When Anthropic, most recently valued at $965 billion USD, acquired AI biotech startup Coefficient Bio in a $400 million USD deal in April, it signaled something beyond a single deal: a wider repositioning among U.S. tech giants toward buying specialized expertise rather than building from scratch.
Nubank made the same calculation when it bought Hyperplane, a U.S.-based AI firm, to get its machine-learning capabilities up to speed across three markets at once.
Such shopping lists increasingly include emerging markets. A quiet but accelerating shift is underway across the region's startup ecosystem, and U.S. buyers are a driving force behind it.
In fact, a growing number of founders are no longer building toward the next unicorn or a standalone IPO, but designing highly-specialized companies – with proprietary datasets, vertical AI applications, regulatory expertise and domain-specific engineering teams – that larger U.S. organizations would take years to replicate internally, and would rather acquire than compete for.
Buying Is Faster Than Building
The broader numbers illustrate what is happening on the ground: acquisitions of venture-backed companies crossed $100 billion USD in the first half of 2025 – a 155% jump year over year. The scenario reflects a structural shift: when AI capabilities can evolve in a matter of months, the calculation of building everything in-house breaks down. Buying specialized expertise is, quite simply, faster.
That same logic is playing out at a smaller scale, too. When proptech firm GetCovered acquired Revyse, an AI-powered vendor compliance and contract management platform, it was not making a headline-grabbing bet, but taking a deliberate shortcut: the calculus of paying upfront for a working compliance layer versus the slower, riskier cost of building one in-house.
Prezent AI made a similar bet late last year, though its math carried an extra variable. The Los Altos-based company acquired Prezentium, a services-led presentation company that operates in the life sciences vertical, alongside an additional $30 million funding round aimed at folding in a team – rather than scaling the firm's own headcount from scratch.
The choice, then, isn't only about acquiring capability faster, but doing it it at a cost structure that organic hiring in a higher-cost market couldn't possibly replicate.
Another example: when Brazilian financial infrastructure firm Laqus acquired goLiza earlier this month, it barely made the regional tech press. GoLiza does niche, unglamorous work – and precisely the kind of thing a larger company cannot easily do in-house: automating fund onboarding and registration.
That is exactly the point. This is not a story about scale, but specificity.
Why U.S. Buyers Are Looking South
Deals picked up sharply in early 2026 across Brazil, Mexico, Colombia, Chile and Argentina. The highest-value trend evidenced in Q1, in fact, resulted in a megadeal where GE Vernova – a spinoff from General Electric – acquired the remaining 50% stake in Mexican utility and industrial supplier Prolec GE, according to global advisory firm Corum Group.
Part of this is structural, showing years of digitization creating acquirable infrastructure. But most of it is a growing recognition, among buyers in San Francisco and Sāo Paulo alike, that the engineering talent needed to build AI products already exists in emerging markets – and that acquiring a team that has spent years solving a hard local problem is cheaper and faster than building one from scratch.
For U.S. companies, that math is increasingly hard to ignore. Although the World Economic Forum highlights persistent challenges in the region in the form of infrastructure gaps, regulatory fragmentation, and limited capital, it also points to Latin America's improvements in foundational infrastructure and public-private partnerships aimed at AI readiness, lowering the friction for cross-border acquirers.
However, not every founder in the region is eager to play that role. The next frontier is the most ambitious yet: not only adopting the technology, but creating it, as Luis Guillermo Pardo, CEO of Colombian AI startup Kognia, says. "Oftentimes, it's these technologies that are imported and not the ones that are fostered and cultivated here in Latin America [that receive the most attention]," he said in May.
A More Selective Market: Exactly What U.S. Buyers Want
The tension is worth watching as U.S. buyers deepen their presence, but the funding picture tells a more complicated story.
Venture investment across LatAm climbed to $4.1 billion USD – up nearly 14% from the year before, as per Crunchbase data. On the surface, it looks like recovery.
But when looking closer, the number of deals hit its lowest point since 2017; capital went into fewer companies at higher average ticket sizes. In sum: investors got pickier.
In practice, that means the startups attracting capital are the ones with real, hard-to-replicate differentiation – which is exactly what U.S. acquirers are hunting for.
The selectivity that's squeezing the broader ecosystem is, from a buyer's perspective, a feature: less noise, sharper signal on which companies are worth owning.
The Long Game
Whether the broader emerging markets' ecosystem benefits from this dynamic is less clear. When M&A accelerates, talent, capital and attention pool around the platforms doing the acquiring, – many of them American – and the companies with good ideas but without the specificity that makes them irreplaceable find themselves in a funding environment thinning out around them.
For U.S. dealmakers, though, the direction is unambiguous: emerging markets have spent the better part of a decade proving that world-class companies can be built here – Nubank, Rappi, Mercado Libre were not flukes – and U.S. forms that move early on specialized, hard-to-replicate targets are positioning themselves ahead of a market that's only going to get more competitive and more expensive.
And for founders, the tension is personal as much as strategic; building something acquisition-worthy requires a kind of long-game thinking – knowing what makes you irreplaceable, and protecting it – that is hard to sustain when you are also trying to make payroll, close your next round, and ship a product that works. What is different now is only the exit landscape.
A generation of innovators may find that the most powerful version of global scale is not ringing a bell on a stock exchange, but building something so specific, so deeply useful, that the world's largest AI organizations came looking for them – and paid accordingly.
The bet is rational and also, for most, untested.
