Rethinking TA: Myths, Misalignment, and the AI Reality Check

Chris Hoyt: All right, everybody. Welcome to the Recruiting Community Podcast. I am Chris Hoyt. I am the president of CXR. I’m with Gerry Crispin, who is the co-founder of CareerXroads, and we are the hosts of this podcast that brings you, we like to think, industry insights and updates in the form of a fun conversation. They’re fun for us, anyway. All brought to you by the CXR CareerXroads community.

I’m excited today because we’ve got Christoph from AMS, who’s going to be sitting down with us for a look at where talent acquisition keeps tripping over its own feet and how to get back in sync with what businesses actually need, what those lines of business actually need. We’re going to dig into the idea, and I love this, that entry-level hiring is a myth and why it doesn’t often align with those business needs.

I think it’s safe to say we’re probably going to talk a little bit about the buzz going on in our space with agentic AI. We had a little chat about that in the green room. Kind of fun. We’ll get Christoph’s take on what’s useful and what he thinks is just noise.

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Gerry, are we ready?

Gerry Crispin: Yeah, we’re ready.

Chris Hoyt: Okay. Awesome.

Announcer: Welcome to the Recruiting Community Podcast, the go-to channel for talent acquisition leaders and practitioners. This show is brought to you by CXR, a trusted community of thousands connecting the best minds in the industry to explore topics like attracting, engaging, and retaining top talent.

Hosted by Chris Hoyt and Gerry Crispin, we are thrilled to have you join the conversation.

Chris Hoyt: All right. Welcome, Christoph. We’re really excited to have you dial in today. Thanks for joining us, man.

Christoph Niebel: Thanks for having me. This is going to be fun.

Chris Hoyt: Well, it’s early. You don’t know. It might not be fun.

For those who haven’t had the pleasure of meeting you, why don’t you give us the escalator pitch of who you are? What do you do? How long have you been doing it?

Christoph Niebel: Today, I am the President of the Americas for AMS. We are, what I want to describe as, about 8,500 people strong, a consulting-led provider of outsourced TA services.

I realize that’s a mouthful, but what we do is we are responsible for about 300,000 permanent hires and a couple billion in external workforce spend for a client set of blue-chip companies with over 13 trillion in combined market cap.

I’d say the reason why they work with us is that they’ve all realized that filling jobs fast and cheap is super important, of course, but it doesn’t cut it anymore on its own. What CEOs need are talent strategies that drive real business results, but it is often HR and TA that face the underlying problems in the day-to-day that we address.

Number one, their operating models can’t adapt fast enough. They’re either stuck in rigid, outdated processes or just have really added cost and complexity.

Number two, there’s a massive gap between AI hype and what’s actually deployed. Without the right environment, data, workflows, and, importantly, redesigning how work gets done, AI unfortunately keeps disappointing.

Number three, workforce productivity in many companies is stagnant because they can’t shift the workforce mix to improve expense ratios and reduce risks.

At AMS, that’s what we do. We solve these problems by bridging the gap between talent and shareholder value, by transforming organizations on how they hire, deploy, and manage talent so they can actually fuel growth and ideally prove it in the language a CEO and CFO can understand. That’s what we call people-powered partnership here.

Chris Hoyt: I love it. How long have you been there?

Christoph Niebel: I’ve been with the business for 16 months now, but in the industry globally for the last 20-plus years. I’m German. I’m not sure if that’s really a secret with my accent, but I worked in Australia for about 14 and a half years. I started there with a company called Adecco, in a number of different divisions.

The last job I had there before I moved to the U.S. 13 years ago was running a business called Pontoon Solutions, which is a large-scale managed service provider, MSP, and RPO as well. I’ve also done a lot of work in startup advising and HR tech investing before I started here.

Chris Hoyt: Okay, so you’ve been around the block. You’ve been in the space for a while.

I want to get into this because you have talked about entry-level hiring being something of a myth within TA. Can you break down what you mean by that and maybe where you see the biggest disconnect between what companies say they want and what they actually need?

Christoph Niebel: Yeah. When I say myth, I think it’s the discrepancy between the messages that we’re all hearing out there right now. Let me frame this up.

I’m based here in New York, and just a couple of weeks ago, and you might have seen this article, we saw the IBM CHRO at an event stand up and say they’re going to be tripling their entry-level hiring, including software developers and all the roles everyone’s been saying AI can do.

