AI is all about tech, or one could think that it is. But in reality, it's about people that have to use the AI in firms. Today, we talked to Suriel Ariano, who is an author and speaker, also consultant, and he implements AI in firms, and he says it's all about the people. So let's dive in and see what Suriel has to tell us.
Welcome to another episode of The Beginner's Guide to AI and interview episode. It's Deep Ma again at the microphone. Hope you have fun and learn a lot in this episode. So as the podcast is not about me, but about surreal.
Let's ask him directly. So you're welcome to the podcast. Can you tell us a little bit about what got you into AI? Absolutely. So actually I've been doing digital transformation for over 20, 25 years. So AI, although nothing new for the last probably four years, I had the opportunity to study AI leadership and MIT.
And of course, that got me more into, I have a Bachelor of Science in Leadership and Management. So leadership has been a really good topic. I'm passionate about leadership, people. And when AI leadership from MIT kind of got into both of my paths, leadership, technology, I love technology.
So it is one of the things that just brought me together and I'd be able to explain AI to people how AI, what AI is, what AI is not. And I think that I'm just passionate about educating people about what AI is and what AI can do for them.
Let's do that. Right jumped in the AI leadership thing. You wrote a book leading in the age of AI. So for many people, for me also, what is AI leadership?
Yeah, it's curious because I always say that AI is not a technical thing. I mean, of course, we know the technology and that it is composed of technology, but the portion of AI is not a technical thing, is a leadership thing. And what I mean by that is that
As leaders, we have the responsibility to either create technology solutions with AI or integrate AI solutions in a way that is ethical, that is moral, and always thinking about the human component of it. It is actually thinking about the
In my book, I have a quote that says, technology needs to empower humanity and not replace it. So I make an emphasis that AI leadership is practically that is being able to empower people in organizations rather than replacing them.
Or does it practically work? Do you have an example? I mean, there's a firm that they want to implement AI.
Absolutely. So my first book, actually, that it's called the Golden Triangle. I use a framework that you probably heard of it is the people process technology. And I do have a lot of clients that they start and a lot of organizations, they start what they call digital first, right? They go for the technology. They try to recreate the processes. And unfortunately,
people are an afterthought. So is Mackenzie consulting says that 70% of digital transformation failed because people are resistant to change. And that is a not a technology problem. That is more of a people management problem.
And the way to go about a people first approach is that you look at the people part of the triangle, right? You look at the people first, look for the skill sets in your organization, look for, I usually advise my clients to, and we have different approaches, different frameworks, where we look at the people component.
Then the processes, what I tell my clients is, don't just bring AI or automation for the sake of bringing in new technology. Look at those processes that the people in your organization really need to be productive.
Again, if you go with the emphasis of empowering the people in your organization, you're going to look at those processes that will make them even to have a better quality of life. I know we always talk about the work, life balance, and sometimes it's just a piece of technology can empower that.
And then the third component is technology. So after you look at the people component, then you look at the processes. What we help our clients is to look at the technology that is kind of like a checklist that they can look at.
see what type of technology. The good thing is that we're agnostic to technology. We're not used to work for IBM and HP. And in this case, I don't have an agenda out on trying to bring a technology basically is we are for our clients, for their organizations.
So that's a little bit more practical. And of course, I can share so many examples in the good and the bad and the ugly. But I think what I always say is, take inventory of your people. And when you focus on your people, basically the technology, the process, we'll come to place.
So it's like talking about the examples. Good, but ugly, I love it. Good. Do you have an example of a good way? We don't talk about the ugly one, but I'm either good, the bad. Yeah, absolutely. So a more more example, I had a client that they so.
I always say, I like to work with people that are actually in defense of integrating AI or not. Of course, I'm NDA, so I'm not going to go into the details. But we were looking at a solution that we could bring the AI. So the first thing that we do is working with the people component is we have an assessment. We call the AI readiness assessment.
One of the things that we do is in this assessment, it goes from zero to five. And if they are over three, three is the threshold. If they are over three, then they are ready for us to continue working with them in terms of how we intake radii.
