Leading TA Through AI Acceleration

The pace of AI model updates keeps accelerating, and it's reshaping hiring faster than anyone can plan for. Strategies that made sense a few months ago already look out of date, and long-term planning has become almost impossible. So, what does effective TA leadership actually look like right now? Keep listening to Find Out. Support for this podcast comes from Codapad. Here's a question that should keep you up at night. When your next engineering hire sits down at their computer on day one, are they the person you interviewed, or are they someone who just knew how to perform for an interview? Meta discovered a dangerous gap between interview performance and actual job performance. So did LinkedIn, So did Yahoo. They all found the same culprit. Their hiring process was testing for skills that no longer reflect how the best engineers actually work. AI hasn't just changed how software gets built, it's changed what it means to be good at building software, and the companies who are winning the war for technical talent, they've already rewritten their interview playbook. Codapad is the platform powering that shift, from AI-enabled live interviews to realistic project-based screens. Codapad helps you see candidates in action, not just on paper. Meta scaled to 16,000 interviews using it. Yahoo cut recruiter screening time by over 50%. MNTN is onboarding new hires in days instead of weeks. This April, if you're still banning AI and interviews, you're not just behind, you're screening out your best future hires. Visit codapad.io/podcast to talk to the team. That's codapad.io/podcast. There's been more of scientific discovery, more of technical advancement and material progress in your lifetime of a mind, than all the ages of history. Hi there, welcome to episode 789, a recruiting feature with me, Matt Older. Some things shifted in AI over the last few months. The pace of AI model updates keeps increasing, and strategies that made sense a few months ago are already out of date. New tools can take on long, complex pieces of work largely on their own, changing what's possible across hiring. For TA leaders, long term planning has become almost impossible, while the recruiters role itself is being rethought as candidates use AI just as actively as employers do. So what does effective TA leadership actually look like right now? My guess this week is Brian Ackerman, head of AI strategy and transformation at Cornferry. In our conversation, Brian shares the changes he's seeing across the recruiting funnel, and how organisations can build the resilience they need to keep pace. Hi Brian and welcome to the podcast. Hey Matt, thanks for having me. It's an absolute pleasure to have you on the show. Please could you introduce yourself and tell everyone what you do? Absolutely, I'm Brian Ackerman. I am the head of AI strategy and transformation at Cornferry, the organizational consultancy, and I have the pleasure of leading a team of HR experts, scientists and engineers focused on what AI is doing to the world of work and jobs. And I have the pleasure of applying it to our organisation itself, as well as really focusing on how it's changing the kind of work we do for clients, both individually helping people find their next great role, but also how organisations are structured and organised themselves. Well first of all, it sounds like a very big job, but also a fascinating job. Do you tell us a little bit about your background? How did you get to do this role? I'm a computer scientist by trade. I've been in technology my entire life. Most of my career has been in consulting, but I took a turn a while back and did about 10 years or so as a sitting chief information officer for a variety of companies. A couple of them in the HR space, and that got me fascinated and passionate about the impact of technology on people. And so I've played kind of at that intersection for quite some time. I've had the pleasure of leading a few of corn ferries, capabilities around assessment and succession, leadership and professional development in coaching over the years. So as a generative AI, started us on the journey we find ourselves now. Our organisation asked me to kind of come back to my technology routes and drive RAI strategy as I just described. So I've always kind of been back and forth between technology and people and I'm happy to do that now. Let's talk about the AI journey that we're on because it's been a couple of years of talking about rapid technological developments and disruptive change. But really the last few months we've seen huge amounts of change in the AI tools and what they can do. What's kind of shifting and why is that important right now? And so I'm only giggling because I think every time at least I feel like I've got to handle it how fast this technology is evolving, something will happen to break me of that belief. And certainly the last couple of months have done that. We're obviously seeing a continued progression of the core capabilities of the models from all the model providers that shows no sign of abating. So we kind of have a basic, oh my goodness, these models can do X or Y this well or that well that we continue to have to work through. But I think even as important as the changes in the underlying models, the fact that a generative AI is becoming better and better at doing long form work has enabled the creation of these agentic harnesses, whether you're talking about clods, apps, co-working code or open AI's code X or what Microsoft is doing in partnership with Anthropic with co-work. The ability to set AI to a series of tasks make it goal oriented. And then the AI, the AI spawning multiple agents and doing long form work on its own to get to a goal. That proficiency is hitting a level and level of applicability that we haven't seen before, which is changing our way of thinking about AI at an individual level from, hey, you've got a super power to assistant to you've got a team of super power people. So it's really been a fascinating change just over the last couple of months. I find myself in a very similar situation. As soon as I think I've just about got to grips with what's going on, it all changes and things that we would have seemed impossible a year ago and now possible. So it's a wild time, definitely. It's I find myself on social media more than I've been in many, many years only because this generation of organizations, that's how they're communicating what's coming. So in my entire career, I've never used X as the way to understand product releases, but that's where I find myself. And they're happening that fast oftentimes. Material changes being announced, either in