Leading AI Without Losing The Plot

If AI keeps turning into theatre where you work, this conversation hands you the script for real advantage. We go straight to the hard truths: AI only multiplies what already exists. With a clear strategy, it accelerates outcomes. Without one, it scales confusion, risk, and busywork.

TLDR / At A Glance:

• AI as amplifier of strategy not a strategy itself
• hard truths on leadership modelling and accountability
• planning across environment, cost, process, and people
• champions embedded in workflow, not just training
• measurement tied to profit, productivity, and cost
• twelve human skills for scale including judgment and verification
• prompts as leadership clarity and better questions
• strategic subtraction to remove low‑value work
• 30‑90‑180 day path from pilots to operating rhythm

We bring on Kristof, a global expert in learning capability strategy and AI enablement, to unpack what actually drives success. Together we map the shift from tool chasing to operating models: visible ownership from leaders, crisp problem framing, rigorous verification, and trust built through behaviour. 

You’ll hear how to turn leaders into customer zero, select champions who influence across silos, and design an engine that translates curiosity into daily workflow gains. We dig into planning that sticks—simple goals, defined decision rights, and communication that lowers fear instead of inflating hype.

Expect a practical blueprint, not platitudes. We outline a 30‑90‑180 day path: set North Stars like profit, productivity, and cost; pick owners; run small, measured sandboxes; and roll learnings into shared playbooks. We also explore the human skill stack that scales AI responsibly: judgment, verification, systems thinking, critical questioning, collaboration with AI, learning agility, and humility. 

Prompts become a mirror for leadership clarity—write better prompts, give better briefs, make better decisions. Pair all this with strategic subtraction to remove work AI makes redundant, and you get a living, breathing organisation that adapts quickly and measures what matters.

If you’re ready to stop adding tools and start scaling thinking, this episode will change how you lead. 

Subscribe, share with a teammate who needs a clearer North Star, and leave a review with the one behaviour you’ll model this week.

Link to Kristof.

Transcript

Setting The Stakes: Value From AI

Kieran Gilmurray 0:04

Alrighty, welcome. If you care about getting real value from AI, not just activity, this session is for you. We're going straight to the hard truths. In other words, why judgment drops when AI rises, why speed without ownership creates risks, and why organizations scale tools before they scale thinking. In the next few minutes, you'll see what actually separates AI theater from AI advantage and how to lead it properly. Today I'm joined by Kristof, a global expert in learning capability strategy and AI enablement. We're cutting through the AI hype to focus on what really determines success. That's ownership, verification, problem framing, and trust. This session is about how leaders scale AI responsibly without losing accountability or credibility. Kristof welcome.

Guest Introduction: Christoph

Speaker 0:52

Kieran, thank you for an amazing introduction. I have nothing more to add. Just we can straight away jump into this fascinating subject, actually. And we need to go into the heart of it. If you'll be so kind, I would like to open it with actually a quote from your latest post.

Kieran Gilmurray 1:12

Oh, go for it.

Speaker 1:15

Across all sectors, leaders are approving AI investments without a clear view of how AI reshapes competitive advantage, cost structure or capital allocation. I think, and I believe, you just tackled the heart and the issue that we have to face at the moment with implementing AI.

Investment Without Strategy

Kieran Gilmurray 1:40

Yeah, yeah. It's funny, isn't it? Because everybody should be implementing AI, but whether they're pointed in the right direction or not, I'm not so sure. And that's the interesting bit for me, Christoph. You know, when leadership teams say we need AI, what do they actually mean? What what do you think they want? Where do you think it goes wrong? And where do you think they actually need to fix it?

Where Leadership Goes Wrong

Kristof 2:02

Especially uh for this occasion, I've looked closely to a great research done in 2025 by you. And this research was focused on organizational competitive advantage with the use of AI with the CRMs.

AI As Strategy And Change

Speaker 2:21

And imagine the point number one that is an issue that creates a failure is focused on only on improved performance. They don't see that as a strategic thing. There's no planning involved. And what's very interesting is we need to look at AI

Kotter’s Framework Applied To AI

Kristof 2:42

as something bigger than just doing a session on prompt generation. You need to look at this as a strategy and as a change management strategy. And Kotter beautifully laid this down in his A-steps framework, which divides on three phases. And imagine the phase one is actually focused on preparation. You have three, I think in the phase two, the fourth step, covers that preparation phase, how it is crucial in order to be successful with AI.