If they are below three, which in this case, this client was below three, that means that they're not ready. And the leadership team, one or two people, I think they weren't ready to move either because of what we said, right, is a fear of
being replaced, fear of not having control. So for those people, for those two people, we actually have I had a one-on-one. And I discuss all their questions, right? Maybe questions about fear, about the replacing people. And they're real, right? They're real questions. And so my goal is to be able to answer those questions that they have.
So when they take that survey again, they go over three. We want to move forward until everybody has that three threshold. And of course, that's the leadership level. We have other frameworks at the people level, which we actually see with the managers and be able to see what are the fears that they have.
We use a couple of change management process like ad-car from Prosai that allow us to go through the different stages of change management. If you notice, I haven't talked about technology yet. It's about people. It's getting the people prepared for that, which is a new book that I actually am in the middle of. It's called Culture Shift.
So it's it's very important for us to offer an organization that is going to move towards AI or towards a new technology that they look at the culture right if the culture is nimble agile into innovation.
It's going to be an easy, easy process. If they're not ready for that yet, in this terms of the client, we worked with the client to make sure that they were over that three threshold. And then from there, practically, is we look at other processes. So in this case, they're a big manufacturing.
So we look at the processes. There were really a huge digital transformation component because they were using very old systems. So for that, it was a little bit of like that training, the people looking at the people, what they need.
Taking inventory again is like what what is it exactly? Let me understand your process This is where we use what aim MIT uses the X teams X teams is is a a form of Influencers X means external right is
not only the people that are in charge of the technology are working on this digital transformation, but also external teams that are somewhat influencers with that, they look at into the project and provide that influence.
And basically after that is like we provide a report. These are the things that you need. These are the things to look at a software. And from there is either we help you if you want us to engage into looking for a software that fits your needs.
Or we also have the development team to actually provide a customized software for them. So in this case, we're still actually working with them in this customized software that we're creating where we're up to the MVP. So we're creating a minimum viable product for them.
But yeah, this is one of examples that literally goes end to end into how organizations can actually create that. And I can share a number of projects, but yeah, it'll take us a couple of days. You talked about fears that mostly the problem is the workers or the managers or whatever, they have fear and you go and talk. What are the typical fears they have?
Yeah, so I say my book, the first couple chapters, I grew up in the 80s and I was born 70s, but I grew up in the 80s and watching movies like Star Wars, Terminator, Robocop.
You know, usually the depending on how you see the future dystopian, utopian, you get that as like Terminator, right? Machines are going to take over the world and things like that. So normally the fears that I encounter in organizations is on the people component is, am I going to be replaced, right? Is the particular fear in their jobs, am I going to lose my job because I'm being replaced by technology?
Second is, are they going to take over the world, right? Am I going to lose control? We as humans, we are naturally in the fear that if I'm going to lose control. So that's another fear.
The other fear is that, am I going to be able to, in this and mostly for leaders, right? Is it, am I going to be able to either afford it or is it really something that can provide what I need in my organization, right, at the leadership level?
So the things that we do and to say to mitigate some of those fears, mostly when we're working with people that are under the three-eath threshold, sometimes I sit down with them.
Practically, it's just understanding where their fear is coming from. I have a certification in executive coaching and part of life coaching as well. So that helps me a little bit understand where this executives are or managers within organizations in terms of like, why sometimes these fears come from beliefs or cultural and understanding where they're coming from, it's really important.
To mitigate that, what I always say, this is kind of my start, right, is we need to understand what AI is and what AI is not. So we understand that AI can be a powerful technology.
But at the end, if you look at it, is AI is just a software, right? It's a software that has the capabilities to absorb data, or in this case, get an input of data and be able to provide an insight with that data. And the better it is trained,
Uh, it's, it's going to provide better insights, but, um, and, and focus on the word training because is when we're training AI is, is not the sound only, oh, the AI is going to think by itself. And then, you know, it's going to take over the world.
Now, the AI is only focused on what the AI was trained for. If you ever use chat GPT, for example, and you try to bring questions about politics, for example, sometimes you'll get is like, well, I wasn't trained for that is my, my,
call it algorithm, it was updated, I don't know, six months ago. So going back again, that's an example. And when we create technology, we do this. We train the AI to focus on the things that we want the AI to do.
