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Latin America is engaging with AI faster than its share of global investment would suggest, but the region is not advancing as one market. ECLAC estimates that Latin America and the Caribbean account for 14% of global visits to AI solutions and 11% of the world’s internet users, while representing 6.6% of global GDP and 1.12% of global AI investment. Those estimates, published with the 2025 Latin American Artificial Intelligence Index (ILIA), point to strong interest alongside a gap in investment and productive capacity—not proof of a uniform regional boom.
How is AI transforming Latin America?
The clearest regional change is widening use of AI tools, paired with uneven ability to turn that use into locally developed products, operational analytics, and productivity gains. ECLAC describes current use as concentrated in a small group of countries and largely oriented toward ready-made, end-user solutions that require relatively little technical expertise. Using an AI assistant is meaningful adoption, but it does not by itself establish that a company has integrated AI into core workflows, built data infrastructure, or developed software and models locally.
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That distinction matters for software engineering. The evidence available here does not establish a harmonized region-wide count of software engineers, engineering productivity, or AI analytics use by sector. It supports a more bounded account: investment and market scale are especially visible in Brazil, while regional AI readiness and adoption vary substantially by country. Treat software engineering capability as a factor to assess—skills, research, implementation, and governance—not as a growth figure that can be inferred from AI-tool traffic.
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ILIA 2025, developed by ECLAC and the National Center for Artificial Intelligence (CENIA), assesses 19 countries using more than 100 sub-indicators. Its framework considers enabling conditions, research, development and adoption, and governance. It places countries in three ecosystem categories rather than presenting a single measure of commercial AI success.
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| ILIA category | Countries and reported scale | What the category indicates |
|---|---|---|
| Pioneers | Chile, Brazil, and Uruguay; each scored above 60 points | The strongest overall ecosystems in the index’s assessment. |
| Adopters | Eight countries, including Colombia, Ecuador, Costa Rica, and the Dominican Republic | A middle group advancing in AI readiness and adoption. |
| Explorers | More than one-third of the countries analyzed | Countries with comparatively less developed AI ecosystems in the index. |
The categories are useful for orientation, not interchangeable country rankings on every capability. A nation can have broad connectivity but limited specialist talent, or an AI strategy without the funding and delivery mechanisms to implement it. For a decision about investment or policy, compare the underlying dimensions—connectivity and infrastructure, research and development, use in businesses and public services, workforce capability, governance, and execution—instead of treating the category label as a complete diagnosis.
ECLAC’s regional estimates also need careful interpretation. The 14% share of visits to AI solutions is an engagement measure, not a measure of locally built software or business value created. The contrast with a 1.12% share of global AI investment suggests a possible imbalance between use and investment, but does not by itself explain its causes or quantify the returns from closing it.
How much is Brazil investing in IT and software?
Brazil provides the most concrete market-scale example in the cited evidence, but it should not stand in for every Latin American economy. ABES, reporting IDC figures in 2025, says Brazil invested US$58.6 billion in IT in 2024, a 13.9% increase over 2023. Brazil accounted for 34.7% of the US$169 billion invested in Latin American IT that year.
| Brazil market measure | Reported value | Scope and source |
|---|---|---|
| Total IT investment | US$58.6 billion; up 13.9% year over year | 2024, IDC data analyzed by ABES and reported in 2025. |
| Software spending | US$18.0 billion | 2024, IDC data analyzed by ABES and reported in 2025. |
| IT services spending | US$12.7 billion | 2024, IDC data analyzed by ABES and reported in 2025. |
| Software plus IT services | US$31.0 billion | 2024, IDC data analyzed by ABES and reported in 2025. |
| Brazil’s share of regional IT investment | 34.7% of US$169 billion | Latin American IT investment total reported by ABES from IDC data for 2024. |
These figures describe spending and market scale. They do not measure the number of engineers, software exports, AI analytics deployment, or how much of the spending went to locally developed products. ABES also reported 2025 forecasts of 9.5% growth in Brazil’s IT investment and approximately US$2.4 billion in AI projects, 30% above 2024. Those were forecasts published in 2025, not confirmed 2025 results.
How widespread is business AI adoption?
