Organized as one of the region’s major technology and business gatherings, ANDICOM 2026 will focus on the theme “Unleashing The Power Of AI,” examining how artificial intelligence is being applied across companies, industries and governments.

The congress will connect technology supply and demand through business meetings, networking opportunities, exhibitions and discussions covering artificial intelligence, digital transformation, cybersecurity, connectivity and emerging technologies.

Dates: September 1–4, 2026
Venue: Las Américas complex & Hotel Faranda Collection, Cartagena

For more information and registration details, visit the official ANDICOM website.

Featured photo: ANDICOM 2025 (Photo provided by ANDICOM)

Finance Colombia: I’m here with Brad Cleveland. It’s great to see you again, Brad. I’ve known you for a long time and been an admirer, as the founder of ICMI. I’ve been kind of an outside affiliate for a lot of years, as a judge for the awards that you all have. We’re here in Cartagena, Colombia, at the CX Summit put on by BPrO, which is the industry association here in Colombia. And it’s quite a nice surprise to see you here. Is this your first time at the CX Summit here in Colombia?

Brad Cleveland: It is, Loren, and great to see you. I know we’ve run into each other at a bunch of other events, and to be here in Colombia — yeah, this is my first time, and I’m really enjoying it.

Finance Colombia: Wonderful. I hope that after the event, whatever you do, you take a couple of days to go out and enjoy it and see things. We’re here in Cartagena, which is a beautiful, historic city. There’s so much to see.

I always try to do that when I’m here on business. But let me ask you: yesterday, you talked about leadership in customer experience, and I believe you also have a book that’s recently come out on that topic. Leadership is such a broad topic. Every industry talks about how important it is. LinkedIn is flooded with posts on leadership — but what is it about customer experience that prompted you to write this latest book? You talked about that yesterday, and that’s why I want to touch on it, because it’s a theme that is obviously very important and that you’ve given a lot of thought to.

Brad Cleveland: Yeah, well, thanks for the question. You’re on the right track. I would say there’s so much on leadership. I felt that customer experience needed more structure in terms of leadership. So Leading the Customer Experience covers the 10 pillars, starting with: what’s your vision, and the values behind that? And then it goes chapter by chapter. The second is that we’ve got to get our team on board. We really need them on board as we establish our vision, right? So these things do work together. And then there’s the customer engagement, the customer service, and the customer advocacy that we put in place as a culture; the budget — that’s a chapter. How do we budget for this? So the idea was to really lay this out step by step — not the customer experience cookie cutter. It’s big. It’s everything. It’s products, services, processes, our brand, our reputation. But I felt like there was a place for a little more structure in how we lead this.

Finance Colombia: You know, you bring up several good points right there, because a lot of times companies… And you see the companies that — not to overuse the word — lead in this area get it, and they integrate the customer experience into the whole fabric of who they are as a company.  And it doesn’t matter whether it’s a consumer products company like Procter & Gamble (NYSE: PG), Smucker (NYSE: SJM), or Nike (NYSE: NKE) that doesn’t necessarily interact with its end user on a day-to-day basis, or those companies that do. We both got here on airlines.

And the airline industry is going through a lot of changes, and people are trying to figure out how to get it right. One of the things — when we talk about leadership — that I see and that concerns me is how AI, which I think overall is a good thing, is being implemented into CX, and how the decisions are being made around that. And my concern is not like a lot of people’s: “Oh, it’s going to replace all the jobs, it’s going to replace everything.” It’s not so much that. But if you remember — I’m old enough to remember — back in the ’90s when IVRs came out, everybody, especially the telecom carriers, went to replace everything with interactive voice response (IVR) systems. And you’d get into a loop. First they tried to have voice — that rudimentary voice recognition — and it would say, “I don’t understand. Can you repeat that?” And you’d get into this loop and you could never get out; you could never reach anybody. They just thought they could turn on this IVR system, fire everybody, go home, and everybody would be happy. It didn’t quite work out that way. I feel like it’s déjà vu all over again. Is there a breakdown in leadership, or what do you see that could be precipitating this?

Brad Cleveland: Well, there were predictions out of the World Economic Forum in Davos back in the 1990s that the internet was going to take over customer service. That proved to be exactly wrong. I mean, the internet grew the need for customer service. We’re seeing much the same with AI. It is a powerful, powerful capability, but we can’t make the same mistakes we’ve made in the past. There are three levels of value, and here’s how I like to think about this. The first level is efficiency. We’ve got to be efficient at what we do. A second level is customer experience: are we making things easier and better for our customers? The third level is strategic: what are we learning in the course of serving our customers that can help us improve products, services, and processes? This is a goldmine of insight. So right now, much of the industry is focused on, “Well, we’ve got this work — how can AI help with it?” Oh, and then there’s agentic AI, and there’s this and there’s that. We’ve got to think of all three levels and really put ourselves in our customers’ shoes: what’s going to work best at all three levels, where AI can be a partner with us — and a powerful one — if we use it right.

Finance Colombia: I think that’s key. People look at it too much as a line on a spreadsheet and say, “Hey, this can reduce these costs.” And yes, it can, but you can do it the right way and you can do it the wrong way. It’s just like there’s nothing at all wrong with running a BPO in India, for example — not to pick on India. There’s nothing wrong with doing that in itself, but so many people did it wrong. India wasn’t the problem; the way they implemented it was the problem.

Brad Cleveland: Well, right. And the same with our team, the same with technologies. It’s really all a matter of going back to our vision and values, and then the support behind that to make it work. Steve Jobs once said — and we’ve all heard this quote, but it’s a good one, and there’s a reason we repeat it so often: “You’ve got to start with the customer and then work back to the technology.” And the same thing is true with anything. You’ve got to start with the customer and then work back to our standards, our objectives, the processes we’re putting in place, the technology — everything to support that.

Finance Colombia: You know, I just had a problem at home with our fiber internet to the house, and I was so upset. I said, “Well, I’ll just change to the other company.” So I went to the other company’s sales channels, and they had tried to implement these automated chatbots. And I was ready — I was so mad at the other company that I was ready to buy. And I got put into a loop. I can show you — I can pick up the phone and show you where they never answered their own system that they had implemented. So that’s a failure on their part. And I sat there thinking to myself: if there were a third telecom option, an additional option, that would charge me more money but give me somebody to handle a problem when I have one, I would pay 20% more, maybe even 30% more. You can’t get ridiculous, but I would pay more.

Brad Cleveland: And the surveys all say that we all want it to be easy. Here’s the irony: it costs less internally to do a great job and to really involve humans where humans are best, because we’re going to get your business, right? And we’re going to have those problems solved so they don’t come back over and over. You put a pencil to that, and it doesn’t cost more to provide better service. It’s very rewarding to the budget side of things.

Finance Colombia: You can charge more, too. I’m not a rich guy, but I did not fly in the budget economy here. I paid more. I didn’t fly first class or anything, but I paid more to get the extra legroom and the free boarding and those little things. So you can charge more, too. Don’t be afraid to do that. There are people out there who will pay. There’s always going to be the bargain basement, but there are people who will pay for that experience. Now, I don’t want to take up too much time, because I see lunch is starting — I don’t want us to starve here. But I do want to mention that ICMI’s Contact Center Expo is coming up, I believe, October 27th to 30th. It’s always at the Loews Royal Pacific in Orlando, unless it’s been moved or something.

Brad Cleveland: Yes, it’s there this year again.