Now, if you think about that, tripling entry-level hiring is a very different message than when you open the papers and see that all entry-level hiring is going away, because that’s the dominant narrative, that AI is really killing entry-level jobs. It’s really everywhere.

The question is, what if that’s not right? I think that’s a little bit of the myth.

There’s an interesting article from a couple of months earlier by Sarah O’Connor at the Financial Times, and she drew on some data with Lightcast, which basically looks at millions of job ads across about five countries. Her take is that the decline in entry-level hiring is less related to the AI impact and much better explained by rate hikes and economic uncertainty than AI directly replacing people.

It’s interesting because you see that slowdown actually started before ChatGPT even launched. Does AI have an effect? Absolutely, yes. But my contention is that right now it’s more of a vibes effect. Boards believe AI will make their current people more productive, and so they pause junior hiring, or certainly some do. The belief is changing behavior even when the reality hasn’t caught up.

I think that’s the problem because, coming back to the words of the CHRO of IBM, pausing entry-level hiring is actually not a neutral decision. It’s a bet, and she believes it’s a really bad bet. That really stuck with me.

Her argument is really simple. She believes that if you stop entry-level hiring now, where do your mid-level managers come from in three to five years? You’re going to poach them from competitors, potentially at a premium. They don’t know your culture. They don’t know your systems. Then, obviously, they take longer to deliver. So did you really save money? Probably not. You deferred cost and made it bigger.

The thing that really stuck with me, and that probably doesn’t get enough attention, is this: they don’t just want to hire three times the number of juniors. They are rewriting what those jobs are.

An entry-level developer who two years ago spent 34 hours a week coding now spends time with clients, with marketing, accelerating product roadmaps, and the role is fundamentally different.

So to me, the question is not, are entry-level jobs disappearing, but are you redesigning them fast enough? That really struck me as an interesting juxtaposition from the general narrative that’s out there.

I’m not sure whether you see that, or how you think about it. I also have some data from AMS on this.

Chris Hoyt: I find that super interesting. What had not clicked with me until you started to break it down was the dent this puts in future workforce planning from an internal mobility standpoint.

We’ve been talking with organizations for years about really leaning into internal mobility, sourcing internally, building internally. This has been going on, and Gerry, counter me on this, but I think for at least the last 10 years we’ve really been talking to organizations that have structured internal recruiting teams. In some organizations this is a formal function, and in others it’s a little bit of a rogue effort, but the push there is that this is the smarter way to hire.

When you make a bet that you’re maybe not going to need that chunk of hiring, at 30 percent or whatever your mobility number is, I think that’s pretty significant.

Gerry Crispin: I think there’s another issue here too, and that is the assumption that the kids coming out of school next year, the year after, and the year after that don’t know much.

What’s happening to them in college is that their ability to make use of AI is evolving in ways companies will be looking for. I see some of these young people coming into the system being the teachers, if you will, helping the workforce really get acclimated to AI and its ability to change workflow.

Christoph Niebel: I think that is a really important point that is often forgotten. The underlying assessment of what good entry-level hiring looks like is completely changing. Because information and knowledge are being commoditized, it’s a very different aptitude and attitude that we’re looking for now.

To your point, Gerry, it’s about making sure they become accelerators in the business. I’m just speaking for myself here: I’m not AI-native because I didn’t grow up with it. Kids in the future will be.

Let me overlay this with some data points that we see at AMS. We have a fairly large-scale early careers practice, and we looked at about 250,000 data points in 35 countries, which point to hiring levels in early careers being down by 25 percent versus 2023.

But the interesting point, and nothing new for you guys, is that applications are absolutely through the roof. For many companies, applications are up 20 percent or more, and for some blue-chip investment banks we work with, it’s just absolutely insane.

Candidates, to your point about knowing how to use AI, are using it to mass apply. Everything starts looking the same. Fraud is rising. Signal-to-noise is completely going out of whack. The skill gap between what graduates bring and what employers need is widening or, at least, shifting. I think that’s a perfect storm.

What is perceived as fewer roles leads to larger pipelines, a widening skill gap, and a narrative telling CEOs to cut these investments and solve it later. I think that’s a really important point.

We live that. We hired, I think, 25,000 early-career talents last year across about 60 countries. What we see on the ground is that companies getting this right aren’t just posting jobs and hiring for the best. They’re completely rethinking how they attract, assess, and develop early-career talent.

