Mervyn Dinnen  0:09  
The HR Happy Hour network is proudly supported by Workhuman. Every year, companies spin their wheels searching externally for senior leaders. Meanwhile, the next VP is already on the payroll, recognized by peers, but overlooked on the org chart. Future leaders by Workhuman fixes that. Using AI and real-time recognition data, Future Leaders identifies your highest potential talent four years ahead of schedule before they burn out, check out, or get picked up by someone who saw what you missed. Build smarter, promote confidently, keep your best people. Future Leaders only from Workhuman. Learn more at workhuman.com that's W O R K H U M A N.com Thank you for joining us. Welcome to the HR Means Business podcast, which is part of the HR Happy Hour Network. I'm your host, Mervyn Dinnen. I've been to two or three events recently in the HR and Turner acquisition world, and it won't come as any surprise to listeners to find that nearly every conversation is about AI. So, what I've decided to do today is turn to somebody who I believe has a lot of knowledge about this, a good friend, my co-author of two books, Matt Alder, who runs the very successful Recruiting Future podcast. Matt, welcome to the HR Means Business podcast, and would you like to introduce yourself?

Matt Alder  1:40  
Yeah, absolutely. A pleasure to be here. Thank you for inviting me. Always love being on other people's podcasts rather than being one asking the questions. Yeah, I think you said it all there. I'm Matt. I run the Recruiting Future podcast, and I've co-authored, co-authored two books with you, and I do a lot of speaking and writing about not just the future of recruiting, but the future of, you know, the talent function inside inside companies, and been having a lot of conversations, as has everyone over the last two years, about AI, but how it's being adopted, what it really means, the implications, and what how organizations are thinking about it.

Mervyn Dinnen  2:21  
Yeah, and actually, talking about books, I was at a HR Global HR Summit in Turkey last week in Istanbul, and they had a lot of books there, and of course, our second book, Digital Tunnel, has just been published in Turkish, but unfortunately, it wasn't one of the ones that was given to people.

Matt Alder  2:36  
That' a shame, that's a shame, yes, it has, just a few, just a few, just a few weeks ago. So, any Turkish-speaking listeners out there, make sure you get your copy.

Mervyn Dinnen  2:46  
Okay. Now, look, Matt, you, you speak to practitioners, vendors all the time. You've got a unique take, I believe, of where reality sits, and the conversation sits around AI. You've also been kind of interviewing people on your podcast for over, over a decade now, so I've spoken to a lot of practitioners, thought leaders, you know, around where TAMA acquisition is heading, you know what the future is for HR. So, when it comes to AI readiness specifically, what's your assessment, your, I suppose, honest assessment of where we are now versus where other people seem to think we are.

Speaker 1  3:24  
Yeah, it's a really, it's a really interesting picture, because I think if you listen to the narrative out there, you know, AI is kind of fully embedded - we're doing this, we're saving this, all these, all these kind of things are happening, but the reality is a very mixed picture. I saw a brilliant presentation, actually, a few weeks ago from Professor Ethan Mollick, who is an expert on all things AI in business, and he describes the way that AI works as a kind of a bit of a jagged frontier at the moment, meaning it's good at some things and less good at other things, and I think sort of jagged frontier is very much where we are in HR and talent acquisition at the moment. When it comes to AI, there are certain sectors where it's kind of full speed ahead. We're seeing, you know, lots of AI implementations, you know, results, things working really well, and that's principally in the front line volume hiring space, where seeing lots of adoption, lots of results, lots of interesting work in the rest of the of the talent space is a bit more of a mixed picture. There are there's a lot of experimenting, but really the bulk of organizations haven't moved away from the most simple, the most simple use cases, which in some cases aren't even, aren't even really things that have been possible for a really long time. For example, automated interview scheduling, it's not really an AI thing, it's been around for a long time, and people using LLMs to rewrite copy to rewrite job descriptions, so there's kind of a long way to go, and there is a gap between the people kind of really running with this and everyone else who still very much at the pilot experimentation stage, which is which is kind of different to some of the narratives that you hear being being told about AI at the moment, in terms of what's possible, it's very, very uneven, very, very uneven picture.

