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Summary of Latin America in the Intelligent Age: A New Path for Growth

Core Content

This white paper explores the potential of artificial intelligence (AI) to drive economic and productivity transformation in Latin America, emphasizing the need for strategic, collaborative action to build a competitive AI ecosystem. It outlines a comprehensive roadmap with 10 targeted actions, based on the World Economic Forum's Blueprint for Intelligent Economies, to ensure Latin America can harness AI's benefits effectively.

Main Points

1. Economic Potential and AI Adoption

• AI has the potential to significantly boost productivity and economic value in Latin America.
• The region could see an annual increase in productivity of 1.9% to 2.3% by 2030 and an additional economic value of $1.1 trillion to $1.7 trillion.
• Analytical AI is expected to contribute $0.6 trillion to $1 trillion, while Generative AI (GenAI) could add $0.5 to $0.7 trillion.
• Latin America has historically relied on workforce expansion rather than productivity gains for growth, making AI adoption a critical shift.

2. AI Competitiveness in Latin America

• AI adoption is growing in various industries and countries, particularly in customer service and software engineering.
• However, only 23% of Latin American organizations generate any economic value from AI, and only 6% report significant value creation.
• AI strategies must be integrated with broader business strategies and focus on reimagining core processes rather than incremental improvements.
• The financial sector is currently the most advanced in AI application, with examples of impactful use cases.

3. Challenges and Opportunities

• Talent availability is a major challenge, as local organizations struggle to compete with multinational companies.
• Infrastructure development, including sustainable energy, high-speed connectivity, and scalable computing, is crucial for AI deployment.
• Data quality and governance remain critical issues, with inconsistent metadata and privacy concerns affecting data usability.
• Ethical and responsible AI development is essential, including transparency, inclusivity, and multilingual models that reflect Latin American culture and language.
• Regional collaboration is a key opportunity, especially in shared digital infrastructure and cross-border projects.

4. Strategic Actions

• Build sustainable AI infrastructure: Develop clean energy sources and ensure robust national grids and water availability for cooling.
• Curate diverse, high-quality datasets: Improve data accessibility, interoperability, and governance.
• Develop responsible AI models: Promote local AI development and adaptation of global models to regional needs.
• Harness AI investment channels: Encourage public-private partnerships, venture capital, and regional investment pools.

Key Recommendations

• Enhance AI literacy and education: Implement personalized and inclusive education programs to prepare the workforce for AI-driven economies.
• Improve connectivity: Address the urban-rural digital divide through public-private initiatives and expand broadband access.
• Strengthen legal and ethical frameworks: Establish clear regulations, privacy mechanisms, and standards for AI use.
• Foster regional collaboration: Leverage shared languages and cultural values to create a unified AI strategy and infrastructure.
• Support AI entrepreneurship and innovation: Encourage innovation ecosystems, open-source collaboration, and R&D initiatives.

Conclusion

• Latin America has a unique opportunity to lead in AI innovation and economic transformation, but this requires strategic coordination, targeted investment, and inclusive talent development.
• Without decisive action, the region risks prolonged stagnation in economic growth, while coordinated efforts can position it for sustained, future-ready development.

Key Data and Examples

• Connectivity: Only 15–17% of Latin American households had fixed broadband in 2024, with a 30 percentage point gap between urban and rural areas.
• Energy: Brazil generates 88% of its electricity from renewable sources, but grid infrastructure remains a challenge.
• Investment: Latin America accounts for 1.6% of global AI investment despite representing 6.3% of global GDP.
• Projects: Initiatives like Chile’s Humboldt cable, Peru’s National Broadband Plan, and OpenAI’s Stargate Argentina are examples of progress in AI infrastructure.

Future Outlook

• The report emphasizes the need for disciplined execution and articulated vision to close structural gaps.
• AI has the potential to democratize growth and reduce inequality, but this depends on addressing the infrastructure, talent, and regulatory challenges.
• The demographic dividend is fading, making AI a vital tool for sustainable development and economic resilience.