availability or upcoming, you know, several times a day, which is really unheard of. So you're constantly redefining what good looks like. And even whether it's the work we're doing internally or for our clients, there's been a very deliberate kind of time horizon that you're planning that happened before, say, the end of the calendar year, the Christmas holidays versus plans that you have after, are beginning to look pretty different because of that technology shift that took place right around the time. Let's talk about the impact on hiring. So I mean, how is the how is the hiring funnel changing, particularly at that sort of the top end of it? Well, I think overall, you've got, you know, several things happening. One is the assumption of AI literacy at all levels. At a leadership level, it's just as important for candidates and do whether it's job specifications from the organization or the candidates that they're sourcing to have a very high degree of AI literacy. And that means different things by level, obviously. At a leadership level, it means a focus on understanding the transformative impact on their role, their team, their organization. their industry as much as it means being able to use it themselves, although that's certainly becoming part of the equation. For some time, we've seen candidates using AI in the recruiting process as much as if not more than hiring managers and organizations, and that's introducing new complexity into the recruiting funnel. But AI has become pretty ubiquitous very, very quickly, whether it's in the production of CVs and documentation by a candidate or job specs by a recruiter. It's impacting many elements of the recruiting funnel at once. From a recruiter perspective, it's clear that some of the ways this is working at the moment is unsustainable. We need to think about how we evolve recruiting, the way it works, the role of recruiters. What does that look like, do you think? What's going to change? What needs to change? I think it makes perfect sense, given all the other automation, that a lot of the mechanics are going to get smoothed out. The role of the recruiter is going to become much more interpretive and grounded in the impact the candidate is going to make and less about, does this person have skill, AI skill, it be a skill C? We see ourselves using AI now to create search strategies, to create sourcing strategies, to canvas, to market map, to do the kind of mechanics of especially in the sourcing side of things that we would have done manually or in the past. That puts the recruiter's role in the center of, frankly, in some cases more data than less. The sort of candidate lists are created much more easily. You still have to be very, very, very careful in how you use AI to filter and select for obvious reasons. That recruiter's role is a lot more about their understanding of the role in the organization they're recruiting for, their judgment, their ability to see both with and then past data about a candidate that's being presented to them. So it's interesting, it's elevating the need for an insightful, thoughtful recruiter who's able to really interpret a much larger set of data in order to continue to look at candidates. This part of that with everything becoming more and more automated, where's the kind of human interaction with this, how does that actually change, how does that change from a candidate perspective? So from a recruiter's perspective, it's not being skeptical map, but it's definitely being able to interpret and process in some cases a much larger set of data. So the early part of the candidate funnel is exploding because candidates are using AI to customize the CV, even as you get more senior candidates are still putting themselves into the funnel with greater accuracy than they used to. The filters aren't filtering quite as much because of the use of AI to match a resume with the job spec. But the same candidates are now using AI to help them prep for interviews, in some cases to help conduct interviews. We're beginning to see it in the use of the other techniques we use to evaluate candidates, whether it's cognitive assessments or behavioral assessments, certainly candidates are beginning to try and use AI to assist in those areas. Which puts the recruiter in a position to really have to be thoughtful and interpretive and listening and processing what they're hearing and seeing from candidates. And it's actually had an interesting phenomenon around when either you detect that a candidate's using AI or you sense that a candidate's using AI, is that a positive or is that something you want to call them on and exit them from the process. We've looked carefully at that, this particular question because a big chunk of our business uses lots of techniques to evaluate candidates, including assessments, so it's a topic of interest for us. And honestly, we see as much behavior engaging in a conversation with a candidate about how they're using AI with the recruiter, so it becomes part of that interpretation of the individual skills as much as we're calling a candidate on it and saying don't do it. As you said right in the beginning of our conversation, the demand for people to have AI fluency and have AI skills is just there in more and more, more and more roles, probably eventually every role. But we are still in this situation where lots of employers would see using AI in the process as cheating. But then it's like how do we assess the ones AI skills in that case? So it is a really interesting, it's kind of a really interesting time from that perspective, isn't it? It is because on one level you can say, well, first of all, there are some great examples out there of organizations just being very explicit with candidates on where they either are okay with the candidate using AI during the recruitment process, where they actually encourage it, especially if it's obviously a technical discipline that they're recruiting for, and where they absolutely prohibit it. For instance, in the assessment process. But even there, I think we have to ask, we're certainly guiding our recruiters to ask, is the use of AI during the recruitment process, a demonstration of that potentially super-powered employee, right? Will that be, is that part endemically of the job that they're recruiting for so that when they see a candidate demonstrate it, it's positive versus, is the candidate trying to give an impression of themselves that is inaccurate? And that wraps back around to how the job specification is being flushed out from the role, right? We were certainly seeing the levels of AI fluency, AI literacy, the impact on AI of a job, becoming an articulate part of the job specification