Mervyn Dinnen  5:25  
No, I get that. I get that. I was at a conference yesterday in London. It was about the future of work, but unlike, I suppose, a lot of the podcasts we have, where we talk to practitioners and stuff, this was kind of academics and stuff, and they were all very, very cautious about everything to do with AI, but there is, I mean, particularly in the recruitment, the TA space, there's a lot of noise, as you've said, about AI transforming recruitment, you know, sourcing, screening, interviewing, all of this, I mean, you have a lot of conversations, TA leaders. Which, which of the areas at the moment that you, you see genuine, I suppose you know, proper, almost embedded adoption, and what's mainly still pilots and presentation PowerPoint slides with people who think you know this is what it is?

Speaker 2  6:14  
Yeah, I think there's a kind of a fundamental thing here, which is you can plug these AI tools into your existing processes, and the way that you, the way that you work, and to answer your question that way, things like interview scheduling, interview intelligence, using LLMs to create content, you know, they seem to be the, the big kind of activities at the moment, but really to get the real value of AI, you have to rethink the way that you recruit and your processes, because very often recruiting isn't working properly anyway, and plugging AI automation into it just kind of speeds up processes that aren't already working and make things makes things worse, so I think the companies that I'm seeing making real progress with this have really started with the problem, not the technology, and worked out how actually it can help help answer the problem that they have. So, for example, this week I've got an interview going live with the team leaders at 711 and Ace Hardware, talking about this, and you know, we talk about it's basically bringing speed to their retail frontline hiring, and but it's doing it in a way that the candidates have a brilliant experience. The store managers have a brilliant experience, and they really kind of live the essence of their, of their, of their brand in terms of being human. So, they've had to rethink the whole way their recruiting process works to do that, you know. Likewise, another interview with a Dutch company called Picnic, which went live last week, they did the same thing. They looked at how their interview, how their process works, what's good about their process, and what AI could bring to it to make it better, to make it accessible for more candidates to do things at scale they've not been able to do. So there's lots of kind of careful thought that needs to go into this to really get the most out of it, and I think that is why adoptions slow, because people are either doing that or they haven't quite realized that that's what they need to do.

Mervyn Dinnen  6:15  
You actually probably answered my next question that I had listed, but never mind. I do structure these things, but yeah, I mean, I was going to ask you about kind of, you know, the concerns about early stage candid experience, and kind of whether or not you think the sector, in its rush to automate, is actually has it really found an answer to keeping that connection and keeping that experience, which you pretty much answered with a couple of interesting cases, but I think, do you see a lot of companies really, they haven't addressed that yet.

Speaker 3  9:09  
Yeah, I think this is this is such a big area. So, with those examples that I talked about, all of them thought very carefully about the candidate experience, monitoring it all the way. There's an interesting.. they also, you know, they also.. a lot of companies that are doing this will give candidates a choice: do you want to fully talk to an AI, you know, an AI screening bot at the start of this, or do you want to talk to a human, you know, if that's possible. And there's a couple of organizations that I've seen doing that, but the uptake on the AI side has been quite high in this particular sector, because candidates - one of the things that candidates are driven by is speed. They want quick answers, they want to get an interview booked in straight away, and they can see that the AI is the source to do this. So I think that there is some careful thought of balancing that needs to happen here, it's kind of where are the humans in the process? Because I don't really believe that we can cut them out of it all together, certainly not at the moment, because of the, you know, the judgment and the nuance that they add, but also ultimately recruiting is a very human thing, you're persuading people to, you know, to change jobs, to join your organization, you know, there's a level of kind of empathy and engagement that really needs humans here, and also, as we're seeing in kind of regulations all over the world, humans have to make the final, the final decision. So, so, yeah, kind of balancing that is really important. I think that there is a bigger issue here that we need to think about as an industry, so with the case studies that I've had on the podcast, there's always been a great feedback from candidates, like candidates love this, candidates were really happy to do this, you know, they reported that it was much better than the candidate experience that they've had elsewhere. Now the reason that I'm talking to these, these companies is because they've kind of come forward and said, actually, we're doing some, we're doing some great things, but I think that there is a massive, massive trust problem out there with, with, with candidates in terms of sort of trusting that AI processes are fair and are going to, you know, give them, give them what they need from the process, because I think that there's a perception at the moment amongst a lot of candidates that every company is already using AI to screen them out, and the reason they're getting a bad candidate experience is because of AI and computers. Now we know inside the industry the reason they're getting a bad candidate experience is because there's a volume of applications unmanageable from the human recruiters. There's not enough recruiters, and you know, companies aren't really prioritizing the candidate experience as much as they, as much as they were when it was more difficult to find people. So I think that there is a kind of a mismatch there, and actually, if we are really going to kind of make this work, then you know, we have to be, we, you know, there has to be much more sort of positive conversation about the benefits that the AI can bring, you know, not just to recruiting process, not to employers, but to the candidates themselves, and it's a, it's a conversation that's not really happening at the moment, I think, I think that's not a good thing.

