The Changing State of Talent Acquisition
The Changing State of Talent Acquisition cuts through the noise in the crowded world of recruitment marketing, employer branding, workforce intelligence, and AI.
Hosted by Graham Thornton, President of Consulting & Growth at Talivity, this podcast brings you unfiltered conversations with industry founders, practitioners, and the occasional contrarian who's actually doing the work – not just selling you on it.
We're not here to hype the next big thing. We're here to help you separate signal from noise, understand what's actually working (and what's just well-marketed), and make smarter, data-backed decisions about your talent strategy.
You'll hear from TA leaders navigating real hiring challenges, founders building solutions worth paying attention to, and experts who see around corners before the rest of us catch up.
Whether you're navigating the AI arms race, trying to figure out your tech stack, or just trying to hire better people faster – this is the podcast for people who care more about ROI than buzzwords.
The Changing State of Talent Acquisition
#62: The Promise of AI – Aligning Efficiency with the Candidate (and Recruiter) Experiences
This week we welcome David Ellis to the podcast. David started his career as a recruiter in New Zealand, before relocating to Europe to work as a talent consultant. After earning his PhD, he moved to Boston to join Korn Ferry, where he currently sits as SVP of Talent Transformation.
Topics include:
The future of talent acquisition, how AI can streamline processes while enriching candidate experiences, how to strike the right balance between AI and human touch, the ethical considerations when training AI, AI in high volume recruiting vs. executive recruiting, the shift towards skills-based hiring, talent acquisition roles of the future, the debate over hybrid work, the importance of critical thinking, approaches to measuring the ROI of artificial intelligence, and how AI is already empowering “wow” moments in recruiting
David Ellis
SVP of Talent Transformation, Korn Ferry
Articles:
Korn Ferry’s Talent Trends 2025: Progress Over Perfection
Welcome to the Changing State of Talent Acquisition, where your hosts, graham Thornton and Martin Credd, share their unfiltered takes on what's happening in the world of talent acquisition today. Each week brings new guests who share their stories on the tools, trends and technologies currently impacting the changing state of talent acquisition. Have feedback or want to join the show? Head on over to changestateio. And now on to this week's episode.
Speaker 2:All right, and we are back with another episode of the Changing State of Talent Acquisition Podcast. Super excited for our next guest, David Ellis, SVP of Talent Transformation at Korn Ferry. David, super happy to have you here. I'm going to start with a softball. Why don't you tell us a little bit more about your background and how you found your way to Korn Ferry?
Speaker 3:Okay, great. Well, yeah, first of all, thanks for having me. It's really, really nice to be here and chat with you guys. I started my career actually back in New Zealand which matches the accent better than where I live now, which is here in Boston and I was actually working in a line manager role in a bank and as part of that I had to recruit dozens and dozens and dozens of people a year, and I was quite fascinated about how kind of subjective that was.
Speaker 3:This was probably, I would say, 20 years ago and I thought, well, this is an area of practice within HR that I can probably get my brain into a bit more and where I can make a contribution. So I ended up leaving that role, going into recruiting in an agency and did that for I don't know six months. Then I moved into an in-house role at one you know one of New Zealand's biggest companies and I ended up, you know, being a recruiting leader there. And then, yeah, I just went off to Europe and worked in consulting there in both recruiting and talent development, and then I did my doctorate after that. So I took a bit of a break. And then Corn Fairy just popped up on LinkedIn one day and just said hey, do you want to talk to us about a job? That was 10 years ago and I was like I don't think so, I don't think I really want to. No, but actually I'm really glad I did, because I just love working here and I love the clients and love the people I get to work with.
Speaker 2:No, that's awesome. Well, I can say, corn Fairy is popping up in our newsfeed quite a bit too, and you know, one of the reasons we are excited to have you on is, you know, you just put out a, you know, 2025 town acquisition trends report and you know, frankly, I thought it was, you know, the more meaty one that we've. You know, come across too, and you know some really great insights. So, you know, I was really looking forward to this conversation, you know. I think you know, maybe the best way to start is with a softball, david. So in your trends report, you talk about what TA is going to look like in the future. So maybe a good place to let you wax poetic is what do you think talent acquisition is going to look like in 2030, david, yeah, and you think there's a softball.
Speaker 4:I was going to say Graham, I don't think that's a softball.
