What happened
If Cluster 1 asked how AI’s benefits reach people, Cluster 2 asked what it takes to close the gaps. UNDP’s Robert Opp named two divides at once: a divide of access (affordable compute, capacity and skills) and a newer divide of adoption: AI already entering countries through procurement and vendors “faster than institutions can keep pace.” Bridging divides, UNDRR’s Loretta Hieber Girardet added, “is more than expanding access”: it is the capacity to develop, adapt, evaluate and govern AI locally, because AI “cannot substitute for strong institutions, trusted data systems, local expertise.”
Knowledge, not just data
Co-chair Jovan Kurbalija of DiploFoundation reframed the stakes around knowledge rather than data: AI is built on “the knowledge of all people who lived before us — from Shakespeare to Dostoevsky to the great Ubuntu oral tradition of Africa,” and the room itself would generate new knowledge worth carrying to “communities and countries that are waiting for answers.” Senegal’s digital minister, co-chairing, tied it to national strategy (a “New Deal Technology” built on digital skills, infrastructure and public platforms) and to a shared responsibility to make AI “a driver of shared prosperity rather than a source of deeper inequality.”
UNESCO on capacity: the fireside
In conversation with El Salvador’s Vice President Félix Ulloa, UNESCO Director-General Khaled El-Enany laid out the agency’s capacity-building push, the anchor of the “bridging” agenda:
- Its 2021 Recommendation on the Ethics of AI (adopted by 194 member states), now moving “from principles to implementation.”
- Training for 50,000+ civil servants and judicial actors across 192 countries; AI competency frameworks already used in 60+ countries.
- A new International Institute for STEM education (I-STEM), launched in Shanghai, prioritising women and the global South; a plan to train 1 million teachers by 2028 with the Varkey Foundation, against a projected shortfall of 44 million teachers by 2030.
- Language and cultural inclusion (e.g. a Kiswahili AI dictionary) so that a handful of dominant languages do not crowd out the rest.
El Salvador, for its part, pointed to its national AI agency and law as its own foundation for “responsible AI”: efficiency in public services without substituting for human judgement.
Why it matters for the SDGs
This cluster is the AI divide made operational, the heart of SDG 10 and SDG 17 (capacity building, technology transfer, and the digital and data foundations without which AI cannot serve development). Its through-line is a caution SDGCounting shares: deploying tools is not the goal; the goal is countries able to inspect, adapt and govern the systems that increasingly run their public services, and the trusted data systems needed to measure whether any of it is working.
Watch & read
- UN Web TV, full recording of Thematic Cluster 2 (6 July 2026, 3h31m).
- Full Global Dialogue coverage.
Quotations are lightly edited from an automated (Otter.ai) transcript of the UN Web TV recording and should be read as close paraphrase; names and titles were reconciled to public records and reflect roles at the time. Senegal’s co-chair is given by role, as the transcript did not render the name reliably.