itself, right? Because that's what's going to allow that recruiter, that hiring manager to understand better when they see the use of AI by a candidate, is it something that's net additive, that makes them a better candidate for that job, or they trying to gain the system or what combination those two things exist? But it's become a very fine-grained conversation, it's not a black and white anymore. It was for a little bit, it was, "Oh, are you cheating with AI or not?" Everybody was using AI to create a job spec, they're excuse me, they're CV, we're kind of past that in a lot of ways, that's almost assumed. Now, is that demonstration of AI detectable, and if it's detectable, is it a force for good for that candidate to the extent that they're being evaluated against a job spec, or are they actually trying to give a perception of themselves that's inaccurate? And I think the thing that fascinates me is where this is all going, because you have AI on both sides of the process, I really think that the candidates are setting the pace here compared to many employers in terms of using AI in this kind of context. Where does it get us to? Does it get us to a point where the candidates have their own job agents running job searches, the employers are using teams of AI agents to recruit, and AI is just talking to AI? Where do you think this goes? I think you're going to see automation, well, no, I think we know, you're already seeing automation on both sides, right? So to your point, candidates are using it to do large scale applications to jobs, which isn't helpful to the early stages of recruiting funnels for the hiring managers. We had one client comment that just to some extent, the efficiencies that they've gained from automating the front end of sourcing and search strategy and the like are being offset by just the sheer number of candidates are at the top of the funnel. So I think that's real, but we'll likely smooth out. I think the question of the use of AI during the evaluation of a candidate process, whether it's from assessments or interviews or, you know, code tests or whatever the topic of the job may be, is going to have to find its equilibrium between demonstrating that this candidate is, you know, a super powered employee and that's a good thing versus trying to to game the system. But I think if this happens, the way we all wanted to, we're going to over a period of time, kind of reset the expectation of what a candidate who is effectively leveraging this incredibly rapid evolution of technology, and what that candidate can then apply to the organization that's evaluating them for work. I think if we do this right, it's an incredibly powerful indicator of that kind of next generation of super power and employee. Yeah, absolutely. And what do you think this will do to the recruiting process ultimately? I think at some point it's just going to be automated to the extent that the elements that matter those interactions with the recruiter between the recruiter and the candidate that are very human. We comment all the time that a senior level recruiting, there's a moment where a great executive recruiter looks across either a table or a video conference into a candidate's eyes and says, "I know you're really happy where you are, but I think I have the next great opportunity for you to come with me and I'll change your life." I mean, it's a little bit overly dramatic, but that's what happens with great executive recruiting. And yet for higher volume recruiting at earlier stages of somebody's career, most typically for whatever reason the industry, no, not for whatever reason, for cost purposes, the industry is trying to automate itself much more highly, first touch to first hire you here being thrown around a lot. And you could ask, well, is there an opportunity for us to take that great moment that happens in more senior high touch levels and make that a moment that happens to as many people as we possibly can, regardless of where they are in their career? I think that's what happens when you automate all the process of recruiting and let that human recruiter to candidate moment really shine through. That really is the direction of travel that we need to be going in. As a final question, I just want to reflect back to what we were talking about at the beginning, which is just how quickly everything is changing, multiple announcements every day, two week development cycles, all these kind of crazy things. What's your advice to TA leaders or indeed anyone in the industry in terms of being able to keep up with this and getting a sense of a real sense of what's going on and what's possible? I think that's a really important question because the pace of this transformation is not flattening right. If anything, it's continuing to accelerate. So I think if you are a talent acquisition leader, you need to be prepared to shorten planning horizons, making three-year plans on anything right now in this space is pretty hard. Be prepared to learn, to experiment, to fail multiple times before one day there is a model shift or a model update in that great idea you had about automating as part portion of the funnel, all of a sudden works. The ability to be resilient and keep working at the ideas that you know will improve and transform your pipeline processes, keep at it. Even the converse, things that succeed and provide tactical improvements to the way you source or interview, you still need to go back to them. Those items, every couple of quarters at least, to understand how the technology is continuing to advance and how it can continue to improve your TA processes. So the biggest piece of advice for giving our clients is to be extraordinary resilient, be ready to pivot and evolve on a much more rapid pace than any of us have had to historically on technology driven transformation. If this is to the extent that we do that, we can continue to take advantage of the technology advancements as they do. And honestly, I think the view of that organization to candidates is impacted positively. Most candidates you know want to see, innovate, want to work for an innovative organization. So I think that even plays to the employer value proposition at some point. Brian, thank you very much for talking to me. Absolutely. Great, great, thank you for having me. Look forward to talking again as this continues to evolve. My thanks to Brian. You can follow this podcast on Apple podcasts on Spotify or wherever you listen to your podcasts. You can search all the past episodes at RecruitingFeature.com. On that site, you can also subscribe to our weekly newsletter RecruitingFeature 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. [Music]