Andreas Welsch: 0:21

Today we'll talk about leveraging the AI hype and disillusionment to drive business impact. And who better to talk about it than someone who thrives in that environment, Lasse Rindom. Hey Lasse, thank you so much for joining.

Lasse Rindom: 0:34

Hi Andreas, and thank you so much for having me today.

Andreas Welsch: 0:36

Awesome. Hey, why don't you tell our audience a little bit about yourself, who you are and what you do?

Lasse Rindom: 0:41

So my name is Lasse Rindem and I am a, first of all, an automation pioneer. I've been working a lot in automation for the last 10 years. And I am the current AI lead at Danish consultancy, BASICO, where I drive our go to market efforts on AI and also on some automation and I also run the podcast the only constant where I've had you Andreas also as a guest. So that's really nice.

Andreas Welsch: 1:08

Awesome. We've been in touch for a long time. So it's always great to connect with you and now I'm looking forward to sharing that with our audience as well. Don't forget to join the waitlist for my upcoming book, the AI Leadership Handbook at aileadershiphandbook.com. I'm keeping it simple. So with that out of the way, Lasse, what do you say, should we play a little game to kick things off?

Lasse Rindom: 1:29

Let's do that. I know you always do that, Andreas, I'm quite intrigued to see what you'll come up with this time.

Andreas Welsch: 1:35

Alright, this game is called In Your Own Words, and when I hit the buzzer, the wheels will start spinning. When they stop, you'll see a sentence, and I'd like for you to answer with the first thing that comes to mind, and why, in your own words. To make it a little more interesting, you only have 60 seconds for your answer. Folks, for those of you in the audience, please put your answer and why in the chat as well. Lasse, are you ready for what's the buzz?

Lasse Rindom: 2:01

Yes, let's do that.

Andreas Welsch: 2:02

Okay, perfect. Here we go. If AI were a movie genre, what would it be and why? 60 seconds on the clock. Go.

Lasse Rindom: 2:14

It's actually quite simple because it the first thing I think is sci fi, right? It has to be science fiction. Also because and this is something I spoke to some other people on my own podcast about that AI is, the only technology we have today that has its own Hollywood genre, right? It's not like we're going to see, we have these, what do you call it? ERP movies with Sean Connery and Tom Cruise running around, or the BI, Keanu Reeves. We don't do that, but we have AI as a whole genre. There's tons of movies about AI going wrong or doing good. And that also means it plays a lot into the imaginations of people and also into the assumptions people have getting into this, and perhaps also, both add to the hype, but also add to some of the disillusionment that we're seeing in the market as well, this whole genre thing. So that's obviously sci fi definitely.

Andreas Welsch: 3:08

I love that answer, but don't underestimate the budgets that some of those vendors have to create even shorter videos for more. I love that that we're not seeing ERP or BI movies but never say never.

Lasse Rindom: 3:21

Let's hope it's not some boring documentary about a budget overrun, right?

Andreas Welsch: 3:26

Yes. Perfect. So we'll make sure that the next 25 minutes are anything but boring. And, if we look at some of the recent coverage, whether it was Gartner just the other week saying that they expect about 30 percent of Generative AI projects never to make it out of the pilot stage, never to make it into production. I think it was Morgan Stanley a couple of days earlier saying there's so much more investment needed in this market. And let's tone it down a little bit. Maybe it's not delivering all the value that we expected so quickly. It'll take some time. You've seen this before, whether it was automation or AI. What do you think happens next when the industry is somewhere between that AI hope and AI hype?