Mervyn Dinnen  12:19  
No. So, okay, so what does a to you, what do you think an AI ready recruiter looks like in 2026? You know, is and how big, I suppose, is the gap between what a recruiter should be doing and what you know, again, you see from all the events you go to and everything that most recruitment teams, you know, where they're at, as opposed to where you know, as I say, an AI-ready recruiter should be?:

Speaker 4  12:43  
Yeah, I mean, I think in terms of, in terms of talent acquisition, the I've done a lot of analysis on the podcast through the people that I've spoken to, and I think there's actually kind of the five areas that people really need to really need to think about, and we've sort of, we've touched on all of these, actually, as we've kind of gone, gone, gone through, so I'll just sort of run through them really quickly. The first one is process architecture, so this is the, the actual, you know, the process itself, and as I say, lots of kind of AI tools being plugged into processes that already didn't work or don't really work if you make them faster. So mapping out the process of how recruiting is going to work, you know. For example, you know, everything at the moment is always hinged on resumes, CVs. Is that really the right way to assess someone? So, there's some really big decisions that companies need to make about the way that they recruit. The second one is decision design. Where does judgment sit? Where do the humans come into where did the humans come into the process, you know, how, how did, how does that kind of flow, how does that flow through, and then probably importantly, but most importantly, I think, at the moment is team capability, because this does change the way that recruiters' jobs work, we're asking them to do things more at the bottom of the funnel than the top of the funnel, I think, which is all about conversations and building relationships and those kind of things, and really understanding the capabilities within a TA team are kind of really are really important here. Do we have the right skills in place to actually run this new process, and really get the most out of AI, and you know, there's a lot of kind of perhaps upskilling or thinking about bringing those skills in that needs to happen. The first one is data and measurement. So, what are we going to measure here? Are we just measuring the metrics that it was easy for our last system to measure, or are we thinking about what's really important to the, to the business, and I think that this is particularly important for the companies who are doing pilots around this at the moment. Are you measuring the right things? Do you know how effective this really, this really is? And I think the, the frontline hiring examples are really interesting, because the speed of hiring just equates directly. To the the amount of money that the company makes in those cases, so you know, if you don't have enough people working in a fast food restaurant, then you're not making as much money as you could, so there's an obvious correlation there, which I think is what's driving the adoption and the investment, and I think for, you know, all the other sectors is just kind of thinking about what that what that measurement might be, and then the fifth one is governance and trust. Trust, I just talked about in terms of the candidates, and governance is obviously there's a lot of ethic, ethical issues and regulation around this that is important to keep on top of and make sure that you're kind of complying with that. So I think it's those five things in sort of, you know, in combination, and I think that, you know, some people have got some.. I think that people talk about governance all the time, that's that's always talked about. I think data and measurement are talked about a bit, capability not so much decision dien, decision design, process architecture, architecture hardly at all, so you know, I think it needs to be all five of those to really get the full benefits from the considerable advantages and value that AI can, can, can, can absolutely drive.

Mervyn Dinnen  16:16  
Yeah, if I suppose expand it out a bit more to, more broadly speaking, HR, as well, so areas like I suppose workforce planning, you know, people analytics, employee experience, and where I suppose are you seeing meaningful AI adoption happening, and where, where does I hate to say, ask the question, but where do you feel HR is possibly lagging a bit behind?

Speaker 5  16:40  
Yeah, I think a lot of this actually comes down to data, because I think the biggest potential advantage that AI can bring to HR is the ability to look at data kind of end to end through the employee life cycle. Now, in our book, Exceptional Talent, which we wrote a few years ago, we talked about breaking down the silos in HR. We talked about that the employee experience is a seamless one, and at the moment is handled by all these different silos within HR, and it creates a really uneven experience for people, and I think this is the data version of that. If you have that, that end-to-end kind of data about what's happening in the employee experience, it really kind of powers and informs the way that HR can work and HR can be strategic. So, to me, I think that's the fundamental thing. I think that it's a bigger undertaking than people think it is. I had a really interesting conversation with the head of the person who leads HR technology at H&M, and they're doing a lot of work on how they integrate that data and how that actually works. They can get the full benefits of a of AI, and obviously a couple of the bigger HR tech providers have made acquisitions to try and kind of create that sort of data layer across the whole piece, but I think there's a kind of a way to go with that. Ultimately, I think at the top of the HR organization, the CHRO, the CPO, the HR director, whatever they happen to be called, has quite a unique role to play in all of this, because this isn't just a technology issue. In fact, it may not even be a technology issue at all. This is a, this is a workforce issue, in terms of, in terms of AI, and actually HR needs to be taking the lead here, in terms of, well, how are we implementing HR, AI here? What does it mean for jobs? What does it mean for the way we design our workforce? So, I think that there are some very big decisions that should be sitting with, with HR and all the, you know, the relevant kind of departments within it that some organizations have got to, and some organizations haven't got to.

