- Around 80% of firms in Latin America and the Caribbean already use AI tools, yet only 23% report economic benefits and just 6% see a significant impact.
- Turning early experiments into wider business use will require more investment, stronger skills, better digital infrastructure, and clearer rules.
- Ultimately, productivity gains will depend on firms redesigning how they work and integrating AI into their core operations.
Artificial intelligence is rapidly transforming economies worldwide. For Latin America and the Caribbean, its significance extends well beyond technological change, as the region continues to grapple with one of its most persistent challenges: weak productivity growth.
Over the past decade, economic growth has relied largely on an expanding labor force rather than productivity gains, with productivity contracting by about 0.4% annually between 2015 and 2024. As demographic momentum slows, this growth model is reaching its limits.
AI could offer a new path by improving decision-making, automating routine tasks, and strengthening forecasting and resource allocation across sectors. However, if adoption remains concentrated among a small group of firms and skilled workers, it could deepen existing economic divides. Ultimately, whether AI boosts productivity or widens inequality will depend on closing gaps in investment, talent, digital infrastructure, and regulation.
The Productivity Imperative: Why AI Matters Now
Latin America’s core economic challenge is weak productivity. Informality, limited competition, uneven human capital, and weak innovation ecosystems have slowed the diffusion of new technologies, leaving the region far from the global productivity frontier.
Artificial intelligence arrives at a critical moment. Investment is rising, including among small and medium-sized enterprises, according to the technical note fAIr Tech Radar: Exploring the Adoption of Artificial Intelligence in Latin America and the Caribbean, developed by the Inter-American Development Bank (IDB) and NTT DATA. Against this backdrop, Chile, Brazil, and Uruguay are emerging as regional leaders, while AI applications are spreading across sectors such as finance, agriculture, energy, healthcare, and customer service.
Around 80% of firms already use AI tools. Yet experimentation has delivered limited value so far: only 23% of organizations report economic benefits from AI, and just 6% see a significant impact, while many firms remain stuck in the pilot phase and lack the skills and governance needed to integrate AI into core operations. The challenge, therefore, is to ensure that growing use of AI translates into tangible productivity gains.
As Figure 1 illustrates, annual growth in output per worker in Latin America and the Caribbean has been highly volatile and generally weaker than in ASEAN, and in many years below the European Union as well.
Four Barriers to AI-Driven Productivity: Investment, Talent, Infrastructure, and Governance
Despite growing interest in artificial intelligence, several structural constraints continue to limit its economic impact in Latin America and the Caribbean. Gaps in investment, talent, digital infrastructure, and governance are slowing the diffusion of AI technologies and limiting the region’s ability to translate their use into productivity gains.
Investment remains a major constraint. The region continues to lag behind advanced economies in both AI investment and readiness. The International Monetary Fund's (IMF) AI Preparedness Index ranks Latin America and the Caribbean sixth among nine global regions, with a score of 42 out of 100, compared with 77 for the United States. Private investment and research funding also remain limited, while uncertainty over data-use rules discourages further investment.
Talent is another critical barrier. According to PISA 2022, three out of four students do not reach minimum proficiency in mathematics, while nearly half struggle with basic reading. Only about 30% of adults have basic digital skills, and brain drain and labor market disruptions place additional strain on already limited talent pipelines.
Infrastructure gaps further constrain deployment. Despite progress in connectivity, 15–17% of households still lack fixed broadband access, while large urban–rural disparities persist. Limited computing capacity, fragmented data systems, and dependence on foreign cloud providers also make it harder to deploy AI at scale.
Governance frameworks, meanwhile, remain fragmented. Only a handful of countries, including Brazil, Chile, and Uruguay, have reached intermediate levels of institutional readiness. Many governments still lack comprehensive strategies, clear regulations, and the institutional capacity needed to develop and implement effective AI policy.
Taken together, these constraints help explain why Latin America and the Caribbean remains less prepared for AI than most of the regions shown in Figure 2.
Policy Recommendations
First, strengthening investment ecosystems will be essential. The region still lags behind advanced economies in AI investment and lacks financing mechanisms to scale digital technologies. Public–private partnerships, venture financing for startups, and incentives for data centers, cloud infrastructure, and high-performance computing can help mobilize private capital. The IDB is already supporting progress in this area through digital transformation programs that expand technology adoption among MSMEs and improve digital public services in countries such as Belize and Honduras.
A second priority is expanding human capital and digital skills. Addressing the region’s talent gap will require stronger foundational education, expanded AI and data science programs, and reskilling initiatives. In turn, collaboration among universities, firms, and governments will be critical to developing and retaining specialized talent.
These efforts must be accompanied by improvements in digital infrastructure and energy systems. Expanding broadband connectivity, improving reliability and affordability, and strengthening computing and data capacity are critical for deploying AI at scale. Reliable electricity supply is also a key prerequisite for digital infrastructure such as data centers.
Finally, progress on investment, skills, and infrastructure will need to be underpinned by stronger governance frameworks. Clear data protection rules, institutional leadership, and regulatory tools such as sandboxes, which allow companies to test new AI applications under regulatory supervision before rules are finalized, can support innovation while managing risks and building public trust.
From Promise to Productivity
Even with strong policies in place, AI’s productivity effects may take time to emerge. History shows that technological revolutions often generate substantial gains only after firms reorganize production around new tools. When factories first adopted electricity in the early twentieth century, for example, productivity gains were initially modest. The real transformation came only after firms redesigned production processes and workflows to take full advantage of the technology.
AI may follow a similar trajectory. Although many workers already use generative AI tools, these applications often affect specific tasks rather than entire production systems. Their initial impact may therefore remain limited until firms integrate AI more deeply into business models, decision-making, and operational processes.
For Latin America and the Caribbean, the challenge is not only to adopt AI, but also to ensure that its benefits spread broadly across firms, workers, and sectors. With sustained investment in education, digital infrastructure, innovation systems, and effective governance, AI could become a powerful driver of productivity growth instead of turning into a missed opportunity for the region.
Special thanks to Camilo Pecha for his valuable contribution to this post.