Smarter, faster, sharper? What’s the deal with AI in talent intelligence?

Speaker A: This is HR in Review, a podcast dedicated to HR thought leadership, actionable advice and all the latest developments in human resource management.

Speaker B: Hello and welcome to another episode of HR in Review podcast with me, Verity. Um, today we're going to be looking at AI and its rise in the workplace, um, specifically around the talent intelligence area. And to that end I've got with me today Toby Kolshaw. Hello, Toby.

Speaker C: Hello.

Speaker B: Toby is the former head of Talent Intelligence at Amazon and Philips, founder of the Talent Intelligence Collective, and author of Talent Intelligence Use Business and People Data to Drive Organizational Performance. That's a long title.

Speaker C: It is a rather long title. We really should have shortened that up. We could have done a better job.

Speaker B: I'm really, really happy to welcome you on today. Thank you very much for your time. Um, so we're going to be looking at specific, um, the things that are happening in the talent space with AI at the moment. This is something that you're very well placed to talk about. Um, obviously there's an awful lot going on. There's a lot of hype at the moment. There's a lot of noise about this kind of thing. So it'd be really good to get some kind of um, examples of where you're seeing things moving, the changes that you're sort of witnessing, and kind of get some tips and ideas of anybody who is obviously in the space and how they can kind of use AI to really optimize things or what to look out for really. So that's the, the plan for the conversation. So as we um, get started then, can you just give me a little bit of an overview about what's happening with uh, this at the moment in the um, the talent, uh, space.

Speaker C: Yeah, a nice easy question to start off with. I like. Huge amount. A huge amount. So I think there's, we're definitely up there in the hype cycle. Uh, in terms of where we're looking at this stuff, we're seeing a lot of stuff being driven from a vendor side in terms of automation and um, bringing new ways of doing the traditional talent acquisition role or talent intelligence role. Uh, so you're seeing automated sourcing or you're seeing automated first screen interviews, et cetera. Um, a lot of it at the moment I think it is being driven from the vendor side rather than the practitioner. But when you look at the practitioner, you're seeing a far greater uh, emphasis on um, efficiency improvement rather than robotic process automation type work. Because process automation, that's been there for a long time. The Gen AI piece is really just Adding another easier layer on the top of it. But um, I think we really haven't seen that kick into gear properly yet. You're still not seeing a huge number of the ATSS and CRMs kicking that in a truly effective way that seeing massive disruption within ta. Beyond the odd example, there's the odd example of the volume type recruitment where you are seeing a much greater usage of this sort of stuff um, and a greater dial up of hiring manager self service. But in my mind there isn't really a great change there versus you've had hiring manager self service in a lot of industries. Retail comes to mind immediately for many, many, many years in terms of TI activities. So I think at the moment you're seeing a much higher dial up on using Genai um, to help improve efficiency within ta. So whether that's writing job descriptions, whether that's um, helping with copy for a hiring manager, etc. Giving us some summary on whatever you're reading or intelligence articles out there, whatever it may be. So it's more that efficiency gain. Obviously there's a lot of nervousness around using generative around um, CVs and um, how we process information down selection, auto selection, etc so there, a lot of people are very very nervous about that at the moment. Um, and I would argue rightfully so, rightly so.

Speaker B: I was going to say I did mention to you before about the article I just was reading and that was exactly what was being discussed and um, saying about how bots are basically talking to bots and there's a lot of people who end up with just reams and reams. I think the example it gave in that it was a New York Post article saying that Somebody had over 1200 applications for a remote position and they're three months later still working through all the applications. Many much of what is just noise and very similar and there's nothing really that's making uh, you know people aren't really applying in the same way as they would have applied for jobs. So this is going to be a very real problem isn't it for recruiters at the moment?

