Cayman Islands Government - NCFC National Digital Transformation Task Force

Geuine global buy-in and real commitment from nations across development levels to participate meaningfully in shaping AI governance. This means developing nations and SIDS at decision-making tables rather than observing from the margins, with voting parity in priority-setting and funding mechanisms that enable sustained engagement from delegations with limited resources. Concrete commitments to work together. Nations face the same challenges in workforce transformation, regulatory development, education reform, and legislative capacity. The Dialogue should produce specific agreements to share implementation data, coordinate approaches, and avoid unnecessary duplication of effort. Real action to help each other. Knowledge-transfer mechanisms that move expertise across countries. Success also means establishing the Panel's credibility as genuinely independent.

• AI capacity-building
• Social, economic, ethical, cultural, linguistic and technical implications of AI
• Protection and promotion of human rights

Capacity-building is foundational. Without infrastructure, trained personnel, and institutional knowledge, developing nations can't participate in AI governance. We're governed by it. UNESCO found half of SIDS have no official AI initiatives. Every year we delay deliberate intervention, the distance grows. And capacity-building isn't one-size-fits-all. My nation of 85,000 people faces fundamentally different constraints than one of 50 million. Social, economic, ethical, cultural, and linguistic implications. This is where algorithmic colonialism lives. AI systems trained on data and values from dominant cultures, deployed in contexts that marginalise local knowledge systems, languages, and creative traditions. Governance must protect cultural data sovereignty or watch small nations become training data for someone else's models. Protection and promotion of human rights underpins everything else. AI systems making decisions about people, employment, credit, migration, justice, without transparency, accountability, or recourse is not innovation. Developing nations often deploy AI systems built elsewhere, with limited visibility into how they work or who bears responsibility when they cause harm.

Workforce transformation. Every nation, regardless of size or development status, faces the same fundamental question: how do we prepare workers for roles that don't yet exist while supporting those whose jobs are displaced? No country has solved this. The most advanced have pilots, not proven models. The Dialogue should establish mechanisms for sharing implementation data across borders. Not polished case studies. Real outcomes. Who is retraining whom, at what cost, with what results. Regulatory coherence. The EU has the AI Act, the US has sector-specific approaches, and China has its own framework, while most other nations are determining which model to adopt or whether to develop something new. This fragmentation creates friction for everyone, not just smaller economies, and interoperability should be understood as efficiency for the global system rather than charity for developing nations. Education systems. Curricula designed for a previous economy, educators unfamiliar with the tools they are expected to teach, and assessment frameworks rewarding memorisation over adaptability represent challenges that are universal rather than localised. Cross-border sharing of approaches would benefit all participants. Legislative capacity. Most parliaments are drafting AI legislation without adequate technical expertise, duplicating effort across borders and often doing so poorly. Model legislation, shared drafting resources, and technical assistance that crosses borders would accelerate progress for everyone.

The Cayman Islands presents a particular case study in AI governance gaps. As a Small Island Developing State with a workforce of 45,000 people and an economy concentrated in financial services and tourism, the effects of AI adoption are immediate and visible in ways that larger economies can absorb but we cannot. Capacity-building gaps affect us acutely. We lack the technical infrastructure, trained personnel, and institutional knowledge to participate meaningfully in global AI governance conversations, let alone implement sophisticated national frameworks. Half of SIDS have no official AI initiatives. We are building ours now, but without deliberate support, the gap between nations with AI capacity and those without will widen rather than close. The opportunity is that our scale allows rapid iteration and whole-of-nation coordination that larger countries cannot achieve. Our creative and cultural industries represent significant economic value, and AI systems trained on dominant-culture data risk marginalising local knowledge, languages, and traditions. The opportunity is that SIDS can pioneer governance frameworks protecting cultural data sovereignty that larger nations may later adopt.

Current AI governance discussions happen in forums where developing nations and SIDS have limited voice. These bodies produce frameworks that the rest of the world is expected to adopt without meaningful input into their design. The Dialogue, by bringing more than 100 countries onto equal footing, can ensure that governance reflects the needs and constraints of nations currently excluded from the room where decisions are made. The Dialogue can also facilitate structured exchange of implementation data, enabling countries to learn from each other rather than reinventing the wheel separately.

Regional bodies with AI mandates. These bodies understand local contexts and constraints and the Dialogue can create pathways for regional approaches to inform global standards. Technical standards organisations including ISO, IEEE, and the ITU, which are developing AI standards that will shape implementation regardless of policy frameworks. The Dialogue can ensure these technical processes remain connected to human rights and development priorities. Capacity-building programmes and technical assistance programmes. The Dialogue can identify gaps in current provision and coordinate resources toward underserved regions.

Governments should share implementation data and structured peer exchange sessions to enable practical learning across contexts. Private sector should contribute technical expertise and transparency about AI system capabilities and limitations. Civil society should represent communities most affected by AI deployment. Technical community should translate complex AI developments into accessible language for policymakers and provide independent assessment.

Small Island Developing States and Least Developed Countries lack the diplomatic capacity to participate consistently across multiple overlapping forums. When we do participate, delegation sizes are small and technical expertise stretched thin. Funded participation, simplified engagement pathways, and consolidated forums rather than proliferating mechanisms would increase our voice. Workers and labour organisations are discussed extensively in AI governance conversations but rarely present at the table. Those experiencing displacement, reskilling pressures, and changing workplace conditions have direct knowledge. Formal labour representation in Dialogue structures, not as observers but as participants, would help. Educators and students are implementing and experiencing AI in learning environments daily. Youth representation should extend to structured input into workforce and education working groups. Rural and informal economy workers in developing nations experience AI impacts differently from formal sector employees in urban centres, yet governance discussions default to formal employment frameworks. Deliberate outreach to organisations representing these communities would broaden the evidence base. unded participation covering travel, accommodation, and preparation time is essential.

If people feel heard and are given a voice they will participate. When people feel overwhelmed or like their views do not matter they do not. To make it fully inclusive under-represented groups need to be given a voice and actively shown their needs have a priority. Problem-based working sessions organised around specific shared challenges with structured peer exchange would give immediate value to participants. Implementation clinics where nations present actual governance challenges and receive input from peers and technical experts would allow collective problem-solving.

I lead the AI and Intelligence strand of the National Digital Transformation Strategy Task Force under the Office of the Premier. We are developing Cayman's national AI blueprint, bringing together government, industry, and civil society into a single coordinated strategy rather than fragmented initiatives. Small scale makes this possible. We can convene the entire ecosystem in one room. I co-chair the National AI Education Steering Group and have delivered AI governance training to Big 4 professional services firms operating locally. We are not waiting for curricula to arrive from elsewhere. We are building it here, tailored to our context. I run a monthly AI meet-up that now draws over 100 participants regularly. It is free, open to all, and community-driven. The agenda is shaped by what participants want to learn, not what institutions want to teach. This creates bottom-up demand for responsible AI adoption alongside top-down governance frameworks. I host a TV programme called The AI Wave, contribute to Forbes on AI governance, and provide commentary for BBC World Service. Accessible public communication is governance infrastructure. People cannot participate in decisions they do not understand. Through Oxford Saïd, I work alongside government ministers and digital transformation leads from the UAE, Greece, Singapore, and Malta who are writing their countries' AI strategies. What works elsewhere informs what we build here.