So if that tells you something, that means that this piece of software, which was created, in this case, programmed by someone, is now you understand that AI is just a tool. Just becomes a tool like money or like weapons is, depending on who has the control of that, is how it's going to be used.
So that understanding, the only, the common denominator to that formula is leadership. And that's when the full circle is, it comes down to leadership, right? Is it?
Leaders are responsible on how we either create AI or integrate AI in our organizations in a way that is ethical, moral, and empathetic to our people. So I normally say, if you understand it in a way that's pretty much AI, then I start giving examples, right? It's like Netflix. You use Netflix.
You probably are using the AI component of it, right? As after a movie tells you, well, what are the...
the different options that you have based on what you watch. If you shop in Amazon, same thing, it gives you options. And I know people sometimes call it the algorithm. All the algorithm is, it's just basically a piece of software that was trained to enhance the user experience. So once you have a hand on what it is and what is not,
You're not going to go be fearful against the AI, the technology. Now what you want to be is be keep your leaders accountable. Because then that shifts the focus on the technology.
more so on the leaders that are creating, integrating this technology. And it goes, we go again to the point of like, is the people component, right? That why is so important to talk about the people?
Hopefully that answers that question. I know it's loaded. But it's interesting because you go away from the technology and what the people do is important and that, I mean, leaders, if you take a normal firm, normal firm is not evil.
Maybe they will play us around, but most firms have one goal. They want to make money and they want to keep their employees. Everybody should be more or less happy and it's a job, obviously, but most of the firms also are small. So they know each other and they probably go drink a beer in the afternoon, evening probably. And if you think about that as leadership and those people won't start programming now on algorithm that is evil.
Yeah, exactly. And I always say is, and for those leaders, again, I have the two types of executives, the one that they see that AI is there and they need to integrate AI because they feel that that's another leadership fear, right? That they think that the competition are going to
leave them or their organization pretty much is gonna get obsolete because they don't integrate AI. And what I say is follow our framework. Follow our framework, go look at the, I have clients and mostly the management level of the companies that I consulted that they already integrated that technology. Now people are quitting
because they're resistant. I always say is like, you could mitigate this or you can mitigate this in the future by just making sure that you have the people interest as a priority. And I know that sea level executives, some executives, they do have genuinely that interest.
But because of those fears of like, oh, my organization is going to be obsolete, they run for the technology first. And then that's what ends up happening, right? People feel that now they're being replaced. They start quitting, looking for other jobs. And yeah, leaders, that's where they say is like, yeah, we should have done that. They hire someone like me.
And then we try to mitigate that at the level of like the HR training level, just to make sure that they go back and track.
That's actually interesting because I just brought down the business adoption question, how our business adopting, but it sounds like what you say is they all run for it, but they are mostly afraid to get left behind. Yeah. Yeah. And there are cases where actually I get a lot of questions from leaders and saying is like, well, I know I have to jump. I know I have to make that jump into integrating AI or bringing AI into my business.
I don't know how to go about it, but I know I needed it. And one of the things that we do based on the framework when we get to the technology aspect, that's where we say is like, well, let's start with a small proof of concept or prototype.
Don't don't don't start big let's start with a small POC and then You go from there like there are different stages, right? You have the the the POC or the prototype you have an MVP and then from there you you start growing and scaling So if if yeah, if someone is interested and get started started small I one of the
I'm fascinated at how much, how reachable, even financially has AI has become before when I was working for IBM. We were talking about Watson and Watson, how expensive it was, only a big enterprise were able to integrate something like that.
Now with OpenAI, LAMA, and all these smaller companies that have created their own LLMs and things like that, now there's more opportunity for small businesses to start creating prototypes.
using AI. Of course, I would say do your due diligence before you start. Don't try to, I get a lot of also some clients that they started with developers that they're just adding plugins with OpenAI. I'm like, well, you need to know that it's open source and everything that you do, your data.
If you use something like chat GPT, basically they're all training their models on your data. So of course, that's a conversation. That's a little more technical that you usually don't get to. But if you're just a small business, that trying to see how AI can make an impact.
