There is a lot of pressure on talent acquisition to adopt AI, and the discussion about how to do it tends to focus on tools and skills. With layoffs attributed to AI in the headlines, the people in TA teams have good reason to feel anxious about the technology they are being asked to use. That anxiety makes people less willing to experiment, and addressing it has less to do with the technology than with how leaders handle uncertainty.
So what does it take to move a recruiting team from anxiety about AI to confidence in using it?
My guest this week is Jennifer Rozon, Division President of McLean & Company, a global HR research and advisory firm whose recent research looks at leadership and AI transformation. In our conversation, Jennifer explains what is driving AI anxiety, how leaders can give their teams the confidence to experiment, and the risks of relying too heavily on AI and cutting entry-level roles.
In the interview, we discuss:
- What is driving AI anxiety in the workforce?
- Why AI anxiety should not be mistaken for resistance to technology
- Leading through uncertainty when you don’t have all the answers
- How leaders can give their teams the confidence to experiment
- How structures, incentives and culture can work against leaders
- What is cognitive debt and why does it matter?
- What happens to future leadership pipelines when entry-level roles disappear?
- Redesigning entry-level roles around the work AI creates
- Why current experience is becoming a less reliable basis for hiring and succession
- What does the future look like?
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Key takeaways
- Anxiety about AI is not necessarily resistance to the technology; it can be a normal reaction to uncertainty about what AI means for people’s skills and jobs.
- People who feel anxious or overwhelmed by AI are less likely to experiment with it, which undermines adoption across the organization.
- Leaders can reduce AI anxiety by acknowledging it openly, giving people permission to experiment, sharing what is being learned, and being clear about what will and will not affect roles.
- Cognitive debt is the gradual weakening of judgment and critical thinking that comes from handing too much thinking to AI, and it is a particular risk for early-career employees.
- Entry-level roles should be redesigned around the new work that comes with AI rather than eliminated, because they are where future leaders build experience, judgment and organizational knowledge.
- As roles change faster, experience in a current role is no longer a reliable basis for hiring and succession decisions; what matters more is whether someone can learn, adapt and make good decisions under uncertainty.
Transcript
Matt Alder 0:00
TA leaders are expected to set the direction on AI while the technology keeps on changing. Their teams want to know what it means for their jobs, and much of that is still unclear. So how do you lead people through a change when nobody has all the answers yet? Keep listening to find out.
Advert 0:19
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Matt Alder 1:50
Hi there, welcome to episode 830 of Recruiting Future with me, Matt Alder. TA leaders are under pressure to bring AI into their teams, and the discussion about how to do that tends to focus on tools and skills. With layoffs attributed to AI in the headlines, the people in those teams have good reason to feel anxious about the technology they’re being asked to use. That anxiety makes people less willing to experiment, and addressing it has less to do with the technology than with how leaders handle uncertainty. So what does it take to move a recruiting team from anxiety about AI to confidence in using it? My guest this week is Jennifer Rozon, Division President at McLean & Company, a global HR research and advisory firm whose recent research looks at leadership and AI transformation. In our conversation, Jennifer explains what’s driving AI anxiety, how leaders can give their teams the confidence to experiment and the risks of relying too heavily on AI and cutting entry-level roles.
Matt Alder 2:56
Hi Jennifer and welcome to the podcast.
Jennifer Rozon 2:58
Hi Matt, thank you for having me.
Matt Alder 3:00
Well it’s an absolute pleasure to have you on the show. Please could you just start off by introducing yourself and telling everyone what you do.
Jennifer Rozon 3:08
I’m Jennifer Rozon, Division President of McLean & Company and in my role I oversee both our commercial teams as well as our non-commercial folks, our analysts, advisors and the teams that run all of our research, learning solutions and diagnostics programmes. And if you’re not familiar with McLean, we are a global HR research and advisory firm. So we help HR and executive leaders with research to help them make decisions, give them direction on what to act, expertise to deliver their top initiatives for the year at their respective organisations.
Matt Alder 3:43
We’re going to be talking about AI transformation. And before we get into that, I just had one question that I wanted to start with, because I think that when we sort of talk about AI’s impact on the workforce and transformation and how it’s changing, the one thing that comes up more than anything else is anxiety, like levels of anxiety. What are you actually seeing happening with employees on the ground when it comes to AI and any anxiety it might be causing people?
