Frances Kleven: Welcome to another episode of The Learning Signal Podcast. I’m your host, Frances Kleven.

 

For this episode, we’re exploring what it takes to re-architect the enterprise in an AI era.

 

My guest is Henrik Yärleskog, co-founder and Managing Director Europe at Lead With AI. Henrik brings decades of experience in enterprise strategy, operations, and organizational design, helping leaders move beyond AI tools and towards real workforce productivity.

 

In this episode, we talk about moving past the AI hype, getting the order of operations right, and what it takes to turn AI into meaningful individual impact, including the potential to give employees back up to a day’s work each week. 

 

Let’s dive in!

 

Well, welcome everyone to another episode of our Learning Signals podcast. Henrik, we’re really excited to have you here, and I’m really looking forward to this conversation. I know we’re all living in a world where there’s so much enthusiasm and energy around AI, but I think we’re also all living in a world where there’s a lot of anxiety around it, a lot of,  just the burden of there’s so much information, there are so many tools.

 

And so it does feel like we’re sort of being squished between these two energy forces of both the enthusiasm and what things could be and what we could do with it, and then also, I don’t know how to wrap my head around this and it feels overwhelming, and it also feels fundamentally a little unsettling. So really interested to hear about how you’re thinking about that organizations need to employ both to survive this and to be able to scale, and that we’re really thinking about building organizations for the future and not being left behind, but also not jumping on hype that ultimately is going to leave businesses behind as well.

 

So, excited to hear from you. I thought we’d kick off, if you wouldn’t mind, about just chatting a little bit about AI theater and what risks you’re seeing there and how you’re defining that, because I think that’s a great place to start. I think that’s kind of where we all feel we’re sitting in, AI theater.

 

Henrik Järleskog: Right. Yeah, and I’m so happy to be here, Frances. I have spent the last couple of years really living in it, the exact space that you’re talking about, right? I’m the co-founder of Lead with AI. I’m also the managing director for Europe. That means that we have taken thousands of people through our programs and our corporate transformation programs, and we’re seeing exactly this, right?

 

You’re pointing at people feeling constantly behind., I think that’s one of the interesting things and as well that there are so many expectations on what it should deliver, right? And if you’re looking at the bigger picture and what we see in the news media globally, you see some CXO members doing town hall addresses for journalists where they say, “We are now embarking on AI transformation strategy…

 

Frances Kleven: Always transformation!

 

Henrik Järleskog: And we have had some, you know, thinking behind it.

 

We have done some rigorous analysis.” And then, without warning, they’re also in the same sentence, often laying off thousands of people, which is a sad story, to be honest.

 

One of the, you know, the zeitgeist right now. Companies who did this, or did it in that approach, a lot of them are also regretting the way they addressed it because they, without knowing it, painted themselves into a corner, calculating all of these automation wins from AI, in for, you know, for the coming two years, without having an AI-fluent organization also instilling this feeling of distrust, right?

 

Or worry or skepticism. Am I next? Or what does it even mean, AI automation?

 

It has been a bit of a strange order of operations, when we’re talking about kind of the AI theater, because it’s easy to say and promise a lot of things, but when the rubber hits the ground, when the value needs to be shown, that has been more difficult for companies.

 

I didn’t say it, but I think I sit between ten, fifteen meetings a week, right, with CXL members, a lot of them being CFOs or chief HR officers, sometimes the CEO. But the question is the same, right? Can you help us increase our productivity? And that’s an interesting question.

 

I don’t know how often you have heard that, Frances, but, for me, being an ex executive myself over the last twenty years or a global strategy consultant half the time, I kind of see it’s a very complex question, so I kind of return the question. I say, “So what do you mean? Do you want me to help you increase your margins?”

 

That’s deliberately a bit pushy, right? Because I don’t– I know that they aren’t asking for that, but I really want to hear what they mean when we’re talking about increasing productivity. And here is also this AI theater comin- coming in, right? Because my counter question is that, “Okay, so have you had the likes of McKinsey, BCG, Bain in the last six months, and they left with a list of ten low-hanging fruit, and now you’re looking at improving your processes. Is that what you mean?”

 

And then they smile and say, “Yes. Yeah. Yeah.”