Finance Colombia: Okay, I’ve got to make my reservations. I always make my reservations early. So if you could — is there a website? I know ICMI is part of Informa. And if you don’t have it, don’t worry, we’ll add it in the lower thirds.

Brad Cleveland: Yeah, you can find it easily just by going to ICMI.com and looking for events — it’ll drop down. And, yeah, I’ve got to make my reservations as well. It’s coming up. It’s going to be a great conference. It’s an important time right now, with all the developments taking shape.

Finance Colombia: And ICMI — I’m there almost every year. It’s so important. It’s worth it. It’s a great conference, just like this one. It’s not a huge convention like something in Las Vegas, but it’s where you interact with your peers. Just like here at the CX Summit, there’s always a lot of thought put into the keynotes. You always leave not just inspired, but having learned something. And it’s big enough to be worthwhile, but small enough to really interact with people — not just the vendors, but colleagues. And I think that colleague interaction is a lot more important. Last question for you: what’s your impression — not just of your first time in Colombia, which I know you haven’t really seen outside of the lovely Hilton — but of the Customer Experience Summit put on by BPrO?

Brad Cleveland: I have loved it so far. It’s a great event, very focused on not just the technology and not just the management part, but the heart of customer experience — how it’s impacting our cultures, our future, our families. There have been some really great sessions that give a comprehensive view of where things are going and how important customer experience is to all of us. And just while we’re here — the food, the people are great. It’s just been a fun experience.

Finance Colombia: Absolutely. Just like with Informa, just like with ICMI, they’ve got great leadership at BPrO and CX Summit, and I think that makes a difference.

Brad Cleveland: Yeah, what a great team. What a great team they have.

Finance Colombia: Great. Brad, see you in October.

Brad Cleveland: Thanks, Loren. See you soon. Thank you.

The conference agenda included discussions on artificial intelligence (AI), smart cities, and cybersecurity. Over 120 speakers were scheduled to present. Keynote speakers included physicist and author Dr. Michio Kaku. Additional participants include Spain’s Minister for Digital Transformation and Public Administration, Óscar López, and a delegation from the United Arab Emirates.

Event Focus and Speakers

According to Adriana Leal, manager of ANDICOM, the event has positioned Cartagena as a hub for technology and innovation. Leal noted the participation of Kaku, an author recognized for his work on quantum computing, and the presence of López, along with the delegation from the UAE.

Yamil Arana Padauí, governor of Bolívar, stated that ANDICOM provides an opportunity to showcase projects such as Mompox Inteligente, a local connectivity and technology initiative.

Agenda and Thematic Tracks

The pre-conference on September 2 featured three main tracks:

• CyberShield Forum: This track addresses cybersecurity, deepfakes, and cyber-resilience.
• Autonomous Agents: This segment focuses on the application of AI in corporate processes.
• CINTEL Future Cities: This track covers topics such as digital tourism, smart cities, and urban mobility.

From September 3 to 5, the main conference focused on digital evolution, the future of the IT sector, and the role of the economy in the AI era. International delegations from countries including the United States, Belgium, Spain, the United Arab Emirates, Israel, the Czech Republic, and Canada are expected to attend.

The conference also hosted three award ceremonies to recognize regional innovation: the Digital Transformation Innovation Awards (in collaboration with PwC), the Smart City Innovator Awards 2025, and the Enterprise Cybersecurity Awards (a partnership between ETEK International and CINTEL).

Business and Networking

ANDICOM’s networking initiatives include the “Meet and Business” room, which will bring together executives from 28 companies, including Coca-Cola FEMSA (NYSE: KOF), ISA (BVC: ISA), Allianz (FWB: ALV; SIX: ALV), and Arturo Calle. This space is designed to facilitate direct connections between companies seeking technological solutions and providers.

The event also features a business roundtable for one-on-one meetings between sponsors and C-level executives, with the capacity for up to 400 scheduled meetings over the four days.

Conference Statistics

• Estimated Participants: 6,s00+
• Participating Countries: 35+
• Companies Represented: 250+
• Speakers: 120+
• Academic Sessions: 80+

ANDICOM 2025. Photo credit: CINTEL.

PROI is recognized globally for leading innovation in methodologies and technological advancements within a rapidly evolving industry. In a world where constant adaptation is crucial — driven by the advent of Artificial Intelligence, the surge of fake news, bots, trolls, avatars, and other digital entities — PROI continues to set the pace for effective communication strategies across the globe.

Mauricio Ferro, an alumnus of CESA and the Darla School of Management Columbia, South Carolina, and mentee of Miguel Silva Pinzón, former Managing Director at Weber Shandwick and FTI, has been a leader within PROI, consistently consulted by C-Level executives of major corporations throughout Latin America, Spain, and the US for his expertise in strategic communication. His career spans over 25 years of delivering impactful insights and materials that support media and public relations efforts.

He has served as a trusted advisor to six ministers of state during a period when such roles commanded significant respect. Through his creativity and resourcefulness, Mauricio has helped shape the positioning and protect the reputation of hundreds of brands, companies, and organizations.

Earlier in his career, Mauricio founded Position Comunicaciones, pioneering social listening algorithms in Colombia. Coming from Microsoft, his natural affinity for technology enabled his team to adapt and parameterize Radian6 software in Spanish, positioning the agency as a regional leader. This innovation attracted multiple international companies seeking strategic partnerships.

In 2015, Edelman Worldwide acquired his agency, recognizing its innovative methodologies and technological edge, appointing Mauricio as the first Edelman President in Colombia.

In 2020, Mauricio launched his current venture, TANK, which has distinguished itself globally through advanced crisis management solutions and immersive training using hyper-realistic Virtual Reality technology — services that are unparalleled in Colombia and abroad. His participation in an expert panel in Stresa, Italy, convened by PROI, exemplifies his leadership and innovation on the international stage.

Today, TANK exports services to multiple countries in diverse sectors, including finance, technology, healthcare, and energy, driven by Mauricio’s innovative approach and Colombia’s top-tier development talent.
His contributions have been recognized internationally; he has been featured in Forbes USA, and in 2014, PRovoke Media named him among their “Innovators25” for pioneering industry innovations.

TANK’s portfolio includes AI-driven tools such as PRejavú, a virtual reality and AI platform for accelerated executive training, a predictive software that analyzes the potential impact of online posts and news, and an advanced digital media buying system optimized through AI and data analytics — all designed to reduce costs for clients and enhance lead targeting.

Mauricio emphasizes that TANK has invested over five years in AI development, well before the widespread recognition of ChatGPT’s capabilities. Since 2023, the full suite of products, now matured and proven, has been exported internationally, showcasing 100% Colombian technology.

In circumstances where companies face reputation and positioning challenges — from stock markets and extractive industries to technology and healthcare sectors — Mauricio’s strategic insights, rooted in extensive experience and data-driven analysis, prove invaluable. This has positioned TANK as one of the most innovative and trusted firms in the communications industry globally.

Global Director of Crisis Management at PROI, Mauricio Ferro. Photo credit: PROI.

Best known for her time heading marketing at her brother’s company Meta (Facebook), Zuckerberg brought her passion for “Leadership in The Age of AI” and how artificial intelligence can support leaders in decision making but also encouraging women and girls to get involved in technology, and specifically AI. She spoke about how so many time she found herself the only woman in the room where important decisions were being made at a corporate level.

After Zuckerberg’s conversation with Loren Moss, executive editor of Finance Colombia, Zuckerberg answered questions from the local press corps with Moss moderating and serving as interpreter for the questions from local journalists attending the event.

Finance Colombia: We’re here with Randi Zuckerberg. First, welcome. And is this your first time in Medellín?

