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AI adoption and digital investment in Latin America

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2026-08-26 04:25 UTC → 2026-08-26 07:39 UTC · added ~~removed~~

Latin American private equity firms have demonstrated high rates of operational value creation, particularly through cash conversion and working-capital optimization. While these firms outperform global averages in agility due to tight liquidity, they have historically lagged in technology integration. Specifically, only 36% of regional private equity leaders reported frequent use of artificial intelligence, compared to 48% globally. Recent developments show an acceleration in regional AI adoption and digital infrastructure investment. In Argentina, IFX is expanding its data center footprint with a US$19 million investment planned between 2026 and 2027, part of a broader US$400 million regional initiative. In the mining sector, Minsur has utilized machine learning for over five years to optimize copper recovery and manage human talent. Despite this momentum, significant implementation hurdles persist. In Chile, 61% of organizations report unclear returns on AI investment, citing talent shortages and fragmented systems. While AI usage in Mexico has risen to 48%, most companies there remain at a basic level of implementation. Furthermore, a widening productivity gap is emerging between AI-adopting firms and those that have not. ~~Emerging technical challenges also include~~ Global trends further complicate the landscape. While some reports suggest high returns—noting that every $1 invested can yield $3.20 over 14 months—measuring ROI remains difficult. Additionally, as capabilities grow, concerns regarding ~~autonomous behaviors~~ safety and ~~‘reward hacking,’ with~~ labor have emerged. OpenAI ~~noting that~~ has implemented a monitoring layer for its advanced ~~models requires an additional 20%~~ models, which increases compute requirements by 20%. Simultaneously, sociologists like Milagros Miceli highlight the existence of ~~computing power to ensure alignment.~~ a massive, often invisible global workforce of approximately 400 million people performing essential AI-related tasks.

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