Ministers and senior officials from around the world used the third high-level governmental plenary of the UN Global Dialogue on AI Governance to outline national priorities for AI, while calling for stronger international cooperation to ensure AI benefits are shared more equitably. Although countries differed on regulatory approaches, participants broadly agreed that AI governance must be inclusive, human-centric and grounded in multilateral cooperation if it is to narrow rather than deepen global inequalities.
Throughout the session, speakers highlighted AI’s transformative potential for healthcare, education, agriculture and public services, while repeatedly warning that unequal access to computing power, infrastructure, talent and financing risks leaving many developing countries behind.
Europe pushes safety-by-design and evidence-based governance
Germany and the European Union placed safety, trust and evidence-based policymaking at the centre of their interventions.
Germany’s Federal Minister for Digital Transformation and Government Modernisation, Karsten Wildberger, described AI as ‘an entirely new paradigm’ developing at unprecedented speed and argued that governments must actively shape its future rather than react to it.
‘We must shape AI because otherwise AI will shape us,’ he said, urging countries to embed safety, security and respect for human values into AI systems from the outset instead of attempting to add safeguards later.
Wildberger also announced Germany’s new National AI Safety and Security Institute, which will evaluate advanced AI systems and contribute to international cooperation alongside industry, academia and civil society.
Representing the European Union, Director-General of DG CONNECT Roberto Viola similarly highlighted AI’s enormous promise, pointing to advances in biotechnology, drug discovery and robotics that could accelerate scientific progress and economic growth. At the same time, he warned that AI could also be used to manipulate children, attack critical infrastructure or amplify other societal risks if left without appropriate safeguards.
Viola stressed that governance should remain grounded in scientific evidence rather than political assumptions, praising the work of the Independent International Scientific Panel on AI as an important source of objective expertise for policymakers.
Developing countries call for ‘capacity before compliance’
If Europe focused on governance principles, developing countries focused on the practical barriers that prevent them from participating fully in the AI economy.
A recurring message throughout the plenary was that AI divides extend far beyond access to technology, encompassing shortages of computing power, electricity, broadband connectivity, quality datasets, skilled professionals and financial resources.
Indonesia’s Minister of Communications and Digital Affairs, Meutya Viada Hafid, argued that AI governance should support development rather than simply regulate risks. She introduced the principle of ‘capacity before compliance,’ warning that expecting countries with limited digital infrastructure to meet the same governance obligations as advanced AI economies would neither be realistic nor equitable.
Pakistan’s Minister of Information Technology and Telecommunication, Shaza Fatima Khawaja, similarly warned that the global ‘capability divide is real and it is widening.’ She urged countries to move beyond discussions of principles towards concrete investments in shared computing infrastructure, open-source models, regulatory sandboxes and a proposed global AI fund to help developing nations build sovereign AI capabilities.
Uganda highlighted that Africa currently possesses less than 1% of global AI computing capacity despite ambitious plans to use AI to support economic transformation, while Malawi described facing what it called an ‘impossible choice’ between accepting unacceptable risks or being left behind altogether.
Other speakers from Chad, Mozambique, Somalia and Mali echoed these concerns, arguing that AI governance should recognise different national circumstances while ensuring countries become active contributors to AI development rather than remaining dependent consumers of technologies designed elsewhere.
National strategies offer practical governance lessons
Alongside calls for greater international support, several governments presented national initiatives that they hope could contribute to future global governance models.
Thailand proposed serving as an international AI governance sandbox where global principles could be tested through practical implementation rather than remaining solely the subject of international discussions. Minister Chaichanok Chidchob warned that fragmented governance risks undermining trust itself and invited UN partners to develop scalable governance models through real-world experimentation.
Singapore shared lessons from its own AI governance experience, identifying reliable digital infrastructure, trusted access to high-quality data and strong public confidence as the three foundations of successful AI adoption. The country also highlighted its work on AI safety research and international technical standards.
Rwanda pointed to its national AI policy, newly established AI agency and broader Africa Declaration on Artificial Intelligence adopted by dozens of African countries as examples of regional cooperation designed to harmonise governance approaches.
Other governments showcased complementary initiatives. Chile proposed creating a multilateral network of AI sandboxes operating under common rules, while the Maldives argued that AI can only deliver meaningful public value when built on secure digital public infrastructure, trusted data systems and clear accountability mechanisms. Zimbabwe highlighted its recently launched National Artificial Intelligence Strategy and called for an international AI capacity-building fund alongside mutual recognition of AI ethics standards.
Interoperability emerges as a common governance goal
Although countries presented diverse national strategies, many converged around the idea that AI governance frameworks should be interoperable rather than identical.
Ireland argued that AI governance requires a shared international language built around transparency, accountability and human oversight, while the Netherlands described interoperability, not a single global rulebook, as the organising principle for the next phase of AI governance. Different jurisdictions, Dutch representatives argued, should be able to develop compatible systems based on common standards without sacrificing national flexibility.
Thailand echoed this concern, warning that fragmented governance could ultimately fragment trust itself. Indonesia similarly argued that trustworthy AI depends on interoperability rather than uniformity, while Singapore stressed the importance of internationally recognised technical standards that enable cooperation across borders.
This emphasis on compatibility reflected broader concerns that increasingly divergent national AI regulations could create unnecessary barriers to innovation, investment and international collaboration.
Cooperation remains the defining challenge
The closing interventions highlighted both the broad consensus and the remaining differences over how global AI governance should evolve.
India called on countries to choose ‘consensus over conflict’ before technological progress outpaces diplomacy, arguing that AI governance should provide every nation with a meaningful voice regardless of its level of technological development. Senegal promoted the Global Network for Cooperation on AI Capacity Building and welcomed proposals for a global AI fund to strengthen infrastructure and expertise in developing countries. Bahrain announced exploratory work on a potential global AI treaty initiative, while the United Kingdom highlighted partnerships helping countries across Africa develop local-language AI tools and strengthen domestic AI ecosystems.
The United States, meanwhile, emphasised voluntary cooperation with industry and a pro-innovation regulatory environment rather than binding international rules, illustrating one of the clearest policy differences to emerge during the session.
Despite these differing approaches, participants broadly agreed that AI’s future cannot be shaped by any country acting alone. As ministers repeatedly argued, the success of AI governance will ultimately be measured not by the sophistication of frontier models, but by whether countries of every size and level of development can safely use AI to improve the lives of their citizens.
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