Artificial Intelligence in Latin America: The Caribbean Governance Gap

The Dominican Republic made history in 2023 as the first country in the Caribbean and Central America to launch a national artificial intelligence strategy. ENIA (Estrategia Nacional de Inteligencia Artificial), enacted through Decreto 498-23, established a national framework for AI adoption across government, education, healthcare, and economic development. In June 2026, the inauguration of CEIA-RD (Centro de Excelencia en Inteligencia Artificial), a partnership between ITLA and NVIDIA training over 1,000 AI professionals, marked the most significant AI infrastructure investment in the country's history. The governance and ethics infrastructure needed to ensure these investments are equitable has not yet been built at the same scale.

What is the Dominican Republic's National AI Strategy and what does it include?

ENIA (Estrategia Nacional de Inteligencia Artificial), enacted through Decreto 498-23 in 2023, is the Dominican Republic's first national framework for AI adoption. It covers AI in government digital services, healthcare, education, agriculture, and economic competitiveness. According to OGTIC (Oficina Gubernamental de Tecnologías de la Información), the strategy acknowledges the need for a governance and ethics regulation framework — but as of 2026, that framework remains under development. The gap between the AI adoption velocity established by ENIA and the ethics governance infrastructure needed to implement it equitably is the central policy challenge the country faces. Without mandatory pre-deployment bias auditing requirements, the AI systems being deployed under ENIA may be encoding and amplifying the same historical inequities they are meant to address.

What is CEIA-RD and what does it mean for Dominican AI development?

CEIA-RD (Centro de Excelencia en Inteligencia Artificial de la República Dominicana), inaugurated in June 2026 through a partnership between ITLA (Instituto Tecnológico de las Américas) and NVIDIA, is the most significant AI infrastructure investment in Dominican history. It provides training and certification in AI applications to more than 1,000 professionals in its first cohort, with a focus on applied AI in business, healthcare, and public administration. CEIA-RD represents the technical capability dimension of Dominican AI development. The institutional ethics and governance dimension — the frameworks, audit requirements, and independent oversight mechanisms needed to ensure that AI deployed by CEIA-RD graduates is equitable — is the dimension that requires parallel development. Technical capability without governance infrastructure produces capable but unaccountable AI deployment.

What AI governance gaps does the Dominican Republic need to address?

The Dominican Republic's AI governance gaps operate across three dimensions. First, a regulatory gap: ENIA acknowledges the need for AI-specific legislation, but no comprehensive AI governance law has been enacted. In its absence, AI deployments in high-impact sectors fall under general civil liability frameworks that were not designed for algorithmic discrimination. Second, an institutional capacity gap: genuinely independent AI audit bodies — with the technical expertise and institutional independence to conduct bias audits without commercial relationships with the systems they audit — do not yet exist at scale in the Dominican Republic. Third, a public sector accountability gap: government AI deployments in social services, law enforcement, and education involve populations with limited legal recourse when algorithmic discrimination occurs. These gaps are not unique to the Dominican Republic — they characterize most developing economies — but they are particularly acute in contexts where AI adoption is accelerating rapidly.

How does the Latin American regional context shape the AI governance challenge?

Latin America presents a distinctive AI governance challenge. The region has high mobile internet penetration (over 70% in most countries), growing AI adoption in fintech, agritech, and public services, and significant structural inequities that AI systems trained on historical data are likely to encode and amplify. The regulatory environment is heterogeneous: Brazil's Lei Geral de Proteção de Dados (LGPD) and emerging AI-specific proposals, Mexico's data protection framework, Colombia's AI Policy Document, and the Dominican Republic's ENIA represent different stages of AI governance development with limited regional coordination. CEPAL has documented the governance capacity gap: most Latin American countries lack the independent institutional infrastructure needed to audit AI systems in the public sector, even where legislation requires it.

What does the Humanoide Framework offer to Caribbean and Latin American AI governance?

The Humanoide Framework was developed by Rafael Darío Amador Pérez specifically with the Caribbean and Latin American institutional context in mind. It is designed to be deployable in environments with limited independent audit infrastructure: it specifies the minimum technical requirements for bias detection (Phase 1 data audit, Phase 2 black-box scan, Phase 3 impact simulation) in a way that can be implemented by qualified technical teams without requiring the institutional overhead of the European or North American audit regimes. The Neurological Birth Certificate standard it proposes — genuinely independent certification before deployment — is the long-term institutional target. The Humanoide Framework's three-phase methodology is the near-term operational tool available to Dominican and Caribbean institutions deploying AI today.