I would say, look at your people, check on the process, and when you're trying to improve a process, start with a certain, that's if you're going to do it yourself as a leader.
as a business owner. Just start with a small POC, a small proof of concept, and then scale from there. Of course, if you're a mid-bigger enterprise, you can hire a consultant like me, like our company, or you can hire a consultant. Yeah, and closer to you that I aligns, and this is so important.
that aligns to your culture, to your, that's why we're so big in going first with people, because that is at the end, we always see it is going to be successful if you are for your people.
Yeah, there's always a people's business. Yeah, firm is not, not yet. It's not totally automated. How is your perception? Do you think most, because you have this framework, or there's numbers from one to five, where you think most of the firms are in which level? I mean, are they, do they have the possibility to adjust quickly?
So it really depends on, that's why we start with the top, the leadership team, right, is we do this exercise with the top leadership. And you'll be surprised, there have been some that are three, four, I've never seen so far someone that is five, like an organization that is five.
because there's always somebody, even if it's almost touching to the three, we have sometimes a lot of ones, a lot of two and a halfs. And because our framework utilizes different sections of like fears, what are the reactions in terms of
the knowledge of what AI is. So there are different components in the survey and the assessment. So depending on where they score lower than three, that's when we put the attention to. So what I've seen in my experience is that some of those organizations, I haven't seen a five. I've seen kind of like a 3.5,
where we actually need to work with one or two executives and again, being able to understand, being empathetic to them and have a one-on-one with me and kind of answer their questions. I wouldn't say they go to five, but at least they go to the three threshold when they understand that
Most importantly that they have control over what's at the task at hand. So, but yeah, you have different. I have one, again, I'm all India. I'm not going to name organizations or names, but I came across about two in one in particular that it was a one.
And I'm actually proud to say that it was like a little bit over three when after the next assessment. And I, like I said, sometimes is your, your deculture and the beliefs that you grow with are very important because sometimes if we embedded a culture or, or a belief that technology is bad from the get go,
then that is going to be a big resistance to that change because you're already looking or in this case this person is already looking at technology or even AI as a bad thing as like is something that is completely
really going to change the world than is, you know, is, is practically kind of like the end of the world. So when you ease those, those beliefs and saying, like I said, is basically just a piece of software that like, don't go against the AI, go against the person who created that solution of AI, right? And that's why I keep saying to, to my executives is,
make sure that when you're integrating AI or creating an AI solution, make sure that is non-bias, that is ethical, that is moral. And of course, there's always going to be a different type of styles and leadership, right? But this is where I say AI is not a technology thing. It's a leadership thing, because it's the traits of the leader that are going to be reflected in that technology.
So, yeah, it's very important that the leadership backs aspect of it.
So let's take a step back from the organization. I wanted to know, did you started relatively early before the TensorDBG hype to go into the AI topic? But why? What was your reason to? So I have always been fascinated by AI. And like I said, I worked with IBM about 2011, 2012, when Watson, although they had already brought Watson before,
But Watson was the pinnacle of that AI burst in the moment. I remember one of the most critics, it was Elon Musk, right? Because he was like, oh, Watson, now they want to take, you know, depending on what the hands are. It's so funny because he was such a critic and now he's like, okay, what are you doing?
with your self-driving cars and now the robots and we're getting closer to our robot, right? So it's definitely, I was fascinated by it and right before I remember about 2020 when the first GPT version, not Chad GPT, but the GPT version that I will allow you to
more of the generative AI and make insights based on what you would do.
I was seeing that there was a shift in AI because we were talking about more insightful technology than the regular automation type of thing, being able to systemize some of the mundane tasks, right? Generative AI started to provide a lot more of that.
insight and recommendations. Of course, when Chad GPT came, that was like accessible to the world, right? But again, with my background in technology and leadership and AI, I was just being fascinated by it ever since.
Oh, there's nothing new. I mean, it's been since 1950. But I've just been fascinated by it. But it's so, like you say, accessible now. And actually, that's the question. As we already had to terminate our question, the last question for you would be, how do you use AI? What do you use, actually? And what do you do with it?
Yeah, so we are integrators as well. So we create, we have a couple of technologies. We actually have one pending technology.
that we have, uh, using AI. And, uh, so basically we have different, the, the most powerful and flexible to be able to build on is a GPT from the open AI as an LLM, not Chad GPT, but the, the,
underneath technology. We use some other LLMs, we use LAMA, Claude, just so in terms of testing out what the different, we're doing a lot of technology with voice recognition and voice assistance to have that more natural language that you can have a conversation and provide an insight.
