Tech Hive Advisory

Success should be measured against what the Dialogue uniquely offers, universal participation within a UN mandate, rather than against the outputs of faster, narrower fora already active in AI governance. Four outcomes would constitute a credible first session. First, substantive parity of contribution. Success requires that jurisdictions outside the current centres of AI development shape the agenda, not only populate the room. This means African, Latin American, and Asian regulators co-chairing thematic discussions, drafting inputs to the Co-Chairs' summary, and featuring in the Scientific Panel's first report as sources of governance innovation, not case studies of adoption challenges. Second, a shift from textual to procedural interoperability. The Dialogue should move the international conversation beyond the assumption that harmonisation means identical legal text. A successful first session would establish mutual recognition of conformity assessments, common incident-reporting taxonomies, and interoperable audit methodologies as the working definition of interoperability, the standard most likely to include jurisdictions unable to participate in bespoke bilateral arrangements. Third, implementation capacity treated as first-order. Transparency, accountability, and human oversight obligations are meaningless where supervisory authorities lack technical staff, audit powers, or budgetary independence. The Dialogue succeeds if its outputs recognise implementation infrastructure as a governance question, not a capacity-building afterthought, and commission the Scientific Panel to assess supervisory capacity alongside model capability. Fourth, technology-agnostic and outcome-based framing in the Co-Chairs' summary. Prescriptive references to specific model classes or compliance tools will date the output within the Dialogue's own 2026 to 2027 cycle and transplant poorly across jurisdictions. Framing that specifies harms to be prevented, not tools to be mandated, travels. Success is a first session that makes the Dialogue the forum where global AI governance becomes genuinely global, procedurally, substantively, and institutionally, rather than a ratification space for frameworks settled elsewhere.

• Safe, secure and trustworthy AI
• AI capacity-building
• Transparency, accountability, and human oversight
• Social, economic, ethical, cultural, linguistic and technical implications of AI

Tech Hive Advisory's selection reflects the four areas where the gap between stated principle and operational reality is widest in the jurisdictions we advise across Africa and the Middle East, and where Dialogue-level action can shift that reality. Safe, secure and trustworthy AI is a priority because safety obligations are being written into national laws faster than the supervisory apparatus required to enforce them can be built. Without international alignment on what safety evaluation, red-teaming, and conformity assessment actually require in practice, jurisdictions with thin assessor capacity face a choice between unenforceable rules and the adoption of foreign rulebooks. Neither outcome is safe. AI capacity-building is a priority because the dominant framing treats capacity as downstream of governance, something to be delivered after frameworks are set. Our client engagements, including work with data protection authorities implementing multi-year supervisory programmes, show the opposite sequence: supervisory, audit, and technical assessment capacity must be designed into governance architectures from the outset, not retrofitted. The Dialogue can anchor this reframing. Social, economic, ethical, cultural, linguistic, and technical implications of AI matter because AI systems deployed in African markets are trained predominantly on data that does not reflect the languages, contexts, or populations to which they are applied. This is not a diversity concern; it is a systems reliability and rights protection concern. The Dialogue should treat linguistic and contextual representativeness as a technical governance question, not a cultural one. Transparency, accountability, and human oversight are a priority because a right that cannot be vindicated is not a right. Oversight obligations presuppose institutional infrastructure, independent audit ecosystems, rights-based redress pathways, and technically competent supervisors, that remains underdeveloped in most jurisdictions where AI systems are scaling fastest. The Dialogue succeeds on this cluster only if it addresses the infrastructure, not only the obligation.

Compute access and sovereign infrastructure. AI governance conversations increasingly assume access to compute that most jurisdictions do not have. The distribution of high-performance compute, the terms on which it is accessed, and the dependencies this creates for national AI strategies are governance questions, not only industrial ones. The Dialogue should treat compute as shared digital infrastructure, with access arrangements that prevent the emergence of permanent technical dependency for the majority of UN member states. Data governance as foundational to AI governance. AI systems inherit the legal basis, quality, and provenance of their training data. Yet AI governance instruments often proceed as though data protection frameworks can be bolted on later. Cross-border data flow rules, lawful basis for training data use, and data subject rights in automated decision-making sit at the foundation of every other thematic cluster. The Dialogue should make this dependency explicit rather than treat data governance as a separate silo. Public sector AI and procurement leverage. Governments are among the largest deployers of AI in areas that most directly affect rights: social protection, immigration, policing, education. Procurement standards, impact assessment obligations, and redress mechanisms for public-sector AI are where governance commitments meet citizens first. This dimension is underrepresented in the current thematic framing. Accountability across the AI value chain. Current frameworks distribute obligations unevenly along the development, deployment, and integration chain, often leaving deployers in lower-capacity jurisdictions to carry responsibility for design decisions made elsewhere. The Dialogue should surface value-chain accountability, including foundation model developer obligations toward downstream deployers, as a distinct cross-cutting question. Addressing these would strengthen coherence across the four thematic clusters rather than fragment the agenda.

