From potential to productivity: Latin America in the Intelligent Age

Artificial intelligence could play a leading role in boosting economic growth in Latin America by addressing a long-standing productivity gap—one the region has historically offset through workforce expansion. According to a new report by the World Economic Forum (WEF), produced in collaboration with McKinsey, productivity growth in the region has ranked among the slowest globally, averaging just 0.4 percent annually over the past 25 years, and even trending negative over the past decade. The AI moment for this region is significant: This consequential technological breakthrough could raise productivity by 1.9 to 2.3 percent per year and generate $1.1 trillion to $1.7 trillion in additional annual economic value.

Although the region has not always captured the gains of previous technological waves, the need—and opportunity—to change its long-stagnant productivity trajectory with AI has never been greater. While value creation has yet to keep pace with rising AI adoption, growing engagement from global technology firms and investors strengthen the region’s position.

The report evaluates these factors through the lens of WEF’s Blueprint for intelligent economies, which focuses on strengthening AI competitiveness through regional collaboration.¹Blueprint for intelligent economies: AI competitiveness through regional collaboration, World Economic Forum with KPMG, January 21, 2025. It also identifies several challenges that stakeholders need to address to unlock broader economic impact:

• Limited value capture from AI adoption. AI use is expanding, but only 10 percent of organizations link their AI implementation to the broader business strategy; as a result, a gap persists between experimentation and scale, with just 23 percent reporting any economic value and 6 percent reporting significant impact.
• Foundational constraints in infrastructure and data. Persistent connectivity gaps between urban and rural areas, rising energy and computing demands coupled with the challenge of meeting those demands sustainably, and uneven data maturity limit the ability to deploy AI at scale.
• Talent and operating model gaps. Shortages of AI-ready talent, weak career pathways, and limited cross-functional collaboration could slow execution.
• A fragmented enabling environment. Inconsistent regulation, constrained access to capital, and limited regional coordination make it harder to attract investment and scale solutions across borders.

To address these issues, the report outlines a road map of ten targeted actions for stakeholders, organized around four core purposes:

• Define implementable AI strategies focused on measurable outcomes in priority sectors where the region has competitive strengths.
• Build the infrastructure and data backbone required to support AI at scale, including sustainable energy sources, digital connectivity, computing capacity, and interoperable data foundations.
• Provide clear paths to develop talent at scale by strengthening education systems, expanding upskilling and reskilling programs, and creating clearer pathways for AI careers.
• Enable trust, capital, and coordination through clearer governance, mobilization of investment, and deeper regional collaboration across public and private sectors.

Ultimately, realizing AI’s full potential will depend on a clear vision and coordinated action among stakeholders to move from experimentation to execution. How effectively they respond will shape whether current momentum stalls or translates into sustained growth and prosperity across the region.

For the full report written jointly by McKinsey and WEF, including a detailed breakdown of the execution road map, see Latin America in the intelligent age: A new path for growth.