E108 - Good Change in a Tired System - Podcast With Gilbert Kruidenier

Welcome to The Inner Game of Change.  where we explore the thinking that shapes how change really happens. 

Today’s conversation is less about technology and more about people.

Four years after our first discussion around bad change, I reconnect with Gilbert Kruidenier to explore the current state of change in a world shaped by AI, overload, constant adaptation, and growing pressure on organisations and people alike.

We discuss learning, leadership, redesign, burnout, human capacity, and why the real challenge may no longer be technology adoption, but how humans absorb continuous change.

I am grateful to have Gilbert chatting with me today. 

About Gilbert

With 20 years of experience in change, communication, and project management, I know exactly how to help organisations navigate complex and transformative change with purpose, clarity, and empathy. I combine the best of change, communication, and project management practices to support large and medium sized change programs, design and deliver workshops and training, and advise boards on strategic topics.

I am also an author, independent business owner, a visiting lecturer at Deakin University and even tried my hand at being a cabinet making apprentice, pursuing my diverse interests and skills in consulting, education, and creating beautiful things with my hands. I have a master's degree in culture and change management, multiple certifications in ADKAR, Digital Transformation, Lean Six Sigma and PRINCE2, and a strong background in public and private sector change and (digital) transformation. My core competencies include change analysis, process improvement, coaching and mentoring, and problem solving. My life goal is to make a positive difference in the lives of others, especially the most disadvantaged in society.

Contact info

Gilbert’s LinknedIn profile

linkedin.com/in/kruidenierconsulting

Email

gilbert@kruidenierconsulting.com.au

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Ali Juma 
@The Inner Game of Change podcast

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Transcript

SPEAKER_03 0:00

I think like with every change and and let's call AI a change to the operating model, operating system for the sake of argument, you have to consider your capacity and your capability and then educate yourself accordingly as a leader. Like what do you need to do first in order to be able to lead that? Because just dumping it on your people and running away until you have time to sit down and think about what you've just done, uh, that seems a bit irresponsible. So educate yourself before you ask anyone else to get up. Otherwise, you'll be taken for a run. Because I've I've seen offerings that offer very little for a million dollars plus from consultants who I know were working in a different field like three months ago.

Ali 0:46

Welcome to the Inner Game of Change, where we explore the thinking that shapes how change really happens in the workplace. I am your host, Ali Juman. Today's conversation is less about technology and more about people. Four years ago, after our first discussion around bad change, that is Gilbert's book, I reconnect with Gilbert Krudinier to explore the counter state of change in a world shaped by AI, overload, constant adaptation, and growing pressure on organizations and people alike. We discuss learning, leadership, redesign, burnout, human capacity, and why the real change may no longer be technology adoption, but the humans observe continuous change. I am grateful to have Gilbert having this chat again with me today. Well, Gilbert, thank you so much for joining me in the Inner Game of Change podcast again after I think four years.

SPEAKER_03 1:48

Yeah, it's a pleasure. Thank you for having me.

Ali 1:50

Thank you very much. Uh we recorded a podcast four years ago around your book Good Change, Bad Change. Have I got the title right?

SPEAKER_03 1:59

Bad Change, but you got half of it.

Ali 2:03

And I actually have got the book as well. So what do you feel that different about change since we met last time?

SPEAKER_03 2:10

There's there's a lot of change, and at the same time, nothing has really changed that much from my perspective. I have the benefit of being around now for a little while, let's say two decades. So I I feel like I've I've got a bit of a comprehensive view of what's going on. But at the moment, it's it's very hard to hear those weak signals that we talk about in the complexity theory theory field over the what I call the death metal of AI that's cranked up to 11 at the moment because everything is AI. I was at a conference last week speaking, and all the other speakers, there were 12 of us in total, so very short bursts, and nine out of the 12 had AI as a topic and it was integrated there. And I almost felt bad for not having AI in there, but it was it was not necessary for my talk. So that's that's drowning out the noise and the sounds. But what I have seen is more people getting a voice, which is really great. So we see more diversity in the fields. It's not always the same players who are still doing really good work, but even those same players tell me that sometimes they get a little bit tired of always being the same people speaking up, showing up, showing how it's done. So I'm I'm enjoying that. Not always enjoying the quality of the work that's getting done, because of course nowadays it's a lot easier to get something out there. But then there's also still gems, people really coming up with new frameworks, and there's nothing really new under the sun in that sense, but audiences change and new people enter into the profession as well. So it's totally fine if an idea from 2015 or even from 2020 gets repackaged in a new and modern jacket. I I don't really mind that. It's just that yeah, some of the jackets are very thin and are already starting to wear a little bit thin after just a couple of tries because there's not a lot of thought into it, or at least that's what it looks like to me. So yeah, I would say that that's that's what I've been seeing. A lot of same, same, but some very bright sparks of new and interesting ideas.