What Leaders Really Want

Kieran Gilmurray 3:19

Yeah, it's it's it's I have to say Caudra's been around for years, but it is a really cool framework. Although I do laugh at hard and soft skills, the way we break up the technical and the so-called soft skills. It's interesting because to me it's more about, you know, less about tech, more about operating models, you know, accountability, quality, decision rights, you know, all of those things absolutely kick in. So, Christophe, if leaders do want speed, they want fewer mistakes, they they want, you know, real results without creating, you know, layers and new layers of bureaucracy, what should they do? What are they really asking for?

Fear, Resistance, And Buy‑In

Leaders As Customer Zero

Champion Networks And Rollout

Avoiding The Post‑Training Void

Why Leaders Hand Off To Tech

Kristof 3:58

They're really asking for the first thing is, as we mentioned, strategic planning. Why do you need this AI? And very often they jump onto AI without answering the simple question. Once you've defined that AI is the key thing that can influence or even brings you the desired results you planned, then you come to a planning stage. And planning stage contains a three or four different levels. You need to use look at organizational level, environmental level, cost, which is one of the most obvious, and the center and the heart of it, which is a human factor. As you notice, very often a lot of research emphasized that people start fearing AI. And you know when people fear, they start creating a resistance. And this is one of the biggest roadblocks in rolling out AI strategy. So in a preparation stage, it's very important you communicate everything clearly. You drive as a leader the whole initiative of AI adoption. You need to have the leadership buy-in in order to roll out AI successfully. This is, I would say, the most important factor that organizational miss, because they have one leader and the other leaders are not on board. And what happens is we have disconnection. And this disconnection is seen by middle management, by all employees with an organization. And then they say if the leaders are not on board on that, if they're not involved, they're not the customer zero using AI, showcasing it, then when we go to adoption stage, it really doesn't drive the results we would like to. And one more thing I would like to emphasize, and this is something I observe in an organization. After preparation, planning, and when you go to rollout, very often leaders not only not engage, but they don't use the internal resources they already possess. Champions, this is the driving engine. Assign people in a teams to drive the adaption on a team level and assign higher management to adoption cross-category, cross-silos level. This is the most important part that is very often missed. Because what happened is you have this rollout of strategy, you have this big amazing training everybody's excited about, and then nothing, a void. You need to have this engine working constantly. This is something that never stops, and we need to take that for consideration.

Kieran Gilmurray 7:00

Is there any real reasons why not? Because I talk about leadership modeling, I talk about lighthouse leadership. You know, the light that they cast upon the business and the teams is absolutely vital. But I see a lot of handoff to technology. There you go, it's digital, it's AI, you go and do it. Where is this coming from? Is it fear? Uh, you know, is it we normally get one person? Are they bad communicators because you expect your leaders to be great communicators? Like, what what are the what are the reasons behind this dereliction in leadership, conscious or unconscious?

Generational Gaps And Fluency

Model The Behaviour You Want

Kristof 7:35

Well, it's interesting you uh you say that recently I actually discovered a great insights from a great conference in the US, and they actually tackled this specific problem. And they said that most of the leadership, not all, but most of the leadership, are still with all generations. We have four generations now within our organizations. And the one who actually wants to drive the change are the most resistant to change. And they're not so fluent with technology. There is a lack of leveraging the last generation Z that can really support them in that. There's a disconnection in communication and engagement. The key is to turn that around and make the leaders understand that they need to be first involved in understanding how the AI is crucial now and how their involvement is paramount to the success of organization. Even you emphasize that 95% of organizations fail to go beyond the pilot stage.

Selecting True AI Champions

Champions In Workflow And Agents

Kieran Gilmurray 8:44

Yeah, it's amazing until you see it on a daily basis. And this is the oddity for me, because what we're talking about is not a secret sauce. It's not you know costing billions. It's about leadership behaviors, you know, they themselves, the leaders who everybody looks up to. Uh, and not what they say, of course, is what they're doing. And it's not necessarily what they're doing, but at times, Chris, of what they're not doing. In other words, leading from the front, you know, trying, even if it's basic prompting, discussing, you know, AI with their teams, running hackathons every week for the first whatever numbers of weeks, you know, admitting vulnerability and and so slightly odd when you see it because I when you look at Coder Great Model, GE Cap Great Model, BCG 702010, you know, they all describe the same thing. But everybody starts with the tech, talks about the tech, and then moves toward more tech. Whereas I wonder if they spent as much time talking about the people and investing in their in their teams, would things actually change? You mentioned, though, just in again, let's connect the dots for people here as well, Christoph. You know, what you might call navigators or AI champions or whatever. What is that, what does a good champion look and sound and feel like? Because in my experience, it shouldn't be the first person who puts up their hand and is excited. There's a range of skills and competencies that are required in the role and influence that uh impacts AI's rollout and resilience. So, what are the skills you see in a champion or a navigator, and what are the best programs constructed like?