Lasse Rindom: 4:13

So I think that if you only say 35% it's actually much better than what we saw with something like RPA, where it's 70% that didn't make it. We talked about back then, the POC cemetery, and that's a phrase that some of us would have hoped we wouldn't have to come up with again. I start talking about again, but unfortunately that is happening and it's not that difficult to understand why, right? Because we're giving people a novel capability tool that's actually very techie. It's very nerdy. The things it does and why it does it is quite nerdy. And we're just saying, Hey, now you're more productive, have fun with it. So we are inviting people to make mistakes and try things out that won't work and we also letting those that lead the discussion be those that develop these tools, right? Someone like NVIDIA or OpenAI, they drive the discussion and the marketing around this. Who's hiring developers, right? That's NVIDIA. And who's hiring graphic workers? That's OpenAI. And you're like, but guys, don't you know the real world? And they don't, because what they do is they produce something that's like the produce airplanes, right? They don't produce airlines. It's up to us to translate this into airlines. So I think a lot of the misconceptions has come from that space here that we hear things that we're supposed to do with this. That's not really necessarily what we have to do with it because it doesn't. Technology has not really touched the world yet. The world has not touched the technology yet. It's still very fresh and very novel that way. But I also think these messages right now, that sort of smell of disillusionment, right? It's a winter is coming from the Game of Thrones thing. But the winter is only as cold as the summer was hot. So it's all relative that way. And, the hype we've had have been so massive, even my grandmother, I know she doesn't exist, but my wife's grandmother knows about this AI, right? Everyone knows about this. AI, everyone's talking about it. So the hype has been massive. And of course there'll be some disappointments there because it can't be like that. Nothing changes that quickly and thank God it doesn't, right? Because that would be incredibly insecure to live in that world as well. So I think that was a very hot summer, I could say. But I think also that most enterprises have, and this is just from the conversations I've had, kept a rather tight leash on the AI. Maybe they've done Copilot or they're giving people access to ChatGPT, but that's still been a limited investment for them, most of them. So I don't think that the hype is really hurting enterprises as much. Most of them have been playing a waiting game. We're used to, from older tech waves, to look at insurance or banking to see where, what they've done with it, because they've always been ahead. But this time no one's been ahead. Everyone has access to the same ChatGPT at the same cloud. There's no better models out there than the ones we have access to all of us. There's no one who's had it for 20 years. It's the same level we are, especially but the foundational models, obviously I'm talking about here. So that also means there was no one to look for, no one to imitate. So everyone's been playing this waiting game a little bit. Done doing some things, but not doing a lot. I think the ones that are going to maybe get a little bit burned here the investors who've been just investing in airplanes when they should have invested in airlines, that might be a real issue.

Andreas Welsch: 7:26

So yeah, real quick folks, for those of you in the audience, if you have a question for Lasse, feel free to put it in the chat as well. I'm going to take a look in a minute or two and pick them up, but keep on going.

Lasse Rindom: 7:35

Yeah, but I think also we have to talk about what is actually the real problem these models are trying to solve, right? The productivity claim is quite unspecific. I used to say that it's an unfalsifiable claim to say that you will use this AI than tomorrow, you'll be more productive. But the point is maybe I wake up tomorrow and I'm not more productive. I'm still just me. I haven't changed them. Oh so why haven't I changed there, OpenAI? Oh, that's because you are not using it correctly. And they can keep on saying that. So it's a free thing to say. It's not Karl Popper would probably turn in his grave with this kind of messaging, right? It's like saying you have a problem with your mother. No, I don't. Yes, you do. You just don't know it yet. It keeps on being on their terms, right? Instead of us saying that, okay, what do we actually want to do with this? What are the problems it's trying to solve? It's, I think the key issue is we need to turn these capabilities from being just an open model that gives us any type of AI we could possibly want into a platform that actually gives us a specific AI. So instead of talking about this, this very broad agents thing that can do anything. The undetermined, non deterministic thing that UIPath is also promoting and many other in automation spaces promoting non deterministic agents just give them your credit card and access to SAP and it will do everything for you. Let's maybe talk a little bit more about how we get them to work in. Be be specific. We want to have consistence, or, broad, because we can't do it all at once. And then, once we have all the stuff that we need, we can narrow it down to a few specific individuals, but we can't point in a role. That's where you get all the value from it.

Andreas Welsch: 9:31

That's awesome there were so many good nuggets in there. I don't even know where to start. There are a number of things that I heard. One was hey, we have technology players pushing the technology saying you can do anything and everything with it. We're not having enough debate about what exactly can we do with it? How do we want to do it? What do we want to do? So the old connection that's often missing between technologists and business people. How can we use it to really drive an impact? And I think something else that you mentioned about the winter really resonates with me as well. Yes, there is going to be some disillusionment that it's not as easy as everybody has been hoping or has been promising, especially those with financial interests in it. Doesn't mean that it's going to be like that.

