Let me start with two numbers: 11% and 14%.
Latin America and the Caribbean account for 11% of the world’s internet users, but 14% of global visits to AI solutions. The region also ranks third worldwide in downloads of generative AI applications, according to the Latin American Artificial Intelligence Index 2025, prepared by Chile’s National Center for Artificial Intelligence and ECLAC.
Read that again: the region already uses AI above its digital weight.
Now compare that demand with investment. The 19 countries analyzed by the Index receive only 1.12% of global AI investment, despite representing 6.6% of global GDP. Ninety percent of the region’s supercomputing capacity is concentrated in Brazil, while more than half of the countries assessed lack critical infrastructure and advanced AI training.
This is not the profile of a market waiting for AI to arrive, it is the profile of a market where adoption has arrived before the infrastructure, investment, and governance needed to control it. Dont you agree?
And that is exactly why privacy and AI governance will become strategic!
Adoption came before maturity
ECLAC’s analysis of AI web traffic found that Brazil, Mexico, Colombia, Peru, Argentina, and Chile account for 86% of the region’s visits to AI solutions.
Generative AI represents 78% of regional AI traffic, compared with 74% globally and text generation alone accounts for 69% of visits.
This use is supported by 70% mobile-internet penetration and 81% smartphone penetration in 2024. In other words, Latin America did not need to build a complete domestic AI industry before millions of people and companies could start using cloud-based models.
But use is not the same as operational maturity, calm down :P
In July 2026, the Inter-American Development Bank reported that around 80% of firms in Latin America and the Caribbean already use AI tools but only 23% reported economic benefits, and just 6% reported a significant impact. The IDB identified investment, talent, infrastructure, and governance as the four main barriers preventing broader productivity gains.
That gap matters because when AI moves from isolated experiments into credit, healthcare, employment, insurance, education, public services, and customer operations, companies need more than access to a model, they need to know which data enters the system, where it goes, which vendor processes it, how long it is retained, how decisions are reviewed, and what evidence exists when a regulator or customer asks questions.
That is AI governance in practice.
Privacy regulation is already regional infrastructure
According to ECLAC’s Digital Development Observatory, 24 of the 33 countries in Latin America and the Caribbean have a personal-data protection law.
The frameworks are not identical, but the direction is clear.
Brazil’s LGPD created a national framework based on principles, data-subject rights, legal bases, security duties, accountability, and rules for international transfers. In early 2026, Brazil and the European Union adopted mutual adequacy decisions, allowing personal data to flow between them without additional transfer safeguards. Argentina and Uruguay are also on the European Commission’s adequacy list.
Chile’s Law No. 21,719, which takes effect on December 1, 2026, creates a dedicated Data Protection Agency and introduces rules on accountability, data portability, profiling, international transfers, and impact assessments for high-risk processing. The official text of the law requires an impact assessment before processing likely to create a high risk to individuals because of its nature, scope, context, technology, or purpose.
Colombia’s data protection authority issued External Circular 002 of 2024, with instructions on processing personal data in artificial-intelligence systems.
These are not copies of a single European rule. They are national systems with different authorities, procedures, sanctions, sectoral requirements, and interpretations. For organizations operating across the region, one global privacy policy is not an operating model.
Regulatory convergence does not eliminate local complexity. It makes operational governance more valuable.
Latin America is a real-world test for responsible AI
The region combines large digital systems with sharp social and infrastructure gaps.
The World Bank estimates that 30% to 40% of jobs in Latin America and the Caribbean are exposed in some way to generative AI. Between 8% and 12% could benefit from higher productivity. Yet up to 17 million jobs within that group may be unable to capture those benefits because of inadequate digital infrastructure. Women are, on average, twice as likely as men to work in jobs at risk of automation from generative AI.
Connectivity is also unequal. ECLAC reports that 80% of the region’s urban population has internet access, while the difference between the richest and poorest households can reach 50 percentage points.
These conditions turn abstract governance principles into concrete engineering questions. Was the training data representative? Can the system be audited across different populations? Does a person have a practical way to challenge an automated outcome? Can sensitive attributes be protected while bias is measured? Does the service still work for people with limited connectivity or digital skills?
The public sector is already confronting these questions. In December 2025, the IDB stated that it had supported more than 100 AI projects and documented applications in health, justice, public safety, and administrative services across the region.
Brazil also demonstrates the scale at which digital public infrastructure can operate. By November 2025, Pix had reached nearly 170 million users, while transactions totaled BRL 11 trillion in 2024. Systems operating at this scale create corresponding requirements for identity protection, security, traceability, fraud controls, data minimization, and accountability.
The missing layer is execution
The Index found that national AI strategies across the region often lack budgets, implementation mechanisms, and evaluation. It describes regional governance as having limited execution.
This is the space privacy and AI governance platforms are built to occupy: the distance between a policy and proof that the policy is being followed.
Organizations need operational inventories of personal-data processing and AI systems. They need impact assessments, risk classification, vendor oversight, international-transfer controls, incident workflows, retention rules, records of human review, and mechanisms for responding to data-subject requests. These controls must work in Portuguese and Spanish, reflect national legal requirements, and support both cloud and restricted deployment environments.
For global companies in cybersecurity, GRC, enterprise software, cloud, data management, and consulting, Latin America is therefore more than a localization exercise. The region combines measurable AI demand, expanding privacy obligations, large-scale public and private digital systems, and a documented governance execution gap.
The strategic assets in this market are not only software features. They include local regulatory content, enterprise integrations, deployment experience, language coverage, and established relationships with companies and governments.
That is why Latin America will become a strategic market for privacy and AI governance.