 

Frances Kleven: And with all the, right, new things that AI can do, and to your point about everyone saying the AI transformation, what businesses are looking to achieve has not changed, nor in some way their ability to achieve those things. It’s not new to look to improve productivity or to improve efficiency. And so the idea that AI will somehow provide the magic solution for these issues and challenges that companies, for the most part, have not been very good at addressing or achieving…

 

Henrik Järleskog: Exactly. And I sympathize a lot with all of these leadership teams, right? It’s a difficult time. There are so many new things on the decision table that are strategic. It’s cyber threats, it’s hybrid work, it’s distributed work, it’s collaboration models, modern leadership, it’s AI, it’s GDPR, it’s legislation. It’s all of these things that are pretty new. And what I see right now is peak anxiety levels, and quarterly business reviews where decisions are meant to be made, where a lot of the time these key decisions are being deferred because they always feel, “We don’t have enough data so that we can act. We don’t feel confident.” At the same time, the fear of taking one faulted decision is huge. So it’s connected to that.

 

Frances Kleven: That’s really helpful, I think even just for me personally. But that is sort of has the top line narrative, but it doesn’t exist in isolation, and all of those things of remote working and isolation and global markets and all of that it’s not just AI that is making people feel that they’re being left behind or that they’re anxious or that they don’t understand what the next six months will look like.

 

That’s not just AI, nor can AI be the sole solution to that

 

Henrik Järleskog: Exactly. But they are part of a bigger transformation to the point, right? And I think the biggest risk companies run right now is to get stalled, right? It’s better to be a bit bold and take a few steps ahead without even knowing what it may mean because there is no blueprint, right?

 

The same discussions in those CXO meetings always revolve around the belief that we can look at our processes that we have right now and have a look, okay, where can we deploy AI into those processes? It may be a B2B finance process or purchase to pay or whatever. But my experience from having driven a lot of complex transformation programs over the years, specifically also the last couple of years with AI focus, right? Is that if you have that mindset today and deploy AI on your existing processes, you will just get faster chaos and a lot of slop

 

Frances Kleven:  And then, but how do you, when you’re having those conversations, how do you balance, right, on the one side, which you mentioned earlier, of companies who said, “We believe that this is how AI will transform our organization in the next two years, so we have reduced our workforce by X, because we are certain that AI is going to take this role in the business”? And so balance that, I don’t know if that’s risk-taking or that was just naivety, but how do you balance that reaction to AI versus I think what’s also very common of the, don’t wanna take any risks and so we’re going to sit in quarterly business reviews every quarter and talk about ideas and not really agree to move forward on something?

 

How do you get them to move forward in ways that you’re taking risks, but also that’s allowing you to be adaptable and nimble?

 

Henrik Järleskog: Hmm. Yes, there’s a lot of things to unpack there. So I’ll just continue. Let’s figure you are in that room in this discussion with the CFO. It’s a larger organization, and they are stuck, right? They don’t really know where to go. And we have this discussion around their processes, and if you’re deploying AI to the existing flows, you get faster chaos.

 

And then the conversation shifts because, okay, so what are you saying? Yeah, I’m saying that if you start with looking at your ways of working and if you start with changing your organization, you’re not on to a great start because it’s old school thinking that we can look at our processes and kind of design the governance of the company.

 

This way or this time around with the AI era, it doesn’t seem to work well if you do it in that order. But the following five, ten minutes of that discussion is even more interesting, right? Because then the question comes, “Okay, so what do you suggest?” Can be counterintuitive, but what we see now from working with global companies within manufacturing, mining, fashion, universities, national banks, what those who do it really well, what they have in common is that they do the order of operations right.

 

So they start with AI fluency, not AI literacy in the organization, but fluency. Really making people feel the value from their individual workflows. And then secondly, what we call the impact per hour. There are different metrics for it, but at Lead with AI, we measure that as our king KPI.

 

So impact per hour means the combination of capability and productivity, right? So being AI fluent in your own workflow, building a set of AI agents and really increasing your impact per hour, basically redefining what one hour work means, what you can accomplish during that one hour. If people feel that, and it’s positive one, right, if they get new capabilities they hadn’t really thought about, if they can get rid of the boring shit in their job, to be honest, like, most people don’t like to sit with, um, a lot of administration, for example.

 

Can reduce the administration time and thereby increase people’s impact per hour, then suddenly you have a positive movement, right? People know what AI is. They know what it isn’t. They have started to build their first agents, and they have a team. Maybe they have one AI agent for PowerPoint presentation creation.