Lasse Rindom: 10:15

But it looks like a UX, right? So everyone thinks it is a UX already. It's something you just interact with. But to be honest, none of us has really been used to interacting with a system that way and talking back to it and it's talking back to me and I have to talk to it. That's not how you go about systems, right? That was also why someone like Google who invented the transformer didn't win in the AI the race for this getting it out, because they thought people wanted accuracy and precision, but then suddenly people were like, oh, it's okay just to chat with something that makes some things up. But I think that the key is actually a lot to look in into the context of these models and the training data and what I said this. Multiple models they have in their stomach, because then you get to a point where you can see you, this can work on any type of unstructured data you have. And there's real power in that because it expands the potential footprint of your digital transformation. You can digitalize anything now with these models, because if they look at something, if you gave it a picture of whatever you do, and you say, what's this, put it in a tabular form, they will actually structure it for you and contextualize it because they have that context. In their minds, most of it, at least, that's quite big. I think that's really interesting.

Andreas Welsch: 11:25

Indeed, yeah. And I'm wondering as we're now seeing on one hand the hype and on the other hand the other side of the slope, the disillusionment, and figuring out where and how can we actually use this? What are you seeing? How can leaders leverage that momentum in the market to still drive business impact? And are there any particular lines of business to, Michael's point here in the chat, where you're seeing them leading or being front and center?

Lasse Rindom: 11:50

I think first of all how can they drive the leverage to momentum? I think it's impossible to miss the momentum. If you're an AI leader right now, you're not feeling the momentum. I don't know what you're doing. You must be living under a rock. Okay. That's one thing out of the way. But what you need to do quickly, it's actually to take the focus away from just. Just buying Copilot and not giving a shit like most other companies are actually doing just buy Copilot, throw it out there and then see what happens. You need to start working on building automation utilizing these well defined, narrow AI's that actually understands what they're doing, and then also train people to use the technology the right way. So the point is, as I said before, UX, but it's not just the UX and it's not simple for that reason. People don't know how to use it. The best use cases have been still with IT developers because they know how, what they're supposed to do with it, narrow it down, make sure it works on that code they know, and that's just intuitive for them. But it's not intuitive for everyone else. It's like with the low code revolution some years back, right? I've spoken to so many. I've said this for years as well, right? It might be low code or no code, but you still need to understand loops and if then and else and variables, you need to understand these things to work with it, and to some extent, it's not the same with the LLMs, but there are some things you need to understand on how to prompt engineer it. How many people have you spoken to outside of IT who says, it doesn't give me the answer I want, right? Tons of people, right? It happens all the time but I'm from IT. I understand. Oh, I need to ask directly into, I need to make sure it answers correctly. And you also asked me and Michael asked that in the chat, right? What line of business presents the strongest case? That's a really difficult one to answer right now, I think. My focus is very much on how we can lift the business support functions into something better. Cause that's what we do in my current company. We transform business support functions like payroll, HR, finance, the facility management, legal, those kinds of functions. But the obvious one is obviously marketing all the time. It's so simple to start doing things there. But I actually think that, what I said, the interpretation of more data, the controlling that we can do the if we ask any business leader today if you could get an army of interns tomorrow or 20 interns, what would you have them do? I would have them control all these invoices for errors and blah, blah, blah, blah, blah. And then we start getting something where it actually gets extremely productive, but because you can get these interns tomorrow using these models, right? Just define the role, have them look at your data and get some responses back. Controlling is immense in this, right? Also, on the other side, we're all going to be controllers as well. We're definitely not going to get out of a job. There's tons of things to control in an AI world as well, right?

Andreas Welsch: 14:29

Very true, right? It shifts from creating to controlling or to reviewing and guiding. What you said having a different interaction with these systems and making sure that they create output that you actually want and that you need, and that's better than me.

Lasse Rindom: 14:45

Yeah, exactly. And also Andreas, the unpleasant question in all this really, right? And the existential question for an AI leader or someone working in AI like you is if everyone gets more productive, is anyone really more productive?

Andreas Welsch: 15:00

On the other hand, what's that what's that expression, a rising tide lifts all boats. So there's some optimism in that as well. Now, again, with those corrected projections of, Hey, we're solving each and every problem with AI, AI will outsmart us by the end of the year. All those exaggerated claims. And now being corrected. Maybe not this year, but next year, five years, 10 years, who knows? How can leaders use still that momentum when the outside market, when the analysts, are saying, let's tone it down a little bit. Are they all just going to sit back and wait for the storm to pass? Can they even do that? What are you seeing there?