Jennifer Rozon 4:09
Yeah, definitely. This is coming up with our members all of the time. And what we’re seeing is that it’s not typically due to one single issue. So there are several pressures that employees are seeing all at once right now. So the strain can come up from keeping up with the technologies that are evolving very quickly and feeling like you need to keep on top of those. But there’s also significant change fatigue happening. And in our recent trends research, we found that only 12% of respondents reported that they weren’t experiencing change fatigue. So that means the vast majority are. So on top of that, they’re worried about what will AI mean for their jobs, they’re concerned, you know, will my skills become obsolete? Will my role be eliminated as AI becomes more capable? And so when employees feel this overwhelm, they’re feeling uncertainty. And what happens is then they’re less likely to experiment and adopt new AI tools, which is ultimately going to undermine organisational AI adoption. And so every day we have employees saying, you know, two competing thoughts, really. If I use AI, this could make me better at my job, but this could also make my job disappear. And so the problem is a lot of organisations are managing the technology while very few are actually thinking about this tension that we’re seeing. And if we’re being honest, I mean, leaders are feeling that as well, too. We’re expected to lead the conversation about AI while everything is still evolving. We’re expected to have answers to questions that we don’t yet have answers to, build strategies around capabilities that are changing constantly, and help others navigate uncertainty while we’re, frankly, navigating it ourselves as well. So what we have is both opportunity and uncertainty arriving at the same time, creating this AI anxiety, and it isn’t necessarily resistance to the technology because it can also be human in response to uncertainty. When employees feel uncertainty, their brain doesn’t treat it as just a change. It could be seen as a threat. And so when we’re in threat mode, performance is going to drop, learning will slow, and people move into kind of protection mode. And so the goal isn’t even to entirely eliminate that anxiety, but it’s to understand the human experience, move people forward. And so the good news is that a lot of the same leadership behaviours we’ve relied on through every major transformation, we simply need to be using those here as well, very intentionally. Acknowledgement, reducing uncertainty, building confidence and turning that fear into dialogue, allowing people to be willing to embrace it. Acknowledgement creates that trust, creates willingness to create adoption. I mean, I think the first thing as well is normalising experimentation with AI. We know AI improves through iteration, but most organisations are still wired to avoid risk and not learn through it. So there’s this hesitation. As I mentioned, people are worried if I go and use AI, am I actually going to make my role redundant in front of my own boss? We’re all doom scrolling the headlines. So that’s real fear underneath that hesitation. But then layer on top of that, if something goes wrong with the output from the AI, there may be consequences to that as well. So both of these things compounding, creating this AI anxiety where people are holding back or avoiding using the tools altogether. So our job as leaders is to help remove that fear, not pretend it doesn’t exist. We know it exists. But be clear about where the company is heading. Make sure everyone gets it. Remove those fears through permission to try, visibility into what’s learned through AI use. And then most importantly, clarity on what will and won’t impact roles at the organisation.
Matt Alder 8:12
Now, you just published a new piece of research called Designing the Leadership Ecosystem for AI Transformation. Tell us about the thinking behind that as we sort of talk more about leadership.
Jennifer Rozon 8:24
Yeah, so I think what we’re seeing is that there’s a lot of focus on the tools themselves. And one thing we know is the tools will keep changing. First, I think ChatGPT was everybody’s best friend. Now, Claude seems to be the hottest thing in the room. I’m sure a year from now we’ll be using something we haven’t even heard of yet. So there’s some focus on the tools and then there’s focus on the skills and leadership skills themselves. But when we talk about preparing leaders for AI transformation, if we’re too focused on those two areas, we’re missing another part of the equation. And while those pieces are critical, the leaders also need the right organisational structures and environment around them to succeed. And so that broader environment we’ve called the leadership ecosystem. And it includes things like how work is done, how decision making is structured, what leaders are measured on, rewarded for. And leaders can only be as effective if the environment around them is set up to succeed in an AI-enabled world. And so our research found five key leadership ecosystem enablers. Those are organisational design, performance drivers, leadership pipelines, leadership development, and culture. And so it challenges HR and leaders to rethink about the readiness, not just as the individual skills capability and the tools, but also the organisational level design challenge. And a lot of organisations, they’re kind of working against three or four of these without even realising it. So if we kind of look at each one, one by one, organisational design, are their structures actually built for the speed AI requires? Or are they still using the structures they’ve always had in place? Performance drivers, are they rewarding the behaviours they say they want? Or just the ones they’ve always had five, ten years ago? You know, have those shifted? Are they building leaders for the jobs that exist today or the ones that existed previously? And then on the development side, are they helping develop leaders, execute what they already know or learn what they don’t? And then lastly, culture is a big one too. Are they giving leaders and employees genuine permission to experiment? Or is it quiet, you know, the culture kind of quietly telling people to play it safe. And I think we’ve all done that where we get something that’s so obviously AI generated and all of a sudden we’re Judge Judy, we see the AI, we see the robot. And so that will kind of manifest its way through the culture as well. And so all of these together can really restrict leadership effectiveness in an AI-enabled world.