Randi Zuckerberg: First time in Medellín, but not my first time in Colombia. I’ve gotten to travel extensively around the country, but I’m delighted to be here.

Finance Colombia: Wonderful. Hopefully, you’ve had time to see the city, and what are your impressions?

Randi Zuckerberg: I have. Well, I got to tour all around yesterday, and I love a city that has a bit of a deep history that makes you think. But what I’m inspired by is how the city has taken a bit of a darker history and is transforming into an art and technology hub of the world. I think it is a model that a lot of other cities should be looking at.

Finance Colombia: Impressive. If you could just, in a couple of sentences, recap the message that you gave today–or that you’re giving today in your presentation later.

Randi Zuckerberg: Yes, I’m talking about leadership in the age of AI, and I’m going to be reflecting on my experience on the front lines of social media, and using that as a way to structure how people can think about being in this next new era of innovation with AI.

“I will eat this table if there are not more women in AI than there were in Web 2!”—Randi Zuckerberg

Something I’m very passionate about is talking about women in technology, and when I was on the front lines of Web 2.0 and social media, I was one of the few women in the room. And now that it’s 20 years later, and we’re on the dawn of a new era of innovation, it would break my heart if that happened again, and things didn’t change. So I feel passionate about mentoring women to be entrepreneurs, about getting more younger girls into technology, and especially making sure that women in universities around the world have the opportunity to study technology in the same way. So yeah, I will eat this table if there are not more women in AI than there were in Web 2.0.

Finance Colombia: How can AI be used as a tool to empower women?

Randi Zuckerberg: I think there are so many ways that AI can be used to empower. First of all, I think it levels the playing field, because AI can now do things like writing basic code, designing, so you can be anywhere in the world, and even if you grew up in an area where maybe girls don’t have the same access to education, you now have the tools to launch a successful business, and be an entrepreneur, and be on the same playing field as people across the world that had the best education and the best resources, and I think AI is going to just open a world of creativity.

Local journalist: One question for the old people who are going to embrace the changes with technology.

Randi Zuckerberg: I think that hopefully we’ll live in a world where wisdom and experience are honored and celebrated side by side with innovation and tech knowledge. I think if you’re just looking into the future, you’re missing a lot of valuable things about an organization, and a culture, and an industry. Likewise, though, we have to make sure that people who grew up without tech as a first language are partnered with a mentor who can bring them up to speed and help them upskill themselves. So I think I’m excited about a workforce where those two live side by side.

Weiss gave an engaging, interactive presentation, evangelizing not just the adoption of generative artificial intelligence (AI) but how to make the best of it the platform, using it to work alongside humanity rather than supplanting us.

After initial dialogue between Loren Moss, executive editor of Finance Colombia, Weiss answered questions from the local press corps with Moss moderating and serving as interpreter for the questions from local journalists attending the event.

Finance Colombia: I’m here with Mitch Weiss of Harvard Business School. You just gave a really interesting talk at this year’s 2025 WOBI. You gave great advice and counseling on using artificial intelligence and its ramifications.

Now I know that you have a history working with innovation in the public sector, and so one of the things I wanted to ask is if we look at… We’re here in Medellín, and you had a chance to tour the city, and you see that we’re kind of in a valley. And if we go into the other side, you know, most of the people here today probably already have some kind of experience with generative AI. That’s kind of the audience that we have here, but if we go on the other side of this mountain range behind us, you have people who still struggle using an ATM. And you know, fraud is a big concern and taking advantage of people and things like that, and what is the role… How can let’s say, governments, because you have experience in the public sector, help protect the consumer? Because now we have things like deepfakes, we have things like… I’m experimenting with ElevenLabs, and they can replicate my voice and things like that.

How do we promote innovation, but at the same time protect not just the consumer broadly, but when we have a big digital divide between well-versed people, let’s say the techno elite, and then people who are struggling to even catch up? What’s the role that you see the public sector and academia can play in maybe policing this wild west that we’re in?

Mitchell Weiss: Well, I think, frankly, policing is going to be hard. I think, as you mentioned, there are so many ways these tools can be used for bad means, and also there are lots of ways to circumvent whatever government regulations are put into place with open source technologies and otherwise. So I do think there’s a place for prudent government regulation, but I think it’d be a mistake to rely on that entirely.

I think we should instead, or in addition, imagine actually, how we can empower people with these tools? It’s true that there’s the ability to use them for fraud and all the rest of it, but it’s also true that anybody with it now has a teacher in their pocket. Anybody with it now has some version of a doctor in their pocket.

Anybody with it, if it’s reliable, now has some version of a fraud protector also in their pocket. So I think my posture would be, how do we make the tools available to people so that they are empowered? And there will need to be a kind of massive, in a way, upskilling or reskilling given these tools, which the government can help bring about also, but they’re not complicated to use at a first pass. I mean, one aspect of these tools is if you can talk, you can use them, if you can see, if you can type, if you can do any of those things, any one of those things, not even all of them, you can use the tools.

And so I think the government’s role, yes, is on regulation, but also a democratization and upskilling of people so they can make the best use of these as teachers and doctors and all the rest.

Finance Colombia: You know, we have… with you and I being from the US, the US kind of has a philosophy of you can do everything until it’s proven dangerous, and then we’re going to step in and regulate it, which as a libertarian I like. But then, let’s say, Europe has the opposite extreme, which is that you have to prove that it’s not dangerous before you can do it. And then most countries, including Colombia, are somewhere in the middle of that.

And again, if we look at this rapidly… I mean, I’m old enough to remember when the internet kind of came into common use, but this is so much more rapid. This is so much more disruptive. And I would say, you know, to show my bias, resist the temptation to regulate, but how can it not just be governments and regulatory entities, but academia… I went to Ohio State, and Ohio State just announced that they’re not going to fight AI. And they just said students are now expected to use it, which I thought was very interesting. And I know a lot of other colleges are as well, but how do we balance the I guess, temptation to regulate or the fear, with, on the other hand, the desire to foment innovation and to break boundaries? There has to be a balance there somewhere. And how do we find that balance?

“You can use AI to market to potential customers better. You can use AI to manage your teams potentially more effectively,” – Mitch Weiss

Mitchell Weiss: Well, I mean, the first thing is, I would agree that there is a balance. I mean, in academia, I’m a professor at Harvard Business School, and we want to make sure that our students have exposure to these tools. We’ve been very AI forward. We were probably the first leading business school in the country to make sure that all of our entering students had access to the most advanced versions of ChatGPT when it came out. And all of our students and staff, and faculty all have access to GPT Edu, and a whole host of lots of other tools as well. We want to make sure that they have access to these tools to help them become able leaders in a world that’s going to be full of them. And to give them a professional edge so that they can get jobs and lead and lead well with these tools. And at the same time, make sure that they can continue to forge and shape the tool that’s on top of their neck. And that is the balance.

I think there are ways to do that. I wouldn’t say that they’re foolproof. Some of those ways include making sure that you set out expectations so people know what’s expected inside an organization or a school. Expectations aren’t everything, but it matters to tell people what to expect. You can make work for students harder, or you can access more metacognition, so they have to think more and work more, given that they have access to these tools. You can use them to teach better so that you’re pushing and challenging students more. You can become a better yourself on the other side. And at the end of the day, I think you constantly have to ask students, How do you know it’s true? How do you know it’s true? How do you know? You have to keep helping them cultivate this part of their brain, too. And so I think achieving that balance is a matter of expectations. It’s also a matter of training and pedagogy. And I think that translates from schools beyond, but it’s not going to be easy.