Speaker C: Yeah, I think we've got a compound piece at the moment where a lot of TA teams have been cut right back because leadership are going well we're not hiring as much as we used to so we don't need as many TA people as we used to. So they're cutting them right back. But then you've got the compound effect there aren't as many jobs out there and candidates that are looking are uh, Having to apply for far more jobs than they used to. But as you say, with the new tooling coming out from a candidate side to auto apply and also, let's be honest, there's a lot of people out there applying for jobs that aren't candidates that are trying to get into companies in uh, an offensive way. It makes it very, very difficult. Um, I was talking to one TA leader who advertised the job and uh, it went out, I think it was 2 in the morning, 2:03, um, and within the first three minutes they had 6,000 applications. And there was no real way for them to know which of those 6000s would genuine candidates that were using tooling to auto apply versus aggressive actors that were applying for um, unscrupulous means. How is any TA team meant to handle this? We just don't have the tooling, we don't have um, the mechanisms to handle this sort of volume because frankly, whenever there has been a quiet period in inverted commas for TA leaders have cut the TA teams. So we really haven't had that breathing space to build the capability and the mechanisms. And this is all new stuff. Like the reality is that what we're facing now, the scale we're facing it now is unheard of. There has been nothing like this in history. So we've got a bit of this chicken in the egg. Candidates are applying for more jobs than ever because there's this black hole in the ats. They apply for jobs, never hear from it, so they want to apply to more and more and more. Um, but because of that volume coming in, TA teams can't handle it and they're just not handling the volume of applications. And uh, yeah, something's got to break. There's got to be a change in the mechanism in the system there somewhere.

Speaker B: What do you think that's likely to be? Because again, I'm just referring to this article. I think it said that one of the companies that was recruiting was an AI company and they put a stipulation into their recruitment process that nobody's allowed to use, uh, AI, uh, tools to apply. They've got some sort of caveat they've put in there so that they're getting genuine the irony, uh, they're getting these very old school, I guess, uh, resumes coming in. So, you know, is that the way things are going to go? I don't know.

Speaker C: I think there's a few things that could happen. I've said a lot recently in the last few years that I think the most damaging thing that happened to TA Was, was easy apply, uh, as soon as we had it, really no barriers to entry and a very easy uh, application process. Great for candidate experience and that they could apply for. People could apply for jobs really easily, but we weren't geared up for that in the back end. We weren't prepared for this. So I think you're probably going to see one of two things. You'll see tech advancing, so you'll end up with either, uh, people applying and then your bot talking to their bot and you just have tech doing its tech thing in the background. Uh, and that will get a down selection at some point. That's going to be, I think, a very difficult road given all of the legalities and um, the culture we have at the moment for law, uh, court cases and stuff in the US particularly, that's going to be a difficult tightrope to walk. I think you're going to see a lot of people go more kind of similar to programmatic advertising. Well, they'll put a job out and then as soon as they've hit 50 applications that say just pull the ad and you'll see more and more people with these job ads that will just flip up and go flip up and gone and it'll be bite sized. They'll see what they can manage from that. Which will be terrible from a candidate experience perspective because you could see your perfect job and by the time you've written a cv, your job's gone. You might never see it again.

Speaker B: It's like Glastonbury Tickets, isn't it?

Speaker C: Exactly that. Exactly that. So I think that's a dangerous path and I don't really want that path. I think the other approach is we see uh, more barriers to entry point into a process. It's ironic that candidates want a really easy process. They complain it's already too hard to apply through some of the ATS suites that, you know, they often get bashed in on the media, etc. Um, but at the same time, if that's what we need to do to limit the volume of applications and to try and have people more invested. But the flip side, there's got to be a return on investment time. So if we do that, we do have this barrier to entry. We've got to up our game internally in terms of there can't be these black holes of information. You can't have 90% plus of all applications go completely unanswered. Not even an automated. No, just nothing. We've got to give that return of value back to say, take the time to apply, take the time to craft whatever it is or do our talent assessment, whatever it is. But we're going to give you something of value in return. Um, and I think that will largely be driven by the vendor side rather than the in house side. It will be the tooling and the vendor mechanisms that we can use.

Speaker B: Have you got any examples of where you've seen this in action? Because I know you work with lots of different organizations, um, or you know what are the sort of main. Well we've kind of outlined the main pain points. How are people responding this actual in real terms?

Speaker C: I think most of the people I talk to, obviously I'm more on the hardcore talent intelligence side of things than the talent acquisition side of things nowadays. So about that a bit more. But in terms of the pure TA piece, most of the TA leaders I'm talking to are pulling adverts. They're putting an advert out there as soon as there's any kind of volume of activity. So whether it's 50, uh, applications or 100, whatever they need for their uh, funnel conversion analytics to say this is how many applicants we need to hire, once it hits that point they just pull the advert. And so I've seen that a lot. Um, I've seen teams working with their cyber security teams to say how do we block automated apply? Because the volume we just can't handle it. As you say, there are teams out there saying you can't use any kind of automated application to apply for us. Um, and that goes through the whole of the process quite often as well. Um, that gets very difficult, particularly if you're a company where when you're in the job you're going to be expected to use Genai tooling a lot. So how does that work? How do you kind of square that one off? Um, but yeah, I think the majority at the moment it's that period of we're just being a bit scrappy and doing whatever we can to try and manage this volume and this imbalance. So the majority I speak to are ah, just turning off job adverts and you're seeing the average advert rate or uh, time to advert, uh, advertise, get cut. You're seeing a lot of people just cutting this or they're just random applications and the, the recruiters frankly are just going to work the top and just leave the rest.

