CX Superheroes podcast - Series 14 Episode 3 - Optimising not Commercialising AI - Umberto and Vittorio Padovano

Hello and welcome to the latest episode of the Customer Experience Superheroes Podcast Series. My name is Christopher Brooks and I'll be your host throughout this series. A series in which we will introduce you to some well-established and some upcoming and rising stars from the world of customer experience. In this episode, we're going to get deep into the world of AI and talk to Umberto and Vittorio Padovana, brothers who run a startup called Destination AI.

I met up with the brothers a couple of years ago in Monaco to hear about their idea for helping organizations to be AI ready, by which we mean responsibly ready. I caught up with them to discuss just what that means, how Destination AI is helping organizations, and how companies can ensure they optimize rather than just commercialize AI. We are here with two of our favourite people from the world of AI. I mean, if you don't know these brothers, then you you need to because they kind of have grown up with AI all around them.

So therefore they're organic AI, you might argue. But we have here Umberto and Vittorio. Welcome to the Customer Experience Superheroes Podcast. Thank you, Christopher.

Thank you very much. Thank you. We've known each other for some time. I think we first met in Monaco um a couple of years ago.

At that point, you were talking more proficiently and more advanced about AI and its capability than anyone was verbalising or regurgitating online. Um, and straight away you kind of identified an importance to be more responsible with with this tool. So that's going to be the flavor of our conversation. And as we go through, I'm really interested to get your perspective on some of the key topics that are dominating the headlines on AI, and also perhaps get your views on how AI is or or isn't going to impact the world of customer experience because I think we have some overclaims in this area as well.

But for now, if you'd like to give me an appreciation of your business, you're you're a startup. So give me an appreciation of how that came about and what the startup is. Thank you for the question. So it has been a very interesting path until now.

That's coming back to a couple of years ago, at least. We started working on our startup, our project. Initially, of course, we didn't have the clear vision of exactly how our services would have looked like, but we just wanted to show up as guides for companies. So to see AI, starting approaching AI in a professional way instead of just commercializing it, as we all know now, deep seek, chat GPT.

And so, yeah, initially we just wanted to be guides, then we started implementing all the different services and all the different parts to complete the services. And of course, customer experience has always been a drive for us, as we believe is the key to understand properly companies, and since our services basically evolve and develop around improving customer experience strategies with AI, so suggesting uh and crafting AI solutions, for sure, we always wanted to start from the problem, from the pain of a company, and leveraging AI to solve it.

So, this is more or less our offering at the moment, our goal. And as you well said, with time things change a little bit. We created destination AI for this. So, destination AI is a consultancy company that aims, as I said, to improve customer experience strategies with tailored AI solutions.

We craft them from scratch, but of course, uh we offer also different services. We start from customer experience, so uh we work a little bit like uh a customer experience consulting company. Excellent. You're based in in Italy, uh that's right, isn't it?

But I'm assuming because of a lack of regulation, it's a pretty universal offering. I mean, most organizations across Europe can benefit in similar ways, and therefore the responsibilities are the same. Have you found any any differences across borders, or would you say no, it's when it comes to AI, it's it's a pretty it's pretty flat the world? Yeah, of course.

I mean it's it's quite it's it's quite simple to see that at the moment there's not much of a difference around Europe in terms of uh approach. It's more about the difference in uh in the people, you know, in the vision that people have. And you know, at the beginning of February was the AI Act in Europe of was officialized. So from that moment on things have changed slightly because now businesses, even if it's still a bit unclear, need to be more careful in how they implement AI solution and they need to follow some guidelines guidelines and some kind of borders, stay in the borders.

But apart from that, I believe it's really a vision of the people and not really of the countries in terms of the culture. It's it's about how how innovative your mind is. Sure. So someone described it to me.

They said it's like you know, when you were young and you got given a toy by your your parents, and if you were to line down sort of five or six children playing with the toys, some would be playing with it exactly as it showed on the box, others would be playing with it in a very different way. If it was some perhaps some figures or something, they might dress them differently or have them doing more adventurous things, and other people would have them doing very basic domestic things, and some people will be sitting there playing with the box, not playing with the toy itself.

