On this episode of The Six Five – On The Road Partner Edition, hosts Daniel Newman and Patrick Moorhead welcome Globant’s Nico Avila, North America CTO for a discussion during MongoDB’s .local NYC event.
Their discussion covers:
- How Globant is using AI internally and with clients across industries
- Globant’s recent additions to its Studio Practices
- How Nico sees enterprise tech continuing to change through the second half of 2023
- Globant’s approach to upskilling and reskilling its global talent amidst the quickly evolving technology landscape
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Transcript:
Pat Moorhead: Hi. This is Pat Moorhead, and we are live at MongoDB Local, here in New York City, 2023. And as you can tell by the background, and the energy, it is happening here. Daniel, how are you, my friend?
Daniel Newman: Yeah, it’s been a great day here in New York. We got to hear from the leadership of MongoDB this morning, and it was a mix of kind of overall updates, a reminder that the company loves its developers, but that it’s also attached really well to all the secular trends, especially AI.
Pat Moorhead: Yeah. I really loved the simplicity element of it, as well. As enterprise gets tool after tool after tool that needs to be integrated, that’s true for security, and that’s also true for data and databases. But without further ado, let’s introduce our guest, Nico from Globant. How are you?
Nico Avila: Good. Thanks for having me here. It’s a pleasure to be with you.
Pat Moorhead: Absolutely.
Daniel Newman: It’s great to have you here, Nico. I think a good place to start, you heard me say AI. Look, I think we all get a little fatigued, because these trends come, and then all of a sudden it’s like all those other things you were talking about …
Pat Moorhead: Exactly what we were talking about in the green room.
Daniel Newman: Yeah. All these other things are no longer relevant. But, I would also say there’s trends that kind of maybe get some hype unnecessarily, like the metaverse. And then there’s trends that are very real. And I think we can all agree this one is very real.
I’m sure at Globant, you being CTO, you’re under a lot of, I’d say, pressure. But also, there’s a lot of interest to say, how are we supposed to be implementing AI across our business, to deliver for our employees, for our customers? Talk a little bit about that, and how you, as CTO, are thinking about and implementing AI in the enterprise today?
Nico Avila: Sure. And it’s great to be talking about AI, because for a second I thought that we were going to be speaking about spatial computing, right? There is so much.
Pat Moorhead: No, no. That was last year.
NicoAvila: It’s amazing how these new trends keep coming at us at a rapid pace. And I can understand, we meet with CTOs, CDOs, and CIOs from different companies every day. And they are under so much pressure.
So, I think that the bright side of this trend on AI is that we had a wave of AI six years ago. For us, we kept the pressure on AI, since the last time that we really put a strong focus. And because we’re in the business of helping companies transform themselves through technology, and find better versions of themselves, operating more efficiently, what we realized is that we needed to focus on ourselves.
And we started using AI. And particularly generative AI, to create products internally that will help us run our process faster, help our developers code faster, learn about the code base faster.
So, for us, when this came to life, we had kind of hit the ground running in that sense. But it was impressive how we brought it to everybody’s attention. I think there is a practicality test that it passed today. Everybody can go and do a test. Everybody can go and try to imagine the kind of problems that they can solve. So, I think in this sense, this new wave is a lot easier to tackle than the past.
Now, I think that we’re getting to a second level of complexity. I think everybody saw the first couple of things that you could do with generative AI. And when they’re really starting to rethink their business processes and compare it with the edge cases, with the complexities and limitations, you really start to divert the things that are easy to implement, and the things that are going to be taking a little bit more time.
Pat Moorhead: So, it’s great. It’s interesting to see how a lot of companies are looking at generative AI. I mean, there’s the pioneers. And then at the other extreme, there’s the laggards, who are going to wait years and years and years, maybe to their peril. But it’s good to see that Globant got a jump on this early. So, your learning curve has to be a little bit shorter.
So you have a lot of different offerings. And I’m curious, I want to double-click. What are some of the new capabilities you’re adding to your studio offering?
