Andreas Welsch: 0:30

Hey, welcome to What's the BUZZ?, where leaders and HandsOn experts share how they have turned hype into outcome. Today we'll talk about bridging the gap between AI and the business, and who better to talk about it than someone who's actively doing that, Camila Manera. Hey Cami, thank you so much for joining.

Camila Manera: 0:48

No, thank you. I'm very happy to be here. We have the amazing time together in a lot of conference, so I am very happy to share this space with you and all of your audience.

Andreas Welsch: 1:00

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

Camila Manera: 1:05

Yes. So I am from Buenos Aires, Argentina. If you don't know, it's very like south of the world. We are in that part of the continent. I am a graphic designer as a profession, but I have been changed to work in AI for the last eight years. I started my career working for the World Disney Company in the creative team. And one day I woke up and say, okay, I want to study AI before ChatGPT BT launch. So it was like eight years ago. In that time it was very hard to have courses and places to study AI. So I went to India to study there and I have an idea of how the Disney could use data and AI for, so I have. I changed from the creative team to being a data scientist. I was in Disney for more than seven years. We launched a product that won the best of Disney Award in technology, in data and AI worldwide. And after that I resigned. And I have go to co-found my startup of AI applied to sports. To football or soccer if you are in United States. So we have developed a product to help clubs and agents to find their the correct player for their squad and their teams. And now I also have gone from the startup and I am working with a lot of companies around the world to help them use data and AI to. To empower their business and also the careers and objectives that they have.

Andreas Welsch: 2:42

Awesome. Thank you so much. I'm super excited to have you on the show today. Like you said, it's been a while since we've been on some of the conferences and panels together, so I'm excited that you. Have made time to be with us today. Camila I remember I forgot to brief you on this. So there's a little surprise here. There's a little icebreaker. And that icebreaker is a little game called in your own words. So I'll read you this question. And you have 60 seconds to answer. I'm curious, what's the first thing that comes to mind and why, in your own words. Are you ready?

Camila Manera: 3:15

Yes, I'm ready.

Andreas Welsch: 3:16

Perfect. If AI, where are a, if it were a book, what would it be? 60 seconds on the clock go.

Camila Manera: 3:27

Oh. I think that it has a lot of sense with AI to be a book because of their super intelligence and all the information that it has. If it would be a book, it would be like a little bit limited because it would have just that information and that's all. So I think that, I think it would be a word that it's called, like transformation. I think I would go with that. Good answer. Yes.

Andreas Welsch: 3:57

We'll let that count too. There's a lot of transformation happening. And sometimes even, a whole book of words that doesn't get across what we actually need to convey. Which in many ways brings us to today's topic as, as well, right? It seems that there are so many words and sentences and concepts being discussed in exchange between business and AI teams and vice versa, but. Even though they seem to be this they seem to be speaking the same language, evidently they're not. A lot of times we see that, hey the technology guys, they just want to play around with the latest stuff. And on the other hand, oh, the business doesn't even know what's new and what's hipping, what what's cool and what we can do. But it's all a matter of bringing those two together, right? When 80 to 85% of AI projects. Fail or don't deliver the value. And we see AI is getting cheaper and that will create more demand. I also feel we'll see even more pressure on AI teams to do something with AI to, to deliver projects. But if they're not already communicating well enough and understanding what are the requirements and what we're actually building, right? That just leads to more failures. I assume. What issues do you see in your work or have you previously seen in your work?