 

Maybe they have one for keynote presentations or, yeah, whatever, you know, business case analysis, M&A, shortlisting, whatever. If that happens, then as a third step… Step one, AI fluency. Second step, drive that impact per hour. Third step, start redesigning workflows and organization. That seems to be really logic this time, because then you’re not painting yourself into a corner as a leader saying that we are now going to automate a lot of what we’re doing as a company, and therefore we are also letting a lot of people go, the first thing you do.

 

So it’s, you know, that’s the reversed order of operations that should be done.

 

Frances Kleven: And it’s interesting, the fluency versus literacy, and I think something that is a challenge but also such an opportunity for people who work in learning and development in these organizations. Because training or resources for AI literacy is quite simple, right? That’s just information that is just watch this video, read this article, take this exam. But to your point of that’s AI, AI literacy is not going to lead to an impact per hour type of metric. And so, how do you envision AI fluency? Like, what is the training? What are the learning opportunities that need to be in place in organizations to help people achieve fluency?

 

Henrik Järleskog: Yeah, you know, I’m feeling that I’m talking to an expert right now, like LearnUpon, and I will not claim to know the answer to that question better than you do. What I could do is to give my few cents on what we see and what we try to build, right? First of all, what we see is that hyper-personalization is mega important to drive AI fluency.

 

So that means that any type of learning going forward has to be one hundred percent relevant for the person that is learning from their job, from their title, their experience from before, their interests, their bottlenecks, their level of AI fluency, for example. So that hyper-personalization is an absolute requirement going forward.

 

So we are experimenting with that, and I think we have done it quite successfully over the last year, where everything is based on a kind of a second brain, knowing what learners in our programs have for kind of background interests, role, challenges, bottlenecks, their wish list. So that seems to be working well, you know, because you get people who are really motivated because they build things or they learn things that are immediately impactful in their everyday.

 

Frances Kleven: And that, which is we should have always been doing that. That’s from the beginning of sort of learning or educational theory, the idea that any learning should be relevant and applicable and personalized. Like that part isn’t new. I think to your point, it’s critical now that you could get away with 10 years ago creating a training video for your customers to learn your software and have that apply to all of your customers generically.

 

And now they have so many resources to personalize training and information that you know, it’s a requirement that that be personalized. How does this impact me? What is the relevance to me? So as somebody who has always worked in education and evangelized it needs to be personalized, it needs to be relevant, I am really excited that now I feel like we’re going to be forced to do that.

 

It has to be. But you do have really incredible tools to do that if you apply them and understand them correctly

 

Henrik Järleskog: Yes. For us, we have built an agent and her name is Lexi, right? She interviews all the learners independently if there are open programs or corporate transformation programs on exactly those questions. Everything she learns then goes into a module selector to make sure that those experimentations or lessons the weeks following are super relevant.

 

And as well, things like personal prompt guides, to make sure that the friction people feel when they’re– whenever they are about to learn something new is becoming lower. So they don’t start from a blank sheet every time, but they get a personal prompt for their setting as a chief HR officer or a chief learning officer to make it relevant.

 

And then the second time they’re doing the same experimentation, it will become much easier. So kind of removing as much friction as possible by this personalization is also a thing. And it would be interesting to hear, you know, from your perspective too, the combination of synchronous and asynchronous learning. What do you see? What kind of trends? What’s critical going forward?

 

Frances Kleven:  So it’s interesting, I, even before LearnUpon, I worked at universities, and so there was a, that was starting the conversation about synchronous versus asynchronous, and, you know, what lectures should be recorded so for students to be able to watch on their own time, and then in person becomes much more collaborative, problem-solving, questioning. But we still… I, and I’m not exactly sure where all of this comes from, but I think across the board, everyone just feels so much more comfortable with synchronous. And some of that is a positive thing of human connection, of, you know, creativity and spontaneity. If we’re honest with ourselves, most of our in-per- or most of our synchronous trainings are not very good.

 

They’re not very impactful. They are not very relevant. But we still hold onto them as if they are, if they are impactful, and they are relevant. But if you look at the scenario, whether that’s in person in a meeting room or a classroom or a Zoom call, if you look at the engagement of the people in that room, it’s quite low. 

 

Henrik Järleskog: Totally.

 

Frances Kleven: We also then, I think, allow ourselves to do very poor quality asynchronous learning and say, “Here’s a recorded webinar,” and call that asynchronous learning. 

