When AI Outpaces the Org Chart: What HR Needs to Know

Julia: Welcome to a new season of L&D in 20, Go1's podcast for HR people leaders building workforce capability and compliance in a rapidly changing world. This season explores a major shift in the role of learning and development and what it takes to prepare for the future. Across 10 episodes, we're exploring everything from managing fragmented systems and training programs to helping organizations build skills, navigate change, strengthen compliance, and lead with confidence.

You'll hear from industry voices, customers, and subject matter experts on what it takes to make learning more personalized, connected, and aligned to the realities of modern work. From compliance and governance to AI, skill growth, capability building, and business impact, L&D in 20 helps HR and L&D leaders simplify complexity and create stronger outcomes for their people and organizations.

This is season three of L&D in 20.

Welcome to L&D in 20, your go-to resource for practical conversations on workplace learning, workforce capability, and business performance, brought to you by Go1. I'm your host, Julia Nieradka. Each episode, we sit down with leaders from across HR, L&D, and business to unpack what it really means to build skills, strengthen compliance, and lead with confidence in a fast-changing world.

Because today, workforce capability is bigger than just learning alone. Today on the show, I'm very excited to be joined by someone who needs little introduction, our co-founder and CEO, Chris Eigeland. Over the past years, we've heard a lot about AI and the impact it may have on jobs and productivity. But increasingly, organizations are realizing the bigger challenge isn't just adopting new technology, it's about adapting how they work, how we operate teams, how managers lead, and how organizations develop capability at scale.

Today, we'll explore what that transition looks like, what it means for workforce capability, and how HR and L&D leaders can help their organizations prepare for what's next. Chris, welcome to the show. 

Chris Thanks for having me. So pleased to be here. 

Julia: Awesome. Welcome back. It's been a little while, but we're really happy you're here, and so let's dive right in.

There's been a huge amount of discussion about AI tools, as you know, Chris, and productivity over the past two years. What do you think organizations are only just starting to realize about the broader impact AI will have on work? 

Chris: It's been a massive year, I think, in the speed at which technology's moved, and then also the speed at which organizations have had to move. And I think broadly what I would say is, you know, a year ago we were all talking about ChatGPT and prompting being the most important skill. Now what's happening is that sort of AI is moving from a tool set that helps you do your job a bit better and a bit faster and maybe a bit more productively- to the whole operating layer of the organization.

And so I think the organizations that are on the front foot and more progressive around that are the ones who've realized that and are leaning in, kind of re-architecting the whole operating infrastructure of their organization, which is a very big task. But that's absolutely gonna be the next shift.

Julia: Absolutely. And I think the ones that are doing it well are going to see that in, in results, and I'd be really interested to know what are some of the earliest signs you're seeing that organizations are beginning to adapt? 

Chris: Yeah. So I mean, generally it shows up in one or maybe two ways. So the first is it always shows up in, I think, workflows and activity before it shows up in org chart.

So, you know, think of go-to-market, for example. I think some of the most adaptive progressive organizations here have built, you know, very strong go-to-market augmentation agents that help their account executives and CSMs better understand the customer needs, the customer feedback, the product feedback, map it all together into a, you know, like a beautiful synthesis to help them manage the customer better.

And very often, that type of tool, I think, will be built and some of the behaviors will change before the kind of formal organization structure actually keeps up. Because if you think about then what a go-to-market organization will look like in the future, you'll have go-to-market engineers. You'll absolutely still have account executives and CSMs, but chunks of their role will either be automated or shift across to other functions to allow them to focus on the very sort of human judgment elements And so you can definitely see it show up in how people are behaving and how some of the key activities are being done before generally I think we all catch up in, like, how we structure the organization formally. 

Julia: Do you think that organizations and that AI will change the shape of organizations faster than they're prepared for? 

Chris: Yes, absolutely. Uh, definitely for those organizations that want to lean in and be at the forefront of this change, but I think in somewhat surprising ways, and I think also in a couple of dimensions.

So the first is that agents themselves are becoming an audience for products and people. So if you think of historically a software engineer would read API documents that a company publishes on the website, you have some organizations like Stripe that now get more traffic to their APIs from agents than from people.

So the way in which you have to think about your product audience is changing, and how do you build for an agent-heavy environment? And then on the, um, sort of, like, people side and in, within the, within the organizational context, I think it's quite clear that the role of kind of the manager in an organization is gonna transform very dramatically to, I think, build a faster, more curious loop of, like, actually how work gets done and how much the team can deliver.

Julia: Yeah, and I guess on that topic about how AI is going to change leadership and management, what sort of practical changes do you expect to see? 

Chris: So this will be a bit of a process. Uh, you know, it obviously will not happen overnight, but I think you can look at a series of AI native organizations to get at least a bit of a flavor for the direction of travel.

And so certainly things that I believe are, organizations will become flatter with a smaller amount of hierarchy because proximity to first party data is so important. And now with AI tools, it's very, uh, much more possible to get, even if you're sitting in my seat, in the CEO seat, lots of rich first party information about our customers and how they're behaving without needing to go through multiple chains of management.