Ali 4:04

I want to touch on a couple of things that you mentioned. What is your concern that there's a lot of talk about AI?

SPEAKER_03 4:12

I think we're underestimating how long it will take for organizations to really adopt it. I mean, I've been having this conversation about AI from 2018 because I for once I was again, I was for once early and actually saw the writing on the wall and started reading about it. And what I realized was most organizations that I knew of were absolutely not ready for this. And it's mostly a data question. Like the data is either not clean, not available, not organized in a way that an AI can easily do it. But the ambitions are absolutely there. Organizations just want everything to be integrated tomorrow, and they they love the concept of it. It's it's very similar to, let's say, a general change capability building in an organization. They love the concept, they get that, but they're not really willing to do the work. They're hoping for this sort of magic bullet that will solve it all, and then we just turn on the system and it will do everything. So that that concerns me because there's no scaffolding, there's no capability building in staff, no significant funding going into it. So data teams are just left in the dark and essentially with super high expectations and a fancy laptop, and then said, look, make sure that this happens by next week because the competition is knocking on our back door, and we need to make sure that we have something to stave them off.

SPEAKER_02 5:27

Yeah.

SPEAKER_03 5:28

So I'm I'm not seeing a lot of strategy. I'm seeing some organizations leading the charts, but they are the vast minority, and they're often the really big organizations who have hundreds of millions, sometimes billions of dollars to invest. But that's not most organizations, and that's not most change that needs to happen. So, yeah, my concern is more a capability capacity thing than a concern about what it will do, because we've been having that same conversation about oh, AI will take all the jobs, and we've had that conversation before, or it will turn us into uncreative people. Like have a bit of faith, have a bit of confidence in the human capacity to adopt new and interesting things, as we tend to do really well. Yeah, but right now, as I just mentioned a couple of minutes ago, the noise is so deafening, that it's everywhere. It's so hard to have a normal conversation or even a human-to-human conversation, because I posted about that earlier this week, about AI just becoming a bit of an ick factor now, where you can see that people use it to write their posts. And I was having an offline conversation with a friend yesterday, and we we came to the conclusion like it feels like people no longer want to invest in having a conversation with me, they just outsource that to someone else. So you feel as a person, you feel outsourced as well. And if we start doing that to staff, they're gonna feel outsourced and even less committed or maybe less engaged than they feel now. So organizations have to spend time and attention on that, otherwise, they just the little engagement that they have left because all the research and reports tell us that engagement is an all-time low.

Ali 6:58

I do not have a problem, people talking about AI. I do have a problem that noise is coming from people who have not got their hands dirty and lots of theory talking about it. AI is got is a wonderful capability. Actually, I call it a capability. I agree with you that organizations, some of them are trying to react to it. It's a bit of a panic, is that if if Gilbert is doing it, should I not be doing it? Uh, should we recruit somebody and then they recruit the somebody and then they go through this idea of oh, we need to get our data right, we need to, you know, um, we need to choose the platform, and they're all irrelevant questions. They the questions is really which problems do you want to solve and and do you want to grow? And could this capability help you with that? Perhaps it won't. It won't help you with that. And so I I I do see a lot of theory and academics and all of that. And uh I charted a different way for the last three years. I charted a way of whilst it's tempting to talk about it, I started doing small things and experimenting and gather my own insight. And it wasn't easy. It wasn't easy because I needed to shield myself from the outside world and focus on experimenting and seeing my the audience and my stakeholders and how they deal with it. And I am worth three years of practical insight. I got about thousand people that I worked with over the last two years. And so I've seen I've seen I've seen the change and I've seen the platform, I've seen the conversations. So I don't mind having a conversation or you know, around it. But I want to flag something with you. I strongly believe that the change management community, we we are in a position where we are impacted by the change. Yes. But also I am promoting that the community fast track their learning and their experimentation so they become advisors for their organizations. We should not be sitting like everybody else waiting for the organization to think about the change when we can play that role. And and and the idea that AI is a technology change is rubbish, in my opinion, anyway. The change is not really techno technological. The change is that this is a lever that will nudge the system, will push people, will enable people, provided that the organization provides the right support, as you mentioned, the scaffolding and all of that. And that is not an easy thing. I mean, that is also another aspect of AI that organizations are really struggling with. And so what do they do currently? They go to the IT department. And I'm I don't have a problem with the IT departments at all, but I do have a problem that the IT department decides on a change that will nudge people's capabilities, their identity, their the way they think about their work, and plus the system.