Finance Colombia: Great, great. Appreciate your time. If you could, you know, go a little deeper on how we can work with artificial intelligence, keeping that human sense in it, humanize it?

Mitchell Weiss: So if the question is, you know, humanizing our AI, I’m not sure that I would do that. I think it’s important to still recognize that it is a piece of technology. And even as it starts to talk more like a human or listen more like a human, it isn’t a human. But to work with it like it’s a coworker, so for example, when I use my AI, I will often say, ‘por favor’, or, you know, ‘gracias’, for me, ‘please and thank you’. And people will say, like, “Why would you do that?” And this happens a lot. Other people are being polite to their AI. Why do you do that? Some people think it will work better. Some papers suggest that it helps or hurts. Some people say it’s because, you know, just in case these things take over, at least I’ll be nice to it. The reason that I do that is because I want to remember to think, sort of interact with it, like it’s a coworker or research assistant.

And so I’m not trying to make it a human, but I’m trying to engage in a conversation and an ongoing iterative conversation with it. I think that’s how you get the most out of it. So I’m not trying to humanize it, but I’m trying to remind myself that I can work with it as a teammate. And there are colleagues of mine who are writing papers about what it means to have an AI, a team that’s made up of people and AI together, and showing that they’re more productive than people by themselves. And so I think it’s useful to think about it like a teammate.

I really believe, and my colleagues are writing and doing some work on this, that you can use AI to understand your customer base or potential customer base better. We saw about synthetic market testing and all the rest. You can use AI to prototype your new products and services better. You can use AI to market to potential customers better. You can use AI to manage your teams potentially more effectively. Entrepreneurs can do all these things.

And one of my colleagues has written a book called The Experimentation Machine, where he tells the story of a founder who was finding that he was spending more time with his customers, not less, because of AI, because the AI was helping do lots of other things. And also, by the way, helping prepare for these meetings so they could be more engaging, and all the rest. So I would say entrepreneurs can embrace the tools and the toolkit and stay heavily invested and involved in their companies with their workers, with their customers, all at the same time.

In this interview, Loren Moss, executive editor of Finance Colombia, spoke with Esteban Carril, Managing Director for Latin America at Chazey Partners, about the company’s latest innovative offering: FlexBPO. This unique service delivery solution is designed to provide organizations with flexibility and agility in outsourcing key support functions such as Finance, Human Resources, Procurement, and IT.

With Chazey Partners’ deep expertise in guiding companies in establishing and optimizing shared services centers, particularly in the Latin American region, FlexBPO presents a novel approach to the outsourcing landscape. The conversation explores the benefits and unique aspects of FlexBPO, delving into when this model is most appropriate for organizations looking for a more adaptable and efficient outsourcing strategy.

Finance Colombia: I’m here with Esteban Carril. We’re here in Bogotá at the Four Seasons, lovely Four Seasons Casa Medina. You just had an event, and it’s interesting because I’ve known you for about 15 years, and to see how Chazey Partners has grown and evolved… However, one of the things I wanted to discuss is that you have just introduced something truly unique in the sector, called FlexBPO. Could you tell us a little bit about FlexBPO?

Esteban Carril: Well, thank you very much for the time, Loren. Yes, absolutely. I mean, given our experience, our track record in implementing captive organizations across the different countries in Latin America, we found out that there are a number of companies, especially in the US, that are looking for more flexibility when it comes to BPO. And we’re offering a kind of captive organization, but being managed by us and empowered by our intelligent automation team, including our transformational background, so this is unique in terms of the value offer, right?

Finance Colombia: Yeah, I was going to say because we have traditional BPO and then Chazey has such a track record in consulting with shared services, companies that possibly are migrating away from BPO and setting up their own shared services operation, especially in Latin America; strong, of course, here in Colombia, places like Costa Rica, Mexico, even Brazil. But this FlexBPO, it really is kind of a new concept. And when is it appropriate for an organization to explore? I don’t want to say hybrid model because hybrid already kind of has a meaning in our industry.

But when is it something that you think makes sense for a company?

Esteban Carril: There are two different types of targets, right? Some companies already have BPOs, and they are not very happy, especially when it comes to analytical work or when it comes to real-time processing or customer-facing roles. So there are several companies, especially in the US, that are not very happy with the existing performance of their BPO providers, and that’s where it becomes an opportunity to move to this FlexBPO model.

There are other companies where you see various mature GBS organizations that they already captured a lot of benefits and a lot of efficiencies, and there is an opportunity to get additional value through transformation and intelligent automation through FlexBPO. So I would probably say both, right? I mean, we have both types of companies where we’re currently targeting this service.

Finance Colombia: I think that it’s an innovative model. I know that you guys are going to have a lot of traction. But I want to shift gears a little bit as well, because Chazey has gone through a lot of growth and evolution, so if we talk more broadly, I think you guys have something like over 150 consultants now, but over 3,000 people altogether on your team. And I know that you guys went through a kind of structural change, you guys took on a strategic partner. Give us a little bit, because we haven’t had a chance to talk for a while, you know…

So maybe give us an update on what’s happening with Chazey Partners.

Esteban Carril: Absolutely, so our company was acquired back in the year 2022 by a big BPO provider called QX Global Group, and this group was looking to provide services, especially in Latin America and the Americas in general. So we’re bringing the transformation and consulting arm that most of the BPO providers currently don’t have, and at the same time, we are leveraging all their experience and practices for the BPO environment, so we can offer them through our FlexBPO model. So this is really a very interesting model, because we mix our consulting background with our BPO background from our parent company to come up with a unique offer to our clients.

“I was surprised by the English skill sets that the new generations are bringing, especially when it comes to near-shoring operations.” – Esteban Carril

Finance Colombia: Now, here at today’s event that you guys sponsored for shared services, you talked about the impact that AI is having. What are the types of challenges that you see with your clients when it comes to adopting, you know, you’ve got some name brand clients here, I don’t want to necessarily name them without permission, that’s, you know, some companies are proud of it, some companies have different reasons… But still, I remember, if you remember back five years ago with the pandemic, everybody was talking about technological debt and the ability to be agile and move from an on-premises to a remote modality, and that was kind of the big thing, and now we look at generative AI. And where are you finding the need and the ability to help your clients, and what are the pain points that they’re coming to you to help them navigate?

Esteban Carril: So there are several challenges right now, right? When we’re thinking about intelligent automation, the first challenge that comes to mind is mainly to build internal capabilities when it comes to, you know, trying to build an internal team to develop bots and maintain bots, etc., etc. So that’s number one. I think there’s a unique requirement in trying to build the capability internally within the companies.

Number two is when it comes to master data management. Most of the companies, they don’t have the right data to scale intelligent automation, artificial intelligence, so I think one of the key challenges that the companies have right now is mainly trying to clean their data, to set up some clear governance models, and trying to have the clean data so they can explore, empower, and scale the artificial intelligence functionalities.

So I mean, I would probably think that GBS is kind of very well positioned to, you know, to drive these initiatives, not only because they have the right skill sets when it comes to talent availability, problem resolution, data analytics; but also when it comes to the number of volume transactions that are coming through the GBS operations. So right now, if you combine intelligent automation and processes, you can really start enhancing your client experience by making sure that you can provide predictive analytics, provide proactive recommendations to internal clients.

