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This season has been kindly sponsored by the Philadelphia Convention and Visitors Bureau. Visit discoverPHL.com to start planning your next life sciences meeting.
AI is everywhere, but is it truly driving business transformation? In this episode, Augusto Salvatto explores the gap between AI hype and real-world impact, the importance of machine learning over generative AI, and how organizations can take practical steps to adopt AI strategically.
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Convene Podcast Transcript
Convene Series: Beyond the AI Hype: How Businesses Can Leverage Machine Learning for Real Impact
*Note: the transcript is AI generated, excuse typos and inaccuracies
Augusto Salvatto: So we have a technology with a lot of hype, a lot of impact in media, but not great impact as far as today in businesses.
Magdalina Atanassova: Welcome to Season six of the Convene Podcast brought to you by Philadelphia Convention and Visitors Bureau.
AI is everywhere, but is it truly driving business transformation? In this episode, we sit down with Augusto Salvatto, a politologist turned tech strategist, who specializes in bridging the gap between disruptive technology and human decision-making. A bestselling author in Argentina, Augusto brings a unique perspective on how businesses can move beyond the AI hype to real-world impact. We explore why machine learning, not generative AI, holds the key to innovation, how organizations can take practical steps toward AI adoption, and why a shift in mindset—from replacement to growth—is essential. Tune in for a thought-provoking discussion on navigating the AI revolution!
We start now.
Hi Augusto and welcome to the Convene Podcast. It's a pleasure to have you here.
Augusto Salvatto: It's a pleasure. Thank you for inviting me.
Magdalina Atanassova: Let's dig into AI. AI is already transforming businesses through predictive modeling.
But what are some lesser known ways AI is driving real time decision making and innovation beyond just forecasting to begin with?
Augusto Salvatto: I believe that the biggest challenge we have or we face today in the field of AI is the problem of the conceptual noise. You know, this usually happens in technology when a topic becomes so popular and relevant and everybody really thinks this is the next big thing.
So everybody's talking about AI and everybody wants to adopt AI in their organizations. And that's really a problem because when it comes to the impact of this technology in businesses, I really prefer to talk about MAD technologies, MAD technologies, you know, machine learning, artificial intelligence and.
And, well, machine learning, in my opinion, has this great predictive power if we have the available data. And however, only 3 out of 10 companies are using it effectively to drive business impact.
So I think first we have a lot to do, a lot of room in this area of machine learning before introducing to AI and a lot of innovation in AI and generative AI.
That being said, AI essentially does two things. Predict things and cluster things.
That's basically all this may seem very simple, but actually it's really important and revolutionary. It enables pattern detections and object recognition in images.
So I think this is the most important thing to do, understanding the real impact of this technology and understanding that the key challenge we have here is adoption before going to generative AI and really innovating things.
Well, we can use data science and machine learning to predict very important things in our businesses.
Magdalina Atanassova: And do you want to make the distinction between machine learning and generative AI just for those that may not Be very familiar with it.
Augusto Salvatto: Yeah, sure. I mean, when we are talking about machine learning, we are talking about machines that like actually learn things out of data, out of a lot of data. Generative AI are like, for example, when we use ChatGPT or MidJourney, is AI producing some new things out of one prompt?
If we have to visualize this,
machine learning and artificial intelligence are a lot of different things. Generative AI, just a little tiny thing in that entire world. So usually when we talk to people in businesses and they talk us about wanting to implement AI, they usually refer to generative AI.
And that's kind of a problem because we don't have a lot of business cases of generative AI, really important business cases. So we have a technology with a lot of hype, a lot of impact in media, but not great impact as far as today in the, in businesses.
So that's kind of a problem because it makes a real misunderstanding between expectations and reality.
Magdalina Atanassova: I think that's very important point that you made. So how do you approach such conversations with businesses? Where, where do you start and how do you help them, you know, set their goals straight so to ensure a smooth transition?
Augusto Salvatto: Well, here in Latin America we have this like saying, common saying that I think it's the same in English that don't put the horse like above the cart, you know, so that's an important thing to do.
I mean, people usually ask, what can we do with AI? And my reply to that is,
what problem you want to solve? You know, the problem is always first, you know, or what do you want to do to make an impact in your business? And if we start there, maybe we'll have better answers than, than asking, what can we do with AI?
I like that approach better.
Magdalina Atanassova: Yeah.
And organizations, I'm sure, approach you with the idea that their whole team will transition and start using AI in one form or another.
But that's quite of an ask because there are so many teams that have different roles and responsibilities.
So what's the right approach here for.