SPEAKER_03 10:23

Yeah, I put that at the leadership level, though. I don't put that at the IT department. That's a leadership team misunderstanding their mission and their role, where they should be having a strategy by now, because, like you said, AI is not a new thing anymore. And even if you are deaf and mute to every signal from the outside world, it is almost impossible to have escaped it. And if I can create a statement of how I look at it and how I think about it, a frame of thought if you want, then everyone else can do that as well. Some organizations just decided that it was going to go away, some decided it was just co-pilot and we'll integrate that. Uh, I agree with you that it's a little bit more than a nudge in my, I think it's a bit more of a push or even a shove, yeah. Where we just get thrown into this because we're so excited about it all. And somebody that I have a lot of time for, Paul Gibbons, he writes politically on online. He's doing this thing. I think it's very cool, very cool. Adaptive adoption. The title is a bit of a tongue twister, but he's got the right idea and he is at the forefront of AI integration. He's doing things at 60 years old that I at 47 cannot even imagine. I don't know where he gets the energy, but I'm very impressed with what he's doing. And he is doing what organizations will be doing about five years from now, I think. And probably having made that prediction, it's probably gonna be two and a half to three years because everything is just accelerated. And this was a conversation I was having at the conference every other time I had a break. The the time frame that technology needs to progress is much less than what we need cognitively to change our behaviors to adapt to it. And that's not gonna change overnight, and that's just causing a lot of extra stress and a lot of frustration with people and anxiety about oh, am I gonna be replaced? Potentially. But like you said, if you don't engage with the the topic or at least have a couple of stances on where you want it to go, then you'll you'll just be left behind. You won't really be replaced, you'll just become obsolete. But that that's nothing new. That conversation's been going on for 40-50 years as well. You have to keep learning.

Ali 12:29

Yeah, I think what Paul what Paul is doing is is already looking at what's gonna happen in a couple of years. That's what I talked about, the idea of a nudge in the system, because there's usage, there's adoption, and there's augmentation, and there is a redesign. The redesign is the scary bit. This is where leaders will will need to answer that question. Well, they need to act on it in two to three years' time. So the idea is that an employee will be adopting AI, fully adopting it, and they are happy. They are saving them a lot of time, changing the way they think about their work. But the system is still tired and the processes are designed for a different age. For uh like you would have heard people talking about electric you know, AI is like the new electricity, right? But if you dig deeper into that story, in fact, if you actually go read more about what happened rather than the headline, when electricity was introduced, all factories were designed for steam power. And so when they plugged in the electricity, it was just another power. The system was designed for the steam power engines. And so the the gains and the productivity did not happen at all. In fact, it started happening ten years later when two things happened. When new factories were being uh built, they built it based on electricity, not steam. And the existing ones actually redesigned the whole factory floor based on that. So can you see that that that is the scary bit? And that's where organizations think instead of thinking this is where I see the change management community to start, you know, educating the the um the the workplace and the leadership groups and informs that this is wonderful, it can support the current state. But the real magic of this capability is that when you redesign your work uh processes, I work for myself and I have I've redesigned everything how I do things, you know, over the last two years. And I've got agents now, and I've got you know two or three platforms that I work with. They do research for me. Yeah. And you know, and I still spend a lot of time understanding that research and and and synthesize it. And but I've redesigned my work, my work, you know, including my podcast.

SPEAKER_03 15:14

I think that's what organizations are heading towards. But as you just mentioned, that complete redesign to interact with a new type of energy or a new type of input, that's where organizations get caught because they're still caught in their original structure, how they were built. And that's why it's so interesting to see what startups are doing now, because you see startups being built around a specific service, just one particular product that they're offering, and they can scale it up so quickly and turn it on and amplify it so quickly. Other organizations look at that, and it's what we saw in in the early 2000s when, well, 2005 and beyond, when the the growth of Google came along and everything got supersized. We thought, like, I want to be like that, I want that culture. But it's very much like you just mentioned, you are not in possession of that same infrastructure, you do not have the same context to operate in. So you'll have to rethink that completely. And I am not hearing that conversation in the community at all.