Challenges Supervisory authorities mandated to oversee AI systems under data protection and emerging AI laws operate without the technical assessors, audit powers, or budgetary independence the mandate presupposes. This framework imposes obligations on automated decision-making that currently outpace the institutional capacity available to enforce them. Foreign AI rulebooks are being considered for wholesale adoption in several jurisdictions, importing conformity assessment infrastructures that do not exist locally and cannot be stood up within legislative timelines. Foundation models deployed across African markets are trained on data that underrepresent African languages, contexts, and populations, leading to failures in system reliability and rights protection in sectors including credit scoring, identity verification, and content moderation. Cross-border enforcement remains fragmented: a harm caused by a system developed in one jurisdiction, deployed in a second, and affecting users in a third cannot currently be addressed through any coherent accountability pathway. Opportunities The African Union Continental AI Strategy and Smart Africa's data governance work provide regional coordination infrastructure that the Dialogue can build on rather than duplicate. National regulators, including the Nigeria Data Protection Commission, are investing in multi-year supervisory capacity programmes that, if supported and connected internationally, can become models for implementation infrastructure in other regions.

The Dialogue's unique role is structural, not substantive. Other fora, including the OECD AI Principles work, the G7 Hiroshima Process, the Council of Europe Framework Convention, and the AI Safety Institute network, already generate substantive outputs. None offers universal UN membership. The Dialogue should use this structural position to do four things no other forum can. Legitimise convergence. Principles, standards, and taxonomies developed in narrower fora acquire international legitimacy when they are surfaced, tested, and reflected in a universal UN process. The Dialogue can serve as the legitimation layer that connects technical work done elsewhere to the broader international community without duplicating it. Correct representational asymmetry. The Dialogue is the first AI governance forum where jurisdictions currently underrepresented in standard-setting can shape agendas as peers rather than observers. Its success depends on actively using this position: co-chair arrangements, Scientific Panel composition, and thematic discussion design should structurally embed contributions from African, Latin American, Asian, and Small Island Developing States participants. Translate between registers. AI governance currently operates in separate registers: technical standards bodies, human rights institutions, trade fora, and development agencies rarely converge. The Dialogue can translate across these registers, ensuring that technical standards are tested against human rights obligations, that capacity-building commitments are connected to governance architectures, and that cross-border issues are addressed coherently rather than within single-register silos. Anchor continuity. Two sessions across 2026 and 2027 create the possibility of sustained international attention to implementation, not only the principle. The Dialogue's distinctive contribution would be to hold international cooperation to account between sessions, tracking whether commitments translate into practice in the jurisdictions that most need them. The Dialogue's added value is its position, not its pace. It should use that position deliberately.

The Dialogue should connect with existing work rather than duplicate it, and concentrate its added value on the gaps these initiatives leave. At the UN system level. The UNESCO Recommendation on the Ethics of AI and its Readiness Assessment Methodology provide an operational baseline for AI governance maturity that the Dialogue can build on, particularly for jurisdictions without national frameworks. The ITU AI for Good platform, where the first session will be held, offers reach within the technical community. The Office of the High Commissioner for Human Rights' work on AI and human rights anchors the rights-based analysis required by the thematic clusters. At the regional level. The African Union Continental AI Strategy, Smart Africa's data governance and AI workstreams, the Association of African Data Protection Authorities, and the Network of African Data Protection Authorities provide regional coordination infrastructure for the African continent. The Council of Europe Framework Convention on AI, the ASEAN Guide on AI Governance, and CAF's work in Latin America offer parallel regional anchors. The Dialogue should treat these as peer inputs rather than secondary references. At the technical and standards level. The OECD AI Principles and GPAI work, the AI Safety Institute network, ISO/IEC JTC 1/SC 42 standards work, and NIST's AI Risk Management Framework generate substantive technical outputs. The Council of Europe Framework Convention is the first binding instrument in force. The Dialogue's contribution lies in what these initiatives individually cannot deliver: universal participation, cross-register translation, and sustained attention to implementation infrastructure. Specifically, it can commission assessments of supervisory and enforcement capacity that standards bodies do not produce; it can connect capacity-building funding architectures to governance commitments, a link currently missing; and it can bring regional instruments into international visibility they currently lack, strengthening procedural interoperability among them.

