  vessels that are outside, everybody's telling me that I've got to be like, so how do they make that start of change without having to completely overwhelm their normal working life. 

Sam: And I think just as you said,  have yet to see,  I say that with,  when transformation is we're doing it all for everyone all the time.  It's just not right. It's not true. So I think  with our organisations, it starts with where do you want to begin and why, taking a little bit, experimenting, innovating in that space and testing it in that space, learning and truly learning.  And again, everyone talks about fail fast learnings are thing and then you see the behaviors of, but that wasn't delivered on time within budget therefore that was. Yes, you've  got to set it up for success in the first place. You've to set up an entirely different way of measuring value in that situation  other than in your kind of BAU what you're trying to deliver, but allowing that and then moving that across the organisation.

that is when we see the most success.  I think the other piece of that, and again, whether it's AI or anything else, the word change, I don't want to use the word change management because that's really super, again, it's just one of those things, but it is, you are changing the way people  and systems work. If you do not spend time doing that, it doesn't matter what technology, what AI you're bringing, it will not make the difference that you want it to make.

So therefore, having that comprehensive view of why are we doing the change? What's the root cause that's happening? Where are we going to start with? And, you know, I work with organizations that actually have a very different views on this and both can work. So let me give you some examples. I have a financial services organisation that decided they were going to look at where to put an AI and they decided to start in finance. And the reason they did is because they believed if they could get the CFO on board. 

Robert: Then it'll be easier for other projects as they come forward.

Sam: because the CFO is going to go,  this is actually worth investing in and going to tell everyone about it. They also knew it was going to be one of the hardest places. So they were going to have to go really slowly, probably  to win the race. was their strategy. That's what they did. That's what really worked. Have another organisation, different industry  who chose a different route that said, actually we were going to put in AI where people put up their hand.  And so they opened their sort of internal system and said who would like to test an experiment? Who would like to be a doctor?  Who's got an idea?  We're going to harness that and we're going to,  and that worked for them  because in their organization, culturally, that's the way things work. 

In the other organisation, they had a strategic intent of how they were going to move things forward. So I don't think there's a  single approach. but you've got to understand what are you doing and kind of go with why have you chosen that path? What is it you're trying to achieve with that and then stick with that and what are the principles that we hold onto whilst being  adaptable throughout that. And that is very true that we see when people are implementing AI  into their organisation, how have they chosen to go about it and where they doing that? So the smaller chunks definitely works.  

Robert: Great, great advice. And let's go back now to the thing that we parked earlier in the conversation around performance. So we understand about process now and we covered that some really good thoughts for you on that one. But the part of why we're changing the process and what we're trying to achieve from this  comes back to that fundamental first principle, quality of hire. And quality of hire  in the future with AI around is going to be very different from what it has done in the past. So how are you thinking about that and how are you advising your clients on that?  

Sam: So, and again, I do not have all the answers on this. I'm  surprising. And because we are working with our clients and often we are not working with them on what best practices, we're working with them on noodling it out, right? And this is one of those examples. Return on investment to value  is a slightly different measurement  and value is a lot more nebulous to measure than return on investment but we think is right in many cases.  

And so what we do with our clients is we work with them on how we're actually going to get that done in this particular circumstance. And we don't have that, here's the formula for how you test value versus return on investment. We don't have that. But we think it is really important because as you say, that is going to change. So however we think about it today  will change tomorrow. again, so how, what are you building into your organisation in terms of that muscle that thinks about what value is and thinks about how you measure it and thinks about how it's  tested. And then changes it, as that goes, rather than ROI is this.  

And again, I feel often TA leaders and other leaders in organisations get stuck in the process that has become quite  known in organisations which says you have a project,  ou go to a board or whichever,  that project has to have a return on investment attached, it has to have all the details set in, life doesn't work like that anymore. And yet we're still using that. And so we are working with the organisation to say, again, out of that, how would you think about this? What's the hypothesis? What's the big idea? And when you think about startup firms, which are driving a lot of the growth, that's what they work on. the hypothesis, the big idea? 