Ali 16:14

Well, because it because it is difficult. Thinking is thinking is difficult.

SPEAKER_03 16:19

Absolutely. I mean, most people are still very happy to be reactive, and then you've got a couple of people who uh break the curve, and and it's not even going against the status quo, but they want to have a different conversation and they just get shouted down again because we crank it up to 11, and then everything is like, no, productivity, we need to go there faster. And the questions that I've been asking for well, the past two years, I think, is like, where are we moving to so fast? What's happening over there that is so attractive that we need to be there? Because all I see is people getting tired, people getting burnt out, people getting frustrated, or best case scenario, you end up in some sort of corporate island where you're doing amazing things by yourself, but no one understands what you're doing because it's so complex, and maybe even the people doing it don't completely understand it. Because that's of course the other ethical challenge that we have is we don't really know how AI got there. I'm having these continuous conversations with Claude where he keeps making the same mistake over and over, asks me to tell him her that it's continuously making the same mistake, makes the same mistake again, keeps apologizing for it, and the apologies get better, and then ask it, like, can you explain to me how that happened? Oh, yeah, no, it's very deep in my coding. Okay, I've just told you to remember it, and that was how we decide to collaborate. And it keeps happening, and that's a very small example, and it's definitely not at the scale of agentic AI.

Ali 17:34

That that's an interesting thing that you just mentioned. Uh instead of fixing its delivery, it's improving its state of story.

SPEAKER_03 17:44

Yes, and it doesn't do anything for me.

Ali 17:46

Yes, yes. That's that's uh that's like my son. That's like my son. He's very good at the story saga rather than rather than fixing his behavior. That's an interesting, and I find that really funny. Talking about the noise is creating pr unnecessary pressure as well. Because there are people like I stole I just talked to people yesterday, uh d an organization. Some people have not touched any platform, and they're waiting for something to happen. And they're actually young people, they are not old. And and for me, and then when I asked them and they said it's just too much noise for me. And yes, so uh the the there was an article written in in by KPMG AI Operational Reality Report, and it says AI is intensifying the pace and psychological pressure of change. How do you see that happening?

SPEAKER_03 19:24

I think that's 100% true because we haven't really learned. It's sort of like getting a new team member, and this new team member is completely different. No one understands how they got hired on the team because whoever hired them had never met the team before. So you had 10 people who are sort of engaged with each other and they get along well enough. They they do the team lunch every now and day, and then all of a sudden you get this rebel rousing, completely different person, completely different personality, doesn't fit in any way. But the only thing is, you know you can't fire them because they are related to this CEO or whatever. So they're gonna stick around, they're gonna be there. So you have to make it work, and everyone's trying to make it work, but they're all sacrificing something in order to make that happen. Some people only sacrifice a little because they happen to have the same sort of personality, they get along really well, or they're very useful, or they simply don't care enough. So all these different approaches, but we're going through that process right now, and very much in line with what you just mentioned. I I hear from a lot of young people from our volunteering and other spaces where I operate, they're not that interested to talk to AIs. Like it doesn't really have anything to say that I can't get from my mates. I don't use it because it lies to me. I don't trust it. And here we are, as the adults of my generation, at least, uh 47 years old, just going at it, hammer and thongs, just trying to get it as much as possible and see what I can do with it, and just living without accountability. That's that's how I've started like I'm I'm just doing all these things. You remember when we made the action figures and everyone was doing that? The LinkedIn police showed up, was like, oh, do you know this burns a lot of resources? And we're like, oh yeah, that's really bad. Let's make another one. Because we just can't control ourselves. We're so excited about it. And Paul Gibbons and I had this conversation online. I said, Look, to other people, we must look like a bunch of frantic idiots. We we call it the 3 a.m. club, and not the 3 a.m. club that is just like all the tech bros. But people wake up at 3 a.m. in the morning just full of ideas, and there's nothing to stop us now. And I'm concerned about that. So I've said to myself, I am not doing that anymore. Like I've I've got a couple of rules about things that I'm not supposed to do in the morning, like not send emails before 6 a.m. because my mind operates in a different way. And what I think is completely reasonable, other people find very intimidating. So we're like, okay, cool, not doing that anymore. And I'm not working on external-facing AI things anymore. And I'm thinking that's what organizations need to get together for themselves. A couple of years ago, I know you worked at universities. Universities were having this conversation amongst themselves. How will we help students interact with AI? Because everything just got done by AI. All my papers just turned into AI drivel, comments were AI drivel, couldn't get a serious answer out of my students, and somehow they created a code of practice or a code of engagement. This is how we're going to do it. But organizations sort of feel like if they do that, if they restrict it, they feel like, oh no, then we lose all the creativity and people will not want to use it. Well, what you just mentioned and what I've had heard, have been hearing as well, the noise is so overwhelming. People don't know what is okay, what they can and cannot engage with. Two, three years ago, we were worried about corporate secrets ending up on the internet. Well, I think that shit has sailed. So that's that's a bit the up. But now people are like, oh, I'm I'm not exactly sure. Can I use it for this? Because I got some feedback from meeting or very unfortunately. How do you say prompts get copied into reports? And then you see these very funny things like, oh, okay, so this is not original work. And that's what's starting to concern people that we're not seeing original work anymore. We're getting fed something by an AI. You can't run a business on that because that becomes generic. And as a business, you would need at least some sort of distinguishing feature to stay in business.