Nico Avila: Building capabilities is the most important thing, right? Building the capabilities and bringing them together is really relevant. So, we have had capabilities on data and AI for over 10 years.
What we saw in the last couple of years, is that we needed to rally these technical capabilities about different industries, and about different specialties. For example, a couple of years ago, we launched what we call the reinvention studios. Those are focused on industries. And they’re looking at how AI can go and fix a particular problem in the life sciences space.
Pat Moorhead: So these are like a co-creation type of studio? A co-creation platform?
Nico Avila: Yeah. A studio is a group of people that have an expertise in common, that they specialize in that.
Pat Moorhead: Right. A center of expertise, or a center of excellence.
Nico Avila: Exactly. And they’re not in an office. They are people that are scattered around the world. And they’re really important in attracting and creating the talent. I actually joined the company to be the best mobile engineer that I could be, and I joined the mobile studio. And I was able to work with the folks that were working in the companies the likes of Disney, or like leaders in the industry, and learn from the best in that sense.
So, what we added was a layer of specialization through the reinvention studios, that basically landed those technologies into a particular offering of an industry. So, for instance, now we’re talking about generative AI, and we’re talking about using it for … In general, you can think like, I don’t know, optimizing email campaigns, and creating copy faster, so you can have more answers to clients.
When you start thinking outside of the box, and you’re re-envisioning an experience, you think of a buying experience, right? You’re thinking of retail. How do I go to an e-commerce and try to filter? Filters are the anti-generative AI experience. You go search for a green bottle, open the filters, and start clicking on options.
That’s not how you choose something in real life. So now we have an alternative to rethink that experience. When you’re shopping for a vacation, you’re not going and choosing, “I’m going to choose this port, and go take this cruise for many days.” You’re actually exploring and saying, “I want to take five days off that are valuable for me and my wife.”
Pat Moorhead: So people have different ways to shop, and different ways to get maybe to the same place, but they’re just coming at it from a different angle. And you have to provide the intelligence to be able to handle that.
Nico Avila: Yeah. And it’s actually bringing the expertise and the technology with the understanding of the art of the possible in the industries, and the problems that the people are having. And I think we’re here on MongoDB’s event today, and I think it’s a really good example of how some of the building blocks can really help you fill that gap.
There is so much that technology leaders have to do. And catching up with the demands of the business, it’s moving faster. Everybody’s trying to be cost conscious. So, the building blocks that help you get it done faster, it’s really what allows an organization, a technology organization, to be a superpower for the company.
Pat Moorhead: Love it. Like a force multiplier. Yeah.
Daniel Newman: So, it’s interesting, as you talk about creating these new experiences, there’s a couple of technological trends. And the first, of course, is the whole generative AI, open AI, has become a bit table stakes. Every company has access to these same large language models, and everybody’s parsing the same internet of data.
So then we’ve kind of quickly come to the realization that enterprises need to find a way to utilize their proprietary data. You heard a little bit here today about search, vector, of course taking all that unstructured data that’s unique to either your customers, your processes, finding a way to build them into your applications to make them smarter, to help get to answers more quickly like you said.
So that seems to be a lot of the trend line right now. But, as I said in the beginning of the show, it’s not all just about this gen AI trend. These enterprise tech trends are, it’s more horizontal. It’s bringing things together, ambient edge data. It’s the multi-cloud. What are some of the trends and technology and emerging trends that you’re kind of continuing to watch as we head into the second half of the year?
Nico Avila: I think that even though the market is a lot more forward-looking today, there is a trend in the last couple months, last couple years, I’d say, about creating efficiencies. And that is an environmental condition that you can’t avoid. Like, being efficient in how you organize your technology teams, that really brought a lot of attention to the fact that even though there are some trends that are undeniable, I actually think that metaverse is going to be a thing on the long run.
What’s ready today? What do I need to do today? And even though many companies want to do a stronger focus on generative AI to change the experience, maybe overhauling processes is a baseline. And there is so much legacy code that it’s becoming a showstopper for that progress, that as leaders are thinking where do they go? That becomes the baseline of what they need to cover.