Matt Alder 11:12
Yeah, I think it’s just incredibly important because I think so many organisations still see AI as a technology issue or a technology challenge. So really putting it into the context is important. Now, there’s a huge amount that we could dive into there. But just to sort of pick out a few things, one thing is you talk about cognitive debt in the report, which is something that I’ve seen referred to in a number of different places. Talk us through what that is and why it actually matters.
Jennifer Rozon 11:41
Cognitive debt is what happens when people repeatedly hand over too much of their thinking to AI. And over time, that’s going to weaken very critical skills like judgment, reasoning, critical thinking. So it’s kind of that gradual decline in critical thinking, judgment and reasoning that results from offloading too much of the mental effort to AI. And that will affect quality of decisions, problem solving, creativity, idea generation. And it’s especially concerning for early career employees, because if they rely too heavily on AI and the output that they just immediately get, they’re not going to be developing those foundational critical thinking skills. And they may miss that opportunity to build that judgment early in their career. And then we layer on top of that AI’s tendency to be very agreeable with all of us rather than challenge ideas. And that further risks reinforcing this bias and reducing employees’ exposure to different viewpoints. You know, I was talking with my son a while back. He’s 11. He’s going into sixth grade this year. And I was asking him about this and about reliance on AI because we’re constantly getting, you know, stuff from school that says the kids can’t use AI to, you know, do their homework, right? And what was interesting is he actually brought up the calculator analogy. And I mean, you might remember this, but I know growing up, we would groan and like, why do we have to learn the maths by pencil and paper? Why can’t we just use the calculator? And teachers would say, oh, well, you know, you’re not always going to have a calculator in your pocket. I mean, now we do. But what he got was actually interesting is that the teachers weren’t wrong, but they were solving for the wrong risk. And the danger being not understanding the maths well enough to use it properly in the first place, to know what to ask it, to know if what you got even made sense. And so it’s the same thing with AI. It’s in our pocket every day. But the judgment to know what to ask it, to know what are the hardest business problems I can solve with it, build that out, and then whether that output actually makes any sense, that’s all still the skills that we need to continue to develop. And the key point being that the problem isn’t AI itself, but cognitive debt becomes a risk when organisations introduce AI without being deliberate about where that human judgment still matters. And this ultimately is a workforce and work design issue, being clear around guardrails for when you should use AI and where the human judgment still remains central and how that critical thinking will continue to be developed amongst your employees.
Matt Alder 14:23
Just to zoom in a bit more about entry-level jobs, because obviously you mentioned there, overuse of AI, people not building up foundational skills. But in some organisations, the situation is even worse because they’re cutting back on entry-level jobs. Now, that could be because of AI, it could be because of the economy, but it’s certainly happening. What happens if organisations just get all of this wrong when it comes to getting new talent into their business?
Jennifer Rozon 14:47
Yeah, and certainly this comes up a lot. And we’re seeing AI take on sort of those routine tasks that you might see through entry-level jobs, but even more advanced stuff as well. And if we think about early career employees, they bring fresh perspectives, strong digital fluency, willingness to question how things get done, and an ability to drive innovation through doing that. And so without them, we risk losing that kind of very important source of new ideas and innovation. They also, entry-level roles is where we all began to build our experience, our judgment, our organisational knowledge that we need to then take on more senior positions later on. So if those roles disappear, where are we going to hire the future leaders from? We might all be looking to do that externally, but then we’re all going to be trying to hire externally from each other, right? So leaving, and that also leaves us with less institutional knowledge that’s been built up through the organisation. So the answer is not necessarily to preserve entry-level roles exactly as they are today, but redesign those roles. It just changes the nature of the early career work. And one way to think about it is to design those roles around the work AI creates, not the work it replaces. So all of those things that I talked about earlier, about bringing judgment and so forth, those entry-level roles are now folks that could be making those calls today at the entry level. It also impacts succession planning because before, you know, we would look to hire someone based on current experience in their current role. But as roles are evolving faster than ever, we can’t rely on that anymore. So what matters is whether someone can learn, adapt, make good decisions in uncertain environments, and focusing on those entry-level roles to develop those future capabilities that we’re going to need, adaptability, critical thinking, ability to lead through change. So the notion that entry-level roles will become obsolete is a bit short-sighted, because every technology shift has redefined, not completely erased that entry-level work. So ultimately, the risks would be reduced innovation, weakened leadership pipelines, and also impact to the culture. So it’s about redesign rather than eliminate.