So, and and I kind of got that, that actually to your point there, it's not totally about the technology, it's about the innovative and the mindset when it comes to the technology. Now, one of the things that I see a lot in, I had a debate recently online with somebody about it who shared a video of a Christmas advert from Coca-Cola and said, we've recreated this using AI. And my response was, why? There's a beautiful ad being created by people created in the first place, and their answer was, well, it's it will save money, it'll be more cost efficient.

So to which I said, Well, the creativity can't be replicated because obviously AI can't create anything brand new, it has to create based on what's gone before. And and secondly, you've actually duplicated effort because you've recreated something that happened before. Are you finding organizations are truly challenged to understand how to optimize AI? Yeah, for sure.

I think that's also a little bit human trait, you know, somehow replicate what you've seen in the past, especially things that worked. So, from what I can say, we've been finding between our clients some of them, because I have to say we divide them into some of them know exactly what they want, so they come to us and they just discuss a little bit the solution they want to implement, but they already know or or they they pretend to know the the problem, they the customer experience problems they that they have.

Some others they don't, so that we we have to find the pain points, and in that case, it's up to us, not really going to dig into the past, would be the past of the company or similar cases, but we can really see that AI differently also from other technologies that we've seen in the past, also in the early 2000s, for example, not going to.com or something like that. It's really a technology that can evolve into anything. You can do really so many things, so many industries, so many different customer experience approaches and challenges.

So I don't want to say that it's difficult to replicate something from the past, but you have really the freedom and the freestyle to do so many things. So I think, as you said, here we come down to to just to the approach that you want to add with it, you know. And then if you underpin the governance has come, for instance, in the the European Act, what is your view? Is is this strong enough or or actually are we gonna learn together here?

Is the regulation going to get adapted and modified as new user cases come up? Because I certainly heard the sense that it's not it it's it's pretty basic in terms of what the expectation of organizations are to do. It's not going to accelerate or innovate in any shape or form. So, what's your take on the regulation and have they got it right?

Regulations are essential and are fundamental to give some order, but apart from that, I believe it's gonna be really a learning process because, of course, new ways of using AI in companies are gonna come up with time. So, of course, this regulation now are just giving a sort of first idea of how we should use AI and what we shouldn't be doing, but of course, new things will come up and we will need just to adapt with it, honestly. Cool. Give me an appreciation of how it works.

You said you've got two mindsets when it comes to customers. You've got clients, they've diagnosed the problem and they just need help to kind of optimize it. And you've got others who are perhaps less aware and you need to help them kind of diagnose the problem. So just talk me through the process at destination of AI.

How do you go about helping organizations to understand where they are and then what more they can do? To start with, we we offer uh an evaluation that consists of multiple questions that help us to understand your AI maturity because, in the end, that's what comes down to us. So we have to understand your company readiness to implement AI, since, of course, first of all, we don't want to give to the pilot you know a too powerful car, and we that maybe he is not able even to drive.

So we have to really understand exactly all the situation, starting from the employees, and then of course, we have multiple uh offerings in terms of research, also, in which we study your company. We understand your we of course we we have to start from from the pain points, but we also want to see your objectives, your goals, your or your opportunities. So combining all this, we come up to uh an internal process specifically in which you could do more, could perform better, and from that we craft an AI solution that helps you getting exactly where you want to go.

Great. And when you say craft a solution, I I guess this could be a combination of solutions that are sort of already on the marketplace. Is that what we're looking to do here? Or are you actually building new solutions yourself?

Oh, yeah, we have the capabilities to build from scratch, and of course, that's something that we discuss with the client because uh, as you mentioned, the other case is that the client already has an idea of what they want, and in that case, it's just a matter of understanding what works best and how to develop and craft the idea from scratch. But yeah, we are fully equipped to create ourselves. What are you finding is a classic sort of outcome? Are you helping the organizations de-risk future issues they may have?

Do they typically look for driving efficiencies from AI? Or is there innovation? Is there new opportunity for them through AI? Where are you finding the recommendations are landing?