Finance Colombia: Great, and I’ll let you go pretty soon. You’ve been generous with your time. I think we both have planes to catch, but last question. You guys have a presence, I know, in over 20 countries. Here in Latin America, you guys are extremely strong. You run the Latin American operations. You guys selected Bogotá, Colombia, for this FlexBPO concept. Of all the places you could have chosen, a lot of places are powerhouses and shared services, and BPO. The Caribbean, Mexico, and Costa Rica, throughout the Americas. Why, of all places, Bogotá?

Esteban Carril: So I probably think that right now, when we look at the landscape in Latin America, and Colombia, especially Bogotá, it brings several advantages. Talent availability. I was surprised by the English skill sets that the new generations are bringing, especially when it comes to near-shoring operations. It’s also in terms of labor costs. Right now, Colombia is probably bringing the most competitive labor costs in the region. So there are a number of factors. The country, or the city, is currently not really saturated when it comes to the number of GBS organizations. So there are a number of factors why we believe that Colombia, especially Bogotá, is very well-placed today to bring more near-shoring operations.

Finance Colombia: Wonderful. Well, congratulations. I know that it’s going to be a successful stage of growth for you guys.

Esteban Carril: Absolutely. And you’re invited next time to come here. Next year, we’re going to have the same breakfast, and you will be invited to come here as well.

Finance Colombia: Count on it. Absolutely.

The event aims to explore how artificial intelligence (AI) transforms organizations and, based on this, define the keys that will enable them to adopt successful leadership in this new digital era.

Participants will learn strategies to integrate AI into organizational culture, customer experience, and foster brand loyalty; the role of leadership in the digital age; and how to prepare employees for new responsibilities with practical cases that demonstrate how this tool drives decisions and creates business opportunities. Some guests include Zack Kass, former director of Go-To-Market at OpenAI; Randi Zuckerberg, former director of marketing at Facebook and founder of Zuckerberg Media; Mitchell Weiss, professor at Harvard Business School and expert in innovation and generative AI; Jesús Cochegrús, entrepreneur and technology expert who has worked in the video game industry and developed projects for companies such as Nike and Coca-Cola.

One company that is finding rapid traction supporting international businesses, especially those in North America, is BI Consulting Lab, located in the residential Medellín suburb of Guarne, Colombia. The company’s offices are a beehive of activity, with data scientists, programmers, and client executives buzzing about. Company founder Brian Castaño Rendón made time for Loren Moss, the executive editor of Finance Colombia and Cognitive Business News to come by and learn more about the firm’s rapid progress.

Finance Colombia: So I’m here with Brian Castaño Rendón, a friend, a colleague, a former co-worker. I’ve known you for quite a few years now, probably seven or eight years. Cool to reunite with you here at your company headquarters in Guarne, which is a bedroom community outside of Medellín. And you’re doing some really interesting things. Tell me about your company. What’s your company called?

Brian Rendón: My company is called BI Consulting Lab. First of all, thank you for having me and for spending time with us.

Finance Colombia: Of course. So, what is BI Consulting Lab? I know it’s software-focused. I know it’s data-focused. But tell me in your own words what BI Consulting Lab does.

Brian Rendón: OK, so basically, what we are is a company that specializes in data and AI. And we use that technology to help businesses make better decisions. We do decision support. And we try to allow the executives and the managers of every company to have the tools to come up with the decisions and support those decisions. Hopefully, by implementing the right decisions, the productivity of the company will progress exponentially over time.

Finance Colombia: I think one of the things that happens when I think about the companies that I’ve worked in, small companies, large companies… A lot of times, the problem is not collecting the data or not having enough data, but not being able to extract the value out of their data. I think that what happens is we might have, I don’t know, let’s say a grocer who has two types of inventory. They have the actual products that they sell, but then they have their shelf space. And it’s easy to say, “How many bottles of ketchup did I sell today?” or “How many cans of tuna fish did I sell?” or something like that.

But then there’s another level to that. And that’s to say, “How do I optimize my inventory when it comes to real estate?” And I don’t mean real estate like buildings or shopping centers, but I mean the shelf space that they have, and how they might not know how it is going to affect sales if I move this product from one level on the shelf to another level. Or “How do I optimize the shelf space?”

One of the things that annoys me here in Colombia, I’m more of a Pepsi guy than a Coke guy, but I go into the store and Coca-Cola has like eight racks of just Coca-Cola. And there’s like two bottles -not two racks- there’s like two bottles of Pepsi. Now, they’re not doing that by accident. They must know something. I do know that Coke is more popular in Colombia than Pepsi, but maybe there’s more to it than that. Maybe the way that the stores optimize their space, they’re going to not just put things on the shelf because they want to, but they have to figure out what the optimum size is.

What are other use cases for where a company might want to call on you all and enlist your help, not just as software people, but as real consultants who can go in and analyze and look at what they’re doing?

Brian Rendón: Yeah, of course. So, to your point there, when you were talking about specifically the retail industry, we do have experience working with large retail stores, specifically in the US. We are working right now with Kroger Acosta, which is a supplier from Kroger. We help them analyze their space distribution, their shelf distribution, and what they call planograms.

Let’s take three steps back. And, what you said first, companies don’t have issues collecting data, not that much of an issue, all of them have spreadsheets. All of them have Excel. Most of them already have SQL databases and stuff like that. What they struggle with is extracting its value. And usually here in the data industry, we say that you usually need three things to be able to extract the value from the data, to convert the data into information, and the information into decisions.

You need three elements to converge: you need the business knowledge, you need the technical side that allows you to do the computations, and then you need the statistics. So you need the ability to concatenate these three elements, like in a Venn diagram. And at the center of it, you kind of have the formula for you to be able to extract information and convert it into decisions.

So, on the shelf space, just to take an example, in this case for Kroger, what we did was to create something called a space analysis tool. What we did for them was to help them get all of those hundreds of millions of records that they have on the different commodities and the different stores and the different departments and sub-commodities and divisions, and stuff like that, organizing it into a cohesive model. When we say modeling in data analytics, we mean the relationship between dimensions and transactions for a company, and how we can take a specific transaction and dimensionalize the transaction into when it happened, how it happened, and why it happened. So we create a cohesive model, take those hundreds of millions of transactions, and we try to put the values into perspective.

And if we alter this or that combination, we could, with probable cost, assume that we could get a better performance, or maybe we could have a worse performance if we do that. So, having the data and organizing it helps you to do those what-if analysis scenarios that allow you to make the right decisions or try to make the more probable right decisions, because this is a game of probability.

Finance Colombia: Crystal ball or something.

Brian Rendón: Crystal ball, exactly. Thank you. Yeah, so what we deal with here is probability. So if you do this, data-supported, it could probably go up; if you do this or that, the data tells us that it probably won’t go as well. And then we do a hypothesis, we test it on our models, and then we give you a possibility and a scenario that you could utilize in your decision-making. That’s an example of how businesses, specifically from the distribution company, the distribution and the retail company, can come to us and we can try to help them improve their decision making, for example, in their distribution or their shelf space in a specific market chain. But that applies to any industry.

That’s the cool thing about data, because data is omnipresent in all industries. There could be problems whether they capture it, all of it, or not, but they are constantly being generated at every time in every industry, in every division of any company. So what we try to do with that is to take it, analyze it, capitalize it, and utilize it in a way that the company can make decisions based on that. By improving their decision-making, they can improve their productivity.

“Companies don’t have issues collecting data…What they struggle with is extracting its value.”

Finance Colombia: I think one of the areas, I look at forecasting, and I think even to stay in the grocery sector, I remember I’ve been down here in Colombia for a long time now, but I remember right before I left and moved down here, a really interesting thing was happening in the US at Christmas season. And that was that, traditionally you have Christmas, and then right after Christmas, you have these big giant clearance sales to get rid of all the Christmas stuff and all the stuff left over from Christmas.

