Research ArticleThe inaugural session of the United Nations Global Dialogue on AI Governance, convened in Geneva on 6–7 July 2026, was the first annual session of a universal UN platform for discussion of international cooperation on AI governance. This paper uses the Geneva Dialogue not as an event to be reported but as a diagnostic case through which to examine a deeper political question: who actually possesses the power to govern artificial intelligence? Drawing on official United Nations documents, the preliminary report of the Independent International Scientific Panel on Artificial Intelligence, and contemporary institutional and statistical evidence available before the publication deadline, the analysis distinguishes seven analytically separate dimensions of governing power—participation, representation, influence, agenda-setting, decision-making, implementation capacity and technological power—and argues that international AI-governance practice and commentary can conflate procedural participation with substantive governing agency. The paper develops an original Advocacy Unified Network (AUN) framework of “AI Governance Agency,” understood as a bundle of epistemic, normative, standard-setting, infrastructural, regulatory, implementation and accountability capabilities. It then maps the global distribution of these capabilities across compute, semiconductors, data, models, cloud, talent, standards, financing and regulatory capacity, and tests the proposition that universal participation does not automatically produce universal governing agency. The findings indicate that the Dialogue’s universalism is procedurally substantial but does not by itself redistribute the capabilities that make a seat meaningful. The paper concludes with concrete recommendations at global, regional, national, technical and civil-society levels, and proposes an institutional test for success that the Dialogue must meet if it is to become more than another layer in an already fragmented governance landscape.
Research ArticleAuthors:Victor Samuel, Francisca Oliviera The 2026 High-Level Political Forum reviewed SDG 9 (Industry, Innovation and Infrastructure) and SDG 17 (Partnerships for the Goals) at a moment when only 36 per cent of Sustainable Development Goal targets are on track and the field is saturated with progress diagnoses. This report argues that the scarce and valued contribution now is not another assessment of how far the world has fallen short but usable implementation guidance that helps countries and civil-society organisations translate means-of-implementation commitments into operational delivery. Drawing on the outcomes of the 2026 ministerial declaration, the Financing for Sustainable Development Report 2026, and the Sevilla Commitment adopted at FfD4, the report identifies the specific implementation gaps in the finance, technology, capacity-building, and partnership domains that constrain SDG 9 and 17 acceleration. It then introduces a practical framework, the Acceleration Delivery Cycle, and demonstrates how two digital tools, the SDG Impact Mapper and AdvocacyOS, both components of the AUN Digital ecosystem, can be deployed to close the gap between MoI commitments and on-the-ground results. The report concludes with a Partnership Effectiveness Matrix that maps the most common weaknesses of multi-stakeholder partnerships for the Goals against toolkit-enabled responses, offering a concrete contribution to the acceleration agenda that is actionable rather than merely analytical.
Research ArticleThe adoption of the Pact for the Future at the September 2024 Summit of the Future has produced a major multilateral governance reform mandate, encompassing twenty actions on Security Council reform, General Assembly revitalisation, international financial architecture redesign, and strengthened cooperation with emerging technologies. Yet the Pact's adoption also exposes a structural tension that conventional reform debates struggle to address: the gap between the complexity, velocity and interdependence of contemporary global challenges and the rigidity of institutional architectures designed for earlier historical conditions. This article, the foundational theory contribution to the Adaptive Global Governance (AGG) research programme, argues that governance adaptiveness constitutes a distinct analytical construct that existing scholarship on representation, effectiveness and resilience does not adequately capture. Synthesising complex adaptive systems theory, adaptive governance scholarship from socio-ecological systems research, regime complexity literature and networked multilateralism, the article develops a four-capacity conceptual architecture — anticipatory, responsive, inclusive and learning — that together constitute the adaptive capacity of a governance system. It then introduces the Governance Adaptiveness Index (GAI), a provisional composite measurement architecture that operationalises these capacities through indicator selection, normalisation, scoring, weighting and aggregation rules made transparent for subsequent validation. The article illustrates the framework's potential diagnostic utility by mapping the Multilateralism Index 2024 onto the four capacities, revealing a distinctive pattern in which state participation has remained robust while performance has declined across every domain and inclusivity has broadly improved. The article outlines a multi-phase validation pathway, addresses conceptual, methodological and political-economy limitations, and identifies normative trade-offs between adaptiveness and accountability. The article does not claim that the GAI has been empirically validated; it presents a conceptual and provisional methodological foundation for the AGG programme's subsequent calibration, case-study and policy phases.
