Ep 714: Navigating AI In Talent Acquisition

Speaker A: Talent acquisition is being bombarded by the rapid developments in AI while simultaneously facing significant market and resource challenges. Harnessing AI effectively isn't straightforward. So how can TA leaders strategically navigate the evolving AI landscape at such a disruptive time? Keep listening to find out support for uh, this podcast comes from Smart Recruiters. Are you looking to supercharge your hiring? Meet Winston Smart Recruiter's AI powered companion. I've had a demo of Winston. The capabilities are extremely powerful and it's been crafted to elevate hiring to a whole new level. This AI sidekick goes beyond the usual assistant, handling all the time consuming admin work so you can focus on connecting with top talent and making better hiring decisions. From screening candidates to scheduling interviews, Winston manages it all with AI precision, keeping the hiring process fast, smart and effective. Head over to smartrecruiters.com and see how Winston can deliver superhuman results.

Speaker B: M M. This is my show. Foreign.

Speaker A: Hi there. Welcome to episode 714 of Recruiting Future with me, Matt Alder. Recruiting Future is a podcast that helps talent acquisition teams drive measurable impact by developing their strategic capability in foresight. Influence, talent and technology. This episode is about influence and technology. Talent acquisition leaders are navigating a, uh, uniquely challenging period, juggling rapid advancements in AI with ongoing operational demands. The opportunity to automate routine tasks is clear, but the real challenge is determining where AI ends and human intervention begins. With AI technologies rapidly reshaping the recruiting landscape, how can employers ensure they develop AI strategically rather than superficially? My guest this week is Chris Reich Weber, VP Business Intelligence and Analytics at uh, Smart Recruiters. Chris shares valuable insights into defining clear outcomes for AI deployment, experimenting effectively and building genuine trust with technology vendors.

Speaker C: Hi Chris and welcome to the podcast.

Speaker B: Thank you Matt. Great to be here.

Speaker C: A ah, pleasure to have you on the show. Please, could you introduce yourself and tell everyone what you do?

Speaker B: Yeah, absolutely. So I'm Chris Reese Schweber. Uh, I am a recruiter turned tech consultant in the ATS and CRM space. Um, and then somehow, uh, found myself on the vendor side of the fence, uh, with Smart recruiters, which is where I am now. Uh, and after several role, um, here I now am leading the, uh, business intelligence team. So, um, my teams are the ones that do all the clever stuff to figure out how our customers are using the product, what needs to come next, uh, lots of interesting data points to go and uncover and find out where we've got some cool stories to tell and uh, what feedback to give our product teams on where we might need to go Next.

Speaker C: Fantastic. So you're the perfect person to answer this next question then. Which is, what kind of challenges are you seeing in TA at the moment? And what's the sort of the real world impact impact of them for the employers that you work with or employers that you're aware of?

Speaker B: I mean, as ever, I think it's not an easy time in ta. Um, I think we can kid ourselves and look back with very tinted spectacles and say there was a time when everything was easy. But I think people have got this dual challenge of what the heck am I meant to do with all this stuff going on in AI? And how do I keep managing a team, running a department, filling the roles, firefighting my stakeholders, building business credibility. Um, and I've always been a big proponent of as a leader, carving out time to work on the business as much as in it, if not more. Um, and I think now more than ever that brings that into sharp focus. Um, so I think there's that element of it. And then I think the second piece is if you lay on the particular industry that you're in, um, can mean a very, very different challenge within ta. So, and we recently did this big benchmark study around what's going on in hiring in many different industries. And some industries have a volume problem in terms of, you know, too many applicants, not enough time. But not everybody has that challenge, so the challenges are a bit more nuanced. And I'm, um, very, very empathetic with TA leaders right now for not just having to navigate all of that, but also then, like I said, the wave of AI conversations and how do I parse that into something actionable and how can I do something with it?

Speaker C: Yeah, I mean, 100%. I think it's just this perfect storm of circumstances at the moment, you know, including the economy and just everything, and just things getting more and more complex. But AI is kind of the obvious game changer here. What do you think the implications are for the way that recruiting's always been done, and what are you seeing in terms of the impact of it already?