We strongly suggest always, always, that of course, innovation must be a drive. Of course, we all have to be a little bit innovative, but we don't have to run behind trends. Also, it's strange to say, but we do selection also between our clients because we prefer not to work with uh companies that focus strictly just on innovation without having a specific need or a difficulty. There was uh example that a professor of mine explained me once that was during the dot-com.

There was an airline that started offering you know 24-7 support online just because everyone was doing it. And the result was that after a few days, the the whole system crashed and resulted in ruining the brand image and the perception clients said about it. So this is a perfect example of don't follow the technology, implement the technology with your company, grow with it, don't force it. So that's also a little bit uh an approach that we have and we want to preserve.

So I guess as part of the assessment, their digital competence and capability and and the role digital plays in their business. Because if you are a very traditional bricks and mortar business and your your whole existence is based on high-end um service through personal service, then I guess AI is is going to have a very different role than if you're a startup that that was built through apps and and digital platforms. Yeah, of course, 100%. It's quite obvious that the the newest ones have already an approach that it's more technological, if you want to put it this way, but whatever it's related to customer interaction and customer processes will have an impact with AI.

So it's really essential to understand how to touch those points, because of course it's a risk sometimes to dedicate and give all powers to AI in terms of interaction with a customer, because most of the time also customers want to be valued, and sometimes to be valued, they need to talk with humans. But many interactions will be will be more seamless and processes more proactive and adaptive also with AI. You must have seen this as well in the world of customer experience. Obviously, we have a small part of customer experience's customer service, where you need to make yourself available to your customers in case things haven't gone as you hoped they would, or you want to use that particular engagement to encourage customers to do more with you when they interact with you.

And I've been I wouldn't say disappo disappointed is too strong a word, but probably um underwhelmed by the focus seems to be very much on um an efficiency drive. Um it's very much on trying to give individuals more data so that the individuals in the contact centre can get to the answer quicker for the customer, which might sound like you know that that's the perfect thing to do, but actually it's going from you know they're self-piloting to co-piloting to autopiloting. So at some point that individual won't be in the in the seat, they'll be be displaced.

Do organizations have a responsibility to consider the human capital that they have alongside the digital capital they have? And whereas just because you can employ an AI, is it essential that we really think about the the human cost of accelerating AI through things like contact centers? I believe that of course the risk and that the people are scared of the idea that AI could, you know, overcome their their role in a company. But the real thing, and what I like to say every time, is that they should work together.

The the thing is that people that don't work with AI are the ones that are gonna lose the pace and will be prostituted not from AI, but from the people that are working and using AI. That's that's the that's the thing. Yeah. I mean there's there's a really uh amusing film called Charlie and the Chocolate Factory, and it's it's to do with kind of factory processing.

But originally the father of Charlie he puts the caps on the top of toothpaste bottles, and then a machine comes along and it replaces him, and he doesn't have a job until it's realized that you know actually someone needs to look after the machine because it will break down once in a while. So perhaps it's just more about accepting we have a different role to play. You know, we don't we don't have to have the same role we used to have, but that doesn't mean we're displaced, we just now have another role within the organization.

Would that be fair to say, I mean, are you seeing the more responsible organizations redeploying their talent and their resources to better serve customers, better serve their business? Yeah, absolutely, yes. As Umberto said, I completely agree with what he said. One of our values, as he mentioned, is to use AI as a tool.

Don't substitute humans with AI, don't substitute employees with AI. For sure, some tasks can be easily automated, but that doesn't mean that humans are taken apart. Time that you can save with AI, you can employ that into something else, into other tasks, into making your company more efficient and more productive. So I think it's all a matter of understanding exactly what is AI and how you can implement it into your company.

I really see a few cases in which AI simply substitutes the employees. As I said, we we don't agree with that. That's not in our values and not in our vision. Yeah.