Mervyn Dinnen  18:55  
So, I mean, who, I mean, in most of the conversations you have, who actually owns AI strategy within the organization?

Matt Alder  19:02  
Yeah, it's a good question. It seems to vary from organization to organization. You have very proactive organizations where the CEOs made some kind of declaration about the company being an AI company or having to adopt AI, so the ownership then is right at the top of the organization. When that doesn't happen, it tends to sit with it tends to sit with technology or legal or compliance. There are loads of organizations out there where people are not allowed to use AI, or or feel they can't use AI, or are very limited in terms of what they could do, because it's sort of sitting in that in that bucket. And then you know there are very few organizations where you know talent HR is is taking is taking the lead and there are some organizations where no one owns it, it's just a lot of noise that's noise that's happening, so it's a really, really mixed picture here, and some of that is down to the type of industry. Yeah, obviously the tech sector and the AI sector are leading the way there, because it's in their DNA, if that makes sense. So, it comes down to the type of industry, comes down to, you know, the attitude of the ultimately the leadership of the business, and very often also down to the individual personalities and, you know, kind of aspirations of the people leading the leading the functions, so really, really mixed picture, you know, no clear patterns emerging at the moment.

Mervyn Dinnen  20:30  
Is is there a risk then I suppose that, that you know, without this kind of ownership, you know? AI and HR, it doesn't create more equitable processes and begins to almost, you know, kind of existing biases, you know, get, get, get, take, take root, shall we say. So, do you think, you know, in practice, do you think that this is what might be happening if there is no clear overall ownership?

Matt Alder  21:00  
Yeah, I think lots of things can happen if there's no clear overall ownership. I think you get to a point where people are making decisions that they shouldn't really be making. So, should your IT technology department be making decisions about people's jobs and the way that things work? But also, I think you're right. I think if there's no ownership across it, particularly, you know, in internal acquisition, there is the risk of that, that can kind of creep in. People, people going rogue, people, we know that lots of, you know, we know that a huge percentage of employees are using AI in their personal lives and are using AI for their job without telling their employer, and you know that is potentially catastrophic from a recruitment perspective, in terms of some of the regulations and the bias that can, the bias that can happen. So it's not just about, you know, saying no, we don't use this, and we can't use this, because it's a bit like telling someone they can't use their phone at home, it's just like, you know, the employers are not able to stop people using this for work, and I think the sooner they realize that, the better. It's about, you know, working together and making sure that you know everyone understands what good looks like, you know, what compliance looks like, and everything is moving in the right direction, because I think the risks of not doing anything, or the risks of just saying this is banned, you can't use it, are enormous, because neither of those things are actually close to the reality of what's really happening out there.

Mervyn Dinnen  22:37  
And of course, a lot of the conversations around AI readiness and stuff is usually framed as kind of technology data, but I think that, as with most of these things that we've been talking about for the last few years with tech, it's actually a leadership and culture issue. Yeah, so what, what, what is good leadership regarding, you know, around AI adoption. What do you think that looks like?

