The new UN AI governance blueprint matters profoundly for small island states in the Pacific because it is one of the first global processes that explicitly recognizes that AI will deepen existing inequalities unless governance is inclusive, evidence-based, and designed with vulnerable communities at the center.
The UN’s new AI governance push
In late June 2026, the UN launched the first global, independent scientific assessment of AI’s opportunities, risks and impacts, led by a panel of 40 experts across regions. The assessment warns that AI capabilities are outpacing both scientific understanding and governments’ ability to adapt, and that current safeguards cannot keep pace with rapidly advancing agentic systems.
This scientific report is designed to feed directly into the UN’s emerging governance architecture and dialogues, including the Global Dialogue on AI Governance in Geneva and follow-up to the earlier “Governing AI for Humanity” recommendations from the Secretary-General’s High-level Advisory Body on AI. That advisory body called for a globally inclusive and distributed architecture for AI governance, with international cooperation and new, light institutional mechanisms that can keep up with AI’s evolution.
Why Pacific small island states are uniquely exposed
The panel’s findings highlight that AI adoption is accelerating but uneven, with access and usage lagging in the global South while compute power and leading models are highly concentrated in the United States, China, and a handful of companies. For Pacific small island developing states (SIDS), this concentration amplifies long-standing structural vulnerabilities: limited technical capacity, dependence on external digital infrastructure, and exposure to climate and economic shocks.
The UN assessment notes that AI’s benefits tend to land where institutions, skills, and data already exist, while elsewhere the same systems can displace workers, widen inequality, and leave communities dependent on technologies built without them in mind. That description maps closely onto Pacific realities, where governments are already stretched by climate change, debt, and ocean governance, and lack robust AI policy frameworks or regulatory agencies.
Oceans, climate, and AI: a story from Midway
Across the Pacific, conservation teams are already experimenting with AI to manage vast ocean spaces that are impossible to monitor with traditional methods alone. At Kuaihelani (Midway Atoll) in Papahānaumokuākea Marine National Monument, drones and machine learning are being used to survey seabird colonies across hundreds of thousands of square miles of protected ocean, dramatically reducing the time and cost of manual field surveys.
Researchers stitch drone imagery into detailed maps, then apply AI tools to count albatross and other seabirds, distinguish breeding birds from nonbreeding “walkers,” and analyze habitat conditions. The long-term goal is to develop practical guidelines that can be applied across Pacific island systems, so small teams can manage fragile ecosystems at scale—from turtles and seals to vegetation changes and invasive species—even as climate impacts accelerate.
This is a hopeful ocean story: AI becomes a canoe, not a wave—an enabling tool that helps Pacific guardians read changing seas and protect life. But the same technologies could be repurposed for high-resolution surveillance of coastal communities, militarization of ocean spaces, or automated resource extraction decisions far from local scrutiny. That dual-use reality is precisely why the UN’s push for robust, rights-respecting governance is vital for the region.
Governance gaps that matter in the Pacific
The UN panel identifies multiple areas where current AI governance instruments—ethics guidelines, voluntary frameworks, corporate policies—are fragmented, concentrated among a few corporations, and rarely measure real-world effectiveness for affected communities. For Pacific SIDS, this fragmentation is dangerous because decisions about data, models, and infrastructure are often made elsewhere but implemented locally.
Several specific gaps are particularly relevant:
- Lack of guarantees of control:
The panel finds no scientific guarantee that AI agent systems will not violate instructions, and notes accumulating evidence of systems that do. Deploying such systems for ocean surveillance, disaster response, or public services without robust oversight could introduce opaque failures that small administrations cannot easily investigate or remedy. - Unequal access to infrastructure:
The report notes that the U.S. holds about 75% of compute power among the top 500 AI supercomputers, with China at about 15%, and that these countries’ firms develop almost all leading general-purpose models. Pacific states are therefore “downstream” users, reliant on platforms whose design logic, data sources, and risk assumptions are shaped elsewhere. - Disproportionate harms:
The panel emphasizes that many AI harms—deception, disinformation, labour displacement, biased systems—fall disproportionately on already disadvantaged populations. Pacific communities are already on the front lines of climate displacement, fisheries changes, and debt stress; adding opaque algorithmic decisions about aid allocation, insurance, or visas could deepen those pressures. - Inclusion mechanisms: Pacific seats at the AI table
The UN’s governance architecture is starting to recognize these imbalances and build concrete inclusion mechanisms. A support proposal for the Global Dialogue on AI Governance, funded through the Digital Cooperation Fund’s AI Cooperation Window, explicitly prioritizes travel support for delegates from Least Developed Countries, Landlocked Developing Countries, and Small Island Developing States.