That’s one of my contentions: this needs to be a business decision. What does your board and executive committee think about the future? How do they think about their career and talent strategy over the next three years? How do they think about how work gets done in the future, obviously through the combination of artificial and human intelligence?

I’m not sure enough companies are asking that question. The simpler answer is just to say, “Let me stop hiring this altogether.” The secondary effects are known, and I’m really interested in how that plays out.

Chris Hoyt: I talked to an investor a number of weeks ago, and they’re leaning their portfolios toward anything that is anti-AI. We talked to a company the other day that’s coming up with $250,000 to bring interviews back, to fly people in for finals.

Gerry Crispin: The hiring practices, the standards for hiring practices, are shifting in a variety of different ways.

We have some clients, some members of CareerXroads, who are saying they’ve added back into the budget the ability to make sure that whenever they select somebody, after they’ve gone through the recruiting process and made sure people are real and done everything down to the point where they want to hire the person, that’s when they require the person to actually come in physically and show themselves.

Exactly.

They want to make sure there’s a real person behind all of this. I find that fascinating. Are you seeing adjustments along those lines as well? I would think we’re also telling people upfront that the first thing we have to do is validate that you are real.

Christoph Niebel: Yeah, very much so. I think this is especially true in heavily compliant industries: banking, financial services, pharma. The risk associated with what we just talked about is huge.

There’s also a cultural element. A lot of banks are requiring people to go back to work in the office a number of times, and this is absolutely real.

I’ve come to the point where I almost feel like this is a different way of framing the same thing you said. We’ve always been focusing on taking friction out of the system. How do we make it simpler and all that? I think we are now coming to the point where we purposefully build more friction, in quotation marks, back into the system, because we reached peak non-friction. We’re now trying to counteract that with security and verification elements.

One fraudulent hire in this context can have so many negative consequences. It also has downstream impacts because we’ve always been looking at fulfillment metrics like time to hire. Now, you need to make sure your qualitative outcomes are being adjusted for this new reality, because that’s part of the problem. It will probably take longer because you’re putting another process step into this.

Gerry Crispin: I think that issue around adding friction back into the system is worth exploring.

What it made me think about is this: if I expect a thousand people to apply to something, some of whom don’t even know they’re applying because they’ve got an agent that’s finding jobs and randomly applying, I don’t need a thousand people in order to find one person I want to hire.

If I have some sense that, with a hundred people applying, there’s a 99 percent probability I will find one real person who’s capable of doing this job and wants to do the job, then I need to close the thing off after a hundred people apply. Do something.

Christoph Niebel: There’s absolute truth to that. But I think this gets me onto the track of where we wanted to go anyway, and I think that’s the context of AI, because it has a similar application.

The thought of building friction into the system is maybe not a bad place to be, because we are right now in this faster-horses territory. You know the old quote attributed to Henry Ford: if I had asked my customers what they wanted, they would have said faster horses.

Instead of cars, we are still in the phase of asking what can be sped up through AI, versus really rethinking from the ground up what we can create.

I’m sure you hear this from your members all the time. I was just on a call with a TA leader last week from a global company, a very sophisticated function, and she said something that stuck with me. She said, “My team is absolutely drowning, not even in work, but in noise.”

I knew exactly what she meant because we’re seeing it across many clients. We talked about it already: applications per opening at some companies have surged four to five times, practically overnight. Candidates are using AI to mass apply, but then we’ve pointed the guns the other way around and recruiters are using AI to screen them.

Both sides are effectively losing because, call it the AI doom loop, candidates spray, employers screen, volumes explode, quality potentially collapses, and nobody’s winning.

It’s just one data point, but before this call I looked at some RM data, and they report in their benchmark report that time to hire hit about 68 and a half days in 2025, up from 44 in 2023. I’m not sure if you see something similar, but that’s their data. At the same time, cost per hire went up.

You go, wait, we’ve automated everything, but maybe we didn’t make things better. Maybe we made them worse.

So let me be clear: I’m not anti-AI, but I am anti-stupidity.

We can agree AI works brilliantly in recruiting, but maybe in a much narrower band right now than the hype suggests. I think in high-volume frontline hiring, we’ve seen a lot of success. Clearly defined roles, standardized criteria, where speed matters more than nuance. In that space, the results have been extraordinary: massive reductions in time to hire, huge cost savings, real measurable impact.