 

This is my next question, but it’s relevant here. I think at the core of sort of face-to-face or in-person training is a lack of trust, and I think that comes from traditional education of the role of a teacher or a professor is to make sure that people are in class, make sure they’re paying attention, make sure they’re not cheating, and to be sort of monitoring them. And I think that’s come into, or I know it’s come into corporate learning, that there’s something embedded in us that we do not trust learners, and you can see that in we don’t allow a lot of our customers, this breaks my heart, where they just, they want to set video settings so that people can’t skip through or can’t watch at a faster speed. Or we create sort of these exams that are not well-written and aren’t really getting at impact, but the idea of we didn’t trust you to learn the material, so we now need to do this exam to validate that. So you said earlier about corporations have lost some trust from their employees, but what’s the shift here where we now need to really have trust in our workforce that they are learning the things that are impactful to them?

 

Henrik Järleskog: Yes, I think it’s number one is inclusion, right? Listening to where the organization is. A lot of the time we hear stories or we see stories, I see stories, where a leadership team have taken the decision to enter an AI transformation and then procure the licenses to Copilot, for example, and then throw the keys to Copilot to the organization and, “Hey, run with it, uh, figure it out,” you know?

 

Frances Kleven: Transform the organization.

 

Henrik Järleskog: Yeah. Maybe measure, for example, how people are using AI, how often they are logging in or how many hours they’re spending on it, right? So it doesn’t really say much about transformation and an inclusive way of driving towards a new North Star, right? But if you double-click on the minus one, minus two, minus three levels, the answers are pretty clear, right?

 

They often know where the need is, where the bottlenecks are, what the rest of the organization probably should prioritize. And it’s interesting, right? Because it is not about those sexy, really cool glossy magazine type of solutions that are super innovative, right? It’s all about the daily things.

 

People are, number one, they’re overworked. The pressure on them is increasing by the quarter. They are not equipped to do that acceleration that is expected from the AI automation, right? So whenever we survey people who either participate in our open programs or our corporate transformation programs, it’s all about personal productivity. Like, help me create an agent for reducing my one hundred and fifty emails per day or at least triage them. Create an agent that translates all of the insights that I receive daily and give them to me in a digestible format because I don’t have time to read.

 

Oh, if I could spend eight hours less per week on PowerPoint, could I do that?

 

Could I have an agent that does all of that for me? So these are the things that are, you know, the real drivers for productivity right now. It’s not that process, that corporate process that needs to be automated. It is the full workforce’s speed, their capability, their productivity, right? Any organization with a pretty high AI fluency level beats an organization with five super users. That’s where it is right now.

 

Frances Kleven: And I think, again, that’s such an opportunity for people who work in learning and development in organizations, because it is always such a challenge to have visibility of what you do and what your impact is in your organization. And if you could show that you can deliver AI fluency to, again, to your point, not to five super users, but AI fluency across your workforce, that is transformative.

 

Henrik Järleskog: That is transformative. And I can give some indicative numbers that we are measuring them from an impact per hour, after people have joined the program. You know, that’s the closest we can get now to quantifying productivity as we speak. It’s a self-assessed number, but also an expectation where we ask them, “Okay, so how do you think your impact per hour will increase now when you have built six agents in your workflow?”

 

So on average, they indicate a forty percent increase. So in a moderate business case, that’s one day per week back in time.

 

So if you transform one hundred persons, that’s one hundred man-days per week right back. It’s a twenty percent productivity increase if you take it from that perspective.

 

So that is, from my perspective, what I see honestly the big business case. It’s the human side of the AI transformation. It’s not that process that’s being automated. Yeah, that’s good too, but that’s not the big one.

 

Frances Kleven:  And then how do you talk to organizations or even leaders around, so okay, so we’ve increased productivity by 40%, or we have saved an hour or a day’s worth of work. How do you talk about then how that saved time will be utilized and so, right, that it’s not just saving time, you’re then carving out time that people can invest in different ways.

 

And so how do you talk to them about what that means to, say, a 40% increase in productivity, and where people will spend their time instead?

 

Henrik Järleskog: Exactly. And this is the big one. This is the big and most important question, I think. We try to do some proper change management around this, right? Starting early in this transformation journey, either, you know, on an individual or corporate level about Ikigai. I don’t know if you have heard about Ikigai. Probably you have.

 

Frances Kleven:  I have.

 

Henrik Järleskog: it’s the Japanese term where, there are cross-sections between five circles of what you love to do, what you’re good at, what you can get paid for, and what the world needs, and where they intersect, you have your Ikigai, right? So if everyone does that self-assessment of if they are in their Ikigai today or not, they have to move it into becoming closer to that Ikigai, right?