So that's that's pretty much what we use again with the 01 well since the 40 from GPT is is being really powerful. So I think they're doing a great job. And again, and it goes all down to how we integrating making sure we have this pen pending technology where
It's not open to the public. It's where we definitely want to keep it out of the hands of just the public because it requires certain responsibility to use that technology. And again, he goes back to the leadership component of
of creating it, right? So, but yeah, those are the technologies that you use now. And of course, we're exploring something like Watson now, that is that I'm on this side, outside of the technology provider, I'm more on the technology integrator. So we are looking at, but for small businesses, I think things like OpenAI,
GPT is the best. I know some entrepreneurs use things like chat GPT. We have our own instance of chat GPT. It's private. That way we can do simulations. We are creating digital transformation simulations as well. But those are in private instances.
And you personally, what's your use case that you use stretchy beyond and call mostly
And so for us, it's been great. So me personally with an internal is data analytics. It's for us in looking at the part of the data. It's been incredible. Like what we're creating this same, we call it the DXM.
is be able to put a large amount of data and it's just fascinated the house seeing how the insights that you get from it is you can even ask them is like okay create a graph or spider graph just to understand our market. I actually recently with my team we sat down and say it's like well let's look at our market
analysts and analysis and see our competitors, what they're doing and things like that. Just to be able to, and of course, my team is the one that does it. I don't even know what, but that's the cool part, right? Is that literally you can ask and it will provide you a very good insight. What other example, the voice, the voice recognition, it's unbelievable is
We are creating a technology that can actually help people with conversations like you and I having a conversation right now and the idea is we're using it mostly on the health aspect of it is like
we are allowing the technology to surf more to the people. And again, without replacing anybody, but is providing transcribes for doctors, being able for them to, instead of having two, three people and translate their notes, so transcribe their notes pretty much, they're able to do it in while they're talking right and dictation.
So there's a lot of, I mean, going back, I guess I'm going away, but the way I use it is for me is just the data, the aspect of it, that you can actually grab an asset leader as an executive. I like to see all that, right? So have it in my hands is really powerful. It's really cool. We are leaving in the future.
That is the crazy thing. I was like, I'm also born in the 70s, so we have the same background, like movie, science, fictional, whatever. And now, yeah, I mean, it's there. The future is here. Yeah. Yeah, it is. Yeah. Yeah. I'm just waiting for the flying cars. So we thought we were going to have that in 20 something. There's just like...
We have just a German company that they wanted to make a taxi or flying taxi, but they never make it. But the US competitor is there, so that's coming. We'll see hopefully in our lifetime for those that like the technology.
So, thank you for this interview. Can you tell the listeners where they can find you and also your books or something? Like, I will put everything in the notes, but please tell. Yeah, yeah, no, absolutely. So everybody can go to serialaddigano.com.
That is my personal brand, and they can see my books. I do executive coaching. I do consults with organizations, and they can go as well to techfordigital.com, T-E-C, the number four, and digital.com. That is my consultancy firm.
Yeah, we will be happy to, even if it's just a conversation and they have questions. Absolutely, I would love to answer those questions. Perfect. Thank you, surreal. And I learned a lot. The people thing, change, management, those concepts. And yeah, thank you for being on the podcast. Absolutely. Thank you so much for having me. I really appreciate it. I enjoyed it.
Thank you. Okay. In the end, AI is yet another form of technology and the rules for implantment in technology, they are more or less the same. That means you have people and you have to convince them that they don't lose their jobs or the AI doesn't take over the world.
So that's a job that is kind of relatable because that exists for longer. It's just a new tech and it's new fears that we have to deal with, but the processes. They are already in place. They are people who can help you implement AI in your firm, like so here. And we always knew it, obviously. It's people that matter, not the AI's, at least not yet.
Thank you for listening to another episode of The Beginner's Guide to AI. Don't forget to go to our newsletter page and get the newsletter. It's algoberlin.com slash newsletter and hit the subscribe button on your podcast app. Thank you. Turning off. It's Deepma from algo.berlin.