But the further you move from that profile toward senior or specialized roles, anything where judgment really matters, I think at this point the weaker the evidence gets and the higher the risk.

One thing that stuck out to me a couple of months ago: I read that OpenAI built a dedicated internal team called Applied Evals. What is that? Their entire job, people paid $300,000 and up, is evaluating whether AI outputs are actually good.

Their team lead said something that should ring in the heads of every TA leader: the art of evals requires real, deep-lived experience and expertise. The team description mentions hands-on, unscalable efforts as a core methodology.

Think about that. If OpenAI needs dedicated humans to judge whether AI is doing its job well, what makes us think a TA function can skip that job?

That’s the insight I keep coming back to. The competitive edge right now is not necessarily deploying more AI, but building the organizational capability to evaluate whether your AI is actually working. Call it evaluation edge or something else, but I think that’s where we are at.

I’d love your perspective on that, through the lens of what your members think. For me, it’s almost like we need to take a step back before we just focus on faster horses.

Gerry Crispin: What you’re really implying to me is a shift in how the organization has to pivot toward much more quality control and oversight.

The ability to assess whether what we’re doing is what we intended to do is a whole different set of skills and structures within, let’s say, human resources. I think the operations group becomes much larger, with a lot of specialized skills to be able to stick their finger into automated processes and figure out whether what we thought we were building is, in fact, working the way we think it should.

I do think that’s going to change the way we staff HR and, obviously, other organizations as well in the future.

Christoph Niebel: Just take the downside scenario of this. What’s the risk? We talked beforehand a little bit in the context of fraudulent applications, but the legal landscape is also catching up super fast.

You guys are familiar with the multiple lawsuits out there right now challenging how HR tech vendors are effectively using AI to make hiring decisions. Courts are starting to rule that these tools aren’t just implementing employer criteria, but that they’re participating in decision-making. If that’s the case, that changes who holds the risk.

I can’t speak for every vendor, but because we also subcontract with vendors in our solutions, I would suggest everyone better make clear on the contract chain where liabilities sit. For example, where do these AI vendors cap their own liability? Is it at monthly subscription fees? Do they really have regulatory compliance? Who is holding the risk?

For tools you cannot fully audit and cannot fully understand, what is the future impact of that? I think that’s another element that doesn’t make this any simpler.

The way we think about it, quite frankly, is that the answer is not “don’t use AI.” Of course not. We cannot stop that train. But how do we actually build an operating framework, whether you do that with a partner or yourself, to orchestrate it intelligently?

By that I mean you need a platform, potentially, but more importantly, a process that routes the right work to the right actor, human or AI. We talked about it. I think the human is super important, based on hiring type, geography, compliance landscape, and the level of judgment required. Not blanket automation, but intelligent orchestration.

Critically, you need to measure whether that is actually delivering better outcomes than the human-only process. You’re delivering to the business, not trying to build a great function on paper. Don’t assume it. Measure it across permanent, contingent, early careers, unified data in real time.

I think that’s what is still missing in organizations. I feel like people celebrate that they deployed an agent or AI somewhere, but they’re not really watching the scoreboard.

The difference for me is this: you can have a competent new hire, and then you have a five-year veteran who actually knows things and understands how they work around you. That veteran’s value isn’t just skills, it’s understanding. Replacing them feels like starting over.

The best AI should work exactly the same way. It should compound. It should get better. It should get smarter about your business over time. That’s the stuff I’m excited about and how we move the industry forward, versus just point solutions.

Again, I’m biased here, of course, but that would certainly be my view.

Chris Hoyt: I think it’s worth a callout to how we’ve seen organizations change how they interview and even encourage the use of AI by candidates, but also change the questions they ask and the responses they’re looking for.

ThoughtWorks comes to mind. We know you’re going to use AI, but get ready in that process. Don’t just answer a question with something that comes out of a prompt. Explain the logic of how you got there. Explain why that makes sense and why it might not make sense. I think that would be a good take.

Gerry Crispin: I think the shift Chris is talking about is how we’re now adapting our interview process so that we don’t ask or downgrade the fact that they’re using AI. Instead, we try to understand how they’re using it and the logic behind how it’s improving what they do. That way, we’re getting a better sense of their capabilities going forward.