Reported adoption percentages differ because they come from different datasets and definitions. The World Bank’s Digital Progress and Trends Report 2025: Strengthening AI Foundations cites one dataset in which 13% of Brazilian firms and 7% of Colombian firms used AI. The same report separately cites the IBM Global AI Adoption Survey 2023, in which 47% of firms in Latin America reported actively deploying AI. These figures should not be combined into a single country comparison or trend line: the report identifies distinct sources, and the measures are not established as like-for-like.
The World Bank also notes that adoption is concentrated among larger firms and businesses in IT, professional services, and financial services. That pattern helps explain why headline awareness or survey results may coexist with limited diffusion among smaller firms or in sectors with weaker data, infrastructure, and implementation capacity.
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What is holding back AI adoption and software capability?
Advanced skills and retention
ECLAC reports that advanced AI training remains insufficient and concentrated in a small number of countries. It says the gap in advanced AI talent relative to the global average has widened since 2022, linking the problem in part to specialist brain drain. Access to basic AI tools cannot substitute for people who can build reliable data pipelines, evaluate models, integrate systems, and maintain them over time.
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According to ECLAC, many national AI strategies lack financing, implementation mechanisms, and systems for evaluating impact. A published strategy therefore signals intent, not delivery. Leaders assessing a program should look for a funded owner, a workforce plan, a sequence of deployable projects, and measures that track results rather than announcements.
ECLAC’s record for an AI economic-impact study identifies low investment and human-capital formation constraints and describes modeling effects through skilled-labor productivity and interactions among productive factors. The record provides an abstract rather than detailed country estimates, so it does not support a precise forecast of AI’s economic effect for any country.
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Governance and reliability
Governance is not only a compliance question; it affects whether organizations can deploy systems responsibly and trust their outputs. ECLAC warns that strategies can overemphasize regulation without building the technological ecosystem needed for productivity and well-being. The practical challenge is to develop safeguards alongside infrastructure, skills, and implementation—not to treat any one of them as a replacement for the others.
The World Bank report also describes risks from inaccurate generative AI output. In the report’s cited 2024 firm survey, 63% of surveyed firms considered inaccurate output a relevant risk, up from 56% in 2023, and nearly one-quarter reported negative consequences from inaccuracy. These are not Latin America-only figures. They illustrate why business deployment needs human review, testing, and accountability appropriate to the task.
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1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitchesHow should leaders compare countries or AI strategies?
A useful comparison asks whether a country or organization can move from access to sustained productive use. Use the same questions for each candidate market or program, and distinguish the existence of a policy from evidence that it is funded and operating.
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- Infrastructure: Are connectivity, computing access, and usable data foundations sufficient for the intended workloads?
- Adoption and use cases: Is AI limited to ready-made tools, or is there evidence of integration into business or public-service processes? Check the survey definition before comparing adoption rates.
- Talent: Are advanced AI and software skills available locally, and can organizations recruit and retain people to build and maintain systems?
- Research and development: Is there capacity to adapt, evaluate, or develop technology locally, rather than only consume external products?
- Governance: Are responsibilities, data practices, oversight, and risk controls clear enough to support deployment?
- Funded execution: Does the strategy name financing, delivery mechanisms, accountable institutions, and timelines?
- Measurement: Are outcomes evaluated—for example, reliability, service quality, productivity, or access—rather than inferred from tool availability or policy publication?
This scorecard avoids a common category error: equating high AI interest, IT spending, or a national strategy with mature software engineering and analytics capability. Each is relevant, but each answers a different question.
What the regional shift means
Latin America and the Caribbean show meaningful AI engagement, but capacity is concentrated and uneven. ILIA’s country categories, Brazil’s large IT market, and the differing business-adoption statistics each illuminate a different part of the picture. The strategic test is whether interest and spending can be converted into skilled teams, funded implementation, locally relevant applications, and measurable outcomes.
As José Manuel Salazar-Xirinachs, ECLAC Executive Secretary, put it in the organization’s October 3, 2025 ILIA release: “But for this to happen, it is essential to align digitalization policies with productive development policies, including the digital transformation of priority sectors, in order to close infrastructure, talent, innovation and governance gaps, while also advancing regional cooperation to ensure an ethical, inclusive and responsible use of this technology,”
Álvaro Soto, ILIA Director at CENIA, described the value of repeated measurement in the same release: “In addition, by producing annual reports we move from a snapshot to a motion picture of the evolution of AI in Latin America.”
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