Camila Manera: 5:10

Yes, so I think like the problem that most companies are having like right now is that these profiles or personalities inside a company that I like to call that like the AI translator. So you have a lot of teams that have a lot of problems and have perhaps a lot of ideas. But previously it was most common that you call like the IT team or the data team. And when they want to take advance in some projects, like they don't know where to call if there's a person inside the company that carry on like the AI strategy or the projects. I think like that, it's like a problem like in the starting point of any project and from the other side, perhaps if they call to the technology team or the data team, they have a roadmap or a timeline. And when they want that project to jump in, they say, okay, let's talk like one here. And now we are not in a moment that we can wait for one year. So I think that or my vision in this kind of moment that we are with the AI hype and also all the things that are going on, is that like we need to have somebody with AI skills and knowledge in every team inside the company. So that would help a lot to be like more independent. To try to carry on their own projects because now with all the tools that we have we can have that type of a structure, so the sales team perhaps have somebody like with the understanding of AI inside the team and they would go like much faster. They will have independence and also like somebody inside the company that carry on the strategy. So I think not having that in the table of conversations and decisions now makes like teams go a little bit slow. And also like being a little bit afraid of what to do, what not to do, if they can use tools or not, if they're secure or not. So I think that we are in that moment of the process. And with, without this kind of profits inside the company I, I think the adoption, it's going to be a little bit more like slow that we all want to do because we want to go do a lot of things and go much faster, but. We need to think about the culture, the teams, and the structure and how they adapt to all the new things that are going on.

Andreas Welsch: 7:36

I think that's a really important point that you're making, right? There's so much push and so much pressure to do something with AI. And just seeing how companies and leaders have e evolved over the last three years when it comes to AI from what is this generative AI thing, to, we need an AI strategy to let's pilot a bunch of things and see what we can actually build and if there's something meaningful and useful out of it. To now actually saying, Hey, show me the money. But it's not just show me the money. It's also I need to invest in training in that cultural change, like you're saying, to bring people along on their journey. It's not just about giving them a tool or giving them a new tool and expect them to be more productive the next day.

Camila Manera: 8:14

Yes I think there is like the keynote to have a very solid idea, ambition and not to do things all like separate, but have a vision where you want to company to take and really create a AI journey for the company. I think that it's my desire but it's a little bit difficult to achieve. So

Andreas Welsch: 8:34

I'm curious there, what are you seeing in South America? What are you seeing in Argentina, maybe specifically, I know that the continent is very innovative in very forward leaning when it comes to these technologies that lots of opportunities. What are you seeing when it comes to AI adoption?

Camila Manera: 8:50

Yes. So I think we are a very high talent region and also high talent country. I have the chance to meet like people, like very young people with very strong AI and also technology skills. But I think we need to be a little bit more potentiated and expanded in what we do because in the region has not much resources and things are more like difficult for us to achieve. So that everything is a little, like harder for us. When I work with companies like trying to help them achieve their AI goals. They all start perhaps like the last year to with something very small to be like on trend. But they were not thinking like in this long vision project. So I think now this year it is changing a little bit and we are more in the in the year of implementation. But last year we were more like in, okay, I want to listen, I want to learn, I want to go a little bit more like slow in the implementation or a process. But this year it's changing a little bit. And now. Where companies reach me out or something they say I want to do. No, that's, that is the biggest change I'm seeing. So I think that it's very good for not just Argentina but the region because we are not, we're going to start seeing a lot of use cases, products and projects more hands-on than last year. That was more like experimental. There's a very bad statistics that for 10 projects of AI, just three go into production. So I think this year we are going to go like perhaps from ten five. That's good because we are going to go a little bit up in numbers but yes we are I think a very like. Passionate country and also region, but we need to create more ecosystem and also more connections. I am working a lot in that, in the country and the region to, to have meetups, to learn from others, to listen other stories in order to incentivize the region to achieve this step. Because I think if we make that we are going to have a lot of business opportunities and we have very good. Professionals here in, in Argentina and also in, I think

Andreas Welsch: 11:09

That's really exciting, right? And I think that speaks also to the broader community and how you can p how you can bring people along on their journey, not just within your company, but to your point, within your region, within your country to get them excited about this too. Now, look I come from a tech background myself, and it's super exciting to see what a new kind of technology can do for you and where its limitations are. I'm wondering how do you recommend then also in your conversations that leaders and their peers work together with the business on these AI projects?