I do think one of the key issues we’re going to have to address is right at the top of the funnel. Are we collecting data in a way that doesn’t just lead to garbage in, garbage out? Should we be adjusting the way we collect the data to begin with?

Because we now have an infrastructure with all the ATSs basically collecting it the same way, and fundamentally we’re just making things more difficult. That’s what’s overwhelming a lot of these folks who are trying to figure out who they go forward with. I do think we need a better approach to the beginning of the funnel, or the top of the funnel.

Christoph Niebel: I’m not sure if this is what you’re touching on, but I can see the top of the funnel leaning more and more into pull strategy, because the noise around applicants, especially for the best talent, is becoming so huge.

The friction of reaching out to someone now means they’re overwhelmed. If I think forward on that, employment brand and the ability to establish a real narrative about why someone should join your company versus another becomes the ultimate differentiator, rather than the right mousetrap that attracts them, because everyone will have access to the same tools.

What will the differentiator be then?

I think thinking along that value chain is more and more important. I don’t have the answer here, but to your point, everything needs to feel much more like a good executive recruitment process, if someone is being headhunted.

We shouldn’t be going after hundreds of people who apply. We should identify what matters most. If we are now not in a critical talent mode and we’re hiring fewer people, but they have a higher multiplier effect, then every hire is more important. Therefore, we need to completely rethink what a funnel needs to look like.

That, to me, reshapes it from volume to much more targeted attraction.

Gerry Crispin: I think there are a number of models we can be looking at. You hear a little bit about those today, but I think within the next six months or year we’re going to have many more opportunities to rethink and reshape the top of the funnel.

I do think the companies that move rapidly to embrace that are going to do something that is a lot fairer and more capable for themselves in terms of building the performance that’s going to drive their companies forward.

Chris Hoyt: I want to circle back a little bit because we talked about the function being out of sync. We’ve talked about some of the AI challenges.

Christoph, for TA leaders who are listening, who know that their function is out of sync with the business but aren’t really sure where to start fixing that, what’s your advice? What do you think is the first thing they should actually do?

Christoph Niebel: Let me frame this in something that recently happened, because it really stuck with me.

We had our growth kickoff, think of it as like a sales kickoff, where we brought about 150 people from our organization together. It was in Barcelona. Very nice weather.

What made it really impactful was that we had a client panel. I can’t name the exact clients, but there were a range of CHROs and senior C-level TA and talent leaders. One of them, a leader who was the Chief People Officer of a major insurer, said something that stopped the room.

You’ve got to contextualize this. Many people in the room who work for us have either been TA leaders or certainly contextualize their skill set and value as talent acquisition experts.

While maybe this is not something new in principle, it was really hard-hitting when she said it. Basically, she said, “Nobody on my board at this big insurance company cares about any of your operational metrics. They care about whether sales are going up or down and whether we’ve got the right people driving that. But if you can’t connect your data, which you have plenty of, to business outcomes, you get 30 seconds. That’s it. Ice flows over, and you lose all credibility.”

Now again, we’ve heard that. We’ve talked about business outcomes for a long time. But when she said that, you could hear a pin drop because everyone in the room knew what she was talking about.

Let’s be honest. It brings me back to the idea that when we started to build TA, we built it around fulfillment. The business says, “I have a demand. I need five engineers,” and you get five engineers. You fulfill that.

When you build to fulfill, everything you measure is about fulfillment: speed, volume, cost per hire. But when you’re really honest, the business has zero emotional attachment to it.

Let me be clear, I say this from the position of not being a TA expert. I think of myself as a business leader with a specialization in talent.

What happens, I think, and what I’ve seen happen, is that a TA leader proudly finishes a massive transformation. They drive down the operational metrics, for example, time to fill and cost per hire. The team is running like a machine. They’re proud, and they should be.

But then they find out they’re about to lose headcount, and they go, “Why is that?”

So you ask them, “When you present this achievement to your CFO, what do you lead with?”

Well, time to fill, operational metrics, cost per hire.

And I think that’s the problem, because you’ve told your CFO, “Your cost line just got cheaper.” So you gave them the business case to effectively cut you.

But I think the flip side of this is where the golden opportunity lies, and that comes to your question.

The other reality unfolding everywhere, and we touched on this before, is this: tell me about a CEO who currently doesn’t have some kind of multimillion-dollar AI transformation commitment. Big headlines on the board, timelines locked in, projected returns. Then, as typically happens in transformations, maybe 18 months later the CTO blames change management, the COO says the vendor wasn’t good, and the CFO still wants to know where the gains are.

