Building AI Governance Capacity in Small Island States

AI governance in Caribbean small island developing states (SIDS) cannot be built by copying EU or US frameworks and scaling them down. A country with 300,000 people, one main regulator, a civil service of 15,000, and no domestic AI industry has fundamentally different constraints from France or California. What it can build is a governance structure that is proportionate, enforceable, and capable of growing as AI adoption grows. That is a narrower but achievable target, and it starts with being honest about what small island governance can actually deliver.

Why SIDS Face a Structural Disadvantage in AI Governance

The governance gap between large economies and small island states on AI is not primarily a knowledge gap. Caribbean public servants are well-educated and internationally connected. The gap is structural. A small island state typically operates with a single regulatory body covering multiple sectors, limited specialist staff per agency, high staff turnover as talent migrates to the private sector or overseas, and a legislative pipeline that moves slowly relative to technology adoption rates.

Barbados, with a population of around 280,000, has one primary financial services regulator (the Financial Services Commission), one central bank (the Central Bank of Barbados), and a telecoms regulator (the Telecommunications Unit). Each of these bodies has staff in the dozens, not the hundreds. None has a dedicated AI division. None has issued standalone AI guidance. This is not a failure of governance; it is a reflection of what small island regulatory capacity realistically looks like.

The same picture holds across the OECS. Saint Lucia, Grenada, Dominica, Saint Kitts and Nevis, Antigua and Barbuda, and Saint Vincent and the Grenadines collectively regulate their financial sectors through the Eastern Caribbean Central Bank (ECCB), which covers all six OECS monetary union members. The ECCB is a respected institution with genuine capacity, but AI governance is not yet a dedicated work programme within it.

This structural reality shapes what AI governance capacity building in SIDS must look like. It cannot be a framework that requires 50 specialist staff to operate. It has to be a framework that five well-trained people can maintain, with external support available for complex assessments.

The Four Institutional Capabilities SIDS Need to Build First

Before any specific AI regulation can work, four underlying institutional capabilities need to exist. Caribbean SIDS that invest in these foundations will be better positioned than those that skip to drafting AI law without the infrastructure to enforce it.

AI literacy at the senior leadership level is the starting point. A regulator whose board and senior management cannot distinguish between a machine learning model and a rule-based algorithm cannot make sound judgements about AI risk. The Bank of Jamaica's 2023 FinTech regulatory sandbox programme included sessions on AI fundamentals for participating firms. That approach, extending AI literacy to the regulatory staff overseeing those firms, needs to become standard practice across Caribbean central banks and financial regulators. A two-day AI governance workshop for regulators, delivered by a regional provider with real Caribbean context (not a generic US-produced course), costs less than one compliance breach investigation.

A legal basis for AI regulatory action is the second capability. Caribbean regulators who want to act on AI risks need to know what authority they have under existing law. In most Caribbean jurisdictions, existing financial services legislation, consumer protection law, and data protection acts together provide a workable legal basis for AI risk-related regulatory action, without waiting for dedicated AI legislation. The Financial Services Commission of Jamaica can act on AI-related consumer harms under the Financial Services Commission Act. The Office of the Information Commissioner can act on AI-related data protection breaches under the Data Protection Act 2020. Mapping what existing law already permits is faster than drafting new law.

A cross-agency coordination mechanism is the third. AI does not respect sector boundaries. An AI tool used in a bank may also be subject to data protection rules, consumer protection rules, and employment law. In small island states, the relevant regulators typically know each other personally and coordination costs are lower than in large bureaucracies. Formalising this coordination, even as a quarterly inter-agency meeting with a shared AI incident register, creates accountability that informal relationships alone do not.

Private sector engagement infrastructure is the fourth. Effective AI governance requires that regulators understand what AI tools are actually being used in the sectors they oversee. This means building a channel for supervised entities to report AI deployments. It does not need to be a formal notification regime immediately. A voluntary reporting arrangement, similar to how some Caribbean central banks have approached fintech sandbox programmes, creates the information flow that formal regulation can later build on.

The Regional Coordination Opportunity That Caribbean SIDS Are Not Fully Using

One genuine advantage that Caribbean SIDS have, which larger nations do not, is that their regulators already cooperate through established regional bodies. The ECCB, the Caribbean Group of Banking Supervisors (CGBS), the Caribbean Financial Action Task Force (CFATF), and the Caribbean Telecommunications Union (CTU) all provide platforms for shared standards and coordinated approaches. AI governance is an obvious candidate for the same treatment.

The CTU's Caribbean AI Policy Roadmap, published in 2023, proposed exactly this: a regionally harmonised approach to AI governance that small island states could adopt as a package rather than develop individually. The IDB has been providing technical assistance to Caribbean governments on digital governance since 2021. The World Bank's Digital Development Partnership programme has funded digital economy assessments across multiple CARICOM states. The building blocks for a regional AI governance framework exist. What is missing is political will to move from roadmap to binding instrument.

For risk and compliance professionals working within Caribbean SIDS, this regional landscape matters for two reasons. First, it means that compliance programmes built today can expect regional harmonisation in the medium term, so designing to the CTU roadmap's principles creates forward compatibility. Second, it means that private sector voices in the regional consultation process can shape what that harmonised framework looks like, which is an opportunity worth taking seriously before the framework is fixed.

A Proportionate AI Governance Model for SIDS Regulated Entities

Regulated entities in Caribbean SIDS, banks, credit unions, insurance companies, money service businesses, face the same fundamental AI governance obligations as their counterparts in larger markets. The difference is that the governance infrastructure they can realistically build is smaller. The model below is designed for an organisation with 50 to 500 employees, one or two risk and compliance staff, and limited specialist AI knowledge internally.