Well, in the later years, those were going away. And the reason… I mean, there’s always some sale, but it wasn’t because they had excess inventory, but because the forecasting got so scientific that they were able to put in all of these variables and economic indicators and all this stuff like that. And they were able to predict very, very accurately how much of whatever product they would sell. So by the time Christmas was over, they didn’t run out before Christmas, but there wasn’t an excess inventory after Christmas.

And I think about how these types of tools and disciplines that you all specialize in can be applied. Do you guys have any cases where you’re able to use your data expertise for predictive analysis, let’s say, or to be able to do forecasting for clients?

Brian Rendón: Yes, we do that all the time. Where we focus is on trying to understand the historical trends. And for that, machine learning is a pretty powerful tool to do that. So when a company has a lot of records and a lot of, let’s say, let’s think in a tabular way. So you have a table with your transactions, and those transactions have a lot of characteristic attributes. So you have the type of store, the type of commodity, three or four subdivisions, they have dates, they have comments, even, like plain text, string elements. And we can use all of that and put it into a deep learning algorithm, for example, an algorithm.

And we can try to understand what attributes are the most impactful about the transactions to discover patterns or clusters, or different elements that allow us to understand the data. And then what we do based on those algorithms is to take the most important elements for us to predict a consistent behavior from the historical data.

So we first allocate the important elements for us to do a calculation, and then we set up the calculation. And what we do then is do an 80% to 20% analysis. So you take 80% of the data to train a model, and 20% to test it. So when that 20% of the data, when the model gives you a performance, or I would say around 98%, 97% of accuracy, then you take that information that you got left, that the algorithm has never seen, you fit it to it. You already know the answers for each of those values. But you want to test how accurately they predict the right price for a specific day, for a specific week, maybe, or month. And you want to see how the prediction compares to the actuals.

And if you see that there is not much difference, you have a statistical base to say, “Okay, based on this statistical way that has proven 80% to 90% accuracy, let’s plan our inventories by that, and let’s keep testing it.” So we do a six-month, three-month, and a year forecast, and we even adjust the model to allow us to adjust the forecast as time goes on. Because as time goes on, the model has more data to be trained on, and has actual factual data that has happened with the respective attributes, and can infer the most important elements for the whole bunch of time you have on your data source. Or you can even segment it, segment it, and then try to find asynchronous spikes or stuff like that.

Finance Colombia: How far away, and I’m sure that there are so many other business use cases for what you guys do, but you guys also are very well-versed in AI, in building AI into your data solutions. How far away are we from, let’s suppose one of your clients says, “Okay, we have AI and we have all of this data, and can I just ask the software, hey, how much shelf space should I allocate to Seven Up?” In plain text, just like an AI, like a generative question, or is it still a lot more complex than that? Even though, yes, I know we can get the data, but how far away are we from being able to just say, “Should the Tide laundry detergent be on the third shelf or the second shelf?”

Brian Rendón: Yeah, so I would say on that one, we’re not that far, we’re rather close, but we need to figure out a couple of things. So let me go into that. So when you or your users use ChatGPT or Claude or DeepSeek, what they do is to enter a context in the context window, the chat window that you have, you start typing a problem or a comment or whatever, you give some instructions, you add some context, and based on the training that the model has given, he will answer you, right? That’s basically how it works.

The issue with doing that with corporate data is that, first, the corporate data is not that well-structured in most cases, so that’s the first thing. And then most of the models limit your ability to input information into the model. So the way it works is that you buy, for OpenAI, which is the most famous one of them all, you buy a subscription to them, right? You connect via an API, and you insert information that you want into the model so it can use it as context and then answer you. So each of those lines, each one of those syllables that you input is are token, and for those tokens, you are charged money.

So it becomes very inefficient when you want to process millions and millions of records, which will turn into billions of tokens, which you will have to pay for to get a single answer. So that is not an efficient solution right away. So, for example, what we do to try to improve that and make that process more efficient is we do the connection to the model, the LLM, the Large Language Model, even Anthropic or Claude or OpenAI, in this case, ChatGPT. We can connect to all of those models. We can connect to the open source, which Facebook is the powerhouse for that; we can connect to Llama. You can connect to all of those models or any of those models.

Brian Rendón: For you to make it efficient, you want to have like a small step in between. So what you want to do is you query your information directly via an API, so that the API provides you with the actual value. And then you use the LLM, ChatGPT, to generate a text-based answer. So it tells you in a normal English-speaking way the answer that you want to hear. But the processing, you push the processing not into the model, but into the SQL engine, or the database engine, or the data warehouse that you use.

And there are different ways for you to do that. There are also ways you can input multiple inputs into the model, so the model processes them and generates an answer.

But usually the most effective way for easy questions, for example, if  you are in finance, you say, “Okay, how many subscribers did we get last week?” You can go and check your database and do a query, and get an answer. But if you want to talk to an assistant, we can do that. We can connect your WhatsApp, for example, to an LLM that will connect to your database. And you ask that, that will go to do a query into your database and get an answer. And that answer will give you back your answer either by text or by speech, whatever you prefer. If you send a speech message, a voice message, it will answer you with another voice message. We can improve the voice using Flask, another model that is out there. So we can do that. And in that way, the LLM, the AI model, is not doing the processing of the information.

Finance Colombia: It’s just packaging it.

Brian Rendón: Exactly. It’s just doing the delivery nicely.

Finance Colombia: Like in networking, we used to call that the presentation layer.

Brian Rendón: Yeah, exactly. And that’s important because the way our LLMs work at the moment is that they get confused. When you give them a lot of information, like you overextend in your context window, the LLM model will start to hallucinate. What I mean by hallucinate is that it will start to give you a random answer that is not correct. And that’s because the model itself doesn’t know what answers are correct or not. They answer in a probabilistic way. And that’s precisely why you don’t want it to process millions of records of information, at least not at this stage. Because it can get confused. And you don’t want to take an answer from it, maybe a hallucinated one that is not accurate, and then you allocate some of your budget based on a not very accurate answer.

Finance Colombia: Exactly.

Brian Rendón: So, at the moment, at least, you try to push the processing with accurate models that we can easily do at the moment using APIs. And you query the information from the model. First, you need to have a very good data architecture, which that’s some other thing that we do. We help businesses to understand how to capture the information correctly, how to extract it, normalize it, and place it rationally into a data warehouse, Datamore, and different databases.

So that their transactional information is arrayed with their dimensional information, so that they can be combined in a way that is efficient and answers questions for you. So when you have a very robust and very good data architecture, it facilitates a lot the transition to implement AI models. Because when you have accurate information, and rather than accurate information, very well normalized and organized information in your company, that information can be easily queried.

And when you query that information, which is easily, again, queried, and you push the processing into a very powerful engine like SQL, for example, you get specific answers, so the right amount of answers that you want. And then you put it into the AI. And then the AI can just give you the packaging that you set, tell you the answer nicely, and it can perform a couple of other layers of analysis as well.

So you can ask it to give me a projection of sales for my next six months. So it pushes into the SQL engine a query for your actual revenue or whatever metric you are measuring for your last 18 months, and uses that as an input for it to calculate your following months. And it can give you a trend. It can give you a chart. It can give you a lot of things. And it is based on actual information that, with the right amount that it can process with a high degree of certainty that is accurate.