Different stakeholders contribute different inputs, and the Dialogue's format should reflect that rather than treat all stakeholders as interchangeable participants. Member States contribute mandate, legitimacy, and the authority to translate Dialogue outputs into domestic law and cross-border cooperation. The current high-level segment format supports this. Statements delivered on behalf of regional groups, where feasible, should be encouraged to surface convergence rather than duplicate national positions. National regulators and supervisory authorities contribute implementation experience that member-state delegations often lack. They should be structurally embedded as thematic co-chairs and scene-setters, not only as observers within member-state delegations. Practical experience in supervising automated decision-making, cross-border enforcement, and algorithmic auditing is the evidence base the Dialogue most needs. Technical community and standards bodies contribute operational detail on what safety, interoperability, and assessment actually require. The Dialogue should draw on ISO/IEC, IEEE, and the AI Safety Institute network without duplicating their work. Civil society and affected communities contribute evidence of harm, rights-based analysis, and accountability demands that technical and governmental actors alone will not surface. Their participation should include, but not be limited to, recognised international NGOs; national and grassroots organisations working with affected populations should be actively resourced to participate. Academia and independent researchers contribute the peer-reviewed evidence that the Scientific Panel will depend on. Industry contributes deployment experience and must be engaged without being allowed to set the agenda. Structural recommendations. Thematic discussions should be co-chaired by a member state and a non-governmental stakeholder, with at least one co-chair from an underrepresented region per cluster. Written submissions should remain open continuously between sessions. Breakout formats should include a structured recording of minority positions, so that dissent is preserved in the Co-Chairs' summary rather than smoothed out.

Four categories of voice remain structurally underrepresented in global AI governance discussions. National regulators from under-resourced jurisdictions. Data protection authorities, competition regulators, and emerging AI oversight bodies in African, Latin American, South Asian, and Small Island Developing States jurisdictions rarely appear in international AI governance fora, despite bearing the practical enforcement burden. Inclusion requires more than invitation: travel funding, language support, and preparatory engagement should be resourced by the Dialogue's secretariat, not left to participating entities. Workers and affected communities. AI systems reshape labour conditions, welfare entitlements, immigration decisions, and platform economies. The workers and claimants affected by these systems are almost entirely absent from governance discussions dominated by developers, regulators, and civil society intermediaries. The Dialogue should resource structured consultation with affected communities through partnerships with trade unions, workers' organisations, and community-based groups, with inputs surfaced in thematic discussions. Indigenous and minority-language communities. AI systems underperform on languages and contexts outside the dominant training data. Indigenous peoples, speakers of low-resource languages, and linguistic minorities have direct governance interests in data sovereignty, consent frameworks for training data, and model deployment in their languages. Their inclusion should be coordinated with existing UN mechanisms, including the Permanent Forum on Indigenous Issues. Practitioners working at the implementation layer. Data protection officers, public-sector AI implementers, clinical AI deployers, and frontline compliance staff hold operational knowledge that international discussions rarely access. Structured practitioner tracks, distinct from industry representation, would surface this evidence. Mechanisms for inclusion. Funding participation is the first condition. The second is designing agenda items around underrepresented perspectives, rather than inviting them to comment on agendas set elsewhere. Recording inputs in the Co-Chairs' summary with attribution, so that inclusion translates into visible influence, is the third.

Innovation in engagement format should serve substance, not replace it. Four formats would add value to the current structure. Implementation clinics. Short, practitioner-led sessions during thematic breakouts where a regulator or deployer presents a live governance problem, and participants contribute operational responses in structured time. This surfaces implementation evidence that panel formats rarely access and gives under-resourced regulators a specific forum to seek peer input. Pre-session regional consultations, reported into plenary. Structured regional consultations in the weeks before the Dialogue, convened by regional economic communities or regional organisations, whose outputs are presented into the first-day plenary. This makes regional convergence visible to the full Dialogue rather than assumed, and anchors thematic discussions in regional evidence. Rotating scribes with attribution. Thematic discussions typically produce summaries shaped by the chair's framing. Rotating scribe roles across regions and stakeholder groups, with contributions attributed in the public record, would distribute framing authority and make the evidence base of the Co-Chairs' summary traceable. Inter-sessional working tracks. A two-day annual Dialogue cannot carry the weight of sustained international cooperation on its own. Time-bounded inter-sessional working tracks between the 2026 and 2027 sessions, each addressing one cross-cutting issue (for example, supervisory capacity assessment, cross-border incident reporting, or data governance for training) would convert Dialogue outputs into continuous work streams. These should report into the 2027 session with visible deliverables. Structured minority-position recording. Dialogues at UN scale tend toward consensus framing. Designing in a mechanism for recording substantive minority positions in the Co-Chairs' summary, with attribution where participants agree, preserves disagreement as part of the evidence base. This protects the Dialogue from false-consensus risk and makes subsequent cycles more honest. Format innovation should be judged by whether it makes underrepresented inputs visible and traceable.

Publicly accessible compliance tools Regional data protection authority networks Supervisory capacity programmes anchored in multi-year frameworks Regulator-led codes of conduct and industry frameworks Risk-tiered and sector-specific regulation under outcome-based frameworks