Speaker B: And I suppose that things are going to be different once uh, again reading around the subject, people putting more um, practical things in place that uh, AI can't do. Um, so, you know, sort of the tests and things like that which might, uh, require them to do certain things. Certainly when it comes to the interviewing process, I know it's a little bit different. So I think there are things obviously people can do. You hope, you know, it's going to evolve, isn't it?

Speaker C: You absolutely will. And I don't know how much of that will go back to fairly traditional mechanisms. So you'll go, well, you know what, we can't do remote interviewing effectively because there were just the tech to cheat is going faster than the check to the tech to stop cheating. So we'll just go back to in person and all our interviews will go back in person and you'll have to come into the office. And obviously we're seeing big moves towards return to office from some larger companies at the moment. That's a very good argument for in person interviewing is, well, you can't use your tech if you're sitting in our office. Um, maybe there'll be a halfway point where you go, well, actually we have a number of designated interview centers where you have to go into whatever this satellite center is or the equivalent of a wework for, ah, a designated center. And you have to go in there for the interview and it's within a controlled environment, it's there, PCs, et cetera, et cetera. And you're just limiting the amount that the tech can interfere with it.

Speaker B: Do you think this is, um, ah, a generational issue then? Because I'm just thinking when you're talking like this and I think about myself and my own, you know, recruitment journey wherever I've been working. And it would never occur to me to try and cheat in an interview because I would hate to be, um, hired on a lie. Uh, I would only want to work somewhere I knew I could do the job. And I had a really good opportunity to progress my career without cheating. And I know people have always cheated, but the way that it can be done now without. So, you know, people just don't really think about it as much. It's more of a the done thing almost. I, um, don't know whether or not it's just the way things have turned out for the younger generations coming into the workforce. I don't know. What do you think?

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Speaker C: I think it's two things for me. One is the, what is cheating in inverted commerce? Because if you're going to expect the uh, candidates to use this tech within their job for your improved efficiencies, etc. And you know, we see the CEOs um, weekly at the moment saying we've saved x headcount because we've got this AI efficiency, etc. Etc. Yeah, why wouldn't they want to use this tech? So is it cheating or is it just our ability to assess them that isn't catching up fast enough? And then I think uh, that kind of leads on to the second point where the employer employee relationship I think is in a very fragile state at the moment. Employers are pushing very, very aggressively with things like return to office. Um, and there isn't really that social contract with the uh, employees particularly. You mentioned the generational piece, particularly the younger generation coming in there is the societal contract of you go to work, you get a degree. Also you get a good degree, you go to work, you get a good job, you get a mortgage, you get a house, yada yada yada, that's not in place. Uh, you look at the younger people coming through, the chances of them getting on the housing ladder are incredibly small. In the UK for example, the job security is pretty much gone. Entry level jobs have plummeted in the last few years. So what are we actually giving them a benefit to play the game? Fairly inverted commons once again. We aren't really giving them any value back. We're saying jump through our hoops. We're not going to give you job security, we're not going to give you a, uh, salary that increases in line with inflation. Um, we're probably going to make you go back to an office in a high cost living area, in a high cost commuting area. So, uh, during a cost of living crisis. So you're not going to be able to afford to live there. Ah, you're going to have to commute in, which will cost you a fortune as well, et cetera, et cetera. So we're giving them very little reason to want to engage with us as employers at scale in a fair way.

Speaker B: Gosh, when you say it like that, you know, who'd want to work? Um, it is hard, it is hard out there. I think that's, and I know recruitment at the moment is generally a tough space. Um, okay, so let's think about, let's talk about what is going well Then let's talk about the good stuff. Stuff where we're seeing all this, all the good things. Tell me about them.

