← Embracing Digital Transformation
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- [00:01]
A
And so the pressure for CEOs isn't only figuring out how do I invest wisely and get transformation or change going at a different rate in light of all this emerging tech, but how do I also satisfy shareholders and board members who are asking questions consistently about when are we going to see a return?
- [00:22]
B
Welcome to Embracing Digital Transformation, where we explore how people process policy and technology drive effective changes. This is Dr. Darren, Chief Enterprise architect, educator, author, and most importantly, your host. On this episode. Overcoming Transformation Fatigue in the Age of AI with Alex Adamopoulos, change agent and CEO of Emergen. Alex, welcome to the show.
- [00:56]
A
Thank you for having me. Excited to be here.
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B
Yeah, this is going to be a great topic because we've been going through so much change over the last six years. Covid Hits OpenAI Releases ChatGPT what? Two years and nine months later, two and a half years after Covid hit, we've been going through a lot of change, a lot of transformation. We're going to talk about transformation fatigue today and AI and all that. But before we drop into that, everyone that listens to my show knows a little secret. I only have superheroes on the show. Don't tell anyone else, because all the other hosts out there are totally jealous. And all of my superheroes that I have on the show all have a background story, an origin story. So, Alex, what's your origin story?
- [01:47]
A
My origin story? Well, I came to the US in 1971 from Greece. My father was in the shipping industry and had to leave Greece due to the 1968 military coup that happened in that country. Otherwise, I would have grown up in Greece and who knows what I would be doing, but have been an entrepreneur from a very young age, have always had a desire to experiment and work in industry, travel all over the world, and all those things came to fulfillment as I got older.
- [02:21]
B
That is awesome. What a great background story from. Were you on the mainland of Greece or were you off on one of the islands of Greece growing up?
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A
So I was born up north in Thessaloniki, the second largest city of Greece.
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B
Yeah, I've actually been there, so.
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A
Oh, fantastic. Great city.
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B
Such a beautiful place.
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A
It is, but.
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B
All right, we could talk about Greece and all that, but we need to talk about this real problem that we're seeing out there. There's been so much change going on. I'm sure you've seen it. I guess we could call it transformation fatigue. Is that a good name for it? Yeah, probably. Transformation fatigue. Are you seeing that out there with your company and what you guys do?
- [03:10]
A
Yeah, that's what we call it. I mean, we wrote some research to years ago on that topic. There's a lot of it. People are tired. I mean, even seeing companies like Glassdoor named fatigue their word of the year last year, which I thought was interesting, but there's a lot of it. People are tired, people are weary. Maybe they're not all articulating it that way, but change is hard. And as you said early on, we're moving at a pace that we just can't keep up with.
- [03:43]
B
Well, but if we don't keep up with the pace, don't we fall behind? Isn't that the big fear that everyone has?
- [03:52]
A
Logically, yes, but we're all overwhelmed. I mean, I personally, I mean, every time I scan my YouTube channels and I see all the AI stuff that changed in the last 24 hours, I get this anxiety thing come up where I'm like, how in the world am I going to keep up with this stuff when I just spent like the last week learning this other thing, so. And now you magnify that, you know, at the, at the company level. And I think people are having a tough time figuring out how to keep up.
- [04:22]
B
Do you think that's one of the reasons why we see a lot of CEOs kind of paralyzed? Because I see that a lot of companies are like, I don't exactly know what to do.
- [04:35]
A
Yes. And I think it's getting worse. Two, three years ago, Gartner did some research on the democratizing digital, I think was the phrase. And basically they were saying how digital budgets are now at the boardroom level. Board members want to know how you're going to spend money on all this AI stuff and all this digital stuff where they didn't really care so much prior. I mean, they cared, but it was more of like, that's the CIO's issue or the CTO's issue. Now it's everybody's issue, you know, and so the pressure for CEOs isn't only figuring out, how do I invest wisely and get transformation or change going at a different rate in, in light of all this emerging tech, but how do I also satisfy shareholders and board members who are asking questions consistently about when are we going to see a return?