Speaker 2:Get your going to print this out too, so we'll remind you in six years here, or five years.
Speaker 3:I can't wait to hear what your other question is. Well, you know, it's really interesting because if you'd asked me that a couple of years ago, I might've given you a different answer than I'm, you know, than I, than I would give today. And, by the way, I heard you guys talking um about our report too and giving it a bit of a, you know, a bit of a soft critique, and I I really enjoyed that. So, if you know, if people haven't heard that, then it would be. It'd be good for them to to hear that too.
Speaker 3:But I do think there's kind of a, there's a sweet spot for talent acquisition here where, you know, efficiency and experience are moving in the same direction. Like that seems to be kind of the ultimate aim within at least forward thinking TA organizations today. 2030, I mean, I'll be a bit more bold about it In 2030, it's going to be at least, you know, 50, 60% more automated than it is today, and I think we'll see a lot of the processes that have benefited so far from AI, from automation, especially in the high volume hiring space, I think we will see them incrementally, you know, creep over into other segments of hiring and I think that you know I'm so optimistic about the potential that that offers organizations and offers talent because, you know, with AI's potential around data collection and the insights that can be gleaned from that, like I said, I'm just so optimistic about that potential. So hopefully that's a start to the softball. But I'm interested in what you guys think as well, of course.
Speaker 4:Yeah well, it's a huge question. I had the same chuckle to myself when Graham called out a softball, because I was like boy. I don't know how I would answer that question. It is a very big question. I thought I have a couple of introductions we could go. David, before we do that, I just want to gush on New Zealand a bit. For some reason, the university is sending me New Zealanders. I have another client with a different project who happens to be from New Zealand. I've been there twice and somehow I missed identifying the accent both times, but anyway, we're thrilled to have you on the show. Probably should have started there. As it relates to this question of what recruiting is going to look like in 2030, maybe you can unpack something you said. You said, and correct me if I misheard you, but I think you said that efficiency and experience are aligned or something, and this kind of alignment is one way of thinking about the future. Did I hear you correctly and, if so, could you just say a little more about those two ideas and how they relate?
Speaker 3:Yeah, of course, and thanks for the plug for New Zealand. I'm sure the tourism I don't know if they need help.
Speaker 3:Yeah, yeah, we'll push up the price of the airfares for me to get home is what will happen. But so my yeah, my point there is that you know when, when this kind of big AI, um, or at least Gen AI sort of blast and fuss and buzz really came to the fore recently, I think a lot of organizations were like, how can we leverage this to do things faster? And, and now what we're seeing is more organizations saying how can we do this better? And those are, at least to my mind, separate but related concepts. Right, speed is one sort of measure, um, and it benefits the organization, of course, and, in some cases, the talent going through the process.
Speaker 3:But actually, I think the sweet spot for AI is where you leverage that to elevate the experience. And you know, I heard a lot of talk early on about how we can either provide, you know, human experiences or high touch experiences, or we can use technology more or AI more, and I actually think that's not binary like that. I think the right mix of people and AI, sort of almost tailored to the segment of hiring that you're doing, is I mean, I keep using that word sweet spot, but I think that's the key and I do think that's where this is going right. Organizations won't just focus solely on the efficiency play anymore, even though that will remain important. They'll figure out how to use AI to elevate the human experience.
Speaker 4:Okay, that helps a lot. I thought that's what you meant, but hopefully for our audience just to have you expand on that was helpful, I think. Well, you make a good point and it's one that probably our industry needs to hear. Hr, talent acquisition, as we've said endlessly on this podcast have historically been seen as cost centers, which takes us kind of maybe in an unshareable way to this idea of efficiency. So organizations and TA leaders are always being pushed to be more and more efficient. But I think what you're raising is a very important point, which is efficiency is a good thing unless the model upon which we're iterating was not very good to begin with. And so if the status quo is not treating candidates very well, not having a lot of human contact or that human side to the recruiter experience or to the candidate experience, is that something we want to iterate and be more efficient at? Is that a fair way of kind of doing that? Or what would you say to that assessment?
Speaker 3:Yeah, I think that's fair. I do think the issue of measurement comes up here too, because how do we know whether this is doing what we want it to do? And so we have to figure out first of all, I think, what we want it to do, because otherwise it makes it harder to measure the kind of the strategic impact of these kind of paths that we're on around technology and innovation. You know we've got our traditional measures of talent acquisition around time, cost and quality, but this is an opportunity here to help us do it cheaper, better and faster, I think. So it actually hits all of those notes, and I think that the organizations shouldn't give up until they have figured out how to create that sort of utopian state.