Research ArticleInternational commitment failure is frequently diagnosed as a deficit of political will. This paper proposes a Governance Gap Theory, demonstrating that implementation failure in international agreements stems systematically from institutional capacity constraints rather than mere political recalcitrance. By examining multi-domain compliance data across environmental, trade, and security governance, we articulate a dual-level capacity model that reconciles commitment intent with operational delivery.
Research ArticleAs the international community approaches the midpoint of the 2030 Agenda for Sustainable Development, available evidence indicates that progress on the Sustainable Development Goals (SDGs) is seriously off track. While financing deficits, pandemic disruption, and geopolitical instability are widely recognised obstacles, this paper argues that a further, less systematically examined condition also shapes implementation: the gap between formal SDG commitments and the governance arrangements required to deliver them. The paper defines the governance gap as the measurable distance between the institutional, procedural, and normative requirements for effective SDG implementation, as articulated in the 2030 Agenda, and the actual state of governance arrangements and practices in a given jurisdiction. It then develops the Governance Gap Assessment Matrix (GGAM), a structured framework comprising five dimensions—normative, institutional, operational, data and accountability, and participatory—assessed across three levels: formal, functional, and outcome-linked. For each of the resulting fifteen cells, the paper proposes indicators, operational definitions, evidence sources, and provisional scoring anchors, and it introduces two derived measures: a Governance Readiness Score (higher values indicate stronger readiness) and a Governance Gap Score (its transparent complement). The paper positions the GGAM against existing instruments, including the Worldwide Governance Indicators, the OECD Policy Coherence for Sustainable Development framework, the SDG 16 monitoring architecture, and the VNR Quality Index, and illustrates its potential application through a qualitative synthesis of evidence from the Voluntary National Review (VNR) process and related literature. The paper is explicitly positioned as a conceptual and foundational framework rather than a systematic empirical study; the illustrative evidence is used to demonstrate analytical utility, not to establish statistically representative findings. Limitations concerning measurement subjectivity, data availability, contextual generalisability, and causal inference are discussed. The paper concludes that the GGAM offers a transparent, replicable scaffold for subsequent empirical validation and for applied governance-gap assessment by governments, civil society, and international monitoring bodies, and that governance is a cross-cutting enabling condition that can substantially influence whether financial, technical, and institutional resources translate into effective SDG implementation.
Research ArticleAuthors:Francisca Oliviera, Priyasa Banerjee, Victor Samuel
Advocacy Unified Network (AUN) | Opus Publica
Research ArticleThis article develops the Global Governance Readiness Index (GGRI) as a composite measurement framework for assessing the institutional capacity of states to translate accepted international commitments into implementation. The framework distinguishes readiness from realised performance and from perception-based governance measures, and organises readiness into five pillars: Legal-Institutional Framework, Administrative Capacity, Fiscal Readiness, Compliance Infrastructure, and Stakeholder Engagement. The design is grounded in established work on state capacity, institutional quality, international-compliance theory, and composite-indicator construction. To preserve historical integrity, the manuscript uses an explicit evidence cutoff of 15 March 2023 and does not incorporate publications or datasets released after that date. The article specifies the proposed indicators, normalisation, weighting, aggregation, missing-data and validation procedures and defines a transparent pilot design. Numerical pilot results and predictive-validity claims are not presented as established findings here because the underlying country-level dataset, reproducible code, and complete technical appendix are not part of the supplied manuscript. The GGRI is therefore presented as a methodological research framework and a pre-specified empirical design, not as a completed predictive index whose performance has already been demonstrated.
