Artificial intelligence has moved beyond novelty. What was once framed as experimentation has now entered a phase where countries are being shaped by how, where, and under whose rules AI systems are deployed. For a small island state like the Maldives, this shift carries particular weight. The question is no longer whether AI will be adopted, but whether the country shapes its use deliberately or allows its economy, data, and public services to be shaped by external systems.
The Maldives is small, fragmented, and constrained by geography. Those same characteristics make the stakes around AI higher. A country spread across more than a thousand islands depends heavily on logistics, connectivity, service delivery, and efficient coordination. Artificial intelligence, if deployed with intent, can reduce many of these structural disadvantages. If adopted passively, it risks deepening dependency on foreign platforms, foreign data centres, and foreign legal frameworks.
The experience of other small economies shows that the earliest choices tend to lock in long-term outcomes. Once public services, banks, tourism operators, and government platforms are built on external AI stacks, reversing those dependencies becomes difficult and expensive. This is why an AI strategy for the Maldives cannot be treated as a technology policy alone. It is a matter of economic resilience, governance, and sovereignty.
One of the clearest lessons emerging from global research is that AI systems increasingly operate in the physical world. For the Maldives, this matters more than for most countries. Maritime transport, energy delivery, waste management, healthcare access, and even environmental monitoring are all shaped by physical distance and ocean conditions. AI-enabled vessels, drones, and robotic systems can reduce costs and improve reliability across atolls, but only if the supporting infrastructure exists. Without reliable connectivity, resilient power supply, and local maintenance capacity, these systems risk becoming short-lived pilots rather than lasting solutions.
This has already been a pattern in the Maldives. Pilot projects attract attention, donor funding, and press releases, but struggle to scale. AI introduces a new risk here. Unlike traditional digital systems, AI requires clean data, continuous monitoring, and ongoing governance. Deploying advanced tools without these foundations creates fragile systems that fail quietly and expensively. A national AI strategy must therefore prioritise infrastructure and governance before large-scale deployment.
Data governance sits at the centre of this challenge. The Maldives generates valuable data through tourism, financial services, and digital government platforms. At present, much of this data is processed using foreign cloud infrastructure and foreign AI models. This creates legal and economic exposure. Data stored and processed abroad is subject to foreign laws, foreign access regimes, and foreign commercial interests. Without clear domestic legislation defining data ownership, consent, and cross-border flows, the Maldives has limited leverage over how its data is used or monetised.
Passing comprehensive data protection and privacy legislation is therefore not optional. It is the legal foundation on which any credible AI strategy must rest. Without it, claims of digital sovereignty are symbolic rather than enforceable. Legislation must clarify where sensitive data can be processed, how automated decision-making affects citizens’ rights, and who is accountable when AI systems fail or discriminate.
The public sector presents both an opportunity and a risk. Platforms such as OneGov and e-Faas have already digitised many services, but digitisation alone does not guarantee better outcomes. AI systems that automate eligibility checks, application processing, or compliance decisions can improve efficiency, but they also introduce new forms of error and bias. If poorly governed, automated decisions risk undermining trust in government rather than strengthening it. Any public sector use of AI must therefore retain human oversight, clear audit trails, and accessible appeal mechanisms.
Tourism, the backbone of the Maldivian economy, is likely to be one of the earliest adopters of advanced AI systems. Personalisation, logistics optimisation, and predictive maintenance can increase value per visitor and reduce operational strain. At the same time, the sector generates some of the most sensitive commercial and personal data in the country. Allowing this data to be captured and analysed entirely by external platforms risks shifting value creation offshore. An AI strategy must recognise tourism data as a national economic asset, not just a private operational resource.
Workforce implications cannot be ignored. AI will not simply replace jobs, but it will change them. In a country already grappling with youth unemployment alongside heavy reliance on expatriate labour, this transition must be managed deliberately. Training Maldivians to supervise, maintain, and govern AI systems offers a path to higher-value employment that aligns with the country’s long-term development goals. Without such planning, the benefits of AI adoption risk accruing elsewhere, while local workers are left behind.
Perhaps the greatest risk for the Maldives is delay. Global AI systems are evolving quickly, and regulatory norms are being set by larger economies. Waiting for international standards to settle before acting may feel safe, but it increases dependence. A proactive AI strategy allows the Maldives to set its own priorities, identify where sovereignty matters most, and decide where partnerships are acceptable.
Artificial intelligence will shape how the Maldives moves goods, delivers services, protects its environment, and governs its citizens. The choice facing the country is not between adoption and resistance. It is between deliberate design and quiet dependence. Acting early, with clear legal frameworks and strategic intent, offers the chance to turn structural constraints into advantages. Failing to do so risks letting the technology decide instead.