Speaker 2:Yeah, I want to first, I really want to touch on this. You know, measuring, roi and hiring, when you know, through the lens of adding AI. But before we do that, like you know, let's unpack a little bit more, david, this kind of idea of you know the human touch between, or balancing the human touch between, ai efficiency gains, you know, and not losing that human touch. Can you maybe give an example of let's talk about how organizations are leveraging AI for efficiency? But what do we mean by not losing that human connection point? Give me an example of how we root that piece.
Speaker 3:I think some of it comes in from.
Speaker 3:Possibly one of the best examples right now is in the high volume hiring context, because that seems to be the biggest sort of level of adoption right now at least, you know en masse by very definition of volume hiring, where the conversational aspect of how a bot will interact with the talent gives it a human flavor, even though there's no human sitting there or manually operating this process.
Speaker 3:There are process steps that are passed between different pieces of software and as the candidate moves through the process, and that has the potential to feel pretty human, as long as it's aimed at the right, you know, as I was saying earlier, aimed at the right segment of talent. Now, if you try that in an executive hiring context and you run that process, you know through a chat bot and you're gathering information about them and scheduling interviews and you know maybe even providing outcomes of processes to the talent, then that's going to fall flat on its face. So in that context, you know for that segment, at least today as it is today, you know you wouldn't typically put such an automated process because it would detract from the human component that's aligned with the expectations of that segment, from the human component that's aligned with the expectations of that segment. And I do think that's really important here is that the experience of the talent and the way that you are leveraging AI and humans through the process those things all have to sync up.
Speaker 2:Yeah, no, I think that's helpful and maybe I'll kind of take a step back on one piece of you know. Take a step back on one piece. So you know, I think one of the exciting aspects you know here is, you know, if we think about AI, you know most HR tech, you know. If we look through the lens of HR technology, you know, and AI and solutions, a lot of that is really focused on identifying patterns from existing. You know, information or automating pieces like resume screening, you know, and that's just you know sort of the basic stuff of, hey, I want to know if someone lives in this state, you know, has these qualifications, and like A, if A, then B, right, and like you know what. You know.
Speaker 2:What gets more exciting is with generative AI. You know. We're quite literally, you know, creating entirely new content, right, entirely new personal. You know new personalized candidate outreach right, it's interview questions that are generated based off of what we're seeing on resumes or how people are answering questions, and so I think just saying to David is like, hey, one of the reasons that the human touch becomes more interesting is generative AI is quite literally, generating new, you know, content. Right, it's about creation rather than automation, and so you know it's, it's difficult, right, but I think, you know, I think if we think of AI as automation yeah, there's really, you know it's hard to see how that becomes you know, has an element of human touch or human connection to it. It is.
Speaker 2:You know, it is just, you know, moving people through a process, right, whereas you know, generative AI just opens up a whole new box of opportunities if implemented correctly, and that's because it's no longer hey, we're, you know, drawing a map to get from point A to point B. It is. You know, generative AI is almost, you know, the Sherpa that is. You know, drawing a map to get from point A to point B. It is. You know, generative AI is almost the you know the Sherpa that is, you know, walking people through, you know, a unique process to that individual. Does that resonate?
Speaker 3:I mean, I do agree with that. I think there's maybe there's a better example too I can offer, not than yours, but the one I gave which is, you know the potential here. So if I've got like, for example, I've got a cohort of professionals that I've hired into an organization Say, I've hired 500 of something you know, whatever sales managers over the past year here in the US how likely that cohort of individuals is to achieve my business goals here, which are probably, if it's a sales population, probably something to do with growth, then AI gives us new potential to take, you know, if these people have undergone assessments. It gives us potential to take that data, roll it into something which gives me a cohort level view or an enterprise level view. If I've hired an entire enterprise of new people and then marry that up against my key business drivers At the same time at individual level, it will be able to, and it is able to throw the new line managers of these people some insights about them that previously we never would have done because hiring was always quite siloed.