So the organizations will get flatter, which means spans of control will increase. You know, some organizations are now targeting 1 is to 20 in terms of manager to sort of IC ratio. A lot of organizations are now targeting at least 14, 15. And so if you think about, well, what's the reality of why and h- what that does and how that changes the role of a manager.

So a lot of the execution is therefore augmented via several sort of different AI infrastructure components. There's a very high throughput of work, and then the manager's role is really one that's very on the tools, helping their team make judgment calls and very human creativity-based decisions on what should be done, how it should be done, where the quality bar is.

And so I think it changes the role of a manager from needing to, like, check in weekly on, "Hey, did we make this progress and that progress and blah, blah, blah?" Actually, oh, I know where all this is at because I've got the visibility. Help me solve the most, like, uniquely problem, uh, unique problems that you have to solve at the moment.

Julia: What do you think that does for the relationship between the manager and the teams over the next few years and how they'll interact long term?

Chris: So I'm pretty optimistic about this. Like, I think it has the potential to, uh, shift the manager IC dynamic, which I-- from one that I think is unfortunately quite typical in organizations, which is kind of like a task check-in, to-do list check-in dynamic to one that's actually based around, um, as I was saying, the hardest, most interesting problems to solve.

And would you rather spend your time with your manager, you know, going through your to-do list and did you check off these tasks and how are we progressing against these, you know, goals? Or would you rather spend it on saying, 'I have this really tough customer who really wants to do these really interesting things.

I don't know how to solve it,' and like how do we get into that together using, I think, like a really core part of like human judgment, which I don't believe is gonna go away. So I think it has the opportunity Whilst you might think, you know, widening spans of control may, I think, have a negative impact on the manager sort of individual relationship, I actually think it can go the other way.

Because when you do spend time together, uh, it's on much richer, deeper, interesting problems than maybe ones you're spending time on today. 

Julia: Yes, and I think this sort of debunks the, the thought that some people may have, and some of our listeners may have, that AI is going to make managers obsolete in, in full.

And I think what I'm hearing you say is that in a lot of ways, it's... AI is sort of making managers more important, and the value that they create will therefore then change. 

Chris: It is. So that, that is true. It will make managers more important because that, again, that human judgment and element... You know, when, when you can do a lot of things, which of course all of our throughput is sort of increasing with AI tools, that's not in and of itself a good thing.

You have to pick the right things to do. You have to exercise the right judgment and the right learning loops to then ensure that you are building, executing on the right things. And I view that as being something which will be elevated in terms of the role of a manager, but it will be very different.

And there still may be actually fewer managers in an organization because of the flattening of the organization, but I think the skill set will evolve so that it's a much, yeah, richer, arguably more like human, you know, relationship than some of the dynamics today in the workforce. 

Julia: Absolutely, and I think just going back to skills, I always like to go back to how this ties into our skills.

And I think the key skills that I know you look for in a manager around vulnerability, curiosity, resilience, critical thinking, all of those skills really become now even more important in this conversation and, and moving into the future with AI. 

Chris: Yeah, the technology is moving much faster than a lot of our skills and capabilities, and will continue to move faster than I, than sort of how quickly I think we can upskill and reskill kind of the workforce.

There's also a lot of hype, which is hard to cut through. So in that environment, what are the things that really matter? It's humility to understand what you do and don't know. It's fast execution. Uh, it's fast learning. It's really like, being honest and authentic around, "Oh, this really worked," or, "This didn't."

And how do you go on those, like, learning loops as quickly as possible? And, like, that's gonna be the skill set that, uh, I think wins the day for, for companies who are going on this transformation. 

Julia: Yeah, absolutely. And I think, I know from speaking from my own personal experience, I, I hear a lot of times customers, for example, requesting- courses on AI.

And while I think it's great to have c- lots of courses on AI and learn AI and how to, how to build an AI, I think those other capabilities are extremely important as the pillars for building people up within an or- an organization. So what other capabilities do you think will be most important moving forward for the workforce and organizations to build?

Chris: Yeah. So it, it is probably the most important moment in upskilling and reskilling, certainly in my lifetime, and I suspect in the next 20 or 30 years. And as I said, it's moving incredibly fast. So I think you have to do, you know, like, two things to meet the moment for capability building So you have to provide the right sort of learning materials and meet learners where they are in the context of which they operate in.

So, I mean, our own research says that I think like 7% of people actually go to their learning system as their first port of call when they want to learn something. No one wants to remove themselves from their current flow of work, jump into another system, log in, do 12 clicks or whatever to learn the, the next bit of the skill that they have to learn to do their job better.

So you have to provide learning in the context of where people are, and that has to be personalized and relevant to, you know, where they're operating, the company values, the company policies, the direction of travel, what an individual likes to learn. So there's very practical elements of how do you do this in a way that kind of meets the moment.