Speaker C: I think we're seeing the potential for a revolutionary era of talent acquisition. So I've said for a while that I think talent acquisition is, we always say talent acquisition is broken. Um, I don't think it's broken. I think we've forgotten what we are though. When we all came from agency side, we all came in house. We changed our names from recruitment consultants to talent acquisition as a kind of broadening of the overall remit beyond just filling jobs. But uh, I think with that we forgot about the consultant bit and we moved from kind of this consulting high touch, low volume, um, consultative advisory service to a volume process efficiency play. And with that, uh, I think we're in a really dangerous era for ta. And that's why you're seeing a lot of the vendors getting a lot of traction in terms of hiring, managed self service and automation, etc. Because they're automating process efficiency. We're not going to ever as a human be more efficient than tech in a process efficiency play. That's not where we're adding our value. So I'm seeing ta. I think we could see a bifurcation where you end up with a process orientated TA function where you're going to have a very, very lean team, a lot of hiring manager, self service, a lot of automation. And really you're there as a small team for escalation and for process control and systems processes, tooling, etc. You're a very lean team. I think you're going to then see other TA organizations that lean much heavier into uh, the consultative piece. And I think that's where talent acquisition will end up taking on a lot of the work that say talent intelligence teams do nowadays. Where you're doing that workforce planning, where you're doing the location strategy, where you're doing the competitive intelligence, you're bringing data to the table and being a consultative partner to your business, uh, think that's where you're going to see a big shift occurring. Um, obviously I hope for the latter. For me, I'm heavy into the talent intelligence side of things. I don't think there's a better time to be building out talent intelligence capabilities than now. We're in an incredibly volatile world. Things are changing daily. Um, whether that's the systems, processes, tools, skills, political environment, tariff environment, you name it, it's an incredibly volatile world. Which means our leaders more than ever need that external lens to understand or get any kind of gauge in terms of what they should be doing. So for me, I think it's an incredibly exciting time for ta. As long as we own that transformation and change, we can't put our heads in the sand. We can't think, oh, do you know what, we're special, we're unique. It's not going to happen. Uh, I don't think there's a TA team out there that isn't going to get impacted. So look at the process and say, where is our value add here? If our value add is we're down selecting CVs and saving the hiring manager time, that really isn't a value add. The systems can automate that stuff. Be really clear about the value you're bringing to the table and what is unique about your offering to help drive your company forward.

Speaker B: That's very sound advice there. And now I know a lot of people because I know you've come from a corporate background. Um, obviously working with big, large, large organizations and volumes of uh, employees is quite difficult for um, SMEs who are approaching it from, from their position. What, what would you say for them? Obviously there's going to be things they can be doing, there's going to be tools. And what advice would you have for anybody in that space who's looking to sort of get more into the ti side of things?

Speaker C: Yeah, I think the beauty is, well, two things. Session number two today, I don't know why, and apologies for the chickens, you can probably hear as well, they're having arguments with each other. Anyway, uh, so I'd say the two things. One is the smaller the company, the more important it is to understand analytics and data and external context to talent, intelligence. And the reason being is if you're uh, uh, you know, my previous employers were 60, 70, 80,000, up to 1.57 million employees. If, if they put the wrong data center in place or they put the wrong software engineering team in place and they put a thousand headcount in the wrong place, it'll be painful, but they'll survive. If they put a contact center in the wrong place, it'll be painful, but they're going to survive. If you're a thousand person company and you put uh, 50 headcount in the wrong place for your software engineering team and you can't stand up your software properly then, or you put the wrong compensation piece so you can't hire anyone or you don't and your competitors EVP well enough so you can't position yourself well enough so you can't get anybody in the front door. If you don't understand that stuff, you could collapse the company. The compound effect, the smaller you are, it's massively important. So I think the need is there. I think the good thing about the Genai tooling and what we're at, the place we're at at the moment, it's incredibly innovative. You can do a lot of stuff with very little resources. And, um, you know, I just ran a competition for the Talent Intelligence Collective where it was how well can somebody write a prompt to do a location strategy? And it was deliberately artificially created as a competition to make it so it would be difficult. You can't reprompt things. It's got to be one and done. Even within the parameters and the constraints, there were some amazing results coming through. Now, is it as good as having a TI consultant? Absolutely not. Is it as good as if you're plugging in defined data sets and you know what you're doing? Absolutely not. But in terms of reducing that barrier to entry and helping with, say, the data analytics or data engineering or the actual writing of the document and the narration of it and making you think around, okay, what should I be drawing from this information? Those barriers to entry are really much, much lower than they've ever been before. So it means that people can suddenly grab that CSV out of their ATS and put it in there and say, help me think about the challenges I should be looking at here. Where are my pipeline issues? What could that be around? This is my company. This is the background, this is the context, this is the evp. How am I positioning it differently from my competitors? Now? Is it going to be as good as I say, having a true TI consultant there that does this for a living? Probably not. But is it going to get you much further down that road with very little barrier to entry? Absolutely, yes.