Speaker 3:It was, you know, we brought people into the organization and yay, our job's done, our handoff is done. But now the potential goes so much greater than that because of what we're learning and how that can inform development plans, and I think that that, in its very essence, is human. Even though it's not like someone sitting there at an Excel workbook doing all this stuff, it's being done for them because the organizations have invested in that type of automation. But the experience for the people who are going through that process I mean that's pretty impressive, as well as the insights that can be produced for the business leaders. That you could also argue helps with human aspects of running business. I don't know what you guys think about that, but that potential is there right now.
Speaker 4:Yeah, I mean that's a fascinating topic, you know. I think I know enough about generative AI to be dangerous. But one of the big topics that seems to come up in the general case, not specific to recruiting, is the importance into training, which in the general case for like a chat GPT means ingest all the information that humanity has created, that we have on record and assimilate it and use that as a resource when somebody asks you a question. I guess it's a long way of getting to a question about training. As it relates to generative AI specifically for recruiting and maybe that's kind of related to my question from earlier, Could you say anything more about that? How do we train a generative AI in a recruiting context to be not only considering the business objectives and all those things, but to be actually representing our company in a human way?
Speaker 3:That's a really good question. So and there I think you're you're talking more about like I don't know, the out, the, the personalization of the outreach and and the sort of experience that the person goes through when they're going through the process steps. Is that is that right, or I think?
Speaker 4:so yeah, well, I mean, yeah, like I said, I know enough to be dangerous, but that's the most obvious place. But yeah, I'm just curious, like, is it much like the chat GPT general case where we're just saying here's all the outreach that we've done to candidates in the past and you can even listen to recorded interviews, maybe, and here's an example of really successful recruiting outcomes, and then the AI compiles all of that and gets some sense of how it should operate and behave on behalf of your organization?
Speaker 3:Yeah, I'm probably less expert in the area of how you train these models. To be honest, what we hear a lot of clients talking about at the moment is risk that is either real or perceived around. You know these machines learning in a way which is discriminatory. I guess you could equally apply that to processes where the outreach, the style of language used, you know the very mode of outreach, whether it's via text message, email, whatever LinkedIn message is selected by a machine and is learnt through the success that it's had and failures that it's had, through, you know, approaching similar people for similar roles through those channels. I guess that potential's all there, right for it to get that, you know, not necessarily right all the time, but I think that potential and that risk is probably much less publicly talked about than the discrimination and bias sort of fear that I think is quite rightly out there in the market still.
Speaker 2:Yeah, and you know, I don't even think of it.
Speaker 2:Like you know, again, similar, you know, not expert in training, you know AI to do tasks, but, like you know, I think you could argue, boy, if you just, you know, pulled in data from your college recruiting team, right, who went on campus to hire engineers, like, boy, like the output of you know plugging that you know sort of you know backdrop of data into, you know your screening for candidates or your outreach, might look a lot different, right, and you know, and so you know, and that's just the things that we don't think about.
Speaker 2:Right, you try to, you know, grab a subset of data and like, start working through it and like there are a lot of you know downstream, you know challenges if you're training, you know training, your, your tools, you know to make decisions based on data and hopefully that's not what people are doing. But who knows, right, I think it's just there's certainly risks and I think arguably that's probably why most of these new jobs that we're seeing that are going to be super high in demand, it's these jobs like ethics specialists and AI quality assurance analysts. It's the roles that people that can recognize. You know, we only used a small subset of data and like, hey, the outputs on that is going to be drastically different than you know, if we looked at things from a different lens.
Speaker 3:Right, I know, I agree, and I do think that's why the I do think that's why the human touch, quite unquote, is important there as well, because anything, any, any use case where we can gather insights about the experiences of people who have been through our process, is going to be useful, as long as we don't blanket throw it into, you know, or generalize against it and then throw it into a population that's just um, it's just not relevant, or or it's it has some danger attached to it because it's not, it's not even valid as to how we're, like you know, approaching that population. So I think, yeah, I do think, we're on the same page there.
Speaker 2:Oh yeah, and, like you know, I'll just say, like, I think it's at least it's exciting to me that, like one of the most in-demand you know, quote unquote, we'll call it a skill set right or capability is, like you know, looking five, 10 years out in the future, is just critically thinking. You know the critical thinking right. And like, boy, like, if you can recognize that, like hey, this might not sit right, like you know, the smartest people in the room are going to be the ones that you know have the ability to say, boy, something just doesn't pass the sniff test. You know, on this one too, right. And like, hey, are we asking this wrong? And you know, I'm sure all of us have.