- [05:28]
B
Well, and it sounds like AI is kind of just exacerbating the problem.
- [05:32]
A
Right?
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B
Because as you said, it's changing so quickly. How can you get a return on something that. It's like chasing mice in your garage. Because we have mice in our garage sometimes. Right. I lift up one box and mice scurry everywhere. And I'm just chasing one of them.
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A
Right.
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B
I mean, I can't get all of them. Can't get them all. That's kind of what AI feels like right now.
- [05:56]
A
It does. And when we did the research a couple years ago, we didn't realize how much that would spark interest in terms of conversation in our community and in our client community. And then the following year, we did the same research, but we applied AI to it by saying, okay, well, fatigue is one thing around transformation, which is a tough buzzword. I don't know what you're saying, but some frustrated people in our community have said, I don't want to hear the word anymore. Because what we really should be saying, it's continuous change. Which is true. It is true. And it's a better way to say it, actually. But when we applied the AI lens last year, we applied it from the perspective of, well, are we getting any ROI on AI investments? And if we're not, how does it relate to fatigue? And what we learned was it's compounded the fatigue because there was a perception or expectation that if I start introducing these kinds of tools into my organization, I'm going to go faster, I'm going to go smoother. And it's actually, it's introduced a layer of complexity no one was accounting for. Meaning the people's skills and their ability to adopt new tech wasn't as quick as everybody thought it would be.
- [07:26]
B
Oh, so that's really interesting. That ability to adapt for individuals ends up being a skill that can hamper the adoption, obviously, of new things. But it's also leading to that fatigue.
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A
Right.
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B
If people are like, I can't handle this much change. AI is actually a magnifier here.
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A
Right.
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B
Because it's changing so quickly. It's this death spiral, it sounds like, for individuals.
- [07:56]
A
Well, again, I'm assuming you're seeing the things I'm seeing. Right. So I was amused to see job postings for prompters. And I thought, what's a prompter? You know, and a prompt. Companies are looking for people who have really mastered the art of prompting LLMs, just. Just so they can get people in the door that can do analytics on these platforms. Because, for example, some companies have consumption licenses to LLMs. So it's not all you can eat, it's all you can pay for, right?
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B
Yeah, yeah.
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A
If it takes you five prompts to get a complete response, and it's taking me 35, we're paying for both. And so that's just at An LLM level, gen AI level. And of course, now we have so many other levels of these technologies being implemented, but it really is impacting the ability for CEOs to stay ahead of change and investments. And I don't know if you saw it, but HR executive put out an article that said change fatigue is now one of the top five reasons for organizations not to succeed. In other words, it's one of the top five barriers to success. So they've officially. Someone officially gave it like a category now.
- [09:19]
B
Oh, that's amazing. Do you think that's because executives and management haven't. They're kind of following the shiny objects too, that they haven't given a straight line or straight path forward because it is too disruptive. They don't know which path to take. So what happens is, oh, we're doing this this week and we're doing this this week, and all this constant thrashing. Do you think that's going on as well, or do you think it's just, we've got direction, but there's so much being glommed onto it that it's. It's just wearing us down?
- [10:00]
A
Well, if I can take it back, I mean, I don't remember the exact name of the study, but in the late 60s, I think it was in 1969, there was a study done that produced an education model called the 70, 2010 model. And that model is interesting because it's never really become outdated in principle. What it taught was 70% of learning happens when you and I are working together. 20% of learning happens when we're kind of in the room observing, and only 10% of learning happens in a classroom. And yet if you look at our education model, we flip that.
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B
Right.
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A
The majority of things, our education model is the opposite. Yeah, it's the opposite.
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B
Right.
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A
So when we do our work and we're thinking about transformation fatigue or big change programs, we come at it from the perspective that you have to work with people's mindset first, because getting them to think differently about work, completely differently about work, is actually more important than trying to convince them how they should use AI, for example. So we think it's symptomatic of a bigger problem. The most sustainable competitive advantage anybody has is the way they work, not the tech they use. And this is how we're trying to solve the fatigue problem by getting. Getting people out of the frame of mind of this is how we always did it. This is how we grew up doing it. Because there's just too much evidence now that if you do things differently, you can get better results. And this is irrespective of whatever tech you're spending money on.