No one really looks at TA, but that’s where I would go. Because what actually happened is that the company tried to execute a completely different strategy with the same people who were hired for the old one.

That’s not unusual. You see it in McKinsey stats and everywhere else. About 50 percent of leaders say skill gaps are the single biggest barrier to AI adoption.

In a place where everyone’s increasing the spend and no one’s really ready for it, this is the opportunity for TA to step into it and make it visible.

Imagine a different story. The TA leader walks into the transformation kickoff and says, “Before you deploy this platform that you’ve gone through the procurement process for, let me show you the gap between the skills profile we have today and the skills profile this initiative requires. Here are 20 roles that need to be redesigned. Here’s what the external talent market looks like for those capabilities, and here is a realistic timeline for building the team this transformation actually needs.”

That’s where a change in the conversation can occur.

What happens to your projection if we don’t close this gap before go-live? What’s the cost of inaction?

And the TA leader just goes from being a service function to being the person who potentially saves a multimillion-dollar strategy bet.

I think that takes you from a recruitment conversation to a board-level conversation that the CEO maybe didn’t even know they needed until someone connected the dots.

That, to a large extent, comes back to your question. I have some more specifics, but I feel like the mindset around not optimizing for the function but for the business is where this whole conversation should start.

Chris Hoyt: Yeah. What I love about that, Christoph, is that you’re really talking about the opportunity to take advantage of positioning work that’s already been done and work that’s ahead.

When we’re talking about a TA leader having those conversations, it’s not just about being a cost center but actually having an impact on the business and helping to drive some of that change through talent.

Christoph Niebel: Yeah, and I don’t actually think the work has to change per se. Let me be careful. I don’t know that for sure.

There’s another VP of TA at a big pharma company we work with, and she wanted budget commitment from her executive team. Everything had fallen flat. I’m not suggesting this was genius, but she was able to reframe operational metrics that no one cared about into a vacancy rate, and the vacancy rate had a direct correlation to revenue impact.

Once she was able to translate it that way, she suddenly walked through an open door.

The skill set underlying that is really P&L fluency.

What made you good and got you to the role, being an expert in recruitment, may actually hold you back once you get into a senior role. It’s like the curse of knowledge. You’ve learned all those details, but now you need to learn what it means to run the business. Then you can translate the value.

If more people were able to make that leap, I think it would be very powerful in the way they could take the function forward.

Gerry Crispin: It also elevates that business partner from supporting just the hiring manager’s needs to much more than that, in terms of what the hiring manager should be doing as a business leader, to look beyond what they have today to what they need tomorrow.

Christoph Niebel: I’m asking you guys, because you spend probably more time than I do with talent acquisition leaders. My hypothesis is that, because of how they’ve grown up in the function, they often don’t have the P&L fluency. They may not be cross-functional enough. They know their vertical very, very well, but they don’t necessarily know the whole supply chain of what needs to happen across the talent lifecycle for it to make the impact.

They may not be very AI-native in the future, or they might even lack some external perspective. I don’t think it is the recruitment chops that hold people back from being successful.

Again, you see so many more leaders in this space. What is your hypothesis of what is required for a TA leader in 2026 and going forward in this functional context to lead into the future?

Chris Hoyt: I wouldn’t disagree. I think a broader vision and understanding of the lines of business is certainly helpful. I like the line that it’s not their chops that hold them back, and that P&L fluency aspect.

I will say this: this is the first time, and I’ve been doing this half as long as Gerry, so I’m coming up on 30 years. What’s been really interesting is that this is the first time in my 30 years in TA, with AI coming in, that I’ve actually seen TA leaders really lean into their own education and really learn how this new shiny thing is going to impact the business.

I also can’t think of anything that’s been as transformative, or potentially as transformative, as AI in our space, at least in my lifetime of work.

Even though we’ve had a lot of things change and a lot of leaders in a state of perpetual transformation, I would say you’re pretty spot on.

I would also say I’ve probably not seen TA leaders shy away from the chance to step up nearly as much as I’ve seen the senior suite hold those TA leaders in their own lane, so to speak.

Christoph Niebel: That is super interesting because, as someone who’s high agency, I generally believe, rightly or wrongly, that my actions drive an outcome I can somewhat control.