Lasse Rindom: 15:46

I think the honest answer is let's just take the assumptions you're saying, at they're toning down their analyst forecast and their projections, but where on earth did they get those projections from, Andreas? To me, most of them seems like they did 30 trillion. And someone else said, no, I'm going a bit more 15 trillion. And it just kept on going like that. And then you had, I think Qualcomm said that the potential for Generative AI is unlimited, and then you can't really beat it anymore. And that also led to these rumors of Sam Altman asking for 6 trillion in an investment. It's what guys, what are we even talking about? So I always had this feeling that, okay, everything they're saying is over the moon. And now it seems like they're toning it down and that makes it everything look negative. But we're still talking about a technology with immense potential, right? If you follow along on LinkedIn, someone like Dr. Jeffrey Funk, I follow him a lot and he's always very critical of these models. There was this news out a couple of weeks ago that 80 percent of workers found that working with with LLMs made them less productive. He was actually surprised and he said, that doesn't hold onto what I usually see, right? I'm critical, but there are definitely value and productivity in this, so this is too much, right? But we just given everyone this tool and giving everyone the pressure of having to work with a tool we didn't train them on and said this looks like an easy to use UX and I had it to make a poem for my grandma so now I will fire one of your co workers and you just have to be more productive. See you guys. And the world doesn't work that way. So of course, people are stressed out about this. They need to know it's like giving them we gave them Excel. You didn't just go around the next day and said, now everyone's more productive. You have to train them. You have to learn what they do or say, okay, so someone invented the steam engine. So let's just put that in a loom factory. But shouldn't it do something with it? No, just, we have a steam engine now. Let's have fun with it. You have to make it, you have to integrate it into the way you work, into your production. This is really simple. It's about we've said this for years. You don't automate things you don't understand. And that was my first thing when this came out. I was like, this still holds true. This will be an eternal truth. Of course I had my moments of doubt because this seems so aggressively. Everything, everywhere, all at once, right? This new tool, right? But, really right now, what we're seeing is, yeah, you still need to know what you're automating. End of story.

Andreas Welsch: 18:12

I think especially around the part of training, adequately preparing people for it, telling them and letting them know, Hey, this is what it can do. This is what it is not really good at. This is how you get better results from it. And I think that kind of goes back to a community of practice, community of multipliers type ideas that I think many businesses, especially larger ones, would be well advised to establish again. And, have some experts have some multipliers that then take that knowledge again back into their lines of business and say, Hey this is what we found. What are you seeing? How can we help you? I think it needs a lot more collaboration and a lot more hand holding to get those excellent results than just to your point, dropping it on them and say here's whatever tool.

Lasse Rindom: 18:57

Training, but also a fair bit of patience, right? That's the boring thing to say. I'm not going to sell anyone patience as a consultant because, but because training is obviously something we can provide. But patience, it also takes that because luckily, as I said earlier, the world doesn't change from one night to the other, right? It doesn't do that. People have their habits, the way they're working, and that's what gives stability to things that was give stability to our organizations, creates our organizations in the end. So this, having this realistic view of things, that's actually quite important.

Andreas Welsch: 19:30

Now, I'm curious if we assume we are only at the very beginning of this, and I think Michael made a good comment earlier when we talked about movies and genres. It's like the like silent movies were at the very beginning. And we can see where it's going 20, 50 years from now. But also, again, in light of those projections, on one hand, the hey, this will create an economic impact or a value the size of France's GDP or Germany's GDP, I think those were the McKinsey projections last year, or 300 million jobs will be impacted over the next 10 years. I think it was in the US alone, Morgan Stanley type quotes. Why do you think we'll see businesses and leaders still continue investing in AI, even though we've reached the peak or so it seems and it's going down the other end of the slope?

