AI Adoption in Latin America: Limited Economic Value
The World Economic Forum (WEF) highlights that while Latin America is adopting artificial intelligence (AI), it’s capturing little economic value, with only 23% of organizations reporting any impact and just 6% creating significant value. The primary challenge lies in integrating AI into core processes rather than merely piloting it.
Mexico’s Focus on Industrial AI
Mexico aims to shift the AI conversation from labs to manufacturing lines. In this sector, crucial to Mexico’s economy, the challenge has evolved from testing models to integrating AI into core processes with measurable effects on costs, times, and quality.
This forms the backdrop of the WEF and McKinsey’s report, “Latin America in the Intelligent Age: A New Path for Growth.” The document, presented at Davos meetings, asserts that although the region is adopting AI, most organizations still report minimal economic value from its use.
Mexico’s Standout Case
The report examines country-by-country examples in sectors where the region holds relative weight. Mexico is singled out with a distinct approach, integrating AI into national Industry 4.0 programs and linking research to factory operations, focusing on predictive maintenance, quality control, and supply chain optimization.
The emphasis is on the programmatic framework and the connection between research and production. This type of integration indicates that AI is being pushed towards operational domains, not just individual productivity enhancements.
Challenges for the Region
The WEF and McKinsey report warns that while adoption is growing, the economic impact remains limited. Only 23% of organizations in Latin America report generating any economic value from AI use, and a mere 6% report significant value creation.
The report further suggests that to accelerate value capture, the strategy should reimagine business processes and complete models rather than incremental productivity tools.
The Gap Between Latin America and Global Leaders
The report compares Latin America to “global leaders” without specifying any country or region, establishing a clear competitiveness pattern. The lowest scores in Latin America are in talent, operational model, and adoption and scaling, with the largest gap being in talent.
In adoption and scaling, the report identifies two operational differentiators explaining why AI falls short in value. These are the ability to establish, track, and communicate value and the integration of AI solutions into business processes.
The scale of the challenge is also quantified. The report estimates that AI could add between 1.1 and 1.7 trillion dollars annually to the Latin American economy, which it places near 6% of the global potential. The condition is sustained execution to convert potential into productivity.
Key Questions and Answers
- What is the main focus of Mexico’s AI efforts? Mexico aims to integrate AI into core manufacturing processes, focusing on areas like predictive maintenance, quality control, and supply chain optimization.
- Why is AI adoption in Latin America limited in economic value? Despite AI adoption, only 23% of organizations report any economic value, and just 6% report significant value. The challenge lies in integrating AI into core business processes.
- What are the main challenges for scaling AI in Latin America? Regulatory uncertainty, with 58% of respondents describing the environment as unclear, and privacy and data protection as the main regulatory bottlenecks. Additionally, Latin America invests only 1.6% of global AI investment despite contributing around 6.3% of the global GDP.
- How does Mexico’s productivity compare to global leaders? A significant productivity gap exists between Mexican small and medium enterprises (SMEs) and large firms, estimated at 46% in Brazil and 53% in Mexico. This gap could widen if AI adoption concentrates on corporates and large plants, affecting Mexico’s competitiveness.