Is that a mindset thing, Chris? Because I generally would agree. Or is this, putting it back on ourselves again, a matter of skill in how to engage them the right way?

Other functions have clearly gotten to the forefront. I’m totally biased because I think talent is, not just as a platitude, the most important part of the business. We need to earn this.

I know we’ve talked about this forever now, but this really is the opportunity right now, because the roles, including HR, are going to get reshaped.

You’ve probably all heard about this concept of a K-shaped economy. People talked about that a lot after COVID. The idea is that if you look at the S&P 500 over the last 12 to 24 months, you see it creeping up 12 or 15 percent. But if you double-click on it, you see it’s really the Magnificent Seven or so that grew by 40 percent, while the S&P 490, the downward K, probably went down 10 or 20 percent.

I’ve started thinking about that K-shaped career trajectory. The vertical line of the K is the starting line. Everyone here is starting at the same point. No one has 20 years of AI experience. So what can we do now, in this golden moment, if we consider that this may be the most important year of your career? What can we do now as TA leaders?

Everyone has access to the same tools and platforms. How do we change our skill set and our mindset to ensure that we are in the top line of that K?

I think about that a lot. I don’t have the answer, but I wouldn’t want us to waste that opportunity.

Chris Hoyt: I love that. The fact that it does feel like there’s been a level set. I hadn’t realized it until you said it, but it does feel a little more like there’s been a reset.

Maybe that explains why we’ve seen more leaders than we historically have raising their hands, doing some self-education, and leaning in on this.

Christoph, we are so grateful for your time today. This is an extended interview, so we can’t let you off the hook, because we’ve got to ask you the question we ask everybody before we cut the show.

If you were going to write a book about the state of things today, what do you think the title of that book would be?

Christoph Niebel: It may not be about the state of things today as much as it would be about how someone has to think about the state of today and behave in this context to be successful.

It would be a self-reflection and, therefore, a personal story that leads into some teaching. It would be called My 50-Plus Failures.

Let me unpack that.

In the nucleus of my own career, and certainly compared to people who are much more successful, if you zoom out it looks like I went from being an individual contributor somewhere in Australia, making cold calls for no base salary, to running a large business. It looks like a line from the bottom left to the top right.

But if you really zoom in, it’s this squiggly line of loops where something works, then I get a huge learning opportunity, meaning I get kicked in the butt, I make a mistake, and I kind of go down in my trajectory. Then I take that not as a failure but as a learning, and that becomes the accelerator into the next loop.

What I figured out is that what seems like a bug, making mistakes, has become the feature of my career acceleration, because it helped me both reframe failure as a learning opportunity and, therefore, seek it out. I try to get out of my comfort zone, where I get challenged, because I know that accelerates growth.

Number two, it has helped me become somewhat antifragile in an environment where we are arguably challenged with what our identity is. If I contextualize myself through the role that I had, and if all of that is changing so quickly, the risk is that people hold on to some identity that might not exist anymore.

So my book would be about how to embrace failure and uncertainty and become resilient in the context of change, because I do think that is a super important meta-skill and capability that we all need over the next 10 years.

Chris Hoyt: I’m all fired up. I just want to follow Christoph anywhere now.

Christoph Niebel: Well, clearly you’d be following me into a lot of mistakes. That’s what you can take away from this.

Chris Hoyt: I love “The Feature, Not the Bug” as a subtitle, though. I love that.

Christoph Niebel: There we go.

Chris Hoyt: That’s great.

Well, look, much gratitude to you, Christoph. We know you’re super busy, and we appreciate you cutting the time out for us today. Thank you so much, man. We really appreciate it.

Christoph Niebel: I really enjoyed it. I wouldn’t mind doing the same thing with you guys, asking you lots of questions. I feel like I have a lot more to learn from you guys than I could share, but maybe for another time.

Chris Hoyt: I think we bring it back.

Christoph Niebel: Look forward to it.

Chris Hoyt: Over a glass of wine. Or two.

Christoph Niebel: Here we go.

Chris Hoyt: One or two.

Christoph Niebel: Or two.

Chris Hoyt: Yeah.

All right, everybody. Thank you so much. Go to cxr.org/podcast for past and future episodes. You can check those out. You can let us know if you want to be part of the conversation. If you think there’s somebody we ought to invite to the show and have them on, let us know.

Until then, we’ll see everybody next time. Thanks, everybody.

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