Speaker 2:You know, you know, used Gemini Claude, you know chat GPT and, like, popped in questions and, you know, looked in an output and just said, boy, like, are you sure? Are you sure this is what you mean? And you know, a lot of times, like you're back, oh no, I'm. You know, I missed looking at something. You, your AI model of, missed looking at something a certain way. And so I still love this analogy of AI being used as an unpaid intern. Boy, you wouldn't take products to market that an intern necessarily built without looking at it first. Last question on AI too is they said we'd get back to it. So, ok, talk a lot about where, how AI is going to be, you know, used, like some of the risks, like how does Corn Fairy? Or how do we think about you know measuring AI's true return on investment in hiring? Because, well, I think there are a lot of different ways that you know AI is going to be implemented. So, you know, how do we think about measuring AI's true impact on the hiring process?
Speaker 3:measuring AI's true impact on the hiring process. Yeah, I think we can point our measures at the process itself, which is, you know, I kind of spoke a bit about this earlier around time, cost and quality. How fast are we doing it, how much is it costing us and what's the quality of the experience as well as of the hire that you make? And so that I mean that's those measures can be a baseline, can be taken pre-AI and then post-AI, again measured, and then looking at the delta. I think the other part which is kind of frankly, a bit more interesting to me is well, it's two things. One is and we're helping companies think this through right now right, this is, this is a question that people are coming to us with, and it kind of covers a couple of your questions. One, what's, what does the ta organization look like of you know, and at the three-year mark, at the five-year mark, and then second, because part of that answer is around more ai. The question is, then is then, well, how do we measure success, how do we measure return for our business on what we've done? And so, yeah, this is where it gets interesting to me. Why did you do it in the first place. Is it because someone in the C-suite said there's a whole lot of talk about AI, you need to do something about AI? Well, I do think we've gone a bit beyond that.
Speaker 3:I do think it was a lot of that, you know, when this whole thing kind of blew up and the measure there should then be sort of attached to higher level metrics which are connected to the strategy of the TA function. What is the function trying to deliver this year and how does that support the broader kind of people strategy of the enterprise? And so measures, you know, I think at least my view of this is that those measures should in part connect back to those higher level measures, um items, strategic items, because they're the ones that we've already decided are going to be the sort of strategic pillars of of the business and of the people strategy. I do think that's, I do think that's part of this, and I also think you know we're we're working right now on a um, a TA professional of the future profile, cause we're we're quite forward thinking, like you guys are right, like we're we're always thinking about future, and we've got this research um, the corn fairy institute, which, um, they kind of powered the report that you, you know that you uh referenced at the at the top of the top of this episode, and so we are actually putting a point of view together about how the ta professionals sort of role can change throughout this evolution as well, and what we think that might look like at the 2030 point.
Speaker 3:And the reason I'm raising that is because I think that should be one of the measures. How has AI enabled us to change the role of the people and elevate the role of the people who are executing on talent acquisition? For us, that's a people-focused sort of measure and metric that also speaks to the way that we organize ourselves to get the job done. So I feel like I'm ranting a bit here, but does that at least partly give a view on what I think we should be measuring?
Speaker 4:Absolutely. I think you're speaking to two guys who think of it in similar ways. Yeah, we can take the most basic approaches you outlined at the beginning, which is, use the same old metrics and see how they change pre and post implementing AI. If we could draw a line in the sand so specifically and that may be hard, but I love what you're saying about. Sure, we should probably do that, as some nod to the past, but this is such a sea change technology that has the ability to impact organizations well beyond candidate experience that we probably need a whole new suite of metrics. Some of them are probably quantitative and others might be more qualitative, but we preach to our clients all the time, and I'm sure you guys have a similar perspective that I think it's very easy as TA folks to get lost in our silos and just be so focused on the job at hand. I have to fill this role today. I have to get this role today. I have to get this seat filled. The C-suite is barking down our necks about this. We got to do it faster and cheaper and all these things. And these things are all fine, of course, but it loses sight of the whole purpose of why do we have a talent acquisition function in the first place, it's not because we want to get really good at screening through thousands of candidates I mean, sure that might be a byproduct, right? The reason we have it is because we're an organization in the world that exists for this purpose, with this mission, and we need great people who are aligned with that mission to deliver on it. And so I think maybe that's what you were speaking to. Hopefully I didn't misrepresent it.