Matt Alder 17:13
What’s the broader impact on leadership? I mean, what does leadership development need to look like in the AI-enabled world that we’re rushing into?
Jennifer Rozon 17:23
I think that if we look at historically, leadership development tended to be very classroom-based, once a year or scheduled learning. And while that’s still very much an important part of it, what we’re seeing is leadership development becoming more continuous, personalised, and integrated into the flow of work. And so allowing leaders to pull the guidance in the moment alongside those structured learning opportunities that also play an important role. And then on top of that, reinforcing through everyday practices like feedback, coaching and performance conversations with their manager. So all of this helping leaders keep pace with changing demands and leaders really need the right input at the moment they’re making a decision. So they need to be able to tap into micro learning options or on demand options and help them build capability as they go, as needed on demand, rather than, you know, those kind of longer term structured training that still plays a valid role, but is becoming less reliant on that as work moves quickly and we find ourselves in this AI-enabled world.
Matt Alder 18:36
Now, I know that a lot of HR professionals are just feeling kind of overwhelmed by all of this and everything that’s kind of going on. And there’s huge pressure to develop effective AI strategies. What’s the single most important thing that HR could do right now to move the AI agenda forward?
Jennifer Rozon 18:54
It’s hard to say that there’s ever a single answer for every organisation. But if there’s a single thing that they could do is look across their own programmes and ask, are they reinforcing or inhibiting the behaviours needed for the AI transformation? So you can look at competency frameworks, performance management, succession planning, rewards, and recognition. Are we encouraging innovation, accountability, adaptability, continuous learning, or are we still reinforcing those behaviours that we always have that no longer fit? And then on top of that, HR really shouldn’t be doing this on their own. It’s all about strong cross-functional relationships, especially partnering with their head of IT, bringing the people and workforce perspectives about how AI may change work and roles. But also bringing in the other leaders from those groups, especially the IT department. They don’t have to figure it out alone. It really should be a shared responsibility across HR and IT. We know the AI pressure is not letting up. But the good news is everything I’ve talked about, this leadership ecosystem, it is buildable. And so an effort like this does require org alignment, shared vision, clear articulation and a path to move forward. But there is a path forward and you just have to kind of take that time to look at each of those programmes and whether or not is it serving you for the future that you need in an AI-enabled workforce.
Matt Alder 20:26
And as a final question for you, the impossible question really, which is what does the future look like? I mean, how are things going to evolve? How do you think they might be different in two or three years’ time?
Jennifer Rozon 20:37
Yeah, I mean, a few things we’re seeing in our research. I think many of the skills used in jobs today are likely to shift and change in the next two to three years. AI will continue to let employees take on more complex strategic work earlier in their careers. We are seeing organisational structures shift already from kind of those rigid hierarchies and very fixed rules to things that are more dynamic and adaptable operating models. Decision authority will keep shifting as well to those who are closer to where the work is happening, closer to where that output is occurring. And then leaders’ value will continue to focus on things that are distinctly human. So judgment, coaching, change management, technology will accelerate the execution, but still can’t replace how people adapt, how people grow. And so ultimately, leaders are the key to helping you transform your organisation through AI, and they will only succeed when the system around them evolves. And so that the leadership skills that we’re looking at and what needs to support that growth are all the things that I talked about earlier, is what are we doing to design intentionally to support an AI-enabled workforce? And that’s the skills that we need to look at and continue to evolve over the next two to three years.
Matt Alder 22:06
Jennifer, thank you very much for talking to me.
Jennifer Rozon 22:09
It was my pleasure. Thank you for having me.
Matt Alder 22:11
My thanks to Jennifer. 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 recruitingfuture.com. On that site, you can also subscribe to our weekly newsletter, 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.