Camila Manera: 12:00

Yes. So I think we developing a very old school ability that is listening. I think that we are like era of being very good listeners. Because it's very very human, like the first part of implementing an A project that it's like seeding. For example, my experience when I create the first AI project in Disney was I sit with a lot of people and just listen and listen to problems. Okay. And I make good questions and I make good questions and over that you start like understanding and going like very deep in the problem. The other like team or person has. And that is not any tech, it's just human tech to really have that ability. Because once you, you understand in all the layers that are when you have a first conversation with something with somebody and they talk, okay, this is my problem. But you make a lot of different questions and you start like understanding that the problem is other problem that they have, but they didn't realize that they have it. So I think that it's like the starting point of anything. And also regarding like business problems and also leadership strategies. And once you have that, then like now understanding how's the pipeline, the roadmap, the projects, it's the easiest part. No, but you have to work also like in the culture, in the communication, in like how you are going to communicate the changes that these perhaps projects it's going to take. And all the more like the human side of implementation. I think there, it's now the biggest challenge that we are having because we are like saying a lot of people that forget your 20 years job and what you have been doing and now you have to do things completely different. So I think that we have to be very careful in that part of transformation because like for this like last, it is chaotic. No, we receive a lot of information. The models based the everything. And for users, final users, it's very confusing. No. So I think now leaders and business have to come a little bit, create the vision. Think of the culture and after that, the implementation, I think it's going to go very smooth in the process.

Andreas Welsch: 14:31

That sounds great. And again, emphasizes you need to work together. You really need to start to listen in and understand what is it that my stakeholders are actually looking for? How can we help them improve their business, improve their process and help them work better and more efficiently? And I think, sometimes we tend to forget that in, in, in all of that mix of technology and the excitement on one side or the fear and concern on the other. And, hey we're actually just people working together and trying to figure this out. It, it also wouldn't be. An episode in 2025. If we didn't talk about the industry's favorite buzzword of the year, Agentic AI. How do you see that making things better or worse in that collaboration?

Camila Manera: 15:15

I think it's going to be very good for businesses because I think for the last years, like AI, it's evolving very fast because first we talk about AI, then we talk about Gen AI. Then we have the Shipt perplexity deep and all the language. For a battle. And now we have another thing that is agent AI. If we think now, like going backwards in the line, it all makes sense. No. And previously we talk about data now because we need the data. Now that we have the data, we can develop models. Now that we develop models, we can create new stuff and now we can make them operate for ourself. I think that if for example, we have a lot of different, like needs in the day as professionals, if we have, can have for example, different agents to resolve different kind of problems. We all wanted to love that. No, I think because for example, and also because now we have to be very like complete professionals because we are professionals. We have to study a. We, things are changing all the time. We have to develop content. We are here doing that also. So I think like the professional scope has changed a lot and we do so much stuff than before. Thanks for all this technology that it's evolving very fast. So I think that if every human can have their own like circle of agents. Resolving things that we don't want. It's going to be great there. It's where we start like putting the limits, no. Okay. These things, yes, this thing. No I want to go faster in this point because I don't like it, but perhaps other people like to do that. So that's why I think it is good because we are going to put our limits, develop depending what we enjoy. Of our day by day and what we not. That is my vision because I'm very optimistic about AI and things. But other people's going to say, okay, no, this is going to take a lot of jobs and that it's not my point of view because I think that we drive the tech and not the tech drivers. So I think although I don't see a lot of implementation here in the region of agents, but I think like for the next month, it's going to be definitely like the game changer of this year. Yeah.

Andreas Welsch: 17:49

By the way I must say I share your sentiment around adoption, right? There's a lot of talk in the market. It seems Everybody that's been doing some kind of machine learning all of a sudden did AI, then they did gen AI. Now they're doing agent AI and they've been doing all of this for a very long time. If you believe them, but I think the proof is still in the pudding. We still need to see more companies adopt this beyond the lighthouses, beyond the ones that say, Hey, we've been experimenting with this for a while. We've rolled this out. And I think it's the classic in innovation management, innovation adoption dilemma. You have a few very early adopters, then there's a big gap, and then the rest will eventually follow. And I think once that happens it'll be really interesting to see how that progress. I think there's a lot of opportunity and, as I'm thinking about this, honestly I'm split a little bit. How big is the opportunity or how big is the promise to what is actually real? We've seen this with technologies like RPA Robotic Process Automation. A couple years ago, we're going to automate everything in a business, and people started looking at this and they said it's actually not that easy. No, we won't be able to do everything part of me thinks well are we going to see the same thing with agents as well? Is there just so much optimism and so much hype that we're not seeing beyond that yet? Have we not seen enough implementations yet? And maybe the truth is somewhere in the middle. But also here in North America. I think companies are slowly starting to look at this and figure out what is this actually and how do I want to use this?