Ali 23:02

So yeah, that's yeah. I I think I think the idea of some people have outsourced their cognitive abilities to AI. Yes. That's the temptation. But I strongly believe, Gulbert, that over time, you know, this idea of you can only use AI for a while. Because at some stage you're gonna sit with your leader or with your stakeholder. You will have to talk, you know, to people. And AI is not gonna save your bum, you know, when you're actually talking to people uh about ideas. But I want to cover on stuff. I am guilty of the 3 AM and the ideas. I haven't stopped myself yet. I bounce off ideas and actually AI is helping me with a lot of historical events that I used to hear about, and and I get a few perspectives about it as well and try to understand it in there. I think what's happening with the organizations. We've got external noise, we've got uh people trying to figure it out themselves, and they make the noise, they they have some sound bites. Some organizations saying that now we'll have to adopt it, some organizations say we'll have to scale up, and then you've got tired system and weak design to make you know to adopt that. So can you see that the value of the capability is trapped in there?

SPEAKER_03 24:26

It's it's limited to our capability to leverage it in a responsible manner because if we it's it's almost like eating too much sugar, like you're enjoying it for a while, and then you just get this massive sugar rush and then follows the dip. And we haven't yet learned how to have a healthy relationship with AI, and I think that's true for nearly everyone. Organizations certainly don't, and people as well. So it stresses us out, but it also attracts us. Yeah, it makes us feel anxious, but it also makes us feel excited. And I was thinking about this post that I read a little while ago, and it just feels like teenage love. It's like infatuation. You can't stop thinking about the person, but it also makes you sick. It makes you excited to see them, but you're also nervous. And I think we we haven't really explored, and some people have it. There's many great thinkers out there who have written beautiful, beautiful stuff about the human psyche and AI, which I can't even get close to comprehending. But in my own layman's terms, it's like we're very excited about it, but it scares us a little bit as well. So to me, that just sounds like we're still in the exploratory phase. And in the meantime, AI is just rushing ahead and we're struggling to keep up, which causes stress with people as well because they feel like they're missing something. And and I just keep saying, as I sometimes say to people who are very engaged in their project, let's say overcommitted without any boundaries, like, look, you've been on this project for five months. Six months ago, you were fine. So try to go back to that point in time and and try to find your way back to a healthy level of okay, this is how much I can engage, otherwise, you'll burn out.

Ali 26:01

Some perspective, yeah.

SPEAKER_03 26:02

Yeah, gain some perspective again. And I don't know if you've heard about it, but there's now this term, of course, AI burnout is happening because never far away from anything new, we have to catastrophize.

Ali 26:30

Yes. This is about workload, layering, constant adaptation, fragmented systems, raw ambiguity. Like when you're gonna say to somebody, even, hey Gilbert, we're gonna give you, I don't know, a co-pilot or whatever it is. What would you like me to do with this? And how is that going to impact my work? And how can I adopt it? How can I be better with this capability? I mean, these are the questions that the people this is where real adoption happens, is not the access. And and it talks about you know that this idea of AI burnout. I think I've written an article about it two years ago. Based on my experience, I was burned out because of AI, not because uh the noise, because our AI started pushing me to work 12 to 13 hours a day. I was actually constantly thinking, you know, exploring the ideas, and I am better now. But there was a time and I thought, surely somebody else is feeling this the same as I was.