At the governance level, the board should receive an annual AI risk report covering all AI tools in use, any material changes during the year, and any identified bias or performance concerns. This does not require a dedicated AI committee. It requires that AI risk is a standing item on the board risk committee agenda once a year, with a written report from management.

At the management level, a single designated AI risk owner, typically the Chief Risk Officer or Head of Compliance, should maintain the AI tool inventory, review vendor documentation, and escalate any incidents involving AI system failures or unexpected outputs. In a small organisation, this is a part-time responsibility, not a full-time role.

At the operational level, any AI tool used in a regulated decision (credit, claims, fraud, KYC) should have a documented control: who approved the tool, what human oversight applies, how errors are corrected, and when the tool was last reviewed. This documentation does not require expensive software. A shared document with version control serves the purpose for a small institution.

The total time investment for this model, in a 100-person organisation using three to five AI tools, is approximately 15 to 20 hours per year at the board level, 40 to 60 hours per year at the management level, and 5 to 10 hours per tool per year at the operational level. These are manageable numbers.

Frequently Asked Questions

What is AI governance capacity and why do small island states need it?

AI governance capacity is the institutional ability to set standards for AI use, monitor compliance with those standards, and take action when AI systems cause harm. Small island states need it because AI tools are already being deployed in Caribbean businesses, banks, and government agencies without any oversight framework. Without governance capacity, harmful AI outputs, from biased credit decisions to manipulative marketing tools, have no institutional check.

How can a small Caribbean regulator with limited staff govern AI effectively?

Small Caribbean regulators can govern AI effectively by focusing on three things: mapping what AI is already in use in regulated sectors through voluntary or mandatory disclosure; building AI literacy in the senior staff who supervise regulated entities; and extending existing regulatory powers (consumer protection, data protection, financial services law) to cover AI-related harms before waiting for dedicated AI legislation. Regulators do not need a 50-person AI division to start. They need two trained staff and a clear legal mandate.

Is CARICOM developing a regional AI governance framework?

As of early 2025, CARICOM has not adopted a binding regional AI governance framework. The Caribbean Telecommunications Union published a Caribbean AI Policy Roadmap in 2023, which includes recommendations for a regional approach to AI governance, data governance, and AI ethics. The IDB has been providing technical assistance to CARICOM member states on digital economy governance. A binding regional framework is likely to follow, but no timeline has been confirmed. Caribbean organisations should not wait for regional harmonisation before building their own AI governance practices.

What is the difference between AI governance and AI regulation?

AI governance refers to the internal policies, processes, and oversight mechanisms that an organisation uses to manage its AI systems responsibly. AI regulation refers to the external legal and supervisory framework imposed by governments and regulators. Caribbean organisations need both. Internal AI governance is something any organisation can build now, regardless of whether their government has enacted AI law. External regulation sets minimum standards that may not yet exist in most Caribbean jurisdictions but is coming.

What role do regional bodies like the ECCB and CTU play in Caribbean AI governance?

The Eastern Caribbean Central Bank (ECCB) sets prudential standards for financial institutions across the OECS monetary union countries, giving it a natural role in setting AI risk standards for banks and credit unions in those territories. The Caribbean Telecommunications Union (CTU) has already produced the Caribbean AI Policy Roadmap and is the lead regional body on digital and AI governance policy. Caribbean organisations should monitor CTU outputs and engage in CTU consultation processes as AI governance standards develop.

How should a small Caribbean business start building AI governance with no specialist staff?

Start with an inventory: list every AI tool the business uses, including vendor-provided AI features within existing software. For each tool, record its purpose, the data it uses, and whether it makes or influences regulated decisions. Assign one person, typically the compliance or risk lead, to own this inventory and review it quarterly. For any tool involved in regulated decisions, document who approved it, what human review applies, and how errors are corrected. This basic framework takes roughly two days to set up and provides the foundation for everything more formal that follows.

What specific AI risks are most common in Caribbean SIDS government agencies?

Caribbean government agencies most commonly face three AI risks. First, procurement risk: buying AI tools from foreign vendors without understanding what those tools do with government data or how they make decisions. Second, bias risk: using AI tools in public service delivery (permit processing, benefits assessment, tax auditing) that were not designed for Caribbean demographic data and produce systematically unfair outcomes. Third, vendor lock-in risk: building critical government functions on AI platforms that the government cannot audit, modify, or replace without prohibitive cost.

Can the NIST AI Risk Management Framework work for very small Caribbean organisations?

Yes, with proportionate application. The NIST AI RMF is structured around four functions: Govern, Map, Measure, and Manage. A small Caribbean organisation does not need to implement every practice under each function. For a business with under 100 employees and two to three AI tools, the minimum workable implementation covers: a designated AI risk owner (Govern), an AI tool inventory with risk ratings (Map), annual performance review of each AI tool against its stated purpose (Measure), and documented controls for any tool used in regulated decisions (Manage). This fits within existing compliance staff capacity.

The Governance Gap Is Closing, Whether Caribbean SIDS Are Ready or Not

Regional and international AI governance standards are converging. The EU AI Act is in force. The UK is consulting on its AI regulatory framework. The OECD has updated its AI Principles. UNESCO's Recommendation on the Ethics of AI is being adopted by member states. Caribbean SIDS will eventually face external pressure to align with one or more of these frameworks, either through trade relationships, correspondent banking requirements, or direct regulation of businesses operating in regulated global markets.

The organisations and regulators that build their governance capacity now, proportionately and practically, will find that alignment process manageable. Those that wait will face it under external pressure, with less time, less bargaining power, and less room to shape the standards to reflect Caribbean realities. The window for shaping Caribbean AI governance from the inside is open. It will not stay open indefinitely.