And then you have to, I guess, tackle the cultural elements, as you were saying, of, like, experimentation and, you know, comfort in admitting that you're wrong and trying to cut through the hype. And maybe you do 12 AI experiments and only two of them work. I think people should take comfort with that's very normal.

You know, no one is trying to rebuild the capability of their workforce and rebuild their organization operating model and getting it right every time. In fact, I think it's like a two out of 10 ratio. It'll be somewhere, like, in that realm. So that's why the cultural elements are so important, 'cause you have to be willing to, like, lean into that failure rate and figure out what works.

Julia: What do you think are some solid first steps that an L&D leader could take right now, Chris, in your opinion, if they're feeling a bit overwhelmed by all the goings on in the world right now and with AI specifically? 

Chris: Yes. Which, first of all, they should feel comforted that they're not alone, and the world is moving so quickly that that feeling is shared across many in the industry, in fact, I'd say the majority.

So you're not alone. You know, there are two really straightforward things that you can do to, to start the journey. Number one is provide a baseline level of system access and knowledge and skilling on the basics of AI skills. You can tackle prompting. You can tackle kind of the basics of what an LLM is, get people comfortable with, you know, actually interacting with a, a large language model.

There's still a lot of fear around them as well, and the best way to, I think, mitigate fear is to understand them and then try them. So provide some of that very contextualized, personalized learning to get people to a baseline level of comfort and knowledge, which is not gonna create experts overnight, but it's getting people from, like, zero to one.

And the second is- This is all about people at the heart of it. And so find your highest performing people in the organization who are absolutely excellent at their jobs. Find the best AE, the best CSM, the best accounts payable person in finance, and then start there. Look at the workflows they're doing, and figure out which components of that can be automated and which components of that need to be rethought completely.

And don't try and do 10, just pick one or two, and the combination of that epic subject matter expert, plus a little bit of process and technical expertise, plus rapid experimentation, will get you to one win. And once you have, like, one win and one demonstrable success, then you can kind of go broader. But don't try and tackle the whole ecosystem.

There's too much complexity and noise, and it's very challenging when the hype is still real and you're trying to find the path through. 

Julia: That's fantastic advice for our entire listening audience, and I think if there's one thing you'd want our listeners to walk away from today's conversation with and remember, what do you hope that it is?

Chris: So we've absolutely moved from AI as a tool from helping me do my job better to AI becomes the kind of operating infrastructure of the organization. And therefore, the future of capability building and capability excellence in an organization is how kind of humans and agents interact, how work is delegated, and how do you maximize the really, really important components of, like, judgment, creativity, customer centricity.

How do you build that operating system together? And building that will not be something that happens overnight. It will take arguably several years, but just start the journey and you'll, you'll, you'll get a couple of wins under your belt. 

Julia: All right. So Chris, we always finish the show with three quick fire practical questions.

Are you ready? 

Chris: Absolutely. 

Julia: Awesome. All right, so the first one is, what's in your feed? What is your go-to spot for practical HR and L&D advice? 

Chris: So right now, I think the place for practical go-to L&D and HR advice is actually looking at how other teams and departments work, particularly engineering and product.

So right now, I'm going deep on some of the greatest product leaders, I think, of our generation, Brian Chesky from Airbnb, um, as an example, and how they work, 'cause I think more of L&D and HR will be influenced by how product thinks in future and how engineering thinks than currently the historical view of HR and L&D.

Julia: And who's at your table? At this time of rapid change, who do you think is a key stakeholder HR and L&D leaders should partner with across the business, and why? 

Chris: Absolutely sort of the engineering and technical side of the organization. That's where a lot of the technical strength will come. Also, your, your best ICs.

So don't get caught too far up here in the strategy. Go down the organization to your best ICs. Figure out how they work, 'cause that's where the opportunity will be to enhance that across the whole organization. And then ultimately, you know, you do need the support of kind of your CEO and executive team, 'cause this is both a skilling journey and a culture journey, and the culture journey starts at the top.

So your CEO and executive team needs to be brought in. And it also may be scary for them as well, like, moments of transformation are not easy, and they will also need to learn to work in an AI native way, which may be challenging and, you know, as I said, be a bit scary for them as well. 

Julia: And lastly, what's the feeling?

Finish this sentence for us: at its best, learning at work should feel... 

Chris: Like momentum. I think we're in a moment where learning should be where you are, contextualized and personalized to you, should feel easy, and it should just immediately help you do your job better and get more done. 

Julia: Amazing. Chris, thank you so much for that.

Thank you for coming to the show again. We always love to have you. 

Chris: Thanks for having me. It's been a lot of fun.

Julia: Thanks for tuning into the show. I'm your host, Julia Nieradka, and that wraps up another episode of L&D in 20. To continue the conversation, send me a message on LinkedIn through the link in the show notes. Your comments will help inform future episodes, and who knows, maybe we'll even answer some of your questions on the show.

We'll catch you on the next episode, and until then, keep learning