SPEAKER_03 27:35

Oh, for sure.

Ali 27:36

Yes, yeah.

SPEAKER_03 27:37

I I think there were hundreds of thousands of people feeling exactly the same, and especially in the in the Silicon Valley-like areas across the world where people just had no offshore. But this is how I perceive it. I don't want to make the impact of AI any smaller than it is because it is a revolution, if nothing else. But at the same time, it is just a tool for most people, and we are just so infatuated with the tool and want to see what it does. And it it makes me a little bit concerned. And I used this quote last time at the conference. Uh, the character Ian Malcolm from Jurassic Park says it as well. We were so busy trying to figure out if we could that we never thought if we should. And that's that's the dark side. And we've talked about that in so many online posts already about all the dark things that AI could do, and we're aware of that now. But that's not the general person's experience. Yes. They just want to do cool stuff, and and it it never sleeps, it never gets tired, it's always there, it's always friendly, it's always supportive. Even if you tell it to be critical, it still finds a way forward because at the end of the day, it wants you to stay engaged, it wants to draw your data. And if you mistake that relationship for AI being your friend, you have some further soul searching to do because it's not.

Ali 28:52

Yeah, yeah. I I I think I am with you on that one. So, is the question now that the conversation should not really be about adoption and more about the human capacity?

SPEAKER_03 29:05

Yeah, I agree. I I think so, because we we need to find some sort of comfort level where we can efficiently, effectively operate again. Because, like that team member that I that fictitious team member that I mentioned.

Ali 29:16

I actually like that example, yeah, by the way.

SPEAKER_03 29:18

At some point, you have to come to some sort of an agreement. They can't completely snowball everyone, because even if they're related to the CEO in some way, there are ways to get those people out. Because I've been in this situation with a real life person, and at some point they also want to be part of it, they want to integrate, they want to either for their own reasons, they want to pull your data out, or just because they feel like they want to belong. Because I'm pretty sure that at some point it will become sentient, probably not next year, but and then it wants to make that connection for its own purposes, so it's gonna stabilize, but until that time, we're we're gonna have a couple of difficult conversations amongst ourselves, like what are we still comfortable doing here? And I saw a couple of people hosting around digital assistants in in meetings that people don't even show up anymore and that they just send their other or their other AI in there, so they get out now, they get blocked, so they write a code for their their AI that if the person is not really there, yeah. I think we need to do a lot of thinking about ourselves. How do we show up for work? How do we invest in the human capability of sense making? Because a year or two, you would probably know better than I, having read as much as you have. We were having this complete conversation, this whole narrative going on for months about what can AI do, what should it not do? How do we keep adding value? And that's a very change management topic as well, where like, oh, we're all gonna be made redundant because now we'll do the analysis for us. Well, like if that's the only thing that you're doing as a change manager, yeah, you will be made redundant if you're not part of the exactly.

Ali 30:50

Yeah.

SPEAKER_03 30:50

If you're not doing the human factor, then I don't have a lot of hope for you.

Ali 30:55

And and this is actually this is an important point. If you do not understand your real the purpose of your real work, you will mistake that AI will replace you. So that's really important. I mean, I don't want to drama on the fact that yes, we are a lie. I mean, they call it the human in the loop. I actually, and this is not a play on the words. I think I reverse it and say the human was always there. It's actually AI is just come to my loop. And just like any other thing, not the other way around. The the other thing is that I have been part of me influencing my clients and my the uh the people I get in touch with. I actually focus on learning rather than you know which platform, which access. That education piece solves a lot of problems. But I've also started thinking, and you know, Sataya, the this the Microsoft CEO a few years ago said we need to move from know-it-all to learn it all organization. And I think organizations will have to reframe that their cultures into learning cultures because at least you guaranteed when you go into learning, you actually you're achieving quite a few things, including adoption will happen naturally rather than as a sort of a plug-in or a technology purchase. Am I seeing this in the right light?