So there is a lot of attention on going back to the basics, on creating the right decisions to be cost-effective on the selection of tools, to choosing tools that are going to be able to scale with the organization, and that can support the modernization.
I think, in that sense, the announcement of the migration tool today is really important, because companies are in need of, how do I move from a legacy code to a new platform in a faster, following best practices? And what else?
Pat Moorhead: Yeah, I loved your efficiency statement. And sometimes with all the fireworks that go off, and digital transformation, the ability to change business models is super important. But, you also have to look at cost and efficiency, too. And that’s why I love seeing hybrid multi-cloud fabrics that work on-prem, your favorite CSPs, and also on the edge. And we’re seeing the security market and the observability market. Also, enterprises are tired of having 27 different tools that they have to integrate. So, I’m really glad to hear you say that.
So, one of the biggest topics, and this is nothing new that comes with new technology, is talent. You ask somebody, “Hey, what’s one of your biggest inhibitors?” It’s, “I can’t find enough of the right people to do what I need to do.” How does Globant keep up upskilling, reskilling? What’s your strategy? Because your customers rely on you to be cutting edge, and obviously everything else, but how do you do that? How do you keep your talent flow going, with the best and brightest?
Nico Avila: We have certain particularities that apply to us, it may not apply to everybody else. Because we are as much a software development company as we’re a talent development company. And actually, we did most of our marketing historically. We’ve done around attracting developers, attracting talent, because we knew that if we had the right talent, we were going to be able to succeed in that.
But at the same time, that’s where the studios became a really important aspect, that creates a sense of community and a high bar. And we’ve created a whole ecosystem of training tools and understanding an engineer 360. You’re not a Java mid-level, you’re actually, you’ve got 50 of the 120 skills in Java, but you might have 10 of the 50 relevant on GCP, right?
So fairly complex systems to understand what people need to do to improve. We create a lot of training. But actually creating the spaces for specialization is really important. That’s why, for instance, we launched our GCP studio a couple of months ago. And those are some aspects, we have similar niche technology. But on MongoDB, we have a strong alliance as well to make sure that we are training. We’re providing feedback on the things that we think that can improve on the technology. And are paying for customers.
And then, on the flip side, make sure that we’re getting the best guidance and we have the best expertise to provide the best solutions.
Daniel Newman: The skills gap will continue to be one of the most talked-about challenges inside of every enterprise. And you’re marrying that to the efficiency equation, where companies know that their people are paramount to the company’s success. But having said that, that question of, do we need all the people? Where are those processes that can be layered on top?
If you remember the people/process/technology thing, we’re actually seeing these things converge. Generative is actually converging people/process/technology into one fluid motion, that enables customers to have an interaction that feels very human, whether it is or isn’t with a human.
I think it’s really great, Nico, to hear from you about this. I’d love to talk a little bit more. We’re out of time right now, but it’s great that you took the time to sit down with us here on the Six Five.
Nico Avila: Thanks for the time.
Pat Moorhead: Thanks.
Daniel Newman: All right, everybody, stay tuned. We have many more conversations here at MongoDB Local, in New York City, 2023. I do appreciate you all tuning in. More to come, Pat? We’ll see everybody soon.
Author Information
Daniel is the CEO of The Futurum Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise.
From the leading edge of AI to global technology policy, Daniel makes the connections between business, people and tech that are required for companies to benefit most from their technology investments. Daniel is a top 5 globally ranked industry analyst and his ideas are regularly cited or shared in television appearances by CNBC, Bloomberg, Wall Street Journal and hundreds of other sites around the world.
A 7x Best-Selling Author including his most recent book “Human/Machine.” Daniel is also a Forbes and MarketWatch (Dow Jones) contributor.
An MBA and Former Graduate Adjunct Faculty, Daniel is an Austin Texas transplant after 40 years in Chicago. His speaking takes him around the world each year as he shares his vision of the role technology will play in our future.