Speaker B: So what about when it comes to things like buy in then? I know that's always going to be a challenge, particularly with new technology. People are scared. We m. You know, you mentioned that earlier on, didn't you? There's fear around this still. Everything seems to be changing and the goalposts seem to be moving constantly. How do you put that case to your executives or your stakeholders and say, look, we need to, we need to do this, we need to move? Like, what would you say?

Speaker C: Yeah, I think there's ask for forgiveness rather than permission where you can. So you're never going to want to put things into this sort of tech where it's business critical. You're never going to be want to put things into this tech where it's going to go against your cyber security regulations in the company. You're never going to want to put, you know, candidate profiles in there and break PII and gdpr, et cetera. Don't get near any of that stuff. Um, pulling stuff together that's publicly available data, uh, into a nice narrative and saying this is what we could be doing if we explored this a bit more. This weekly business review or monthly business review or whatever it is your mechanism. If I use this tech to help me write it, this is how it looks much better. It took me an hour to do rather than 10 hours to do. And that efficiency gain has meant I can do this, this and this as well. I can now pull this newsletter together that used to take me half a day and I can do it in an hour. With that extra time I've given us back to the business, we can do A, B and C. Um, you use those kind of low barrier, uh, free pieces first. I think the investment side of things, uh, that comes when you're proving the ROI and there's a demand for working. You say, well, actually without this we can't, I think longer term, within most TA and HR pieces, I think there's going to be a huge amount that's driven from the vendor side because the data engineering that you need to get all your data aligned, get it all structured and clean, uh, to be able to run a lot of these models on top of it's a lot of heavy lifting. Whereas if you can do it within the infrastructure of your HCM suite or your ATS suite or your CRM or your TI vendor, whatever it may be, if you can do it within the vendor, they've uh, already got the data, it's already structured so you can do things a lot cleaner. So, um, I think use those vendor relationships as well and see what you can push from your vendor side.

Speaker B: So if somebody was interested in, in going down this path more, um, what resources would you recommend? Is there any podcast people should be, you know, because this is a big topic, this is like a whole new era of digital stuff to get your mind into. If you're, if you're somebody who's just a generalist HR person and you're dipping your toe and you're starting to explore these, these, um, these topics, could you recommend any reading, anything that people should be getting involved with that you think, you know, just to spike their interest a bit more?

Speaker C: Yeah, for sure. So I think it's such a broad and big topic. It's going to be pretty pervasive across every podcast or newsletter you read within hr. The ones that I like, because I'm incredibly biased obviously is, um, obviously we do a talent intelligence collective podcast so you can listen to that and hear about the TI side of things. We don't, thank you very much. We don't generally get into the kind of, the technical and the AI stuff as much we kind of talk about it, but we're more interested in the consultative and the people behind the story, as it were. Um, I think you've got, if you're into HR analytics, you've got things like David Green does some amazing stuff. You've got directionally correct podcasts with, um, Cole Napper. Um, there's some amazing podcasts out there. But I'd say also don't be limited by what is within, um, hr. Like the reality is the tech that's coming with this, it's hitting all functions. And so it will be just as relevant listening to a marketing podcast where they're talking about kind of AI impacting marketing, for example, um, as it will for us. Or if you're looking at procurement supply chain. I don't know if there is a procurement supply chain podcast, but the supply chain efficiency, et cetera, that's going to be very similar to the sort of stuff you see coming into our world. So I'd say be curious and listen to uh, as broad a base as you can, like Freakonomics Radio. Some amazing economists perspective on this sort of work. How skills are changing, how the workforce is changing, how our relationship, uh, with employer, employee, like we've mentioned, is changing, or how that changes with the government relationship like the L and D and the education system. Have a broad context because it's all going to impact you downstream somewhere.

Speaker B: Well, that was a good note to round it off on actually. Toby, thank you.

Speaker C: Thank you so much, Verity. Have a good one. Thank you.

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