Camila Manera: 19:19

Yes. And also I think that we are like putting like boundaries to everything. No, I think we are also like in that moment, like deciding what it's okay and what no. So we are like finding like the right way to do things with agents also.

Andreas Welsch: 19:37

Yeah. And I was thinking about this the other day. On one hand we see so much innovation come out on a regular basis. You mentioned a few of the things that were in, in the news just in January and February from we're headed for AGI and we know exactly how to build it to, we are running out of public data to train on to, hey, here's this thing called deep seek and it's way cheaper than the Western models and incumbents two I dunno what the next thing was. Grok, GPT-4.5 and so on and so on. So there's a whole range of news if you want to give in into that. Yet I feel the adoption in companies will be a lot slower because there are risks, there are concerns, there are skills you need to build, you want to try this out. So on, on some on, on, on some level there's more technology that then you can adopt fast enough to keep up. Which is an interesting time to, to live in. I think in many. Now you mentioned some of the headlines. And I'm curious to me it feels like the last four weeks yes, there was an Nvidia GTC Yes. There were a couple other things, but were there any big headlines that, that stand out to you, maybe even from this first quarter that are relevant for business and AI teams?

Camila Manera: 20:48

Yes. I think that from different like aspects, like all the companies want to show us how good they are or how important they are or how they are the best. And I think that it's not like the scope or the vision that we have to do. We have to center more like in people. Than companies. And also this is mainly because people are going a little bit like slow in the adoption as we were talking about, and having all the time like this, like big tech like battle to say I'm the best, I'm the best. It doesn't matter who is the best, what does matter is what best for people. So I think that also companies has to be a little bit more like humanized than they are now. Like not trying to like in that battle for who is the stronger or biggest or that I think that from that aspect, my, my favorite like news of these weeks, it's like all the launches that OpenAI has given mainly because I think they're the ones that are going a little bit more like far away in the capabilities of the model in the more like deep search and making also agents to operate. Because what is the best answer or the best model now? I think it's I'm not for now. And also I think that all the a product that I have been using a lot, it's like n eight, nine for also like making some automatization and I think they're like. Making a very good user experience interface for non code I think are like the most important launches of this month. I don't want to go much deeper like in the group or deep seek or that file because I think. What they have been launched are all like, quite the same and not very innovative on that aspect. But I think that open AI with the agents and also NH nine I think they are the most innovative right now. Although I know that in April we were having like Google next, so they're going to launch very, Google is going to launch, I think very important stuff for that event. So perhaps that so surprise us a

Andreas Welsch: 23:11

bit. Who knows? Seems like there's surprises all around us in this day and age with AI. Now, hey we're getting close to the end of the show and I was wondering if you can summarize the key three takeaways for our audience today.

Camila Manera: 23:23

Yes. So first of all, for all businesses that want to apply AI, you need a translator. You need a business AI translator in your company. You have to think of independent structures so everybody can create and develop AI inside the teams. Don't get confused with all the information that it's going up there. You have to center in what your company needs and what your culture needs, and develop a long-term vision plans and know just one month AI implementation because if not, you are gonna have to get frustrated on the road. And once you want to get real big changes, you need to have very good long-term strategies. Wonderful.

Andreas Welsch: 24:06

Camila, it was a pleasure having you on the show. Thank you so much for sharing your insights and your learnings and how business and AI leaders can work better together.

Camila Manera: 24:16

No, thank you. It was a pleasure to be here. To tell you a little bit about how South America and Argentina it's developing and strategies around AI. So it was. A pleasure for me to share this space with you.