Let's test and learn, test and learn. I had a really interesting conversation with a startup AI firm last week who actually, mean, it's fascinating, because literally boldly goes in and goes, so I've got a builder of talent acquisition, I've got an analyst of what happens in your data, and I've got a recruitment agent. And they are working, I've put them in organisations, everyone loves them, everyone should have them, how are you going to help me put them out there? There's no like, oh, hang on a second, is this the right or wrong thing to do? 

Let me ask you I've already proven this the confidence level in those startups, which is amazing and terrifying all in one. So there's a bit of, well, hang on, why would firms want to do this? And they kind of look at me like, why would they not? This is mad. This is the way the world's going. And so I think there's this, this like two speed. How would you test that? How would you put that into your organization in a way that feels good? And one of the things we talk to organizations about, again, I realise, yes, measure, all of those things are important. What feels good and what doesn't feel good? If you were doing things that don't feel good, as a human, should probably think about that.

Robert: Yes. Well, that's right. And a lot of the time, you know, the poor TA teams are so inundated with just trying to get the day-to-day done that if somebody comes along with confidence, and what appears to be a silver bullet for their problems. go, hallelujah,  know, that's, that'll make my life easier. And so I think you're right. We have to think very carefully about  what those return on investments, what the performance criteria are around that.  

Where I'd like to go also on this performance piece is what does good look like? So the whole thing about recruitment is we want to get to this output. That's the golden thread piece. What is the output? But the output in the future is going to be different for a lawyer. It's not going to be, I want somebody who can read through loads and loads of documents. AI is going to do that  so much better. It's going to be the same for so many other of those entry level roles. And we're going to have to rethink a bit now. I mean, you AI can create graphics it can create videos. 

So, what's what's your  thinking about? The the output  piece and how is that changing and how should organizations be thinking about that?

Sam: It's a great question It's probably where we spend most of our time and work whether it be TA or elsewhere But I can take TA. If I think about the skill of a recruiter in the future  one of the scenarios very strongly could be that they spend time with the organization that they're hiring for in understanding work design. To your point. Yes, has to be really thought through and structured, that work design. So instead of a hiring manager just come and saying, oh, Robert, I want you to go and find me a person who does this, this, this, and this, because I know, because I've had seven others like that that seem to work well.

Robert: Yeah. Yeah. Give me the cookie cutter. 

Sam: Give me the cookie cutter. What the, I think the skill set of the recruiter might become is.

Right, so what are the outputs we're trying to get in this work? What's the task that then associated? What could be done by AI and other? Do we have that now? No. Are we going to put that in every time? Therefore, what is it left for the humans to do? Therefore, what skills are the humans  and what potential would we need to have that sit underneath those skills?

When I talk about skills, I don't just mean a list of technical skills when I say that.  Therefore, how do we understand,  we're going to bring a set of people together with these skills in order to work together to get those outcomes? That is a very different recruitment process and activity than what happens today. 

Robert: It is and quite challenging. mean, you you're going to a hiring manager and talking to them with slightly different language  and it probably feels a little bit confrontational in some ways too of  what task and they're going, hang on, just get me another one of these. But I think you're right, it has to be a bit more of that trusted advisor.

Sam: It's exactly what it is, right? And so I think this is again an opportunity for  talent acquisition and recruiters to change from a process person, as in just running a process into,  because again, if you think about what a hiring manager wants, what do they ultimately They want to have confidence that whoever is joining their organisation  is going to  improve the performance and how it feels.  If you can rely on the fact that your recruiter can tell you how to do that then they won't care if you're telling them because that's what they're looking won't be exactly asking questions that feel challenging, actually ultimately they are All the right reasons, exactly that. 