Cross‑Silo Sharing And Measurement

North Stars And KPI Discipline

Human Skills To Scale AI

Twelve Skills: Own, Verify, Judge

Systems Thinking And Collaboration

Kristof 10:17

I have to actually build bridge on one of your amazing trainings when I was a witness of the outcome. You inspired a lot of champions. They need a reason, an inspiration, and someone who can show them how they can leverage this technology. And once they've shown the technology, they are curious. So curiosity may be the first thing. They're solution driven, but also they understand how different guide waves need to be implemented while using AI. So a champion is someone who takes things in their own hands, proposes solution, experiment. And I saw after your sessions, people building their own agents and creating a special environment which is a next stage of implementation. When we're in this implementation stage, we need those sessions, we need the engine to work. And when the training is finished, we need someone on a constant basis, implement that in the workflow. So something we need to take for consideration, another pattern. Those champions, by experimenting, show the easiest way of using AI on the job. Because people resist in if they see it gives them additional work. They don't understand something. They resist to implementing AI tools. However, a champion with someone who actually shows them, look, your work can be much easier. You get much more done. And by implementing this specific tool, in this case, I remember with AI agents, on the daily work of a team, you cannot imagine how this one person can really lift the level up of the AI implementation on a team level. Now, you take those champions, yes, and make them meet on a monthly basis, together, from across all categories. Okay? You don't want to create silos that one team is super AI enameled and the other teams are far behind. Those champions then talk to each other, exchange the best practices, and then you lift the whole organization level up. But that's just one level, okay? We always need to make sure that everything is measured, how we use this AI. And when you have this engine level, you have those specific small trainings that bring up wherever changes in technology. So they need to be all up to date, and that complements the biggest uh program rollout, which you have on six-monthly basis or yearly basis. Yeah. So that system of three layers, if it's implemented correctly, only then organization is able to keep up with the changes and get the real advantage of AI implementation.

Learning Agility And Process

Asking Better Questions Beats Tech

Is AI Exposing Old Skill Gaps

Kieran Gilmurray 13:34

Yeah, I've seen that. I think it was McKinsey were talking recently, you know, about actually, you know, making sure that AI is actually measured, you know, KPIs are put in place, that you point things toward the North Stars that you were mentioning in a moment, you know, profit, productivity, cost efficiency, or all of them at the same time. You know, so so again, nothing new, you know, rather than what I call, Christoph, AI theater. In other words, people doing AI for the sake of AI, it doesn't make any sense. What are you seeing as the human skills then that are required to scale AI across an enterprise? Because if you look at the World Economic Forum report, and again, uh go with them folks, not necessarily me. And I'll tell you what I see on a daily basis across the globe, literally traveling and working everywhere, you know, the the idea of resiliency comes into play. The the word you used a moment ago, and I loved it, is curiosity, you know, a hunger to learn. And the other word I heard recently was humility, the ability to admit that you actually don't know everything and are vulnerable. And then you become an enabler, not a teller or or or a just doer and not explainer. What do you think are the key skills and leaders? What do you think are the key skills in these navigators or AI champions that create really successful scale programs over numbers of years, not quick sprint and runs, uh, to get an AI project in place. We're talking about a capability, a way of working, a new beginning, a new way of actually delivering value over the longer term.

Prompts As Leadership Direction

Kristof 15:08

I love that you asked this question because this is something I actually spend a lot of time researching, transforming your research into something easy to understand for leaders and implement. And I discovered that there are 12 skills that are very much crucial for using AI and not always the skills that we would think would fit under that category. If we talk about judgment, verification, or ownership, their verification sounds very technical. But here you need to verify the output. Judgment,

Adapting Faster Than The Change

Speaker 15:44

you can make a decision how far you want AI to be involved in accessing your data. You have to have that awareness and ownership. You need to own the outcome. And I think that is the most desired skill when you are involved. You're part of the process and you own the outcome. Of course, critical thinking and problem framing, because you need to critically assess the output. You need to be able, as an expert in the field, yes, to pick up what is the part that AI

30‑90‑180 Day Leadership Actions

Strategic Subtraction And Focus

Kristof 16:23

is hallucinating about or not, even though AI is way better than before, we still need to be vigilant, especially in relation to the output. System thinking, we have to see that AI have access to more things than we do. Okay? And it's incredible that whether people who design the framework or the people who use AI need to have that skill. Because the AI can pull up documents and show to the people that shouldn't be accessible. Collaboration. It's great to see AI agents now or AI as your partner, as a tool that you use within your work. You own the outcomes of support. And you need to collaborate. So that's a new thing for people. That scares them because they need to have to learn a completely new way of collaboration with this artificial intelligence, which is changing very rapidly. So this learning agility is very important also, and this adaptability and reflection, because very often uh leaders use AI to support their decision and a process optimization. Process is the key. AI is a great enabler and support in that, but you need to see this AI in a whole working environment, not as something is taking out uh as a small element of the whole puzzle.

