Should Jamaica and CARICOM Build Their Own AI Capacity — or Risk Renting Someone Else’s Worldview?

Kingston, Jamaica — 7 February 2026

As governments around the world accelerate their use of artificial intelligence, a quieter but more consequential question is emerging beneath the surface: who is shaping the intelligence that governments rely on?

This week, UNESCO, alongside the University of Oxford’s Saïd Business School and the Mohammed Bin Rashid School of Government, announced the launch of an Arabic-language version of the global course AI and Digital Transformation in Government. The initiative, unveiled at the World Governments Summit in Dubai, is designed to equip civil servants across the Arab States with the skills needed to govern artificial intelligence responsibly, inclusively, and in line with regional realities.

On its face, this is a capacity-building story. In practice, it signals something far more strategic: a recognition that AI is not neutral, and that language, culture, institutional history, and regional values matter deeply in how digital systems are designed, deployed, and trusted.

For Jamaica — and for CARICOM more broadly — the development raises an unavoidable question. Should small states actively build their own AI capacity, governance frameworks, and regionally grounded training systems? Or should they continue to rely on imported AI tools, platforms, and datasets shaped elsewhere, often by ideologies, legal assumptions, and economic priorities that do not reflect Caribbean realities?

This is not a technological question alone. It is a question of sovereignty, resilience, and long-term security.

AI as Infrastructure, Not a Gadget

Artificial intelligence is often discussed as a tool — something governments use. Increasingly, however, AI functions more like infrastructure. It shapes how decisions are made, how risks are assessed, how resources are allocated, and how citizens interact with the state.

In housing and land administration, AI is already influencing:

• Risk modelling for climate exposure and disaster recovery
• Land registration systems and fraud detection
• Property valuation, taxation, and revenue forecasting
• Infrastructure planning and urban growth modelling
• Access to credit, insurance, and public support

When these systems are trained on datasets that reflect different legal systems, social norms, market structures, or historical patterns of ownership, they do not simply become less accurate. They can systematically misinterpret local realities.

For post-colonial societies like Jamaica, this matters. Land ownership patterns, informal settlements, generational tenure, family land, and climate vulnerability do not map neatly onto datasets built around North American or European assumptions. An AI system trained elsewhere may “work” technically while quietly reinforcing inequities, excluding lived realities, or privileging models of ownership and development that are misaligned with local needs.

The Arab States Example: Capacity Before Control

What distinguishes the UNESCO-supported initiative in the Arab States is not that governments are building their own AI models from scratch. Rather, they are investing deliberately in human capacity — ensuring that civil servants understand AI well enough to govern it, question it, and adapt it responsibly.

The decision to localise the course into Arabic is significant. Language is not cosmetic. It determines who can engage deeply with policy, who shapes regulatory frameworks, and whose perspectives are reflected in governance decisions. By anchoring AI education in local language and regional context, the programme reduces dependence on external interpretation and imported frameworks.

For Jamaica and CARICOM, the lesson is not necessarily “build a Caribbean ChatGPT tomorrow.” The lesson is more foundational: without deliberate investment in local AI literacy, governance capability, and regional datasets, governments risk becoming passive users of systems they do not fully control.

Small States, Big Asymmetries

Small states face a structural challenge in the AI era. They rarely control the platforms, cloud infrastructure, or foundational models that dominate global markets. Yet they bear the full consequences of how these systems shape public policy, service delivery, and economic outcomes.

This asymmetry is not new. Jamaica has navigated similar dynamics in finance, trade, telecommunications, and energy. The difference with AI is speed and opacity. Decisions can be automated at scale before their assumptions are fully understood.

In land use and housing, this could manifest subtly:

• Automated planning recommendations that prioritise efficiency over community continuity
• Risk assessments that undervalue informal or hybrid tenure systems
• Climate models that under-represent small-island micro-geographies
• Credit scoring systems that penalise non-standard income patterns common in the Caribbean

None of these outcomes require bad intent. They emerge naturally when systems trained elsewhere are applied uncritically.

AI, Trust, and the Public Interest

One of the most striking elements of the UNESCO initiative is its emphasis on trust. Trust in public AI systems is not built through technology alone. It is built when citizens believe systems reflect their realities, protect their rights, and serve the public interest rather than external priorities.

In Jamaica, trust is already a fragile asset in areas such as land administration, housing allocation, and development control. Introducing opaque AI systems without strong local governance risks deepening scepticism rather than improving outcomes.

Conversely, a measured, transparent approach — where AI is governed by people who understand both the technology and the society it operates in — can strengthen institutions over time.

Does CARICOM Need a Regional AI Strategy?

The question, then, is not whether Jamaica or CARICOM should isolate themselves from global AI ecosystems. That would be neither realistic nor desirable. The more relevant question is whether the region can afford not to develop a shared strategic approach.

A regional framework could include:

• Joint training programmes for civil servants and regulators
• Shared ethical and governance standards grounded in Caribbean realities
• Regionally relevant datasets, particularly in climate, land, and housing
• Cooperative engagement with global AI providers from a position of informed strength

Such an approach mirrors how CARICOM has historically addressed trade, education, and climate diplomacy. Individually, small states have limited leverage. Collectively, they can shape terms of engagement.

Housing, Land, and Long-Term Security

At its core, this debate intersects with housing and land not because AI is a “property technology,” but because land remains the primary store of value, security, and identity for Caribbean families.

Decisions about where housing is built, who has access to land, how risk is assessed, and how resilience is planned will increasingly be informed by digital systems. If those systems encode assumptions that do not reflect Caribbean history, climate exposure, or social structure, the consequences will unfold over decades.

AI, in this sense, becomes part of the long arc of development — shaping not just efficiency today, but inheritance, affordability, and intergenerational equity tomorrow.

“Artificial intelligence will quietly become part of how governments decide who is seen, who is counted, and who is protected. If those systems are trained on assumptions that are not ours, then over time we outsource judgment itself. The real question for small states is not whether to use AI, but whether we understand it well enough to ensure it serves our people, our land, and our future — rather than reshaping them in someone else’s image.”
— Dean Jones, founder of Jamaica Homes

A Question of Intentionality

The Arab States initiative illustrates a crucial point: meaningful engagement with AI begins with intentionality. Governments that invest early in understanding, governance, and local relevance are better positioned to ensure technology serves public goals rather than distorting them.

For Jamaica and CARICOM, the choice is not between building everything locally or using global systems wholesale. The real choice is between:

• Passive adoption, driven by convenience and external design, or
• Deliberate capacity-building that allows informed use, adaptation, and oversight

In the long run, the latter is not a luxury. It is a form of institutional resilience.

Looking Ahead

As AI becomes embedded in the machinery of government, the costs of disengagement will rise. What begins as a technical decision can become a structural constraint — one that shapes land use, housing access, and economic security in ways that are difficult to unwind.

The UNESCO-supported Arabic MOOC is a reminder that governing AI is ultimately about people, not machines. It is about who understands the systems, who sets the rules, and whose realities are reflected in digital decision-making.

For Jamaica and the wider Caribbean, the question is no longer abstract. It is whether the region will approach AI as something that simply arrives — or as something that must be shaped, questioned, and governed with intention.

The answer will matter long after the headlines fade.

Disclaimer: This article is for general information and commentary purposes only and does not constitute legal, financial, or investment advice. Readers should seek professional guidance appropriate to their individual circumstances.