![]() |
Pan American experiences
|
------- |

Enter caption1
|
LATIN AMERICA ------------------------------------------700[FEATURE] | |||
Artificial Intelligence in the Global SouthLatin American Perspectives on the Future of InnovationBy Jazmin Agudelo for Ruta Pantera on 11/19/2025 8:00:25 AM |
||||
| On the streets of São Paulo, an algorithm predicts bus routes to reduce traffic chaos; in Bogotá, AI-powered drones deliver medicines to rural areas; and in Santiago, chatbots handle government inquiries 24 hours a day. Artificial intelligence (AI) has arrived in Latin America not as a distant futurism, but as an everyday tool that promises efficiency and equity. However, behind the optimistic headlines lurks an uncomfortable question: are we facing a productive revolution or a new speculative bubble similar to the dot.com boom of the 2000s? With regional AI investments surpassing 3.5 billion dollars in 2024 — a 48% year-over-year increase — local experts debate whether this technological wave creates real value or just inflated hype (IDB Invest, 2025; Statista, 2025). The Latin American AI Boom AI adoption in the region is growing at Asia-like speeds. According to the IDB, 62% of medium and large companies in Brazil, Mexico, and Chile have implemented at least one AI solution, compared to 45% globally (Inter-American Development Bank [IDB], 2024). Startups like NotCo (Chile) use machine learning to create plant-based alternatives to dairy products, valued at 1.5 billion dollars after rounds led by Bezos Expeditions. In Mexico, Kavak applies computer vision for instant valuation of used cars, disrupting a traditionally opaque market. Governments are also betting big. Uruguay leads with its Agency for Electronic Government and Information Society (AGESIC), which deployed an AI system to optimize medical appointments, reducing wait times by 35% (AGESIC, 2024). Colombia, meanwhile, launched in 2023 the Center for the Fourth Industrial Revolution affiliated with the World Economic Forum, focusing on ethical AI for precision agriculture. However, the landscape is uneven. While 70% of investments are concentrated in São Paulo and Mexico City, countries like Bolivia or Paraguay barely register pilot projects. A formidable digital divide persists: in the region, only 52% of rural households have access to broadband internet, limiting the deployment of cloud-based solutions (ECLAC, 2024). Concrete Applications Beyond laboratories, AI is solving numerous sector-specific challenges in Latin American: • Health: In Peru, the Ministry of Health uses natural language processing algorithms for symptom triage via WhatsApp, handling 1.2 million monthly inquiries during pandemic peaks (Ministry of Health of Peru, 2024). In Brazil, the SUS implements radiological AI that detects tuberculosis with 94% accuracy in Amazonian areas without specialists. • Agriculture: Platforms like Agrofy (Argentina) and Agritech (Brazil) use satellites and predictive models to alert about pests, increasing soybean yields by 22% (FAO, 2024). • Inclusive finance: Nubank, the Brazilian neobank valued at 41 billion dollars, uses AI to approve credit in seconds for unbanked populations, relying on alternative data such as mobile consumption patterns. • Public security: Medellín has reduced homicides by 30% since 2016 through predictive systems that assign police patrols in crime hotspots, though not without ethical controversies over bias (City of Medellín, 2023). These cases show measurable impact, but require infrastructure: local data centers (still scarce), specialized talent, and regulatory frameworks. | ||||
|
|
Structural Limitations and Risks In the Global South, enthusiasm often collides with harsh realities. Latin America represents only 1.8% of global AI researchers, according to Scopus, and loses talent to Silicon Valley at a rate of 15,000 professionals per year (UNESCO, 2024). Universities such as UNAM or USP produce graduates, but 70% emigrate due to salaries up to ten times higher. Technological dependency is another Achilles heel. Eighty-five percent of AI models used locally are imported — mainly from OpenAI, Google, or Meta — creating vulnerabilities in data sovereignty and dollar-denominated costs that make solutions more expensive (CAF, 2024). Additionally, the energy consumption of data centers for training large models is equivalent to that of medium-sized cities, conflicting with decarbonization goals. Algorithmic biases amplify inequalities. A study by Universidad de los Andes found that AI recruitment systems in Chile discriminated against Indigenous surnames in 28% of cases (Ramírez & Gómez, 2023). In Brazil, police facial recognition has produced disproportionate false arrests in Afro-descendant communities. Bubble or Revolution? The Economic Debate Analysts compare the current hype to previous cycles. “We are in the ‘trough of disillusionment’ of the Gartner Hype Cycle, but with stronger fundamentals than the dot-com era,” argues Martha Gabriel, a Brazilian expert in digital transformation (Gabriel, 2024). Unlike in 2000, AI generates tangible returns: McKinsey estimates it could add 2.6 trillion dollars to Latin America’s GDP by 2030, equivalent to Brazil’s current GDP (McKinsey Global Institute, 2023). However, signs of speculation abound. Valuations of Latin American AI startups grew an average of 300% between 2022–2024, despite modest revenues. The “ChatGPT effect” inflated expectations: 40% of regional companies that announced AI initiatives in 2023 have yet to implement them, according to Deloitte (Deloitte, 2024). Human Innovation vs. Automation The real risk is not technological, but societal. Will AI replace jobs or transform them? The IDB projects that 34% of positions in the region are automatable, affecting women disproportionately in administrative and service sectors (IDB, 2024). Cases like Claro’s call center in Peru, which reduced its workforce by 60% after implementing chatbots, illustrate the tension. Experts such as Mexican researcher Alejandro Frank advocate for “human-centered AI”: “AI must amplify human creativity, not replace it” (Frank, 2023). Projects like Laboratoria train low-income women in prompt engineering and data ethics, creating hybrid jobs. Regulation advances slowly. Mexico passed an AI Law in 2024 requiring bias audits, while Brazil debates a similar framework stalled in Congress. Organizations such as Al Sur warn that without regional governance, AI will deepen technological dependence on the Global North. Toward a Hybrid Future For AI to become genuine transformation, the region needs: Investment in local talent: Scholarships like those from the OAS for master’s degrees in AI at public universities. Regional data commons: Open repositories of anonymized data to train local models. Collaborative regulation: A Latin American treaty on ethical AI, similar to the European GDPR. AI for social good: Prioritizing applications in rural education, public health, and climate mitigation. AI in Latin America is neither a panacea nor a pure bubble. It is a mirror of our capacities and shortcomings: where there is strategic vision (as in Chile or Uruguay), it generates progress; where improvisation prevails, the risk of exclusion grows. The challenge is not choosing between human and automated innovation, but forging a symbiosis in which technology enhances the best of our cultural diversity. Only then will AI cease to be a speculative cycle and become the engine of truly inclusive development. Latin America represents only 1.8% of the world’s AI researchers, according to Scopus, and loses talent to Silicon Valley at a rate of 15,000 professionals per year (UNESCO, 2024). | |||
|
Click on images to enlarge:
|
||||
|---|---|---|---|---|
| |
|
|
|
|
| Enter caption 7 | ||||
×
|
||||
Please leave a comment about this article: 700 |
|
| Enter your email address: |
Your email will not be displayed. |
| Your nickname: | |
| Your comment: | |
| Was this article helpful to you? | |
|
|
|
Articles about exciting travel experiences in our hemisphere.