Simple Plans, Clear Stakeholders

Process, Managers, And Friction

Continuous Measurement And Updates

A Living, Breathing Organisation

Kieran Gilmurray 17:54

No, it does need to be living and breathing. You you talk about an interesting point there, you know, leaders need to get a little bit better at assessing the outputs. And again, I'm sort of in my own head here, thinking of a lot of things all at the same time, because we've sort of been saying that for a while as well. I deliver a course on you know data analytics, but it's actually a course on curiosity and insight more than data analytics. And what I'm teaching is how to ask really great questions. And when you can ask a really great question, notice I haven't mentioned the word AI at all, you get really great insights. And once you get really great insights, you can make a much better business decision. I think it's Bain, BCG, all the usual characters, say that, you know, ask a great question, get a great insight. There's a 95% correlation between that and a business decision and the outcomes you get. Why I'm telling you that is are we starting to use AI as an excuse? In that AI is starting to uncover a lot of skills that were actually lacking before AI. And by that I mean the ability to ask a great question, the ability to critically judge any output, regardless of whether it was AI, you know, the ability to judge human output, the ability to interpret content or information or research reports, the ability to actually have systems thinking in place because AI is exposing the fact that we're a bit disorganized, that we don't have systems, that we don't have SOPs, you know, that we're not actually leading. You know, uh again, the ability to ask a great prompt is the ability to provide clear, clear direction. So if we're struggling to give a machine a prompt, have we been struggling as leaders to give our teams accurate prompts? What's your sort of thoughts on that? Are are we uncovering a whole host of skills that we should have and blaming AI for that? Or is AI just highlighting something that uh we should know, should be doing, and it's a new opportunity to reset and go again. But we've got now got a tool that's allowing us to do whatever we should have been doing and need to do at scale.

Final Lessons And Takeaways

Connect With Christoph And Resources

Book Launch And Closing Thanks

Speaker 20:01

I love what you said because it's actually connects to this adaptability piece and learning agility. So uh I would say it's a process that once we involved in it, we slowly will adapt and evolve. Now, when you said bad questions, brilliant. And you're right, the art of asking questions is absolutely crucial here. I love neurolinguistic programming. So I like, you know, wherever you create the question, you were thoughtful about that, especially when you put that into AI. And you're right, it's actually AI brought us and showed us that people don't reflect at all. They don't understand that this is a process that they need to work on with this AI, understand it better. Uh, and there is an art and there is uh a science behind it, why you use it. And something that we need to get used to now, change is a constant on a much faster pace than before. If you look at that, how technology changed quickly, look at the AI agent six months ago or now. Look at the outputs we can get, the quality of things. So seeing that lots of new skills emerging, but I see that as a process. I don't see that as a reset done, uh, nothing what you had is is important. No, it's a different emphasis of this specific type of a skill. The art of asking questions, the part of communication is emerging there very nicely and clear. Learning agility, working with the process changes faster, yes? And what's fast already? Yeah. So that's why maybe uh we're going back in the circle, the leadership. What's why maybe they also struggle uh because that changes faster than when they start working.

Kieran Gilmurray 21:50

Yeah, but there you're kind of hoping that AI allows them to absorb information and analyze it a lot better. As long as they ask the right question, of course, put in The right prompt, then we're a little bit more certain. Before we finish, my thoughts are, you know, if we're going to recommend to leaders, because with leaders listening into this, you know, webinar podcast, and they're going to say, Well, look, I want to be credible, you know, I want to take action. You know, what do I do in the next 30 days? And by the way, folks, it's the next 30 days is key, but so is the next 90 days, the next 180 days, the next 360 days. And Christoph, you mentioned you take what I describe as personal accountability and personal ownership for your own development and learning. You're not waiting on your organization to tell you what to do. I think everybody should start with that. And I also think this is the second thing. Very often when we put AI in, we layer it on to more, the more work, more things to do. You know, and I call it not the age of AI, I call it the age of more. Uh more, more, quicker, faster. I'm a huge fan of strategic subtraction, which is a regular rhythm of actually stuff out, removing things that don't add value. So if I start my first two, which is lifelong learning and dedicate time to research and uh actively implementing that and highlighting that and demonstrating it to teams, and secondly, practice strategic subtraction and celebrate and reward it. What else should we be telling leaders to do, you know, to get AI into place, to get it to be part of their natural operating rhythm, and to develop their teams, their champions, their business to cope and not just survive this age of AI or age of more, but to thrive in this age of AI and more?