Speaker 4:One thing I have a question I had is and maybe you know, being relatively close to the AI as it relates to recruiting. You know anyone who's messing around with like a chat GPT has had. Most people, I would say, have probably had like a wow kind of moment with it, just like you know, I've shared some on the podcast in the past. But you can ask it to do something that would require all of your day, or maybe several of your days, and it will deliver an output that's maybe 95% as good as what you could have done in a few minutes, and we can think of lots of different examples of that, but it is stunning when you see what it can do. Do you think in your experience that there are any organizations delivering wow moments that are being powered by generative AI currently? Or do you think, as an industry, the recruiting function is still having quite gotten there yet, where it's not quite delivering those wow experiences in a recruiting context?
Speaker 3:I love that question, such a thoughtful question. So I think, yes, there have been wow moments. I think some of them came early on and possibly some of the ones you were alluding to around okay, this thing can actually generate a job description for me, it can generate interview questions for me, it can probably come up with a simulation exercise for me. I mean, how valid those things are is a whole nother. But if it's 95% there to your point and all I have to do is go through and sort of um, you know, correct it, add to it whatever, then great. I think you know my view on this is that a lot of these wow moments around what it can generate in terms of content are yet to come. I mean, I just love some of the memes that it can generate.
Speaker 3:I know that's not related to recording, but when I first saw the potential of that, I was like, oh my goodness, and it got me thinking okay, this is what you can do today. What are you going to be able to do in three years' time? And when we think about the kind of holy grail of judgment and empathy and these sort of human qualities that we're told that AI can't actually help us with? And I was sitting, I was sitting in a bar the other day you might want to edit this out with um. He was having relationship problems, he goes.
Speaker 3:I asked chat gpt what to do about this and chat gpt told me to ask you, david, wow. So that's it. Hang on a minute. Maybe this thing is smarter than I thought, um, but I think and that's why I think, some of the wow moments are like, some of them are going to be like smaller wows, and some of them we just can't even imagine what they're going to be, because, yeah, I mean, we have. We have to imagine this thing's going to be even bigger than what we've seen so far, don't we? I mean, what do you? What do you guys think?
Speaker 4:Yeah Well, I mean it was interesting hearing you talk about some of those wow moments, because we want to measure things. You know I'm a scientist by training. Talk about some of those wild moments because we want to measure things. I'm a scientist by training, so I certainly resonate with that. I love measuring things, but my biggest wild moments with generative AI have not been measurable. I mean they have been measurable, I suppose, but when I asked ChatGPT to create 200 multiple choice questions based on a dense pharmacology textbook for my partner and it spit it out in 20 seconds, I wasn't sitting there thinking, boy, let me crunch the numbers to see the ROI on this. I paid $19.99 and it saved me eight hours and here's my hourly rate and we could have done that right. But it's almost beyond the quantitative at that point when you have some of these wow moments. So I just think it's really exciting to hear that some of them are happening already and even more exciting to see what future wow moments might look like in a recruiting context.
Speaker 3:I agree, and some of the ones that you can use that are embedded in what you use every day, like the co-pilot in Microsoft, and you know what it can do within Excel, what it can do to generate PowerPoint slides out of Word documents, you know, like that. I think some of that stuff was pretty wowing. Well, it's actually it was quite wowing for me when I first used it because it didn't. It didn't do what I wanted it to, but I think that was more user error, but but it's going to get better at that and so maybe that will produce some of the wows. But okay, this this thing's way better at doing this than I, than it was last time I did it a year ago, or whatever. Yeah.
Speaker 2:Yeah, no, I think that's just absolutely spot on and like I think we can um continue that talking point, these talking points, for a while. I want to want to pivot slightly, david, just because you know I don't want to wrap this episode. We're talking a little bit more about, you know, skills, skills-based hiring. You know, I think you know we all understand that. You know AI is creating a whole new you know generation of skills that are going to be required, only generation of jobs. You know that people are going to be hiring for.