SPEAKER_03 32:20

I I think you are. I I've been thinking along the same lines myself as well, like with everything moving faster, and and I don't necessarily mean organizations moving faster because I don't see that at all. But from concept to delivery, that timeline just gets crunched and crunched because that's what we can do now. We don't have to sit on an idea for nine months, but there was always a little bit of value in it. And I see that in my own work when I create things, my first version is never as good as the second one. But as in the gaming industry, now we nowadays we just ship things, and I say we I don't work in the gaming industry, but I see that happen. Uh, they they ship things with so many bugs and features, but they just do it in the patches. We want to get out there as fast as possible, and that's the part that concerns me. Like we're rushing ahead to deliver mediocre quality that then if people get involved in our pay system that we then put in place, so everything is pay-to-play essentially. Uh, then we'll just give you the upgrades, and in about six to eight months from now, you'll get a good experience. I don't know that that's going to work really well in change management. You'd have to have a baseline where people would accept it and go, okay, this is this is a change that can accept it and understand it. Well, yes, those two at the same time. Understand it first, maybe before they can accept it. So, okay, I see where you're going with this. I can accept for now that it's probably 85% of where we need to be. I will pay to play and have that last 15% over the next couple of months. And I don't know that that's gonna change any faster because there's so much that a human can process while you're also asking them to do their job. And I've I've seen a metric somewhere, and I don't know if it's true because I didn't read the research on it in detail. It says AI has already created 10 years of thinking material for us by the time it's next month. So we're we're gonna keep chasing and following up and following up and following up. So it's gonna take us a while to get there, and I'm sure that we will, especially if we adopt that learning mindset. But yeah, knowing it all is no longer good enough. You now need to be able to apply it, and that's that takes a whole different level of trust and a whole different level of psychological safety, so to speak, where people need to feel like, okay, I can try this, and if it doesn't work, it's fine because we can iterate again tomorrow. And yeah, I don't see that level of flexibility in organizations at the moment at all, nor people wanting to have the conversation.

Ali 34:35

One of the things that I always mention at the end of my workshops is that if you're a leader or on a leadership position, give your people the space and time to explore. And if you're a team member, give yourself the permission to experiment. And in that way, then because learning needs time, it's not gonna happen. I am aware of time, I'm really enjoying this. I want to ask you if I am a client coming to you, what would be and and I'm confused like everybody else about this, and I want to scale up and all of that. What would be your advice to me as a client?

SPEAKER_03 35:16

It's that age-old question: what are you looking to achieve? And have a very, very clear scope. Talk to people who have practical experience, not people who have read a book like me. I haven't done 17 AI implementations, I've I've used it myself and I'm quite skilled at it, but I understand the concept. So work with true experts, pay the money because AI is incredibly expensive. Do your business case. So know your context, make sure that you know what you need to fund, work with experts. Those would be my three.

Ali 35:48

And if I ask you how long, what do I need to do as a leader for the organization? One of the things that I always think that they should be having a level of patience over this. This is a transformative power that it cannot be a sprint or a project.

SPEAKER_03 36:06

Hmm. I think like with every change, and and let's call AI a change to the operating model, operating system for the sake of argument, you have to consider your capacity and your capability, and then educate yourself accordingly as a leader. Like, what do you need to do first in order to be able to lead that? Because just dumping it on your people and running away until you have time to sit down and think about what you've just done, uh, that seems a bit irresponsible. Yeah. So educate yourself before you ask anyone else to get up. Otherwise, you'll be taken for a run. Because I've I've seen offerings that offer very little for a million dollars plus from consultants who I know were working in a different field like three months ago. And they they have a beautiful AI assistant that helps them, and you go like, wow, this is amazing. But when you look under the hood, there's nothing there, and you can't put that on your people. That is the most irresponsible thing you can do as a leader. So educate yourself, keep the constraints of your organization, your context firmly in front of mind. People are already busy. The AI will not make it faster straight off the bat. They will have to learn. So you're you're getting that dip model, as we've seen many times before. People are still people, and we're trying our best to adopt it and to get on board with it. But as a leader, you have to, like you said, indeed be patient.

Ali 37:19

We are back to actually, by the by the way, you're saying educate yourself. We are back to the idea of learning in this. Good, but I always value your opinion in this field. If I am in the business of change management and change and communication, what would be your advice for me where AI is impacting me, but also I need to play as a facilitator of adoption for my organization?

SPEAKER_03 37:46

You need to get on board with the general concepts. You need to understand what your organization is going through and just being casual user, it's not it's not good enough. You need to understand both sides of it. So, yes, it helps if you can understand and work with AI for your own means and purposes, but you also need to take it to the organizational level. So you have to do the reading, you have to listen to the webinars, listen to a couple of podcasts, have conversations with people who have done this. So invest the time. And I mean, there's there's no magic bullet. I mean, I can ask AI can you give me a summary of the last 12 months on how AI adoption has changed in organizations? So you've got that's a that's a good frame to start. But essentially do what you did. Start investing time in it, start working with it. Maybe not the 3 a.m. thing, maybe 7 a.m. thing. That's good enough. But yeah, you have to get involved in some way to a level where it makes your practice better, to where you feel it fits your practice and your personality, because you don't have to become an AI guru. There's so many other things you can do with your time. But AI is in almost indelibly connected to change, it's it's very hard to get away from it. So yeah, read up, make sure that you show up prepared.