Speaker 23:36

It's a brilliant question. So I would say first, simplicity, and I like your way approach of subtracting things. Simplicity in planning and focus on that stage very, very well because your planning decides how you're gonna roll out and what results you're gonna get. And sometimes we try to create a new frameworks, overcomplicate things. Work with your change management team. It can be as simple as answering what problem I'm trying to solve, what I want to achieve with implementing this specific AI tool or AI strategy. Once you have clarity on that, then you're able to prepare your communication, get your key stakeholders up, identify your champions before you start even rolling it out. Once you have that done, you create processes that enables people to actually implement this AI. And here is very crucial. Not only do you have the key stakeholders on board, you also need to make sure that your managers are working with them. The instructions are simple but clear. You have already done a research within the best use and best practices. If you don't have in your organization, you can lean on a great expert like yourself or people who do a research and looking in the companies that actually made those mistakes, and you can learn from that. We already have a great indicators, what can predict success. So then you roll out this within your organization, but this never stops. You measure your impact in team, you change what brings friction, you adapt that, and in the same time, you learn from whatever happens on the market. And you need to make this as easy, as frictionless as possible within your organization. And then you're able to have that natural engine within your organization that will give you the results you desire. So going through that process is a key, understanding that process is a key. Don't hurry. As you said, don't jump into it too quickly. Make sure you reflect on it, make sure you plan, make sure you involve the right people. What's the latest research about that and leverage that within your organization? If you don't have time, leverage professionals to get that. If you have and you have a team dedicated to that, even better.

Kieran Gilmurray 26:21

It's interesting because I love what you're describing. You know, that to me is a living, breathing organization. Because it's not that I don't like digital transformation. I don't like what happens when you need to digitally transform. By that I mean you've forgotten to keep innovating, you've forgotten to keep learning, you've forgotten to do all of the things that you're describing. Everybody gets busy, they forget to improve, they forget to remove the stuff that doesn't actually add any value. So, therefore, if you can get to that operating rhythm where people are involved and engaged and innovating all the time and learning and challenging and checking and asking great questions, developing themselves and great people, we're in a much better stage. So, folks, look, let's close this out with some lessons. Look, AI in itself is not a strategy, it's an amplifier of the strategy that you've got. But if you haven't got a clear business strategy, it's also an amplifier of confusion. It's an amplifier of uh avoidance as opposed to ownership, of chaos as opposed to discipline. And the organizations that are winning are not the ones with the most AI pilots. They're the ones with the clearest uh in the direction, the strongest problem framing, the visible leaders who are accountable and building technology and innovation and change management and all of the great things that you should be practicing every day into the work. So, folks, if you take anything away from today, you know, define what the outcome looks like, what is the win? What's the purpose of the business? Before you implement anything or scale anything, do that, and AI and leadership starts to become an advantage. Ignore it, and AI tends to become theater. Christoph, if folks, and I hope they do, and I'm going to encourage them to, if they want to try and connect with you some of your research, some of your writing, some of your thoughts, how do you go about doing that?

Speaker 28:17

It's quite simple. You can go to the nextskillacademy.com where you can find all the recent guides I've released for organization in relation to human skills in AI, prompting AI, and all the lectures I delivered recently and talks. And what I've noticed, the market, as you know, changes so quickly. I will be releasing updates because I noticed what I released uh six months ago might not be up to date uh in the next few months. So I encourage everybody to look at those guides. If if you need uh guidance, I'm here to help. And also, Karen, you're doing a fantastic job. The book uh is coming out, or oh, it's already out.

Kieran Gilmurray 29:01

We got it up on Amazon and we got it up on Audible globally, thank goodness in the last couple of weeks. Brilliant.

Kristof 29:06

My next step after this talk.

Kieran Gilmurray 29:10

Brilliant, Kristof. Thank you for your kind words. Thank you for your time. Thank you for your leadership. Thank you, everyone, for listening in. Until next time, we'll see you soon. Thank you very much, Karen.