Speaker 2:I'm just curious, you know, where do you think you know skills-based hiring? You know this concept that has been talked about ad nauseum over the last three, four years. Do you think this is part of the impetus where we're going to see a real changing point on skills-based hiring taking over the traditional resume? Do you think AI can speed that up in the sense that, hey, we're really starting to look for very, very specific, very, very specific skills that are related to new roles that you know arguably didn't exist a year ago. Right, like, where do we see skills-based hiring go going over the next, you know, half a decade?
Speaker 3:Yeah, that's a yes from me, by the way. I do see what you just described, so this has been so interesting. We do talk about this in the report, as you said, because the progress on this has not really matched the level of ambition that organizations had in this area, and I do think that we will see this speed up a little bit, especially in organizations that aren't afraid to get in and make some changes. We talk about progress over perfection. In fact, perfection is the enemy of progress, and so what can you do now? What can you do today to advance your sort of journey towards this North Star?
Speaker 3:And one of the issues that I see is organizations that are really big and complex struggle to get the buy-in from. You know, when we think about large enterprises as an example, they struggle to get the buy-in from the hiring manager community, which is where this, you know, lives or dies, because you might encourage them to focus less on professional qualifications, where they're less relevant, or years of experience in a role, where that's less relevant. And then you know, then the candidate gets to the hiring manager interview and well, how many years did you spend over here? And so they just take a different lens, which is a bit more traditional. So I think pace here can be gained from organizations that address some of those kind of buy-in change management aspects.
Speaker 3:Ultimately, I do think you know if I conceptualize the resume as a marketing tool, it's something that I can pull together to sell myself to you, my experience, my whatever my skill set to you. And AI potentially enables a process which is a bit more objective because it can both infer skills that I've got but also match me to roles. I mean, these are well in production now, these features, and so it's almost a case of you know why hasn't the story here quite matched the capability? And I think in some organizations it has, but others have got a long way to go. And it's to those ones we're kind of saying hey, just make some, take some steps here, um and and the rest will you know, and then you'll be able to take more steps because those ones will become embedded. That's kind of how I've been thinking about this. But yeah, what do you guys think?
Speaker 2:Yeah, no, I mean, I completely agree, and I think you know, hopefully we see more maybe publicity is a word I'll use around you know organizations that are investing in we'll call it. You know skills-based work right or skills-based you know programs and so, like you know, or skills-based, you know programs and so, like you know, you see stuff. Like you know Amazon, you know investing. You know, arguably, you know, billions of dollars in upskilling their workers. You know, and you know, at&t investing. You know a billion dollars in their future ready program, figuring out what skills of the future are going to look like, and so I think, like, hopefully it was as more and more of those programs you know kind of front and center, amazon and you know and AT&T are not saying, hey, like we're going to invest on sending people to, you know, get a bachelor's degree from you know a certain university. Or hey, like, let's make sure that we're investing in, you know, getting people to do a certain job for the next 18 months. You know it really is.
Speaker 2:You know companies and smart companies and large ones are investing in skills, reskilling, upskilling, and I think that's a logical, you know connection point to boy, like, if companies are investing in certain skills. Why aren't we, you know, as an industry, investing more in hiring based off of you know certain skills? Skills-based hiring too. Does that make sense, david?
Speaker 3:Oh yeah, it does, and I think you know. The other question is how do we so, how do we define this whole skills-based hiring anyway? Is it connected to a skills-based organization sort of programmatic approach? And, at the same time, what is a skill? Because you know, I mean, is a skill a technical skill? Is it a behavioral competency? And our view is that, actually, if you just focus on the technical skills, then you're not going to find the performance sort of differentiation factor that you're looking for in selection. If you've got five people who can all use Excel, how are you going to figure out which one's going to do the job best? And it's to be found in their behavioral competencies and their identity, their personal identity. So yeah, I think there's a lot of questions that some organizations have been able to answer, or at least taken a view of, whereas others are a little bit potentially just bogged down by just the enormity of this. And I think Graham, your dog, agrees.
Speaker 4:Very much, very much. It's possible. Normative, um, you know of this, uh, and I think graham, your dog, um, agrees very much, very much possible as well. No, david, I know we're short on time, but there's one thing I really want to get your feedback on. So you were talking about hiring managers, but how important it is to bring hiring managers along for some of these evolutions that we're seeing with AI and skills-based hiring. Just anecdotally, can you comment on why you think it's?