Matt Alder  23:05  
Yeah, I think it's.. I think that's really important, because we seem to be existing in this magical world. If you look at some of the narratives out there, where we've got this current state, and then tomorrow we're going to wake up and there'll be no recruiters, and everything's AI, and all the data is there, and it's great. And yes, this is going very quickly. This is going far quicker than any other technological driven change that we've seen, but even with it going so quickly, there has to be a journey and a process that someone needs to, a path that people need to sculpt, and I've sculpt, and I think that that's where the leadership really comes in here. So, I think there's two aspects to this that to me are the most important. I think the first one is kind of setting a clear vision. It's like, right, this is this is where this is what we want to do, this is where we need to get to, and this is how the technology is going to help us get there. I think that's that's that that's important, but I think the other one is really, you know, comes down to, I know this is talked about quite a lot, but it really comes down to the psychological safety around all of this, so and there's two parts to this, there's the safety of people saying how they're using AI, and you know, being prepared to talk about it, and sharing their findings, and you know, having honest conversations about where it can be, could be used, and feeling safe to feeling safe to do that, and then also, you know, there's the the element of risk about this, because you know lots of these pilots will fail, lots of the way that the implementation will happen will fail, because this is this is new, this is changing, and yes, there are some big risks with with with kind of bias and legislation and all that kind of stuff, but actually you know, leaders need to be prepared to, you know, tolerate some failure with all of this, with all of these kind of pilots, just because everyone needs to work out how this is going to work in their organization, and it's not going to be perfect the first time, and also going back to what I said at the beginning about AI having this kind of jagged frontier. There it's very good at some things and not very good at other things, and sometimes telling working out the difference is quite hard, because it can be very confident about what it's not very good at. So, which is why you know using it is really important. I think from a leadership perspective, you just have to be using these tools and really understanding what's changed. I think that so much has happened in the last three or four months that this is why it's kind of essential just to be experimenting and kind of hands on, because I think a lot of the conversations I see about AI are actually about how AI was 18 months ago, or a year ago, or even two years ago, they don't actually reflect the reality of where it is now, and I think that is a big danger.

Mervyn Dinnen  25:47  
No, I get that, and I think I mean one of my pet topics, obviously, is intergenerational workforces and things, and I think this is a big issue here as well, in that organizations have mixed age workforces. In fact, we're recording this conversation when on a day when the lead, the lead item on your Apple News on your phone is from, is actually a UK thing from one of the UK national newspapers about companies who are, who are actively going out to recruit only people over 50, and you know, mixed-age workforces, you know, as we've known over the last 10-15 years or so, have very different relationships with technology, particularly when it comes to AI, and also because of, I suppose, AI is new and unfolding at the time, again, the slightly older end of the workforce might be a little more uncomfortable with it. I mean, is this something you see from all the kind of speaking, talking you do at interviewing? Yeah, is this something that TA and HR leaders are actively managing, or is it something that they're almost like putting to one side and leaving, hoping it will all come out in the wash, kind of thing.

Matt Alder  27:06  
Yeah, it's interesting. I had one great interview with, is EY actually an EY had done, have been doing a lot of work around AI adoption, because I think we're seeing, in you know, in that type of consulting, you know, they've been very, very - they've had to be very, very forward thinking with, with AI, because you know the danger of it replacing consultants is potentially, is potentially quite big in the future, and I think that those big consultants are doing some really interesting things, and they talked about, you know, that issue in their, you know, in their adoption, and how they were sort of trying to do the reverse mentoring, and all the things that happen, but I think that I don't think it's quite as clear cut with this. I think it's interesting. I think that, yes, I suppose on average, you know, the younger workforce are more used to technology, they've grown up with it, they're used to that, that kind of change, but the kind of the older part of the workforce have seen a lot of technological change, you know, now over the last, over the last sort of 20, 20 years or so, 20, 20, 30 or years, and also kind of have the knowledge about how the business works, so I think kind of aligning those two things is is really is really important because this isn't just about technology, it's about the business problems it solves. So, you kind of need to align those two, those two kind of skill sets. I also think that a lot of younger workers are actually very suspicious of AI in the workplace, because of the threat that it poses to entry-level jobs. So, I think that is a, that is a consideration as well, to you know, to really think about. So I think it's a mixed picture, but I think that understanding where people are at and where their strengths are is crucial to this, because not everyone is in the same place, and you know, there are people who are very enthusiastic, using AI to do everything. There are people that have probably not touched it beyond a quick search on Chat GPT to see what all the fuss was about.

Mervyn Dinnen  29:07  
Yes, so if you were advising, I suppose, a head of TA or CHRO, who really wants to move the needle on this on AI readiness over the next 12 months, not just like adopting new tools, but building capability. I don't need to put you on the spot, but what are the two or three things you would advise them to prioritize?