And customers had called up with issues with the energy. And and whereas previously the operator would have very limited information at hand to be able to explain what was going on, now they had available to them because their AI tool was picking up on other conversations that customers had had. So customers were saying, Oh, yes, I can see there's a van down the road that's doing repairs. Now, that van, as the the company explained, would be provided by the company, but it would have been outsourced to a third party and their systems wouldn't be talking to each other.

But because now it could actually incorporate the conversation that another customer was having, it could stir that information up to say, yes, we are now aware there is a van on the street that is doing the repairs. So I can see how it really can create a lot of value for customers as well as for employees who would feel like they're that they're they don't have the answers that should be ready available to them. But I want to just get your point on on this, which um was another conversation I was having with somebody who runs a contact center in in the US.

And they said to me, well, the good thing is that our customers now uh will get the answers they need through their their AI um solutions, and therefore our employees would just be able to focus on the really challenging problems that our customers have. And I thought to myself, I'm not sure that's such a good thing because as an individual, I also like to solve easy problems to be able to get the answers that um are readily available to me, and that then gives me energy and gives me motivation to solve the tougher challenges.

If all I've got on my desk every day is really tough challenges that I may not be able to solve, I think that's going to impact my mental health. And I just I just wondered if you've seen any evidence of people or organizations recognizing that giving humans the more complex and allowing AI to be the hero, saving the simple, can have a bearing on people's mental health. Yeah, of course. I mean, I I fully understand your point.

It's it's a tough perspective, you know, because of course companies, specifically in this stage and in these years, are perform are trying to perform as much as possible. So aspects such as mental health for employees are aspects that are a bit under, let's put it this way, they're not very they're not a big concern for companies. So because they are more oriented towards increasing profitability, increases in efficiency, and increasing performances. But I can definitely see the fact that if you are always put under pressure working on hard tasks can be difficult.

But at the same time, I believe that uh this could should give you motivation. Because, of course, if you are given those tasks, it's because the company believes you're able to do them, so should be kind of a fuel for you and for your uh motivation and make you understand that your capabilities probably are higher than what you believe. Yeah, I think that's a very good point. I mean, I think it's a transitionary period anyway, because obviously in the future you'd employ people in there who are problem solvers, who like difficult problems to solve.

And I think this comes back to I think one of the first points you made was the difference between optimizing AI and commercialising AI. And I guess invariably, you know, when whenever a new technology comes in place, or as we we've agreed, you know, this isn't a new technology, but just seems to become famous or popular because of um large learning um uh databases, then invariably there is a group of people who look to say, how can we make money out of this? Where do you see this going?

Do you see AI becoming a level playing field? So it's not a differentiator, it's actually just a fundamental. Every organization will have uh an appropriate level of AI within their business to make sure that they're as efficient as possible. Or do you see it being a differentiator?

So the organizations that are optimizing AI, we as consumers recognize are better serving us. How do you see it going? No, yeah, I believe that at the moment, so far, for the stage in which we are, for the implementation of it on a global level, let's put it this way, I believe that it's gonna be a differentiator because, of course, companies that are using it already and are gonna implement it in the next year or next month are gonna have some competitive advantage towards their competitors and in the Industry they work in.

But on the long term, I believe it's gonna be much more in which processes you're gonna be able to use it the best to make customers feel more understood from the others. Because of course we will reach a point where this will not be something new, will be something that most of companies will need to compete in their industries. And at that stage, what will make the difference will be in which processes uh they still give the humans uh an important role, and in which ones they completely give the role to AI agents or AI solutions in general.

Would you say we're still in our infancy with understanding how to optimize AI fully? Yeah, completely, completely. It's still it's still an early stage. I don't know if you saw this recently, but Netflix have been able to release a much wider selection of films because they're using AI to auto-dub the films.

And I thought to myself, is that a good thing? I guess from a customer perspective, I get more films for my membership fee, I get access to international films that I may have previously not worried about watching. But then I thought to myself, well, actually, Netflix could have always done that. They could have employed actors and actresses to do the dubbing, but they've chosen not to, probably because it was too hard or too expensive for them to do.

