Brazil holds a singular position in the global AI race: 3rd largest market for weekly AI users in the world, 2nd in number of developers. But the country's competitive edge has nothing to do with training models. It comes from applying them better than anyone else in a context it knows from the inside.

I spent a week in California, between Brazil at Silicon Valley and the Google AI Summit, talking with leaders from the biggest tech companies in the world, founders, and investors who are at the center of the AI conversation.

The story being told out there — that AI is a race between the US and China to build the best model and everyone else is just watching — misses what's actually happening.

Because this race isn't only about who builds the best model. It's about who applies it best in the right context. And that changes everything for Brazil.

The real game is in the application layer

While the US chases Artificial General Intelligence as a strategy for global dominance, China is betting on "good enough" models, open source, diffused across industry. Different paths pointing toward different goals.

But the side effect is that frontier models are now accessible — and getting cheaper fast — for anyone who wants to use them. You don't need to spend hundreds of billions training your own.

What is the application layer? It's where generic AI models become specific solutions for real problems. Where the value isn't in the model itself, but in whoever understands the problem and knows where to point the technology.

What you need is to understand a problem and build a solution that takes advantage of the infinite possibilities generated by models improving week over week. That's where the application layer wins the real game.

AI models are available to anyone. What isn't available is the strategic understanding of context — the market, the behavior, the culture, the specific pain of a segment or a geography — combined with the ability to execute and a sustainable go-to-market strategy. That's a different competition. And whoever has those skills and knows how to use AI to solve real problems is winning it.

Brazil is already the 3rd largest market for weekly AI users globally and 2nd in number of developers — according to the report Unlocking Economic Opportunities for Brazil, published by OpenAI in August 2025. For the first time, Brazilian founders are building at the same pace as Silicon Valley — with access to the same technology, the same models, the same cloud infrastructure.

The question isn't whether Brazil can play anymore. It's whether it's playing on the right field.

Why local context is a competitive advantage in AI

For Brazilian founders, this is an enormous opportunity. Building solutions for markets you know deeply — markets you live in, whose pain points you feel daily, whose nuances you grew up with — is worth more than any model.

Call it cultural intelligence: the ability to translate local complexity — regulatory, behavioral, cultural — into product decisions that no model trained abroad can replicate on its own.

Brazil has a business and cultural complexity that is, counterintuitively, one of its greatest competitive strengths in AI. Whoever learned to work through that complexity can do something technology alone can't do.

Whoever owns the cultural context and the value chain doesn't compete on price. They compete on relevance. And relevance can't be imported.

AI isn't just about efficiency — it's about what becomes possible

But the opportunity goes further than applying AI well and with precision. This is the point I consider most important: the biggest benefit of AI is doing what wasn't possible before.

Most companies still look at AI and think efficiency — the same thing, faster, cheaper. But whoever captures disproportionate value thinks about possibility. The right question isn't "how do I do this cheaper?" — it's "what becomes viable now that simply wasn't before?"

What we're doing at Pupila is a concrete example: a global brand faces the challenge of maintaining visual and verbal consistency across thousands of pieces for dozens of markets. Personalizing that content — adapting it for each channel, local context, and audience profile — would mean turning one piece into hundreds. It wasn't a cost problem. It was an impossibility problem. With AI, it became viable.

In healthcare, quality diagnosis reached populations that never had access to specialists — not because it got cheaper, but because it became possible. In education, personalizing content for different learning paces and contexts at scale stopped being a fantasy. In brand communication, maintaining consistency across multiple languages and cultures without losing local relevance became something you actually execute, not just aspire to.

Brazil has big, complex problems. It always has. What changed is that there's now accessible technology to tackle them at scale. And whoever understands those problems from the inside has an advantage that no amount of venture capital can buy.

For Brazil, the AI moment is now

Everything converges toward one conviction: this is the most exciting time to build new solutions.

Models improve every week. The cost to build drops every month. The gap between having an idea and putting it into the world has never been thinner. Thirty years since the last wave of this magnitude — and this time, Brazil isn't late.

We now live in a world where you can build anything you want.

What's missing isn't technology. Not talent — Brazil has plenty of that. What's missing is the willingness to play. To stop underestimating itself. To recognize that the cost of not acting is larger than the risk of acting.

I see this energy in the founders I meet at events inside and outside Brazil — people thinking big, solving real problems with creativity and speed that rival anything coming out of the Valley.

The race that matters isn't between models. It's between whoever understands a problem and has the intelligence and drive to solve it.

Brazil understands its problems. Its culture. Its complexity.

That's exactly why the time is now.

‍

Looking closer

What is the application layer in AI?

‍It's where generic AI models become specific solutions for real problems. The value isn't in the model itself — it's in whoever understands the problem end to end and knows how to direct the technology to solve it, combining market knowledge, execution capability, and business strategy.

Why does Brazil have a competitive advantage in AI?

‍Brazil is the 3rd largest market for weekly AI users in the world and 2nd in number of developers. Its biggest advantage isn't infrastructure or capital — it's context. Brazilian founders have deep understanding of the regulatory, cultural, and behavioral complexity of their local market, something no model trained abroad can replicate on its own.

What is cultural intelligence in the context of AI?

‍It's the ability to translate local complexity into product decisions. Regulation, consumer behavior, cultural nuance — whoever owns that context competes on relevance, not price, and builds solutions that outside companies simply can't copy.

What's the difference between using AI for efficiency and using AI for possibility?

‍Efficiency means doing the same thing faster and cheaper. Possibility means doing what was previously unviable. Companies that capture disproportionate value with AI aren't just optimizing existing processes — they're building products and services that literally didn't exist before the technology became accessible.

What does Pupila do with AI?

‍Pupila uses artificial intelligence to create brand creative assets at scale, maintaining visual and verbal consistency. What used to require manually turning one piece into hundreds — across different channels, markets, and audience profiles — becomes viable with AI applied to specific brand context.

‍