Augusto Salvatto: Generative AI, you mean? Yeah,
well, first of all, one of the things we ask when we start this process is what are you using AI for? Are you using to do things you usually couldn't do before, or are you doing just easier stuff?
For example, I don't know, helping yourself to write an email. Okay, that's not really transforming, you know, it's just time saving or a little bit time saving. That's not a huge case.
But if we start through the problem, we can actually identify what things are taking you a lot of time or making you inefficient and we can start through there. And that's one part of the conversation.
Another part of the conversation that is actually more interesting is okay now you are saving time with Gen AI, for example, writing emails or editing podcasts or writing a script for the podcast or that.
What can you do now? What are you going to do with this extra time? And I think that's the interesting conversation for businesses. I mean we have like this replacement mindset.
You know, we think what can we replace with AI? And that's actually, actually is problematic because a lot of people are afraid to that. But we don't have this AI growth mindset and I prefer this growth mindset.
And now that we have AI, what can we do extra that we didn't do before?
Magdalina Atanassova: And I would add to that, how can we build on that relationship? And I'm putting relationship in quotation marks, this relationship with Genai,
but still use our human intuition for better results.
Augusto Salvatto: Well that's really, really interesting because I truly believe we are not living through the revolution of artificial intelligence, but rather we are living the revolution of intelligence itself. I mean we humans thought until now that we were the only ones that could have intelligence in the whole world actually.
So I think this process is enhancing human intelligence and human decision making.
So we like to put this like this framework with three intelligences. We have computer intelligence, that's like algorithms,
I mean technology itself, AI, Gen AI tools. That's computer intelligence, that's just a tool. And then we have human intelligence. Actually that's what I do. And that's cultural things, training,
learning in an organization. And then we have decision intelligence. So this has to be useful to take better decisions, more intelligent decisions. If you want to adopt artificial intelligence in an organization, you have to take into account these three intelligences.
If you just take one of them, that's not going to work. I mean usually organizations say okay, we hired, I don't know, co pilot and, or ChatGPT. So now we have AI.
And that's just the beginning. Just one part. If you don't change your culture, if you don't change the way you make decisions,
that's not going to have an impact in, in your, in your life.
Magdalina Atanassova: Yeah. And speaking about that, AI is providing accurate, we can say to an extent, data driven insights. But how can businesses balance AI decision making and make it ethical as well?
Augusto Salvatto: So this is an interesting point because when we think about ethics and AI we make it like a whole different point of humans and Ethics.
So that's like an interesting thing to do because humans like to put the default of things to other things. So we are not judging the AI just as we judge humans.
We expect AI can do more being more ethical than we are. So that's kind of a problem. When we think about the ethics of AI, we must think first in the ethics of humanity.
AI makes decisions over data that it is trained of. And if this data is biased because it has human biases, it's not going to be the most efficient data to make decisions.
So if we want to solve this AI and ethics problem, I think first we have to go back to the philosophy and go back to ethics and understanding human ethics.
I work with many organizations that have these small halves of AI governance and there you can find people from HR and people from technology and people that come from a philosophy background.
I think that's a really interesting thing to do.
Magdalina Atanassova: Yeah,
I'm thinking just in our case, in the events industry, event professionals can allow for such a mix of brains to solve the issue,
but maybe to also come with time. There is another thing with AI. It really relies on past data, right, to make predictions. Nothing is really new in terms of it just happened now.
And AI already has it in its kind of bank of knowledge. So how can businesses ensure fairness and mitigate bias in AI driven decision making?
Augusto Salvatto: Well, I have two things to say about this point that I find it really interesting. First it two or three years ago, I will tell you, okay, that's exactly, it works exactly like that.
I mean that AI relies in past data to make predictions. However, generative AI is kind of changing a little bit that, you know, that's a synthetic AI and synthetic data, they are creating new data and making like inference of new data.
So this is kind of changing. There's other discipline, really new discipline, that's a quantum machine learning, that's really important for that. So maybe in the following years this statement wouldn't be completely precise.
Actually today it is. But maybe this is changing and that's an important thing to say.
But regarding to your question, I think that the answer depending what's our, our final goal, you know, or whether we aim to build a better world or simply make better business decisions.
And I'm going to explain this. I mean it may sound like a cynical remark, but as I was just saying, when we talk about AI biases, we are referring to human biases.
So my question is, do we hold the same standard when making organizational decisions, ensuring that they are free of biases. So I Don't think so. In most cases the answer is no.
So that's a problem because as I was saying, it shift responsibility away from humans and place it just in a technology tool, you know. So I believe the right way to address this challenge is ensuring we have well trained professionals that are capable of making ethical decisions and establishing strong governance frameworks for AI.