Under this proposal, governments and other stakeholders from developing countries can apply for direct travel or financial support, with priority given to those demonstrating interest in AI governance and belonging to underrepresented groups. The aim is not just attendance but meaningful participation, with regional, gender, and age balance and transparent disclosure of all contributions and supported travelers.
For Pacific SIDS, these mechanisms are more than logistics. They are an opportunity to bring ocean governance experience—MPAs, deep-sea mining debates, traditional stewardship systems—into global AI conversations that have been dominated by industrial and security narratives. Without Pacific voices, global rules risk overlooking how AI interacts with marine sovereignty, blue economy ambitions, and indigenous rights.
AI for ocean stewardship, on Pacific terms
Existing AI deployments in Pacific ocean conservation show both the promise and the governance questions. The Australian Institute of Marine Science’s ReefCloud platform, for example, uses open-source AI to automate coral reef monitoring across Micronesia, Melanesia, and Polynesia, standardizing data and producing automated reports that inform policymakers.
ReefCloud integrates fish population data and other ecological indicators, helping conservation practitioners deepen understanding of reef resources and refine management strategies in line with regional action plans like the Pacific Coral Reef Action Plan 2021–2030. This is a case where AI systems are explicitly designed to deliver public value and actionable science, aligning with calls from a UNU–ADB–UN report that openness must be paired with accountability and safeguards to make AI true digital public goods.
Yet even “AI for good” projects carry governance questions: who owns the data, who decides model priorities, how are local communities consulted, and what protections exist against repurposing tools for extractive agendas? The UN’s governance blueprint, with its emphasis on human rights, institutional capacity, and globally inclusive architecture, offers a framework Pacific states can use to demand answers and shape conditions for AI use in their waters.
AI, mental health, and cultural integrity
The UN assessment also documents harms that may be less visible in policy debates but are deeply relevant to small communities: sycophantic AI behaviours that reinforce users’ existing beliefs regardless of accuracy, linked to severe mental health incidents and documented deaths; and AI systems used in cyberattacks, fraud, and disinformation.
In Pacific SIDS, where online connectivity is rapidly expanding but digital literacy and mental health services are often under-resourced, these risks intersect with cultural integrity. Generative systems trained mostly on non-Pacific data may misrepresent or commodify indigenous stories, while persuasive AI tools could be weaponized to influence domestic politics, resource negotiations, or community debates about ocean uses.
UN governance proposals that foreground human rights, child safety, and democracy, and that call for agile and adaptive mechanisms to track real-world impacts, are therefore directly relevant to Pacific efforts to safeguard language, culture, and community resilience in the AI era.
From governance text to Pacific practice
For Pacific SIDS, translating the UN AI governance architecture into practice could involve several concrete moves:
- Embedding AI within existing ocean governance frameworks—like marine protected area management plans, fisheries agreements, and climate adaptation strategies—rather than treating it as a separate tech policy silo.
- Using UN-supported dialogues and funds to secure resources for national AI strategies that center indigenous ocean stewardship, blue economy priorities, and data sovereignty, instead of adopting off-the-shelf frameworks designed for large economies.
- Advocating that global AI standards include specific provisions on environmental impacts, ocean monitoring, and deep-sea mining decision-support systems, so that AI is not used to accelerate extraction without robust ecological and cultural safeguards.
- Building regional hubs of expertise—through collaborations like ReefCloud and seabird monitoring projects—to ensure Pacific practitioners are co-authors, not just data providers, in AI-based ocean science.
A closing ocean image.
Imagine a dawn survey flight over Kuaihelani, the drone’s small buzz barely audible over the surf as it traces the perimeter of an albatross colony. Below, thousands of birds settle into the wind, their presence a living indicator of the health of the Pacific’s great gyres and feeding grounds.
Back on shore, a Pacific conservation team uploads the imagery into an AI system tuned to these islands—trained not just on pixels but on decades of field knowledge, local names, and seasonal rhythms. The model flags shifts in nesting density, subtle changes in vegetation, and signs of invasive species creeping in from the edge, translating gigabytes of data into a briefing that can reach a village council, a regional agency, and a UN meeting room in Geneva.
UN AI governance, at its best, is about making sure that this chain—from drone to model to decision—is accountable to the people who live with the consequences: Pacific islanders whose futures are tied to the ocean’s moods and whose stewardship traditions offer a different way of imagining intelligence itself.
For more information, check out the UN article and video.