Speaker B: It's a question I ponder on a lot, given mine and my team's role. And I found myself the other day thinking back to one of my first recruitment jobs, which was, uh, working for Barclays Bank. And I ran a call center, uh, of about 20 people. And the job was very simple. It was handle inbound calls from people who wanted to work in the branch network. We asked them five simple maths questions, and if they passed, we booked them into an assessment center with the branch. And that's all we did day in, day out. Thousands and thousands of calls every week. Massively, um, high reject rejection rate, um, and really an incredibly inefficient way of getting people in front of a hiring manager. But it was, you know, it was brute force and it was the best available tool that we, that we had. And you know, I think forward to now, and the amazing thing is there are still some businesses that have that kind of setup. Um, you know, when you, if you think about the breadth of tools that are available now, there's so much more available, but there are still people who operate in that kind of way. So I think that, you know, the general principle and general processes that we follow in recruitment haven't necessarily fundamentally changed. And whether they will or not remains to be seen. I think a large part, um, of it will still remain, um, you know, the same kind of steps. But, uh, I look at the possible and now very easy to implement increases in efficiency that are available. And that for me is the obvious one, um, is there's so much more there and if you're not using those things in the right way, then you can very, very quickly get, get left behind. Um, so I think we're seeing a bit of a widening gulf in the haves and have nots in terms of, um, ability to execute really, really well on a process. Um, and I think you and I had a conversation about this a couple of weeks ago, um, after your LinkedIn post about what's going to happen to the number of recruiters. Um, I think we like to tell ourselves that we're not under threat as much as we think we are and that everything's going to be okay. The answer is none of us really know. Um, but I think what's clear is that, that that role is going to fundamentally change. And whether that means a net result of less people, it could well do. But I think the key question to answer is if that capacity change happened overnight, suddenly we become incredibly more efficient as recruiters and TA teams and I, as a TA leader find myself with all that extra capacity, then if my CFO or CEO, uh, walks up to me tomorrow morning and says, great, you've got all this free time now what are you and your team going to do? You need to have an answer. It can't be a kind of, oh, well, we'll be more strategic, we'll spend more time doing value add things. That's great and you should, but, uh, what are those things? Um, and I've heard a Very, very wide range of answers. But it feels like maybe we're not wanting to put too much thought into that because we're kind of hoping it doesn't necessarily fully come because it's a little bit uncomfortable.

Speaker C: No, 100%. I think I wrote that article just because of all of the wide range of answers that I get when I ask people. It's like we're going to focus more on high value stuff or more human stuff. And everyone's got a different answer as to what that, as to what that is and I think is the issue. I'm kind of sort of working through a follow up actually at the moment where, you know, I think you could list out the things that a recruiter does that a machine can already do better, the things that a recruiter does that a machine can't do better. But actually recruiters aren't doing them very well at the moment because they don't have capacity or the right processes and systems and a computer could do better and then stuff that a computer couldn't do. And I think it's almost that kind of, of sort of exercise that people need to be sort of going through and um, you know, really, really thinking about when it comes to, you know, obviously smart recruiters, you're building, you know, from the ground up with uh, AI as we kind of move forward. What do employers need to take into account when they're sort of deploying AI into their, into their processes, into their company? I mean, how. It just really strikes me sometimes that people have kind of no idea of its full potential or how to, how to realize that. What's your advice? What do you think?

Speaker B: Yeah, I think, yeah, there's a list of three things that comes to mind and I'm actually going to go backwards because I think the first, the third one as I think of it, is probably actually the most important, which is, you know, you need to be crystal clear about the outcomes you're trying to achieve with that. And, um, it's easy enough to sit there and say, well, I understand what outcomes we're trying to get to and maybe it should be obvious to everybody else what these outcomes are because if you understand what the solution does, you must understand how it translates into what difference we're hoping to see with it. But I think too often in change management in general, we do a poor job of really outlining the benefits. And It's Change Management 101. What's in it for me? Why is this going to be more beneficial for me? Why should I care about it, why should I use it? So I think it's that be very, very crystal clear about outcomes. Um, and it can't be generic things like, well, this is going to make things easier for you, or you can answer These customer questions 10 times faster by using this AI search tool or whatever it might be. Um, so I think you've got to be very, very prescriptive, build it around the foundation of those use cases and those outcomes, and that will help gain traction. I think the second thing is, um, see if you can experiment because depending on the size of business you're in, you may have many hurdles to clear in terms of infosec and legal and data privacy and so on. Um, and I think it can be quite easy for businesses to get a little bit, um, defeated if they come across some potential roadblocks early in those conversations. So I would say constantly look for how you could pivot or change the scope of what you're trying to do, um, to force an experiment. Because even if you can't get to the end result you're looking for immediately, which is, I want to roll this tool out across my 5,000 hiring managers or whatever it might be, um, if you can do it with a small pocket and prove it again, very much Change Management 101. But start small, build the success story, uh, and roll out further from there. And I think that's even more beneficial when it comes to deploying AI because one of the main things is about building trust. Um, and if you can't do that early, uh, on, um, you're going to really struggle. So, um, I think deploying it in the most thoughtful way and gaining that trust quickly is probably one of the biggest ingredients to getting it done well. And then I think the last thing really is find the right partner. So depending on the tool, the tech, the solution you're looking for, um, look past the product. And I say this as a product person, but look past the product. Get under the skin of the people that you're talking to. Try and understand not just what they're pitching, what they're selling right now, and what the benefit is for you and your team today. But really get curious about their business, what they see is coming in the future, what's on the road back more than six months beyond. And it won't be specifics, but it's. Is it matching up with what you're thinking about in the long term, or are they teaching you things? That's one of the things I, um, say to a lot of my colleagues is if we're not teaching and educating the people that come to us for advice when we're failing them, we're um, not here to sell them a piece of technology. We're hopefully here to guide them towards some good outcomes. So I'd say you've really, really got to find the right partner. Uh, um, so try and look past the technology, as shiny and whizzy and exciting as it can be, and get under the skin of the vendor a bit more as well.