So I do think that's where a really strong scenario of a future will look like around that. And then it will be what technology do we have, including AI, that would help us bring that to life. Because I think there's two different… branches of AI. One is the products that we have and some of the technologies that we use, whether that be in TA or elsewhere, and it's built into that. The second is  that is how we work. It's not just a technology or a product. It's that we work with it on a regular basis. And again, I think we're at the early stages of how do we think about that? You know, we talk about self-automation. So when do you hand it over to something, an AI, because it is better.

And I just need to validate and be a checker in that When do I work work with it in a sort of central type of way where I'm doing some pieces because that's what humans do and it's doing some pieces  and Then we are coming together. And then when are we cyborg ing which is  we are doing things together all the time I Don't think in work design and it's one of the things we work with our clients on people are thinking about that So not just work tasks and skills, but how does the work actually get done, where you build in ethics, build in morality, you build in great outcomes. Where you're working together in that way, because some things are self-automated. We were speaking about the legal sometimes. You don't, I wouldn't want a human looking through the same documentation. I would want. 

Robert: AI is going to be more efficient, more reliable. 

Sam: I want the human bringing  some form of nuance in their lived experiences, but I don't want that. I want that to be self-automated.

But on other things, I don't, I want that to be Cyborg or Centaur, and I want us to be thoughtful about  what that is.  

Robert: Sure. And so if that's where we're going on this, then that's going to create a very  different  emerging early careers, talent pipeline, because that's not how we have thought about or developed are emerging talent around that too. how do you think that's going to change things? 

Sam: 190 % agree with you on that. I think that's going to change fundamentally. I think actually for even experienced hires, and we call it that, right, which is interesting, because they have some sense of experience, but actually their experience isn't necessarily going to lead them to what we them to do. therefore the ability to understand potential.

What people actually bring to the party, what they are at their inherent core and what they show up with, I think will become even more important. So I'm sure your business is,  I think it's fundamental in those type of things. And I think that's a changing market too, right? Which is also going to take some- 

Robert: It's gonna be much more focused on potential, isn't it?

Sam: Much more, and therefore scientific around that, right? I think for emerging talent specifically, and again, the team and I are working very strongly on this because we see numbers declining.

So if we look at overall employment numbers, they don't look bad. But when we take out the emerging talent numbers, they actually are declining. And again, my colleague, Lynn Cathy, has posted about this, my colleague Francesca and I are working very strongly on what that looks like. So we see a different role emerging for emerging talent then. The word emerging seems to be coming up lot. And that's because… they are not going to be doing the same things that sadly us older generation had to go through. 

Robert: Well, it was a different, exactly. It was a different world of work that we coming into. 

Sam: You were doing some of the things that you were just learning stuff by rote and what have you. Actually, that is no longer going to be needed. So what is the role going to be? And  we use the analogy and again, my colleague Francesca is working strongly on this  around the beehive and you have a queen bee, you have workers, but you have scouts.

Robert: Scouts, I've been studying bees enough that it's a lovely 

Sam: So 10% of the beehive always has scouts and those scouts are not going and finding the food where they know where it is, which the workers are. They are finding new things. They are finding new things. Just new things to look at. New food sources of food, new ways of journeys, all of those good things. That is their sole purpose. Emerging talent, actually the most neuroplastic and again, want to give kudos to my team.

Harriet and my team, I think you may have met, whose psychologist will tell you this is super important, they are most neuroplastic. They are set to be scouts just by their very nature at that point. They want to go and investigate.

Robert: Well, that's right. They're coming into the world of work to learn, figure out where they are.

Sam: They are almost predisposed to scout work. So how do we think about what scout work looks like in an entire organisation? 

Robert: And we've never thought about it, but scout work  in the past, it's just been grunt work. 

Sam: That's it. So scout work can be anything. The other thing is they are in proper learning mode, right? They haven't got the deep canyons of learning that and more executive type of leader will have, which in some ways brings great things, but also brings other things because you're in your deep canyon. So they can actually disrupt that and help those people unlearn some of the things that are no longer relevant. And so we see two really strong roles for emerging talent, scouts and unlearning from others. And they could actually play a very different role in an organisation. 