- [11:46]
B
You know, I totally agree with you on this one. That's why on the show we always say leveraging people, process policy, and technology. Technology's last. And the people part is first. And I love what you said there. It's the way we work. That's our competitive advantage.
- [12:02]
A
Yeah.
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B
Not the tools that we have. So this is, this is really, this is really profound. So how do we start making this change, Alex? Because if, if we don't, we're going to start seeing a lot of burnout. We already have, both as an individual level and as organizations. You're going to see organizational burnout where an organization can't function anymore because collectively they, they're, they're, they're burnt out with all the change. So how do we, how do we prevent this from happening?
- [12:47]
A
Well, I mean, again, in our, in our world, we, we see that fear kills more transformations than failure does. People, you know, don't know which path to take or they're not sure around how to speak up or take initiatives in some cases. And part of that is also because corporate culture has conditioned them to operate that way. So one of the, one of the things that we definitely emphasize, and this also comes out of Amy Edmondson's research. Amy Edmondson, of course, is one of the top business professors in the world out of Harvard. We wrote a paper with Amy last year on this topic called Breaking the Failure Cycle and talking about how product led organizations can actually overcome fear and fatigue. In the spirit of not throwing out another buzzword, what is product led? It's this whole idea of being able to frame a problem first, have a mindset of doing more discovery and experimentation around the things you're trying to solve versus just jumping in and spending money on tools and thinking it's going to get solved itself. And also creating environments where you're not punishing people for taking intelligent initiatives. I mean, there are some, there are some things that people do we could call sloppy work. They haven't thought it through correctly. Right, right. But we tend to punish all failure the same, and it's not the same. Intelligent failure is almost a calculated risk and a discovery mindset. We're going to go do this, we're going to learn from it, and that's a good type of failure. Basic failure. That's kind of the sloppy stuff. When someone just doesn't really can care enough and does something that maybe doesn't Land. Well, but the, the conditioning of companies and the mindset and the culture around how they work is really what you have to start addressing first if you're going to see people move forward.
- [14:52]
B
Well, I, I like the fear that. The fear designation, I think, is really interesting and cool because we're seeing something interesting with generative AI. Generative AI is giving people that used to do sloppy work, polished sloppy work. Right. Because Gen AI does a wonderful job at polishing things up, even though maybe you didn't do all your deep research on a decision that needed to be made. And it looks good, but then once you get into working it through, you find all of the sloppiness once you delve into it deeper, so it's a little more insidious. I think it's hiding some of that. That's going to be a really difficult thing to distinguish between those different kinds of failures. As you mentioned before, it was pretty easy to see someone didn't do their due diligence. Now they can hide it behind pretty pictures and diagrams and outlines. Right.
- [15:57]
A
And you raise an interesting point because the real, I think the real crux of what we mean when we say product led, it's not about the product. It's really about capability development. It's really about helping organizations acquire the thinking and the skills to think. Like modern, you know, modern product managers. Not product managers as a title or a role, but as a. As a craft. You know, in other words, everything from ideation through to experimentation through to production. How do I think of things in cycles, irrespective of the tools? And I think this is the thing that we're trying to emphasize a lot. We need to be careful about AI, because a few years ago it was RPA and before that it was something else. So in two years, we're not going to. Maybe we won't even say AI. Maybe we'll have something else to say. It won't change the fact that capability development and Brett built into teams is much more effective if you want it to be sticky. It's that whole lifelong learning mindset that companies need to slow down in order to go faster with.