Again, we are still working on the probabilistic element. The different models right now, what I believe they’re doing based on the news that we hear, is to make more efficient what we have, to reduce the number of hallucinations, to make it have short-term reasoning and long-term reasoning, which is basically what we do. We come up with an easy answer, but then we reflect on that answer and maybe confirm the answer. Or in other words, change the answer.

Finance Colombia: Refine it.

Brian Rendón: Refine it, exactly. So if you see one for OpenAI, the ChatGPT model, that one usually gives you, when you ask it something, it starts reasoning. And you can visualize the questions that it is asking itself, and how it conceptualizes the question that you asked, and the possible answers, and try to refine it. It was way lower, like eight months ago, but it gives you more accurate answers nowadays.

Finance Colombia: What are the applications that companies can use that you’ve seen in your business, and with the kinds of companies that you’ve all been able to help? Where companies have engaged you to help them improve their customer experience. How can the work that you do translate into a better customer experience for companies? Do you have any examples of that?

Brian Rendón: Yeah, we have a couple of them. Usually, in the context of virtual engagement, for example, they have multiple challenges to be approached. And they are struggling to be able to answer, one person to answer in different channels, keep track of the different requirements, and answer them in ways that are more optimal with the whole context at every time.

So it’s hard for them to keep track of all their chats in WhatsApp, Instagram, and maybe others. So what we do for them is we create automations that connect up their context database. So we create a context database for them. And then we connect that context database to ChatGPT, for example, to OpenAI or other AI models. And those AI models get, we’d say we create a custom ChatGPT, trained for that specific business. And that way, whenever there is a person who comes, that triggers a reaction in our pipeline, that pushes the question or the comment from the social network as an input, and then sends it to the LLM that has already been trained with the context of the company. So they have the context on how to answer that question, or comments, based on whatever the company has at the moment. So it is very important, the connection, the connectivity with the databases of the company, at every turn. Even more so when you are trying to do a service on time, and live services and stuff like that. So we have a couple of restaurants with that. And we are discussing a solution for a stockbroker here in Colombia. They… I met him at the event that you held at the Marquee.

Finance Colombia: Oh, great. Last year. So, Finance Colombia events lead to business.

Brian Rendón: Exactly. Yes, it does. So he told me that time, “Look, I’m the CEO of the company. We are a very large stockbroker company. And whenever we have, let’s say, the dividends coming from Ecopetrol, it is a madhouse in my company because we have 13,000 customers calling at the same time trying to confirm that we are depositing their dividends, on how they went or how much it came, stuff like that.” And he told me, “I have 15 people at customer service and they get overwhelmed immediately with that type of information.”

So I thought at the moment a couple of ways to reduce that pressure from customers trying to get access to their data specifically. I asked him, “Okay, we could do dashboards for them, dashboarding and reporting, custom reporting for them that they will automatically get once the transaction comes with the usual context that they ask for, so that they already have it, and that way they get this incentivized to call because they already have the information and that could reduce the number.”

Another thing is to try to automate part of your customer service using these LLMs. There was a more recent solution that we proposed to him, because he said people want to talk to someone, to hear, and since we are advancing pretty fast in the speech element of the AI, the sounding is less robotic, it can be trained.

Finance Colombia: It’s getting pretty spooky. Yeah, it’s getting pretty impressive.

Brian Rendón: Yeah, it’s getting pretty impressive. Today we can connect to those models and train it into a Colombian, Argentinian, Cuban, Mexican, whatever type of accent that you want, it can be pretty realistic and can help you send automatic messages or answer calls if you need to and give the answer, the simple answers to people based on a couple of parameters. So you need to parametrize all of that.

Finance Colombia: You’ve been very generous with your time. Last question for you. So we’re here in Guarne. Guarne is kind of a bedroom community, a suburb. We’re probably about 20 or 30 minutes out from the city limits of Medellín. You’re Colombian. I realize that, but why does Colombia work for a business of this type? If we think about your clients that are in the US and other parts of the world, a lot of times, people think of IT, they think of a company being in India, or something like that. Why Colombia and why the Medellín metropolitan area for a tech company of this type?

Brian Rendón: Okay, so I’ve been working with you actually for a lot of years now in the BPO business, and understanding the relationship, the US relationships in terms of outsourcing and in general, and specifically for technology. I know that there are three major hubs for outsourcing technology services. So we have Latin America, we have India, and we have Eastern Europe, right? So, when you have Latin America, I would say two elements may differentiate us from the other two. First is the time zone. We have a very good time zone.

“I would say Medellín stands high as a digital nomad center. We have a lot of people coming from different places. The last time I checked a nomad list, I think it’s called Nomad List. We were ranked, I think, first or second in Latin America.” – Brian Rendón

Finance Colombia: We’re in the US Central Time right now, Texas, Chicago.

Brian Rendón: We have the same time zones as the US, so that’s a first element. And then due to our proximity to them, we are more culturally close to them than an Eastern European from Ukraine or Belarus, or Macedonia.

Finance Colombia: Very true.

Brian Rendón: Or also an Indian. Our accent is usually more familiar to them. Our way to speak to things that are relevant to both sides is also closer. So there are ties, cultural ties, that facilitate the communication. So I would say that that’s something that maybe can be impactful for a decision-making process for a US company to choose a Colombian or Medellin company over a Belarusian company. That could be some major points there. But the other element that I would say is that we have… specifically Medellín, which is particularly high-skilled in technology than other areas in Latin America in general.

I would say more than Lima, more than Monterrey or Guadalajara, more than maybe Montevideo. I would say Medellín stands high as a digital nomad center. We have a lot of people coming from different places. The last time I checked a nomad list, I think it’s called Nomad List. We were ranked, I think, first or second in Latin America. And in the world, here in Colombia, we were like third or fourth after Bali, Barcelona, maybe another one. So we have a lot of talent coming over here. We have a very friendly environment for development. We have cultural ties, like I described before, the ability to work in the same time zone, the cultural ties, and the high-skilled people.

So that, I think, makes a pretty good combination that differentiates us from the Indian and the Belarusian. Also, we are a bit more expensive than our other Eastern European and Indian counterparts. But I think the quality part, which is hard to quantify sometimes, but I would say in most cases, the quality part, which is the more humane part, like the easy to speak in a way that is more understandable for people, can be a very good point.

We are very, very present in most of the operations. And within the Latin American people, Colombia and specifically Medellín stand pretty, pretty high in the rankings of people. Wherever I go, there are half-Latin American teams. I usually see people from Colombia, and specifically from Medellín.

Finance Colombia: It’s kind of like the Silicon Valley of Latin America. It is, you know, access is easy. We’re probably half an hour from the airport right here. And then once you’re on a flight, it’s two hours to the US. And yeah, I think that, you know, you also have that Paisa entrepreneurial culture that you find specifically in this part of the country, maybe a little bit in the Coffee Axis down in Coffee Country: Manizales, Pereira, which is part of this region. It is, you know.

So Brian, what is, if people want to get in touch with you, if people want to get in touch with your company, what are your if you could remind us of the company name and, of course, your website, but any other channels of communication that would be convenient for you and potential collaborators or clients?

Brian Rendón: Of course. So, first of all, our webpage, again, is www.biconsultinglab.com. My corporate email is brian.castano@biconsultinglab.com. You can also find me on my LinkedIn profile with the same address, Brian Esteban Castano Rendon. When you go to our web page, you have a Contact Us page, and that will automatically help you to set up, to direct you to a landing page where you can set up a meeting, a 15 meeting with one of our sales representatives. So we can do a first assessment, a quick assessment on whether we could be a good match for whatever you need.