One that is crucial to a survival of an organisation going forward particularly as we spoke about where we're going to have to adapt in a much more agile way. And if you think about a system of adaptability that can inherently be built in with emerging talent and how exciting. 

Robert: Fantastic and exactly and I think there's a lot of  worry about what the role of emerging talent is going to be but  when you describe it like that and I love the  analogy on that it can be incredibly exciting and incredibly rewarding and valuable  both for the organisation  and for those individuals  coming in to have that type of role. 

Sam: Because you know we've all aspired to do grant work right?  

Robert: that's right exactly. Well, you  you've come out of university thinking, right, how can I use all these you found  skills of problem solving and creativity? So let's use it as opposed to, right, here's just a stack of documents for you to look through. 

Sam: I just want to pick up on that's interesting. Yes. I think tertiary education and institutions are going to have some interesting times. 

Robert: They're going to have to change a bit too. 

Sam: Yeah. think universities being one, but there are a plethora now therefore of where you would create problem solving, collaboration, creativity that doesn't necessarily come from a university degree. 

Robert: No, that's right. You've got T levels. got further education colleges. of whatever it is. 

Sam: Yes. You can open that up, is again. 

Robert: Apprenticeships. I absolutely agree. Final question. Just thinking about emerging talent and looking at potential. I know that neurodiversity is really important to you work with the  brilliant  Kate Griggs from Dyslexic Thinking and there's a lot of change that's come about in the last few years about what different thinking styles, different brain structures can bring to the world of work. How do you see AI impacting that see it as levelling the playing field? Do you think  access to AI may  actually hinder things? Yeah, what's your take?

Sam: Again, I think it's how we think about it, but to be honest,  and if you speak to Kate and again, my colleague Matt and… Kate have done so much work on dyslexic you and us and from a workplace perspective,  if you think about dyslexics as an example, all of their skills, if you partner with them AI just takes them to  the next door. So the things that AI is great at are not necessarily the things that dyslexics are good at, but the things that AI is good at  re dyslexics can just knock  the ball out of the park.  That is true of, and again, I'm going to steal a word,  Dart Linsley who does humans for work, uses neurodistinct rather than neurodivision and I really like that. think it's a dartism.  

I think that again we can think about AI which completely takes away barriers that have been artificially put in in the past  for neurodistinct people. It is very close to my heart as have my family are  full of  neurodistinctions. But again I think and we've worked actually and again I can talk about this openly if you Laura from HSBC has been amazing in working with Kate and  thinking about the process of hiring and removing barriers fundamentally to bring in neuro-distinct people into their organisation and has done some incredible work. It takes leadership to go, how are we going to make this work?  The other thing that is really important on this is if you do it for neuro-distinct individuals.

It just makes it better for everyone. For everyone, doesn't it? It's not like you have to have 17 paths. Which one's for dyslexic and one's for autistic and one's... That's not true. If you just remove the barriers for...  Everyone has a better experience. So it's literally like, why would you not do this? But it's taking the time and energy from a leadership perspective to do that. 

But again, with AI, I think we're going to be almost… forced in a lovely way because  it's going to remove those barriers. is. So the playing field to your point will become, well it's AI versus AI, well then what's the differentiator? And that's where our humanity comes in, in its  beautiful squiggly craziness. 

Robert: It does. And I think on that positive note is where,  you know,  we want to and need to look at what  AI is going to bring to us because with all change, disruptive change, there is an element of fear, but there's an element of opportunity.  And you've shared with us today a lot of really good reasons why we should be looking more at the opportunity rather than the fear, but we should never keep our eye off the dangers of it. But it's been fascinating talking to you, Sam, lots of really great advice and thank you for coming on the podcast. 

Sam: Thank you.