- [17:12]
B
So. All right, so that brings up a really interesting point. A lot of workers are sitting here on a precipice of their careers. They're like either starting or the mid, mid part of their career. And if it's the way I work, that means there's some skills I could learn on how to do this appropriately, that continuous learning attitude. All right, I get that, but let's Talk about the individual and then I want to talk about the team and then the organization. Okay. As an individual. All right, what, what, what are my first steps here? Do I, do I learn how to work in a specific type of career? Do I double down on being really good at a certain type of career with the danger that career may be going away? Or are there some general skills that I can build up that I could now apply to different types of careers as the career sorting is going on? Do you see where I'm going with that, Alex?
- [18:14]
A
Yeah, I think I do. Okay, let's roll it back a little differently. If we assume that AI is the future for everybody to some degree, and to do our jobs we have to have some interaction with these tools, which I think is fair to say in most vocations this is going to become quite. Right. Right. Quite common. Then what makes it most impactful and successful for me as an individual? How do I get the most out of the requirement to take a job where these tools are going to be part of my everyday job? Okay, so I look at what people like Andrew Ng says from Stanford, who's the co founder of Coursera. Right. And he's one of many who have made this statement, and I'm paraphrasing, not word for word. AI is not about coding. AI is about product management. And there are dozens now of articles around coming from all kinds of organizations, HR groups, the World Economic Forum said this about product management, their future of jobs report. You know, MIT and Sloan have produced data on this, that the ability for people to frame problems and think like product strategists is going to be much more important than anything else, regardless of their background or education. So if I want to become a lawyer, if I want to become a doctor, if I want to get into manufacturing, yes, I need those specific skill sets. But I have to bring that product mindset to those jobs in order to be effective. Especially given that I'm going to be using AI related tools to do my
- [19:56]
B
job or, or other new technology. What, what is Quantum gonna do to this whole space?
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A
Right, Exactly.
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B
Another thing as well.
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A
Yeah.
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B
All right, so I like that, I like that. So we need a, a problem solving problems, problem scoping skills. These are fundamental types of skills that you could apply across, across everything. As a doctor, you know, what, what capabilities, what services am I going to deliver? Right. In manufacturing, easy product and capability delivery lawyer, same thing. So I like this mentality that you're starting to come across. How do I now take that from an individual? Can I Just apply that across the board to teams and organizations as well. Then it sounds like I can.
- [20:50]
A
Well, you can. And there are several techniques that have been in the market for some time, not only introduced by people like us, but people that have written great books about these things. It's just knowing how to bring it intelligently together and also construct an environment. I just want to keep going back to two principles here. One is the mindset shift that has to happen. So you're asking people, okay, here's a good example. If we've all grown up with the mindset of project management, then one of the principles of projects is certainty. Start date, end date.
- [21:30]
B
End date. Yeah.
- [21:31]
A
And everyone who does project management will tell you there's no such thing as certainty because we don't typically hit dates and we don't hit budgets. Right. So teaching people how to live in a world of uncertainty where it's not so much about hitting the date as much as it is about experimenting and incrementally delivering value over a period. I kind of liken it to the shark tank mentality. What if instead of projects that have some 12 month, 18 month end date or some transformation programs that go out two years, what if we didn't just sign off on a big budget for them and said instead, here are the milestones we have to hit in order to keep validating. We're doing the right thing. And let's say with those milestones have to be in 90 day increments. So every 90 days you have to come back and demonstrate that we're driving something forward, the output and the results matter. And why do you have to do that? Because then I'll give you the check for the next 90 days.
- [22:32]
B
So this is very Agilesh, right? I mean, this is what Agile is all about, right? Is hey, incremental improvement and things like that. But we all know there's some downsides to Agile, right? One of them is technical debt, right. That I build up. Right?
- [22:51]
A
Right, right. But I'm not talking about Agile in the sense of an IT methodology like Scrum. You're talking more around. I'm talking more around business agility. Not agile the methodology, but business agility in the way we work. Which means you're my cfo, I come to you and say, hey Darren, I delivered this milestone last quarter like we, you can see that what we need to do is gonna work. Yeah, I need, I need you to keep funding this because here's the other thing, right? And you'll hear this from innovation leaders all over the World. The number one thing that executive teams struggle with when it comes to, you know, new programs and new ideas is knowing when to kill them. If you can't kill an idea fast enough and you keep burning the cash, which we've seen in so many examples, we can go back to the dot com era, back in 2000, then you have the age old problem of not knowing when to. So really what we're saying is it's around incremental value delivery, not just throw it over the wall, write a check and see what happens. So that would be one example of project versus product mindset. Product mindset is around incremental value delivery and a little bit of uncertainty because we know we have to keep discovering and demonstrating along the journey Versus here's a project plan, here's a big check. Hope we hit the timeline, right?