Matt Alder  29:30  
So, first of all, have a really good idea about where you're going. So, I think that's that's really important. Now, the technology is changing so quickly, it's very difficult to say what's going to be possible in a year's time, and all those kind of things. So, you almost need to divorce yourself away from, away from the technology aspect of this, and say, okay, we know the direction of travel, we know what the capabilities potentially are here. What's our vision for, for TA? What are the issues that we have? What are the business challenges that we're solving? We could do, you know, if we could achieve anything. How would we, you know, what would it be? So, I think starting with that clear direction and vision is really, really, really important. And then from there, I think that really understanding the shortcomings in your process is is critical. I did a presentation at the ERA Recruiting Innovation Summit a few weeks ago that was called, you know, is talent acquisition is inherited, not designed, and actually a lot of the ways that we do recruiting haven't changed in 200 years, and now's the time to actually ask some very, very difficult questions, questions that are never asked about your recruitment process. Do we really need resumes? Do we need to do interviews this way, and rather than constantly trying to make the same things better or quicker, it's asking questions about, do we actually need this, or do we just do it because we've always done it. I think that's really, really important. And then I think the team capability is a key part of that, because that will give you an idea about where your process is going and what you need to be able to do as a team, and what the team you know might look like to be able to do that. So, I think it's you asked me for one thing, I gave you three, so there we go, very much linked, they're very much linked.

Mervyn Dinnen  31:09  
Yes. Okay, so a final one now, given everything you see in here, and obviously you know over the chat we've just had, you know that there's you're seeing and hearing a lot. What do you think is, I suppose, the thing about AI, future recruiting, future of HR, that is kind of under, under appreciated, or possibly under reported. People aren't even talking about it yet.

Matt Alder  31:34  
It's, it's being spoken about, but in the wrong way, and not enough. And it's the candidate side AI. So, one of the things that's causing huge issues in people's recruiting processes at the moment is the sheer volume of applications they're receiving. Now, a lot of that comes from the economy that we're going through. In many, in many countries, there are more people looking for jobs than there are jobs, so this, this is this, this happens every time this that happens, but obviously candidates using AI to apply for jobs is, is kind of exacerbating that. We don't, perhaps, know, know exactly how that splits down, but it's definitely, it's definitely a factor. When we talk about candidate use of AI, it tends to be talked about in terms of cheating, or, you know, there are software companies that are grifting and selling things to candidates they don't need or enabling ways of breaking the recruiting process, and not actually about the genuine innovation that's happening on the candidate side, and I think that none of this is going away. It's not a fad. There are some very dodgy software companies doing grifty things. There are also some really great companies doing great things to help you know to help the job search experience for candidates, and the obviously the appetite for candidates to use the tools that are available is enormous. So I think that all the innovation in our sector is going to come from the candidate side and employers responding to that rather than the other way around, because the candidates can move quicker, they can, you know, they, they move, they move volume, if that makes sense. So, I think that actually dictates the speed of adoption, not what employers and vendors are doing, and that is not a conversation that I'm hearing at all at the moment,

Mervyn Dinnen  33:15  
And that's, that's, that's interesting, because if we go back to the very early days of people like you have been meeting online and through social media and stuff. One of the first debates we always used to have is Who cares what the candidate thinks, and now we seem to have come to the point where I think organizations have to really care what the candidate thinks.

Matt Alder  33:36  
Yeah, and I think that all this happening is all this really happening is that the, you know, the candidates are exposing the shortcomings of recruiting processes, so you know, I hear people complain, oh, you know, I've had all these applications and now everyone's resume looks the same, and it's like, well, who's to blame, is it the candidate or no, they're just using the tools that they've, they've got available, is it the AI? Well, it's definitely the AI, but we can't really blame the AI or do anything about it. It's the resume, it's the wrong format for the age that we're living in, and it's very easy to say it's very easy to say that, and that we should reinvent it. And I've been saying we should reinvent it for about 16 years now, but I think now the time that now the time is here, and I'm actually seeing really clever companies doing things like moving assessment up in their hiring funnel, so people are doing soft skill assessment and softened assessment tests as the first thing before they even submit a resume, because actually that's the data that's going to really help in the increasing process, so it needs kind of some really creative thinking, to you know, to solve this, but the tools are there to make things better already. But I think that, yeah, I think it's exposing the shortcomings of recruiting by just, just, just applying speed and scale to it.

Mervyn Dinnen  34:57  
Okay, Matt's been an absolute pleasure to talk to you today, if people want to connect with you, what's what's the best way to reach you?

Matt Alder  35:04  
The best way to reach me is always on LinkedIn, and you can reach me via the podcast, or find out more about the podcast, or the past episodes at recruitingfuture.com

Mervyn Dinnen  35:16  
Matt, it's been great to chat to you, and thank you for your time.

Matt Alder  35:20  
My pleasure. Thank you.

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