And I think that's a complicated thing to do.
Magdalina Atanassova: Yeah, but as you said, we're all flawed and sometimes we're just emotionally attached to the outcome.
Magdalina Atanassova: After a word from our sponsor.
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Now back to the program.
Augusto Salvatto: Yeah, sure, maybe we should just accept that our decisions are biased. But one thing that's important, and there's this concept in AI governance that's human in the loop.
So you shouldn't give the AI full responsibility for taking a decision that's actually important or will have ethical implies. You know, let's put an example.
Let's suppose that you are using a predictive model to decide whether you give or not loan to someone you know. So maybe that's a great tool to analyze a lot of data of people.
However, the final decision over that, I think it should be a human decision based on insights that data and artificial intelligence can give you. But at last it's a human decision.
Magdalina Atanassova: Yeah, I cannot agree more.
And speaking about this human side, many organizations are using AI to process very sensitive data, be it for customers or their own businesses. So what would be best practices here that businesses can adopt to safeguard privacy and prevent data misuse?
Augusto Salvatto: I have to say I'm not an expert in cybersecurity or data protection, but I believe this is a really important discipline and it should be taken really seriously and require highly trained professionals.
My recommendation is always to strive to comply with European General Data Protection Regulation. That's GDPR and these are like guidelines that are really important in Latin America. We don't have lost that like force us to use the GDPR, but my recommendation is always trying to address that.
They're really profound and well think guidelines. So if we are trying to protect our customers data, that would be a good point to start.
Magdalina Atanassova: And have you seen a difference between using a free version versus a paid version in terms of safeguarding what you're inputting into AI? Or do you think this is more or less similar no matter if you're using paid or free?
Augusto Salvatto: Well, it depends on the tool, but usually the paid version. For example, in OpenAI tools are better to protect your data. However,
this is a governance decision, so we shouldn't adopt AI tools without having governance decisions. For example, I use ChatGPT for my personal use and I don't really care about the data that I put there.
I don't think that's sensitive data. So I don't take a lot of governance decisions. But when I use it, for example with a client, I have to have other things into account.
So that actually depends on how we are using the tool anyway.
Magdalina Atanassova: Yeah, good point. How do you see AI transforming the business events industry? And do you have any practical applications that can help business event professionals enhance maybe their attendee experience or their operational efficiency?
Augusto Salvatto: I believe that every stage of an event has AI application that can add value on it, for example in even planning and logistical optimization. Predictive models can be incredibly useful even in lead generations or marketing.
They can play an important role. And I'm currently working with an organization that uses AI to edit images and event reels and videos almost in real time. Just a few years ago this process would have taken at least a couple of days and was expensive.
So that's an important point. But let me share with you something I always tell organizations when I start working with them. The number of business cases for your industry specifically is almost infinite.
But they won't be discovered by someone who only knows about AI or just understands AI. They will be discovered by someone who deeply understands the business. And that's the most important part and has also a solid grasp of what AI can do.
I think that this roles that maybe do not exist in organizations yet will be really important because this is a very important thing to just delegate it to the IT area.
You know I'm just kidding with this, but this is a business thing, not a technology thing.
Magdalina Atanassova: So how can businesses set realistic AI adoption goals to ensure sustainable transformation?
Augusto Salvatto: First thing to say is going back to something I said before that first of all starting with the problem. When you start with the problem and you can identify for example what things are problematic in your business, something that really inefficient, then you can set some goals to to make projects,
AI projects and machine learning projects and all that. But I think the most important thing for organizations is taking into account three things. People, training, culture,
that's what human intelligence would be. Then technology, tools, algorithms, and then business cases. So I think a good point to start is taking into account these three things and then choosing the people inside the organization that could do this.
Magdalina Atanassova: Having in mind that now most organizations are testing the waters with AI, what do you feel will be their biggest competitive advantage if they stick with it and adopt it long term?
Augusto Salvatto: My vision here is that AI will become like a Commodity, you know, so in the next five years or so we will be talking about competitive advantages and that's okay. Organizations that adopt this technology will be more efficient, will reduce costs, they will be definitely growing.
And that's a good point. However, in the next decade, I mean, let's put in 2000s, my prediction is that organizations that do not adopt AI will be certainly replaced by others that do.
And that's not a competitive advantage thing, but a survival thing.
And I like this parallelism. It's like adopting Microsoft Word and Excel in the 90s.
At first organizations that adopted Microsoft Excel, maybe they were more efficient and they had some advantages over others. Right now you cannot think about organizations that don't have these tools.