Speaker C: Yeah, I think that makes sense and I think that specifically with the AI thing, I think it's also important that people have enough knowledge about it so they can tell whether their vendor is using this m strategically building something interesting and new or literally just kind of plugging it in so they can say that they've got it. There's a real kind of range of ways that people ah, are ah, doing this, aren't there?

Speaker B: Yeah, there really are. And I talked with um, somebody about this a couple of weeks ago and applied the analogy of um, put on your own mask before helping others. And I think when it comes to your education on AI, um, as a, as a TA leader, it's incredibly important. You need to be able to validate some of the conversations that you're in. Look beyond the pitch, look beyond the spin, um, and make sure you understand what's happening. Because as you say, if you, if you approach it as a checkbox exercise and say, right, we've got AI now we must be more efficient or more productive, um, at some point somebody's going to ask you to prove it. And that's the key bit. If you don't understand the, you know, the foundations of it, it's going to be, going to be hard to prove it from there.

Speaker C: We've talked about that. This is a disruptive and difficult time for talent acquisition at the moment, but also full of opportunity with new tools and new ways of working and all those kind of things. But obviously it means that people are going to have to get investment to update their technology and really sort of look to how they achieve their goals and their vision. What's your advice on building a business case for investment in technology?

Speaker B: Particularly with all the general economic situation, um makes it uh, doubly hard uh, for people to get the level of investment they're looking for because CFOs are rightly scrutinizing, uh, purchases more and more. So I think back to the hundreds of sales cycles that I've sat through, um, and been a part of and the best prepared teams uh, on the customer side, when it comes to getting a business case successfully signed off, they do a few key things. Well, they partner with their finance and their IT teams early on in the process. They don't go away and do it in a silo and then take it to them for a sign off. They're really building that case up early, uh, and using it as a way to build internal capital. But also just get good advice, um, because uh, nobody can know everything about a business. And using those people in the right way to help, um, make that business case a little stronger or more concrete or aligned to costs or revenues you weren't aware of, um, can be incredibly helpful to show that you've thought beyond your team, your function and you're looking at it as a wide range, uh, piece. And that also then helps build to what business priorities are you aligning to as well as the functional priorities for you, what are the other clearer business priorities that you're aligning that, uh, required, uh, investment to?

Speaker C: Absolutely. I mean that makes perfect sense. Going back to the kind of this sort of recruiting evolution and everything that's kind of going on. What do you think the current split between humans and machines should currently look like? I mean obviously this is something that is continuing to evolve, will continue to evolve over time. But where do you think people should be right now?