So I sit on the fence with this one. I think to myself, should they have, if it really mattered to them, should they have put the investment in and said, yeah, this is really important to us? Or is it something that they've always wanted to do and and AI has come along and enabled it? Or is it just a case of, and I do worry, and I'm sure you come across this, that some people or some organizations look and say, because we can with AI, we now will, and they're not really thinking through.

What is this? Is this does this connect with where our business is going? Do you understand what I'm saying with that point? Yeah, yeah, no, no, no.

We see what you're saying, and again, I want to repeat that it's not a sprint, you know, it's a marathon. I think it's this is the perfect moment when your values and your uh maturity, your preparation towards AI should meet the opportunity and uh the technical uh aspect of the technology. I think that what happened more or less with Netflix. I agree with you saying that that's something that it's really easy to project to see that they won't always wanted to do that.

That would make sense, but I think they they match the opportunity now with AI to do that in a cost-effective manner. As of cost, of course, uh costs are important. Uh we cannot uh deny that, especially now with AI. It's absolutely true.

We don't have to follow the trends, but there are some uh tasks, some uh processes can be done very easily, can be uh developed and implemented even more easily. So why not in that case when the risk reward is is so uh unbalanced, uh, it makes sense. I mean our conversations keep leading back to this point that you brought up, which is very core to this, which is yes, the technological capability is there, but it really boils down to whether it's appropriate for the business and who the business are, and if the people involved understand what they're they're dealing with.

It's like giving someone who's learning to drive a Lamborghini count ash and saying, you know, gone off you go and practising that we're equipping them with with perhaps tools that they're not able to use. In your experience, when you make your recommendations, are organizations recognizing and accepting that our people need training, they need skills development, they need capability development, or are individuals in the organizations believing I know how to use AI, you don't need to train me how to use AI.

What is your view? So I think that these are really interesting questions because I think it all comes down to selecting and uh understanding your your clients. You know, as I said, we really push towards working with clients that have the maturity to implement AI, or at least they are cautious of where they are. Okay.

Starting from that, we we have to say that we've been maybe lucky, but really most high percentage of clients they ask for education, they ask us to help them comprehend and understand the technology, not only on the technical side, of course, that that's essential, but how also how to leverage it. They try to understand in more in-depth how it can evolve, how they could in the future vision another idea developing, connecting to the current one that they maybe decided to develop.

So education is fundamental. We've been lucky because so far we didn't have to push too much towards educating them, you know, telling them to educate themselves rather than uh them asking us to help them comprehend the technology. Well, I think it's as you say, it's sort of finding those organizations in the first place. They're responsible enough to want to reach out and use an audit.

If they're not responsible, maybe they wouldn't come knocking on your door because they know that what they will find. And I guess we've got to hope there are the better organizations succeeding and win because that is one of my worries is that poor practice from poor practitioners can impact everyone, can affect the rest of us. And as a consumer and as a customer, I don't really know the difference. I think I'm gonna have to rely on regulation.

I'm gonna have to rely on organisations like Destination AI, who are actually working with companies to keep them true and keep them optimizing rather than commercialising uh AI. I think that that's that's a very important point. So just kind of wrapping up here, then, in terms of three things that you would recommend if you're an organization, we'll conclude by giving people details of how they can get hold of you because uh I'm sure some people have listened to this and thought this is a really valuable service.

It's a very important thing to get an objective view. The world is changing very, very quickly. Are we equipped to be able to optimize AI? If you talk to your colleagues internally, you'll probably get the answer yes, let's just go for it.

But you really do need some professionals with with now experience as you've had it, um, to come in, spend time, really understand what you're trying to achieve, really appreciate what the capability is, and to be able to put forward a recommendation which will really help the organization. So we'll give details at the end because I'm sure some people will find that a value. But um, in in the meantime, if you could leave them with three things that you think are the most important in this space, what would they be?

Yeah, of course. The first one is quite simple, and we just discussed about it. Of course, education and literacy are fundamental and are the most important thing to understand what you're doing and be able to then use the solution the best way possible. Apart from that, I believe that it's also important to remember that AI is for how we see it and how it should be seen, it's a process.