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B
Yeah, yeah, yeah. Okay, so that's a mindset change. I love that. All right, what's the next thing I can do?
- [24:38]
A
Well, the next thing that we would always recommend someone would do, whether as an individual or a team, is familiarize themselves with the tools that you would need to be able to use in order to bring that mindset to life. So how do I demonstrate I have the mindset? I might do something like, you know, in modern vernacular around modern product management. I might build a business model canvas. I might develop ideal customer profiles or icps. I'm going to develop core value propositions. The most important thing I can do is develop experiments that will help me go test my hypothesis about my product ideas. You know, and if I do these things, I'm going to get feedback and results that I wouldn't get if I just followed up a different kind of path.
- [25:35]
B
Okay. So that tells me that there's a bunch of methodology and tools or mechanisms that I want to use when most, most my audience, when they hear the word tools are thinking, oh, I'm going to go learn, you know, chatgpt or I'm going to go learn Microsoft Project or. But you're talking about methods, methodologies, techniques. These are the sorts of things that you're talking about with tools, right?
- [25:57]
A
Yes, that's correct. I'm not talking about Microsoft Office or LLM. Right, you're right. That's a better way to say we're talking about methods and techniques that you use to demonstrate the thinking and demonstrate the practice.
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B
So to me that's building up like that subject matter, expertise. These are core fundamental skills that I need regardless of the underlying technology. Right. Critical thinking, planning, trade off, analysis, all these Sorts of things are important skills that all fit into these types of methodologies. Because these methodologies, I'm familiar with some of them, they kind of reinforce those key principles that you've already talked about.
- [26:43]
A
They do. And organizations that are truly moving to that product LED model or, you know, maybe have arrived. What they've done very well is they've collapsed the silos of the organizations and they've brought together people from all functional departments to work around a product idea. Right. So if we were together and I was drawing on a board, I would draw you a traditional, like comb. You know, the top of a comb is like a long arc and underneath you have all the. Oh my gosh.
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B
Whatever they're called.
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A
Yeah, whatever they're called.
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B
Right.
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A
There's a name for those things. And anyway, the, the top of the arc of the comb is the product. All the, all the things inside of it, all those little blades are the individual projects that you need to complete to build the product. That's the visual I usually will draw for people. Because organizations are focused on the individual siloed projects most of the time and they're in teams. But we ask people to take a step back and look at the product we're trying to build, bring together stakeholders from across the business that have to work on it, sales, finance, marketing, et cetera. And that's where you start applying these principles. And that's what actually starts collapsing the silos. That's what actually has a massive effect on morale and culture and gets people to deliver outcomes. Not just output, because we get a lot of output, but sometimes we don't know how to measure it.
- [28:28]
B
I really like this, this shift though, I've seen before. I mean, because we've seen this in organizational management before. Vertical structures, horizontal structures, matrix structures. This is a matrix, but with a little bend to it, which is the outcome. I love that. Outcome based delivery, not output based. So that's a mental shift for a lot of people. But this is really a matrix. A matrix organization is what you're talking about, or are you talking about verticalizing organizations with It's.
- [29:09]
A
Yeah, it's less matrix, it's more vertical.
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B
Okay, okay. So taking something that was there before, kind of smashing, breaking down the silos and going vertical with a different mentality.
- [29:26]
A
Right. And you mentioned agile before. Like in, you know, 15 years ago, when everyone was doing agile transformations. Really what an agile transformation was was a transformation of the IT organization, not the IT and the business organization. Correct. Although some people would argue with me and say, oh no, no, we did the business. Well, you didn't really. You might have touched some roles on the business side, but it wasn't a true like enterprise or department wide transformation.