Speaker 4:What is the hesitation with hiring managers to adopt skills-based hiring? Is it purely risk aversion? We've been doing this a certain way for a long time. This candidate seems to have great skills, but you know what? They don't have a lot of experience. And you're telling me I'm going to hire someone for our organization that does not have a bachelor's degree potentially. And what happens if it turns into an unmitigated disaster for the organization? I'm the hiring manager I was in charge of this. Is that as simple as it is? Or do you think people have valid for lack of a better term not risk associated, but just they don't trust or don't fully understand skilled space hiring? But it's not purely about taking the risk averse approach.
Speaker 3:I do think some of it's fair. I do think some of it is misunderstanding or potential underappreciation of the potential and what I get, what I get from, like, what's in it for me, um, so we can help tell that story better. And then I think, yeah, it's, it's I do. I do think in some cases it's a bit more complicated as well, because maybe I've just got a different opinion as a hiring manager than whoever's been creating this program about what good looks like for this position. Maybe before I worked here I worked in the same job, you know, five for five, exactly the same job for five years in a competing firm.
Speaker 3:What I do think there's some validity in is the notion that actually skills are both acquired and developed. So the proficiency level goes up from experience. So if I, if I learn a skill and I don't use it, have I learned the skill but I practice it every day, there's a better chance that I'm not just mastered it but I've been able to build proficiency. So there is some. I think there's some validity to the. So there is some. I think there's some validity to the, you know, to the sort of tenure argument, but at the same time I yeah, I think this is more about saying, hey, we need to focus on skills more than we do some of these other items which are perhaps less relevant to performance, which is, you know specific tenured experience in the same job or professional qualifications, unless you're a doctor or you know whatever, you absolutely what these roles that actually do require you to have professional qualifications.
Speaker 2:I think that's great. Well, you know, I think we could keep this conversation going for hours. David, I'm going to ask you one question that you know, I think is just top of mind for me. You mentioned doctors. I saw a quote earlier this week. It's like oh, why aren't doctors working remote? Well, I think there's an obvious answer for that one, hopefully. But I'm curious, hey, with still a lot of chatter, especially over the last six weeks, on this future of hybrid work in office versus remote, just curious, has hybrid work reached its final form? Or how is hybrid, you know, or this, you know, hybrid 360 model sort of evolving, you know, with the workforce of the future?
Speaker 3:Well, I love listening to you guys talking about this I don't know if it was on the most recent episode or another one where you were kind of I think one of you was like, look, if I, if I, hear one more sort of argument against hybrid work. You know, my view of this is that. So what we did in the report is we said that hybrid isn't just about, you know, whether I'm in the office or not. Actually, it's more towards this concept of work-life integration, where I work when, where and how suits me to produce what I need to produce, for me to get the job done.
Speaker 3:And I heard you guys talking about, well, what happens if, with mouse clicks as a check of like, I've just never subscribed to that whole notion where we have to monitor people all the time. And I think there's a problem, you know, in professional, certainly in professional segments, where if you don't trust somebody to get the job done and can't measure them by the work they do, then that's a bigger problem than you know. Anyway, not to re-have the conversation that you had the other day, but yeah, I just think the potential here to allow people to work when, where and how the best suits them should be maximized because it makes business sense. It makes business sense because it's what the talent wants and it works for them in their lives. So, yeah, that's kind of my view on that and I think what we're trying to get through in the report as well.
Speaker 2:Yeah, no Well. I think that's kind of my my view on that, and I think what we're trying to get through in the in the report as well yeah, no, well, I think that's fantastic and I think that's probably a logical place for us to put a pin in this one. Last question, david, it's easy. Where can people find you online?
Speaker 3:Where can they find me online? Well, they can find me on LinkedIn and they can find me on, um, they can actually find me on the corn ferry website as well. Um and uh, yeah, I've, I've really enjoyed the conversation today. Thanks for having me on and I, um, yeah, I hope you hope you guys, uh, and and whoever's listening got something out of it as well. So, yeah, thanks again thanks, david.
Speaker 2:it's been great, david, and you know we'll make sure that we're, you know, linking all of these corn fairy reports, you know, and upcoming webinars too, because I think there's just a wealth of content that you know we think is some of the better content that's out there too. So this has been a great episode and, you know really appreciate you joining us. All right, thanks for tuning in. As always, head on over to changestateio or shoot us a note on all the social media. We'd love to hear from you and we'll check you guys next week.