In the past, LatAm has been slower than its global counterparts to adopt and adapt to changing technologies. However, the need to integrate AI is more urgent and immediate.
Artificial intelligence has been pegged as a key factor in boosting economic growth in Latin America, as it could address the region’s productivity gap. Traditionally, LatAm’s productivity gap has been offset by workforce expansion. A report jointly produced by the World Economic Forum (WEF) and McKinsey revealed that the region’s productivity growth averaged a mere 0.4% annually in the last 25 years. However, it has been estimated that productivity could rise by 1.9% to 2.3% per annum and generate $1.1 trillion to $1.7 trillion in additional annual economic value.
In the past, LatAm has been slower than its global counterparts to adopt and adapt to changing technologies. However, the need to integrate AI is more urgent and immediate. While AI adoption is currently outpacing value creation, improvements in digital infrastructure, shared language, and cultural ties could strengthen the region’s position.
The report has highlighted some challenges which need to be addressed to reap the economic benefits of AI in the future. One of the main issues is that although AI usage is increasing, only 10% of Latin American businesses are capitalising on it to maximise profits. Infrastructural lacunae like rising energy and computing demands, and the challenge to meet these demands sustainably, along with rural and urban connectivity gaps, are also common in the region.
LatAm also suffers from a lack of AI-ready talent, inconsistent regulation and difficulty in garnering the large volume of capital and investments necessary for AI expansion. Therefore, scaling solutions even country-wide is a major challenge, which is only further complicated at the cross-border level.
As demand for cloud services and AI workloads increases, financial arrangements are changing to enable the expansion of data centre capacity throughout LatAm. Rather than demand, one of the main barriers to development as the region gears up for a period of expansion is access to cash and favourable regulations. Building data centres requires huge capital, and supply expansion is greatly aided by the availability of many financial sources. A Moody’s report suggests that because data centre operators have fewer financial choices, development has halted in the region despite high demand.
New data centre developers will initially find it challenging to obtain bank financing. By the end of 2025, Latin America’s installed IT load was roughly 1.4 gigawatt (GW). Instead of using venture funding to obtain hyperscale tenant agreements and sustain early expansion, the majority of developers have looked for powerful, well-known sponsors. In contrast to financing structures that are mostly focused on equity,
Latin American data centre operators use more debt in the early phases of project construction and often move away from equity-based financing options. The financing options only change when operators secure a long-term lease agreement with a hyperscale tenant, energy requirements are met and once operational capability is proven. Long-term contracts with hyperscale tenants result in revenue visibility, minimising refinancing risks and cashflow uncertainty.
For US-based AI firms, LatAm is the perfect region to forge partnerships to satisfy their resource needs. These firms require large amounts of energy, water and land for their new generation of data centres. Therefore, they are seeking out countries like Argentina, Mexico, and others in the region, where the governments are willing to enter into agreements with these companies, discounting the risks it poses to the local population and ecology.
LatAm countries are keen to hop onto the digital era bandwagon and become regional AI leaders. Argentina, Mexico, Brazil and Chile are resource-rich countries. These governments are being accused of making provisions for water and energy for data centres, despite the local population constantly suffering from water shortages and power outages.
However, the governments are determined to expand their AI capabilities, much like the rest of the world. Despite the challenges, Chile made headlines when it launched the region’s first indigenously developed generative AI model- Latam GPT in February of this year. A collaborative effort between Chile and 15 other countries in the region, Latam GPT is the first LLM specifically trained in Spanish and Portuguese. The model is also trained on regional data to improve context and accuracy, which other generative AI models lack.
In a bid to improve its AI capabilities, Latin America also understands that it cannot neglect the primary sectors, which have consistently driven growth in the region. As the producer of 15% of the world’s food supplies, and still not meeting its agricultural potential, LatAm is now looking to AI to fill this gap. Smallholder farmers, who are 70% of the region’s agricultural producers, are using precision agriculture platforms which employ satellite imagery, drone data, and machine learning models to correctly predict yields, optimise resources and also access credit financing options based on performance data instead of collateral.
In Brazil, the agritech sector saw an influx of $1.1 billion in investments in 2023. Chile and Peru have also witnessed a 40% drop in water consumption on pilot farms owing to the AI-driven irrigation systems. Crop yield prediction models have also achieved 85-90% accuracy, having been trained on LatAm-specific soil and climate data.
Similarly, AI is also being used in climate conservation in the region. Using satellite imagery, illegal deforestation can be detected in near real-time. Brazil’s space research agency INPE is monitoring 5.5 million square kilometres of the Amazon forest with the help of AI. Machine learning models are also able to accurately predict solar and wind output for grid management, as renewable energy deployment in the region increases.
AI offers Latin America a game-changing opportunity to close its long-standing productivity gap and create more than $1 trillion in economic value. Despite the region’s many issues, including inadequate infrastructure, a lack of skilled personnel, and difficult financial circumstances, the effective implementation of programs like Latam GPT demonstrates a developing resilience.
Governments must, however, carefully strike a balance between ecological sustainability, social justice, and quick digital growth. LatAm may transition from being a late adopter to a specialised worldwide leader in resource-efficient AI by utilising local data and languages for region-specific results.