This one may be important for people to know. So, the way we classify a company that can be a potential customer for us, we don’t receive anyone, because our solutions could help anyone, but not all companies are prepared, or at the stage where our services can be of good value for them. So, we are pretty sincere from the get-go, and we tell them, “Okay, look, we want companies that already have some sort of infrastructure of data or have enough transactions that they think is necessary for them to start setting up a data infrastructure.” We can help them there, where you want to make sense of your data, we can help you there, and when you want to start automating and maybe do predictive analysis and try to incorporate AI into operation, we can help you there.

Either you know what you need, we say, okay, maybe you specifically need this. We both agree, we give you a quote, and then we start our payment process, and then we do an onboarding, and we start working together.

Or if you want to kind of implement the concept of what we sell, like getting the data, if you have to improve your decision-making, but you don’y know how to do that practically, what we do is we offer you a free diagnosis, we take around three hours to make with your top executives and department, head of departments. And it has to happen within a week. So, we take the three, maybe four hours, we sit down, we understand your business, we understand your applications, the integration within the application, how you extract information from them, what are the pain points that you have, each of the departments in general, and also each of the departments, what are your strategic goals?

And we try to combine all of that information to understand your current state and where you could be. Once we understand those two, we lay out a plan that says, okay, maybe from, coming from where you are to where you could be, we think that you could do this and this and this or that steps, and we can help you do those, for this amount of money. And we will send you a formal offer. We did a diagnosis that, again, is free. So, you get your diagnosis at the very least, you get a good sense, a better sense of where you are, and how you could eventually implement AI or data in your day-to-day operation. And if, maybe, if we see that we could be a good fit and you like our proposition, we start working together, we discuss the quotation, you pay us, and we do an onboarding session with you. And hopefully we can bring you value, we can start a long-term relationship, helping you do the transition from a business model that is not AI or data-centric into one that very, very much values their data assets and can monetize them along the way.

Finance Colombia: Impressive, you know, and it’s been impressive to see your success grow as a person, you know, I’ve known you for almost 10 years, but, you know, we’re here in your offices, and it’s full of people. I walked in today, and it’s just like a beehive, everybody’s on computers and having different calls and things like that. So people must realize these aren’t just a couple of guys with a laptop; this is an impressive operation here.

So I would encourage, of course, any kind of company that is looking to better utilize their data to support their corporate decisions, or not even just companies, but even organizations, government agencies, things like that, that you guys obviously, you have the advantages of being based here in suburban Medellín, Colombia, but are already serving clients in North America and throughout the world. So, I’m excited for you, I’m excited to watch you guys grow, and of course, we’ll continue to keep in touch, and I can’t wait to hear about future successes, so congratulations.

Brian Rendón: Thank you so much.

Japan, the event’s guest of honor, showcased its technological innovations and contributed speakers who presented the country’s vision in areas such as AI and cybersecurity. A Memorandum of Cooperation was signed between the governments of Japan and Colombia, focusing on enhancing collaboration in cybersecurity, AI, infrastructure development, and promoting connectivity in rural areas.

The event included a pre-conference featuring sessions on AI, smart cities, and blockchain, attended by 450 participants. The primary agenda covered a wide range of topics, including AI, robotics, 5G, cybersecurity, and digital transformation. Colombia’s Ministry of Information and Communications Technology (MinTIC) outlined its progress in advancing the country’s digital capabilities. MinTIC launched the National Observatory of Information and Communications Technologies (Ontic), a platform designed to consolidate key connectivity data for Colombia.

Additionally, Gabriel Jurado, Colombia’s Vice Minister of Connectivity, introduced six key initiatives aimed at expanding internet access nationwide. These included strengthening mobile and fixed access networks, increasing connectivity for educational institutions, improving affordability, and enhancing institutional capacity.

The event also addressed gender inequality in the technology sector, with representatives from various organizations signing a manifesto to promote women’s participation in science, technology, engineering, and mathematics (STEM).

Telecommunications Sector Challenges

A key focus of ANDICOM 2024 was the challenges facing the telecommunications sector. In a panel discussion on future connectivity, industry leaders emphasized the need for robust infrastructure to support AI and smart city initiatives in Colombia. While efforts to close the connectivity gap are underway, panelists called for regulatory attention to issues such as network traffic management, energy costs, and the “fair share” debate, which centers on whether content providers like Netflix and Google should contribute to network infrastructure costs.

The panel on “Innovation and Equity: Exploring Fair Share in Telecom” sparked diverse opinions, with discussions covering governance, spectrum management, and consumer impacts. Panelists largely agreed on the importance of maintaining net neutrality, which they argued could be at risk from potential regulatory intervention.

AI: Present and Future

Executive Director of ANDICOM organizer CINTEL, Manuel Martínez Niño

Artificial intelligence was a recurring theme at ANDICOM 2024. Oracle announced the deployment of Nvidia’s latest generation GPUs in Colombia, which will be used to expand AI capabilities for businesses and government organizations. Marcelo Christianini, Oracle’s VP of AI and Cloud Engineering for Latin America, highlighted the company’s investment in AI infrastructure as a key step toward enabling large-scale AI adoption.

Speakers at the event included Gabriele Mazzini, principal architect of the European Union’s AI Act, who discussed the importance of local considerations in AI regulation. Hiroshi Ishiguro, executive director at AVITA and professor at Osaka University, presented on the use of AI to create avatars aimed at enhancing human physical and cognitive abilities. Ishiguro’s research focuses on using AI to improve quality of life by providing better access to healthcare and education.

AI’s potential in the financial sector was also discussed. Panelists in the session on “Economic Transformation through AI” noted that AI can streamline verification processes and improve decision-making. However, challenges such as technology investment, data sovereignty, and skills development remain barriers to wider AI adoption.

Innovation and Technology for Social Transformation

Innovation and technology were central to ANDICOM’s discussions. Diana Barrero Zalles, head of research and sustainability at the Global Blockchain Business Council, emphasized the role of blockchain in driving innovation and sustainability in the region. She stressed the need for harmonized regulations, particularly regarding tokenization and digital assets, to facilitate global exchanges.

The conference also addressed Colombia’s energy transition with a panel on sustainable energy. Participants from various sectors discussed the barriers and opportunities in transitioning to clean energy, with a focus on user adoption and the environmental impact of new energy technologies.

Andra Keay, director of Silicon Valley Robotics, concluded the event with a presentation on the role of robots in society. Keay argued that while robots are increasingly capable of performing repetitive tasks, ethical considerations must guide the development and implementation of AI and robotics technologies.

Networking and Business Opportunities

In addition to the academic sessions, ANDICOM 2024 provided a platform for business networking. Attendees participated in meetings with technology buyers, including chief technology officers (CTOs) and chief information officers (CIOs), to discuss short- and medium-term investment plans.

CINTEL’s Digital Leaders community hosted workshops on cybersecurity and AI for CIOs from various industries, facilitating discussions on the potential of digital tools in different sectors.

According to CINTEL’s executive director, Manuel Martínez Niño, ANDICOM continues to be a key event for the region’s technology sector. The conference is a space where government, academia, and industry come together to discuss the role of technology in social transformation. Plans for the 40th edition of ANDICOM in 2025 are already underway.

Key Figures from ANDICOM 2024:

• 6,000 participants
• 35 countries represented
• 215 companies in the commercial exhibition
• 2,000 business delegates
• 150 international speakers
• 110 academic sessions
• 250 square meters dedicated to the Japan Pavilion
• 450 pre-conference attendees