Speaker B: Yeah, I mean you said, um, earlier, you know, there's an exercise to run through of, you know, what can we do well versus what can machines do well? And I'd like to think about it in a similar way. You know, if I were to do a kind of Moscow matrix of what should my AI, you know, must do, could do, should do, et cetera. That's an interesting, uh, exercise to go through. I think at a general level. My answer, the way I think about it is the optimal split is probably something akin to the machine doing a little bit more than I'm actually comfortable with. So I need to be challenging my own perception of what's possible, um, and seeing if we can take things ah, a little bit further to your point. You know, the basics of it. Automating my easy tasks should just be a no brainer, taking, taking meeting notes, scheduling, follow ups, etc. That should just be happening right now. Anyway, then my next thought moves on to how can I get it to do more of the heavy lifting when it comes to my more complicated tasks. Rather than bifurcating that as a pure the machine does the easy tasks, the human does the hard ones, it can still help me in A massive way with my, with my more complicated tasks as well. And I think, you know, through the lens of a recruiter or a hiring manager, uh, then yeah, interview, scheduling, job description, generation, all of those um, easy but heavy lift tasks absolutely should just be given to the machines, uh, to do for the most part. And then you have the human element on top of that to finesse it and provide the context and so on. Um, but yeah, I would say that the optimal split is probably just if you're not feeling uncomfortable with it then maybe it's not optimal just yet.

Speaker C: Yeah, I think that's a really good point. I think that bit about the obvious automation but then the augmentation bit and actually defining what that looks like is probably important. And I guess, and this probably leads into. My next question actually will be at a point where there's a third category which is the things that AI can do that sort of change the process or that humans could never do that makes us think completely differently about recruiting. So on that note, my final question is what does come next? What do you think we might be talking about in two years time?

Speaker B: Say let's see if this ages well, it's always difficult to make predictions and I say this as a, you know, as a data leader, uh, um, making predictions is incredibly difficult even with all the data and context in the world. I think in the recruiting tech space particularly, um, I think we're going to see AI give rise to some interesting consolidation. Um, because I think we're going to see very quickly those providers, um, that maybe don't have the right infrastructure or otherwise to build on top. They're going to be doing their best to keep up and potentially just won't be fast enough. So I think we'll see some interesting changes in the landscape of vendors available in the market and who they align with. Um, so we'll see where that goes as um, recruiting in general. Um, my prediction is we probably see the biggest positive shift in the presence and capabilities of hiring managers in the recruiting process than we ever have. Um, and this is a view that I think uh, uh, Adam Gordon and I share. I've seen a lot of his writing on it recently. Um, you know I think, I think as recruiters and I say this with love, having been one for a long time myself, we're very fond of, you know, saying how much of a nightmare it is if managers do self service more and you know, we've all got the horror stories of somebody who wrote a terrible job advert or you know, asked the Wrong interview question. And we needed to gatekeep it for them. But I don't think having a human backstop is a good long term answer. Um, so I think we need to give our uh, uh, hiring managers and our stakeholders way more credit. We also need to give them far better tools and capabilities. Um, and I think then that will really increase their ability to play uh, a big part in the recruiting process. So I think the role of the hiring manager as a recruiter goes up an awful lot more, um, in the immediate future. Um, and I think nowhere is that more obvious than the fact that one thing that you get with everything that's coming with AI is the ability to really embed all of this into their general flow of work. You don't necessarily need to pull them into a specialist platform. Um, we have customers who are, um, making a lot of recruiting actions available through Slack and through teams and the other tools that managers do day to day so they can perfectly achieve the outcomes they're looking for using our technology, even though they never touch it. And that level of it being used outside the platform or uh, through an adaptive ui, whatever that might look like, I think that will be a big piece, um, in the next 12 to 24 months. Um, and then I think the only other thing that I feel like we've been talking about as an industry for a long time but still haven't quite cracked is skills based hiring. Um, I don't necessarily think it will have solved in the next couple of years, but I think what will have changed is how we transact and how we operate as part of recruiting will have changed significantly and that may well send the skills based hiring conversation into a slightly different direction. Um, uh, but the main thing I think is like I said earlier, ah, we've got this divide between the haves and the have nots in terms of recruitment, tech and processes. And I think that's really going to start to show itself in the businesses that have not invested in good technology, good processes, good enablement for their teams. It's going to result in them having to fight really, really hard for the talent that they want and it's going to just make that divide even greater.

Speaker C: Chris, thank you very much for talking to me.

Speaker B: Thank you Matt. Absolute pleasure.

Speaker A: My thanks to Chris. You can follow this podcast on Apple Podcasts on Spotify or wherever you get your podcasts. You can search all the past episodes@, uh, recruitingfuture.com on that site. You can also subscribe to our weekly newsletter, uh, Recruiting Future Feast and get the inside track on everything that's coming up on the show. Thanks very much for listening. I'll be back next time, and I hope you'll join me.

Speaker B: There's been more of scientific discovery, more of technical advancement and material progress in your lifetime and mine than in all the ages of history.