 

By removing, as I said earlier, sorry for swearing, but the boring shit. Be more engaged, do more meaningful things, be more purposeful probably in your everyday. A lot of these things are fluffy on the onset, but super important to have with you. Because whenever you build your first five or six assistants that take away and save, let’s say, sixteen hours a day, or a week for you, what do you do with that time?

 

Do you just work more? Do you perfect every Excel spreadsheet even more? Do you, you know, do the last percent of your keynote presentation for four hours instead? You know, don’t do that because what you want to do is to reinvest that time in more meaningful things that are part of your Ikigai, right?

 

So for example, a lot of people would like to spend more time with their small kids. Why don’t you pick them up one hour earlier if that’s okay with your boss, if you deliver on your outcomes anyhow? A lot of people want to have better health. Okay, you have saved sixteen hours, maybe you can take two of those for doing some exercise.

 

Many people want to get closer to their peers, because of either distributed work or, you know, being disconnected from the brand that they chose to join. So a lot of people we hear about now that they are starting to pick up their phone, like calling impromptu to their peers, their family members.

 

Although not every generation loves that, but my generation can give someone a call without asking first and being perfectly fine. So those things are happening, right? So it’s a new type of self-leadership and self-management that needs to be applied. And what happens inside all this is that’s a super difficult thing to do from a self-management perspective.

 

I talked to a chief risk officer the other day from one of the biggest financial service companies in the world. That person said, “I’m almost ashamed, right? Because I found that one point five days that you were talking about, Henrik, but I don’t know. I can’t be open about it. I don’t know who to share this with.

 

Should I sit around here or… Wow, it’s this Lutheran work ethic that comes back and bites you, and that leadership thing has to be exercised in any company that is driving an AI transformation. The leaders themselves have to be the best examples and say, “Hey, I know. I also saved that one day. I use AI for these things openly.” Just kind of drive away that fear that exists in so many organizations because it is real fear. Like a third of them are skeptic

 

Frances Kleven:  But I think too, I’m a people manager, and I always, before AI as well, if I could make any improvements on my team, that I would say I want them more engaged and I want them more self-managed. Because that has the biggest impact on me as a leader, um, to have a highly engaged and self-managed team.

 

And so there is real transformation possible here if done, if sort of done along those principles of the goal here is higher engagement, higher autonomy, and those have, those are transformative in the business rather than just, “Hey, we’re going to automate processes.” I know we’re coming up on time, so I wanted to end with actually, we did an episode a couple episodes ago with our CEO and our head of product, and they were too nice to answer half of this question.

 

But I know you’ll want to answer this, of leave us with all of our listeners, one thing to stop and one thing to start.

 

Henrik Järleskog: Right. Yeah, that’s an easy one. One thing to stop with, and a lot of people probably do not agree, but I’m gonna tell you why, it’s all of the status meetings where humans tell again what the system already knows, right? It’s a totally unnecessary activity, and it’s such a waste of time.

 

It’s better to build those systems around you so that you don’t have to do it, right? Because you don’t have to pay that translation tax of going into a system, looking at it and telling it, ’cause systems already know if you do this well. Please, work on that. Stop doing the status meetings.

 

They can be nice and important, but not in the way an old-school company does it. What to start with, for any individual non-technical leader out there, what are you spending most time on that you don’t like? And go out, figure out how that could be automated.

 

And believe me, it’s not as difficult as you think. So, for example, I used to be an executive myself and a strategy consultant for twenty years. I’m probably one of the persons in this world who have done most PowerPoints. I don’t do PowerPoints anymore because I have a chief of staff agent that does it for me. Stop doing what you don’t like and take a lot of time on and automate it instead.

 

Frances Kleven: I love that. I am happy to kill off any time that is spent on slides. I just find them soul-crushing. I’ve loved this conversation. I think there are many opportunities for takeaways for individuals to think about their own AI fluency, and then also for to be thinking about AI fluency through the, with the opportunity for real organizational change, both for improved results, but also to not be left behind in what is a very competitive and fast-moving space that we’re in right now. Henrik, delighted to have you here. Really appreciate your time and look forward to future conversations.

 

Henrik Järleskog: Absolutely a pleasure to be here. So thank you so much for inviting me, and I echo what you just said. You know, this AI transformation era is a human-centric one. So love having these discussions with experts like you.

 

Frances Kleven: Fantastic. And for everyone, keep an eye out for our next episode and take a look at our Learning Signal podcast page on the LearnUpon website, and we’ll see you next time!