- [29:57]
B
Right.
- [29:58]
A
So in respect of that, if you have, you know, a change program just within that silo, then it's just going to stay within that Nucleus. It's not going to really go out. I do think going Back to the 70, 2010 model for a second, because one of the key things you embed in an organization is not just this idea of continuous learning, which we throw around this phrase a lot as well, another buzzword, but it's this idea of work based learning. In other words, learning while you're applying these principles on real work. That's why we've been massive fans and proponents of this 7D 2010 model. Because 70% of that learning is happening when you're working alongside people, applying all this new thinking to your words, these methods and techniques on real work, not putting them in a classroom and sending them back to go do it.
- [30:57]
B
So you know what this is telling me, Alex? It's telling me we need to re establish stronger apprentice type programs or mentor type programs because we've got a lot of junior people coming in to the marketplace. If we use this 7020 10, that means I could assign junior people with senior people and improve productivity and Invest long term, 100%.
- [31:27]
A
You know what a real good example is on the AI side? Are you doing any Vibe coding yourself?
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B
I've gone beyond Vibe coding already. I'm like full blown. I've got agents out there coding with me and.
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A
Yeah.
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B
So. Yeah, yeah, yeah.
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A
All right. So the wonder of Vibe coding is that anyone can do it. And now you can get non technical people involved in coding an idea because they prompt the software like it's an LLM.
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B
Yeah.
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A
And they can build something, you know. And now, now it's easy for a C suite person to vibe code a new product idea with finance in the room and marketing in the room and it in the room and help bring that idea to life a lot easier than it was obviously two years ago. So I find the Vibe coding example good because it's a demonstrable way to say, look how that brings everyone together from the SME, who's the person who's got the idea, who's never coded a line of code in their life.
- [32:25]
B
Right.
- [32:25]
A
To the organization that has to be responsible for building it.
- [32:29]
B
No, I like that idea too. As long as we take Vibe coding as a prototype and to work out all the interaction but taking Vibe coded projects to full production in the new.
- [32:41]
A
Oh, no, that's not a good idea.
- [32:43]
B
That's not a good idea. I just want to make sure my audience doesn't go that route.
- [32:47]
A
We're not suggesting that. We're saying it's a good ideation tool for sure.
- [32:50]
B
Ideation tool. Oh, good, Alex. That's good.
- [32:53]
A
Thanks for the clarity.
- [32:55]
B
This has been wonderful. I've learned so much today. I appreciate you coming on the show, but we're out of time. So if people want to learn more about you and your company, where do they go? What does your company bring to the table to help in this problem space that we've been talking about?
- [33:14]
A
Well, for 17 years, we've been doing everything we just talked about for companies. We were considered leaders in the industry on establishing product led companies, everything from capability development to building their operating model and also how to use the use of AI. Actually, we were so frustrated with how do you get more people to do this stuff that we built a platform and an AI model that sits on top of it that is a product management platform for people to learn and do this work. And it's called Praxis. But anyone can go to emergent.com and learn more about us or just reach out to me. I'm just Alex. Emergent.com I'm easy to find.
- [33:56]
B
All right, Alex, this has been wonderful. You're opening my eyes to new things and reinforcing things I already believed, which is always makes me feel good, right? Like, oh, I have the right mindset or at least someone else thinks I do. So that's. That's good. Again, thank you for coming on the show.
- [34:13]
A
Thank you for having me.
- [34:14]
B
I'm really grateful.
- [34:15]
A
Thank you.
- [34:18]
B
Thanks for listening to Embracing Digital Transformation. If you enjoyed today's conversation, give us five stars on your favorite podcasting app or on YouTube. It really helps others discover the show. If you want to go deeper, join our exclusive community@patreon.com embracingdigital where we share bonus content and you can always connect with other change makers like yourself. You can always find more resources@embracingdigital.org until next time, keep embracing the digital transformation.