I have been building AI in the Caribbean for fifteen years. In that time I have seen the region get about three real chances to lead in some part of AI, and let each pass. A few people worked hard each time; the institutions that make decisions did not move.
This time several things have changed together, and I think the opening is larger than before. Whether it becomes a fourth missed chance depends on decisions Caribbean governments, businesses and universities make in 2026.
Three things that changed
Building with AI got cheap. For most of applied AI's history, the barrier was compute. Training a capable model needed infrastructure costing tens of millions of dollars, which ruled out a startup in Kingston or a ministry in Bridgetown. Today the leading models are available through an API, and a team with a US$10,000 budget can build a working product on them. AWS, Google Cloud and Microsoft Azure all rent GPUs to Caribbean customers by the hour. That is how StarApple AI built production systems for Caribbean financial institutions without Silicon Valley venture capital, and how a two-person team in Trinidad can ship a product that holds its own against North American competitors.
Caribbean data now exists at scale. Institutions here have been digitising for two decades. Banks hold years of transaction records, governments have moved citizen services online, hotels hold booking and operations data, ports hold logistics data, and hospitals keep more records digitally each year. Models tuned on local data do better on local problems: a fraud model trained on Jamaican transactions will catch more Jamaican fraud than one trained only on American patterns.
Regulation is still being written. Large economies are fitting AI rules onto industries that already exist, against companies with political weight. The EU AI Act, the most serious attempt so far, entered into force in August 2024 and is creating heavy compliance work for European firms. A CARICOM framework agreed now would shape a small industry from the start, with far less resistance.
We have the talent and the ideas. What decides the window is whether we move before global consolidation of AI markets leaves no room for smaller players.
Four sectors where Caribbean AI firms can win
| Sector | Problems AI can take on | Why a local firm has an edge |
|---|---|---|
| Tourism | Revenue management, demand forecasting, dynamic pricing, staffing, food and beverage purchasing, resort maintenance | Operators already buy these tools from North American and European vendors; a local firm knows the seasons, source markets and suppliers |
| Financial services | Fraud detection, anti-money-laundering compliance, customer service, credit for the unbanked | Correspondent banking pressure and local data matter here, and foreign vendors rarely understand either |
| Agriculture | Climate risk, crop monitoring from satellite images, price forecasting, supply planning | Few established vendors and few legacy systems, so the field is open |
| Government services | Document processing, citizen enquiries, benefits eligibility, tax compliance, public health | Knowing how Caribbean procurement works is a real barrier for outsiders |
Tourism is the largest sector and one of the least analytical in how it runs. Hotels generate far more data than they use, and every item in that row is a problem they have both the data and the motive to solve.
In financial services, many adults in several Caribbean countries still have no bank account or no credit history, and conventional lenders cannot serve them profitably. Credit models built on payment and remittance histories change that calculation. StarApple AI has worked in this area for years, and it is far from crowded.
Government is the slowest to buy. Public sectors here are cautious about technology, and rules for responsible AI in government are still being drafted. Firms that can show results inside those rules will have little competition.
Three threats that could close the window
- Consolidation. The economics of AI favour a handful of the largest platforms. If Caribbean institutions standardise on them and build no capability of their own, the region stays a customer and captures little of the value.
- Brain drain. Caribbean AI talent is good enough to be hired anywhere, and remote roles for North American firms pay far more. Keeping people takes paid work at home, reliable infrastructure and a local community of practice.
- Institutional caution. Governments and large firms here have seen many technology projects fail and many consultancy reports end in nothing. That caution is earned. The only answer is local AI firms delivering working systems, one contract at a time.
Of the three, I am least sure what to do about brain drain. The other two can be met with procurement choices and good work; this one depends on salaries that small Caribbean firms mostly cannot yet pay.
What to do this year
- Caribbean businesses: choose one operational problem, such as fraud losses, room pricing or invoice processing, and put it out to Caribbean-based AI firms before calling a foreign vendor. Ask for a fixed-price pilot of 60 to 90 days with a measured baseline.
- Governments: adopt a minimum AI procurement standard this year. Any AI system in a public-facing service must be documented, tested for accuracy on local data, and open to citizen appeal. In most jurisdictions this is a procurement policy decision and needs no new law.
- CARICOM ministers: put a short regional AI governance framework on the agenda while the industry is still small enough for rules to shape it.
- Universities: pair each AI research group with at least one Caribbean company or ministry on a live problem, with student placements attached.
- AI practitioners: publish what you build, what worked and what failed. The community is small enough that each write-up raises what everyone else can do.
Caribbean music, athletes and writers have shaped global culture from small islands the world consistently underestimates. There is no structural reason AI should be different.
Frequently Asked Questions
Does any Caribbean country have a national AI strategy?
Several are drafting or have published one, and the picture changes quickly, so check each government's ministry of science, technology or digital transformation for the current document. Jamaica has a National AI Task Force advising government on policy. Regional bodies such as the Caribbean AI Association track national progress across CARICOM.
Where can a Caribbean startup get cloud credits or funding for an AI product?
AWS, Google Cloud and Microsoft each run startup programmes that give cloud credits to eligible early-stage firms, and applications are made online. The Caribbean Development Bank and other development lenders run innovation and challenge funds that open calls from time to time. Credits cover compute; they do not replace paying customers, so line up a pilot client first.
How should a government test an AI system for Caribbean accuracy before buying it?
Give the vendor a test set of local cases the vendor has not seen, such as real (anonymised) forms, accents, names and addresses, and score the results against known answers. Compare error rates for different groups, for example rural and urban applicants. Write the minimum acceptable score into the contract before the test is run.
Will the EU AI Act affect Caribbean companies?
It can. The Act applies to AI systems placed on the EU market or whose outputs are used in the EU, regardless of where the provider is based. A Caribbean firm selling an AI product to European customers, or processing data for them, should check which risk category its system falls into. Obligations phase in between 2025 and 2027.