So even if you implement one solution, you should never treat AI as one-time project. You should use it as uh uh a process that uh once you implement a solution, you can do something else, and it's a continuous learning process. The third one, and I want to underline it because I believe it's very, very important, it's don't underestimate data quality. So, of course, when you plan to implement a solution in within your processes or your company, the first and the most important thing, which is then the one that is going to be used to teach and make the solution learn on it, is the data quality.

So before everything, check you have good data and everything it's it's better. Excellent. Thank you so much. Uh I want to pick up on that last one actually.

I've I've grown up through the world of direct marketing and database marketing, and the one truth that's remained throughout that is the quality of data just isn't good enough. It seems to me in this new paradigm that many organizations have either given up trying to get it right or have just made a massive leap and assumed their data is in good enough quality, because we we we don't seem to have that discussion so much. Yes, we're seeing evidence of it. I saw a very amusing customer feedback the other day from a lady who was contacting an organization and was treated as if she was calling some sort of dating line.

It was really strange, but obviously they'd they'd blended the data with the wrong data set. But you know, organizations have taken years to try and get their data right and failed. Is it fair to say that the data still isn't there? It's not good enough quality to really maximize the potential of AI, or or are you finding no no, in fairness, companies have now got their data into good shape?

I believe that really depends on case by case. Of course, training uh a model or a solution on high-quality data makes the model work the best way possible and do the least number of mistakes possible. But of course, uh we are not there yet. Many of our, for example, customers were struggling to have a clear idea in terms of which data to feed to the model.

So it's it's really a matter of doing a bit of a selection, also. If you don't have full and clear data that are of high quality and precise, it's a matter of selecting at least the right ones. Yeah, that's part of our guide role that we projected at the beginning. In the end, we support companies also into these little but fundamental parts of the process.

It is fantastic. My son, who's reading history at the moment, put a very interesting point to me and said, you know, when it comes to AI and history, history is written with two very different versions, the winner's version and the loser's version. And depending on where you stand in the world, you'd get a very different answer. And if you blend that information together, it still doesn't work.

So I think data is a really important source. And I do hope organizations are taking the time to accept our data isn't good enough quality or to improve the data quality before the AI starts serving up answers against things that it is has all those sort of biases in there we know we have. But it's reassuring to know that a destination AI that's a fundamental part of your offering, and I guess that does you know play into readiness, doesn't it? If if the data quality isn't there, you're not ready.

Absolutely. Yeah, or you can uh you you are for sure not in the same position as other competitors that they have it ready, they already passed through the digitalization phase in terms of data, you know. That's that's quite clear, absolutely. So look, if people want to get hold of you chaps, what is the best way to get hold of you to engage you to talk more about what an audit for their organization would look like?

We have a LinkedIn page, they can look at destination AI or at Vittorio and Umberto Padovano on LinkedIn. We are really, really happy to accept those connections and to discuss anything about AI or customer experience. That's something that really drives us into the deep. So feel free to contact with us, and we are more than happy to have a chat with all of you.

Great. And and just to manage people's expectations, what does that first chat look like? What what do people need to come to that conversation with? It's really up to them, even if they already have questions and doubts.

We are really very open to to chat and discuss on anything. And if already they have a clear idea and doubts on how to use AI in their personal companies, they can reach out. Yeah. Brilliant.

Well, uh, as as it was the last time we spoke, you know, it's just such an informed and an advanced conversation with you two when it comes to AI. And all of our focus is on the responsibility, and I love the difference between optimizing and commercialising. I'm going to use that because I think that's really undermines the integrity and the credibility of your service. So I wish you well.

I mean, the one thing it's going to be is busy in this space. I think if you're in auditing or consulting, or if you're a lawyer in AI, you're going to be very busy over the next few years. But uh, so thank you for sharing how it works and the importance and really, you know, being open about the different areas that people need to consider. So uh I wish you um all the best of the future, and perhaps we'll have a catch up in a couple of years' time and just see how the world has changed in terms of responsibility when it comes to AM.

Absolutely. Thank you very much. Thank you very much.