Lasse Rindom: 20:24

The technology is really great, right? This is something that's quite astonishing. And I think still it is astonishing what it can do if you just, sometimes it feels like you're saying something when I say this can work untrained, because it's pre trained on unstructured data. It sounds like I'm narrowing it down and making this a small thing, but it's actually a huge thing. If you've given this to me three years ago and said, I have a tool that can do this, I still think this is a novelty in all of it, like ever, right? We've never seen a technology that can do this out of the box with no training. That's absolutely crazy. And the sheer potential in using that to expand the digital transformation footprint, as I said, for companies is immense. Not even mentioning the chatbot feature, because I think that's still there's some hallucination things that needs to be weeded out. It's a little bit tricky with that. I actually think that's tricky. That's what people have been trying to do initially. I don't think that's where you should look initially. I think you should look at assisting, helping you write things and being a personal productivity assistant and working with unstructured in an automation setup, that's where you can get value right now. But a lot of people have been trying bigger things and then gotten a little bit disappointed with that. But I think the value is just so immense in that, that I see obvious reasons for people to keep working with it. And also they see, they start to see other companies getting some value. I have a lot of companies coming to me saying that, okay, now we've heard real stories about other companies getting something from this, and that's why we want to move on it as well. But you also see companies where, you know companies of a couple of thousand people saying that, Hey, we saved 100,000 last year using AI. And they're writing stories about it. And you're like, nah, that's just very little. But that's why it's crawl, walk, run, right? And we still need to do that. We get the tech, but we didn't get the change. Tech's not change, right? Technology doesn't just change the world. The world needs to change the technology. I think we need to understand that.

Andreas Welsch: 22:28

That's a very powerful quote. That's awesome. Now, I'm wondering, in the Nordics specifically, where I believe you do a lot of your work, what are you seeing there? Is there anything specific, anything that stands out, how people are approaching it, how they're thinking about it? Is it more collaborative, we can use this automation and it frees up people so they can do higher value work? Is it more of the we need fewer people where's the discussion going? What are you seeing?

Lasse Rindom: 22:59

I don't see anyone saying we need fewer people cause the economic growth is still on. And I think, most of the Western world have. I'm 40 years old, so I'm in the smallest generation in Denmark in 150 years, and I don't see any reduced demand for anyone in my generation, to be honest. So I don't see any layoffs that way, but I see a lot of people in Denmark adopting it to the extent they can. Whenever you talk to someone, they're saying like, okay we tried it. We using it for some things we'd like to get more productive with it. We had to know what we can use it for more specifically, learn how to prompt it, get some guidance on how we integrate it into our processes. That's the discussions I'm having right now. Obviously every developer has embraced it immediately. So this is happening and it's coming. And Denmark has for years been the most digital country in the world in the public sector. That mirrors the rest of the of the country as well. So, our adoption rate is something that people are looking at as well. And I think it was a survey that said they surveyed 300,000 Danes where they almost all of them have been tried ChatGPT and I think 30 percent or 40 percent of something that was working with it. I'm still curious where they got 300,000 Danes from, because we're only like 6 million, so 300,000 Danes is actually quite a lot of people to survey. I don't think I've ever seen that big a survey in Denmark. So I have my doubts about that survey a little bit, to be honest, but it is true. People have worked with it. People know what it is and they're not afraid of it.

Andreas Welsch: 24:25

That's awesome. That's great to hear. And I love a good success story and seeing what is working well in different parts of the world, in different countries even.

Lasse Rindom: 24:35

I see a lot of comms about risk and everything. It's okay. I share a quote from from my last my last episode on my podcast as well, because I spoke to someone called Bohan Blili Hamelin. And he said, cause I said to him he works with AI risk. And I said, aren't you afraid that everyone wants to talk about AI innovation? You're talking about AI risk as well. This seems like you're talking the wrong, barking up the wrong tree. Those things are the two sides of the same coin you can't have innovation. You can't take a chance if you don't understand the risks associated with that chance. And I think that's something we really need to get to grips with in this market. We need all the AI influence to stop either being yay sayers and nay sayers and understand that we need to have the common conversation saying that, okay, in order for this to actually change some things, we need to talk about what could go wrong. You're right. That's, important. And I think people need to get to that point very quickly.

Andreas Welsch: 25:25

Nothing else to add. It's perfect. The, only thing that I would, say though, is that we're coming close to the end of the show. And I was wondering if you can summarize the key three takeaways for our audience from our conversation today.

Lasse Rindom: 25:37

Yeah the thing I just said let's get innovation and risk to be a part of the conversation at the same time. I think also let's focus a little bit less on the airplane and focus more on building the airline. And then let's get specific and let's make them all specific, make them productive, talk more about roles than agents. I think that's where we definitely need to go. And we need to start talking about that too, to make it work right now.

Andreas Welsch: 26:00

Wonderful. Lasse, thank you so much for joining us and for sharing your expertise with us. It was great having you on.

Lasse Rindom: 26:07

Thank you so much, Andreas. Thank you for having me.

Andreas Welsch: 26:10

Perfect. And thanks for those of you in the audience for joining us as well and for learning with us.