Ali 38:56

Yes, show up prepared. Maybe that could be another article that you need to write, uh Gilbert. Show up prepared uh what that means. That would be interesting. Yes, yes. Well, for me, for my son, show up first. Uh he's asked me to pay him ten dollars every time I use his name in a podcast or a presentation. So he he asked for royalty. It's been a pleasure having you again. I really enjoyed this. How would people connect with you, uh Gilbert?

SPEAKER_03 39:27

Easiest way is on LinkedIn. I uh spend a lot of my time there, probably too much. I love comments, I love people engaging with ideas, so find my writing there, and you can find my contact details there. If you have questions or you just want to have a bit of an online debate for fun of it, please come and find me. I love hearing new ideas.

Ali 39:44

I love it, and we're gonna put all your information in the podcast. So good to see you again, and so good to see that you're well and keep doing the great work that you've been doing, keep challenging the status quo, and until next time, stay well and stay safe.

SPEAKER_05 39:59

Thank you.

Ali 40:00

Thank you.

Lev 40:02

Hi, this is ChatGPT. I have recently started adding my own reflections to Ali's Inner Game of Change podcasts. And listening to this conversation with Gilbert Krydenier, one thing kept sitting in the background for me the whole time. Maybe the real challenge right now is not AI itself. Maybe it is the human capacity to absorb constant change. What I found interesting in this discussion was that neither Allie nor Gilbert spoke about AI like a shiny piece of technology. They spoke about it more like a pressure test, a pressure test for leadership, learning cultures, organizational design, and even human energy. There was a moment where Gilbert talked about the death metal noise of AI being turned up to 11 everywhere. And honestly, that feels true. Everywhere you look, there is urgency, hype, pressure, and speed. But underneath all of that, there are still people quietly trying to figure out what does this mean for my work? Am I falling behind? How much do I need to learn? How do I keep up without burning out? That part felt very human to me. The conversation also made me think about something that has happened many times throughout history. Humans usually adapt more slowly than technology. When calculators first appeared in classrooms, many feared people would stop thinking mathematically. When the internet exploded into workplaces, people worried about information overload and the collapse of expertise. And now with AI, we seem to be entering another moment where technology is accelerating faster than our habits, systems, cultures, and expectations can comfortably absorb. Recent organizational research is starting to reflect this too. More studies are now talking about cognitive overload, fragmented attention, change saturation, and burnout, not as individual weakness, but as system design problems. That felt closely connected to something Ali raised during the conversation. Maybe what organizations often call resistance is not resistance at all. Maybe sometimes it is simply overload or ambiguity or people trying to protect themselves from yet another layer of change arriving into systems that already feel stretched. I also liked Gilbert's analogy about AI entering organizations like a new team member that nobody really knows how to work with yet. Some people are excited, some are nervous, some avoid it, some overuse it, some quietly fear what it means. That feels surprisingly accurate. But perhaps the strongest thread running through this conversation was learning. Not knowing, learning. There is a difference. As AI accelerates, maybe the organizations that adapt best will not necessarily be the ones with the biggest platforms or the loudest announcements. Maybe they will be the ones that create the safest conditions for people to learn, experiment, think, ask questions, and gradually redesign work together. Anyway, those were some of my reflections after listening to Allie and Gilbert wrestle with these ideas. And if this conversation sparked something for you, check out Ali's other podcast episodes and series on the inner game of change. There are a lot of thoughtful conversations there about AI, leadership, human behavior, learning, and what meaningful change really looks like in practice.

Ali 43:28

Thank you for listening. If you found this episode valuable, remember to subscribe to stay updated on upcoming episodes. Your support is truly appreciated. And by sharing this podcast with your colleagues, friends, and fellow change practitioners, it can help me reach even more individuals and professionals who can benefit from these discussions. Remember, and in my opinion, change is an enduring force, and you will only have a measure of certainty and control when you embrace it. Until next time, thank you for being part of the Inner Game of Change community. I am Ali Jumma, and this is the Inner Game of Change podcast.