Magdalina Atanassova: Yeah, that's true. Even though many of us would imagine a world without Excel in it and we'll be fine.
Augusto Salvatto: Yeah, yeah, sure. But that's an important point there because maybe there are some things we can do without Word or Excel or Google Docs or whatever. But for example, we couldn't be sharing an email with a presentation with someone today.
So technology is advanced, like by steps, you know, short steps. And maybe you may see one of these steps, like not really important, but if you don't start climbing, you'll never get to the top.
Magdalina Atanassova: And do you see Gen AI in this case also adding any creative edge in terms of, you know, when we're speaking about competitive advantage, I think that.
Augusto Salvatto: We don't have a lot of business cases of generative AI yet.
We can be more efficient in our day to day life and that's great. But we don't have real business impact with this. And this is not a good thing to say because many people are expecting that you tell them, okay, you will adopt Genai and this is going to change organization just for $20 a month.
And that's simply not true. So I'm like the bad guy here and I had to say, okay, if this is hard working thing, adopting AI is not easy. It takes time.
It takes like, you know, tries and errors and it's not going to save your life in just from one minute to another. There's this joke in the AI industry that many people talk about machine learning, like magic learning, you know, so not really good joke, but thank you for laughing.
But you know, people usually sees AI as kind of magic. That's problematic.
Magdalina Atanassova: Yeah, I feel there's also this disappointment sometimes when for example, ChatGPT does not deliver some groundbreaking text, for example, that you've asked to create and then people are really, really disappointed.
But it's like, it's not a magical being that just,
you know, produces things into existence out of nothing.
Augusto Salvatto: So, and, and that's an important thing to say because humanity seems to have lost is its, like, surprising capacity. You know, I was just remembering that back in 2021, I was helping a friend of mine who was writing a book with his prologue and his introduction to the book was written by GPT Chuk.
And it was a really bad text, you know, standard text, but it was kind of an amazing thing. And actually the editors of the book decided to put this in the book cover.
You know that the introduction to this book was written by Nai.
And if you compare this to what GPT can do now, it was like, awful. However, by the time it was really surprising because we didn't have this technology and it was like four years ago.
So in this, I think that. And this is maybe more a philosophical thing, but humans should recover its capacity to get surprised of things because actually surprise is key point for understanding new things and wanting to learn new things.
So if we lose it, maybe it's going to be really bad for us.
Magdalina Atanassova: Yeah, I cannot agree more.
And wrapping the conversation up. If businesses could take just one essential step to use AI safely and effectively while driving transformation, what would it be?
Augusto Salvatto: There was this Greek philosopher, he said, like, the only way to know how to walk is like just walking, you know. So I think that the first step would be start using it, start using the tools, because that would be a way to understand why it is good for you or in which cases it would be good for you.
I mean, these baby steps are really important because if you want to start for a predictive model that can change a core point of your business,
maybe you will be disappointed. For the first results, you will spend a lot of money and business decisions are usually like, benefit driven. I will tell you another Latin American saying, I don't know if the same in English, but when someone gets like burned with milk, when it sees a cow,
it starts crying.
So if you fail with your first approach with AI, maybe you're not going to try it again. So baby steps and start using it.
Magdalina Atanassova: Was there anything we didn't mention we should.
Augusto Salvatto: Before we close,
we have a great challenge with this AI process and this hype.
There's an enormous hype in this technology, especially in the media. Some leaders, they really think this is magic and this will solve every problem you have. So this makes our job really complicated because we are the bad guys here.
And if I have to just say one thing that could be, I think, the most important thing right now. I'll say, like,
this is not so easy. It's hard. It's really business transforming. But it takes time and hard work and education and learning.
Magdalina Atanassova: Yeah. I love it. We often speak about efficiency with AI, but you have to invest time to actually make AI help you be more efficient.
Augusto Salvatto: So let's really generational thing.
I think our generation, in wide sense of it feels like there shouldn't be processes for things. And processes are really important in life, in relationships and in businesses, too. So valuing the process, it's a really important thing in this matter and in every matter.
Magdalina Atanassova: Yeah. I love that. Well, thank you so much for your time and shedding some light on transforming businesses with AI.
Augusto Salvatto: Thank you.
Magdalina Atanassova: Remember to subscribe to the Convene Podcast on your favorite listening platform to stay updated with our latest episodes. We want to thank our sponsor, Philadelphia Convention and Visitors Bureau. Visit discoverPHL.com to start planning your next life sciences meeting. For further industry insights from the Convene team, head over to PCMA.org/convene. My name is Maggie. Stay inspired. Keep inspiring. And until next time.