ACG - Abdin's Consultancy Group

In my view, the first Global Dialogue on AI Governance will be successful if it delivers outcomes that are not only representative in discussion, but actionable in practice. First, it should produce a clear and balanced summary of shared priorities across the main areas already identified in the preparatory process: safe and trustworthy AI, capacity-building, interoperability, human rights, transparency, accountability, and open-source ecosystems. Second, it should lead to a practical framework for supporting developing countries, focused on AI capacity, institutional readiness, access to infrastructure, and local talent development. Success should mean giving stronger voice to developing countries and ensuring that global AI governance is shaped not only by advanced economies, but also by the realities and needs of the Global South. Third, the Dialogue should create a mechanism for continuity beyond the event itself. This could include multi-stakeholder working groups, follow-up consultations, and a platform for tracking progress on priority themes and partnerships. A successful first Dialogue should be the start of an ongoing process, not a one-time exchange. Fourth, it should surface practical examples and pilot partnerships that show how AI governance can support real progress in sectors such as education, water, healthcare, and public service delivery, especially in emerging markets. Finally, success would mean capturing the collective intelligence of the Dialogue in a usable way. This includes synthesising stakeholder inputs into a cohesive reference point that policymakers, experts, and institutions can build on in future rounds. Ultimately, success is when the Dialogue moves from broad alignment on principles to credible pathways for collaborative implementation.

AI capacity-building;Interoperability of governance approaches;Transparency, accountability, and human oversight;Safe, secure and trustworthy AI;

Our priorities for urgent action and active engagement are the following four areas, as they are the most critical for turning AI governance into practical, inclusive, and scalable action, particularly in developing economies. 1. AI capacity-building This is the most urgent priority from our perspective. Many countries and institutions still face major gaps in AI literacy, institutional readiness, technical skills, and access to enabling infrastructure. At ACG, this directly aligns with our work in executive AI literacy, workforce readiness, and cross-sector transformation, including initiatives such as Leadership X: AI for Senior Executives. Capacity-building is essential if developing countries are to move from participation in the dialogue to meaningful implementation. 2. Safe, secure and trustworthy AI Trust is foundational to adoption. We prioritize this area because governments, enterprises, and institutions need practical ways to assess risk, strengthen safeguards, and ensure that AI deployment is responsible and context-sensitive. This is particularly important in emerging markets, where institutional trust and public confidence are essential for scaling AI responsibly. 3. Transparency, accountability, and human oversight These are central to operationalizing responsible AI. Our engagement focuses on helping leaders and institutions translate these principles into governance processes, decision-making protocols, and oversight mechanisms that are usable in real organizational settings. 4. Interoperability of governance approaches This is a key priority because fragmentation across frameworks remains a major challenge. We see strong value in approaches that help align international principles with national realities and sector-specific implementation, especially across research institutions, public sector entities, and private sector actors. Greater interoperability can also help connect Global South priorities more effectively into the broader governance landscape.

Yes. While the listed themes are highly relevant, several cross-cutting issues deserve stronger emphasis to ensure the Dialogue is more inclusive, implementation-oriented, and responsive to the realities of developing countries. First, there is a need to explicitly address the gap between policy and implementation. Many frameworks exist, but institutions still struggle to translate them into operational practices, regulatory processes, leadership capability, and deployable use cases. Second, the Dialogue would benefit from stronger attention to ecosystem connectivity, especially the role of policy in linking research centers, academic institutions, private sector actors, and public sector entities. In many developing countries, innovation remains fragmented, and stronger governance support is needed to turn research and technical expertise into practical impact. Third, equitable access to AI infrastructure should be treated as a more visible cross-cutting issue. This includes access to computing power, relevant datasets, local-language tools, and the institutional capacity required to participate meaningfully in AI development and governance. Fourth, there is room to elevate local context and Global South representation as a substantive issue, not only a participation issue. Governance discussions should better reflect different levels of digital maturity, sectoral priorities, and development realities across regions. Finally, an emerging issue is the importance of continuity mechanisms after global consultations. Beyond dialogue, there should be structured ways to gather feedback, monitor evolving priorities, and synthesise stakeholder contributions into actionable insights. AI-enabled analysis of pooled interventions could be especially useful in helping identify patterns, consolidate recommendations, and support more coherent follow-up. Together, these issues can help strengthen the Dialogue as a practical, inclusive, and implementation-oriented global process.

In MENA region, the main governance gaps are not only regulatory, but also institutional and operational. The most significant challenge is the gap between growing interest in AI adoption and the limited readiness of many institutions to govern, implement, and scale AI responsibly. This affects both public and private sector entities, especially where leadership awareness, internal governance models, data maturity, and technical capacity are still developing. A second challenge is fragmentation. Different actors across government, academia, research centers, and industry are often working in parallel rather than through coordinated ecosystems. This slows the translation of innovation into real use cases and limits the ability to align governance approaches with national development priorities. In practice, this means that promising research, talent, and pilot initiatives may not progress into institutional adoption or broader sectoral impact. At the same time, this creates major opportunities. The region has strong momentum: rising policy interest, expanding digital transformation agendas, growing youth talent, and increasing openness from both government and business leaders to engage with AI strategically. There is a strong opportunity to build AI governance in a way that is proactive rather than reactive, embedding trust, transparency, accountability, and human oversight early, while institutions are still shaping their adoption pathways. In our sector, this is especially visible in leadership and capacity-building. Many executives are aware that AI is a strategic priority, but they need practical guidance on governance, risk, and implementation. This is why initiatives that connect policy, executive literacy, and real deployment are so important. Overall, the challenge is fragmentation and uneven readiness; the opportunity is to build collaborative, context-sensitive AI governance models that help Egypt and the MENA region move from isolated pilots to coordinated, responsible scale.

The AI Dialogue can play a valuable role as a neutral, inclusive platform for aligning diverse stakeholders around practical areas of cooperation on AI governance. Its importance lies not only in convening Member States, but also in creating structured engagement between governments, private sector, academia, civil society, and the technical community around shared priorities and implementation pathways. First, it can help reduce fragmentation across the global AI governance landscape by identifying common principles, shared concerns, and areas where governance approaches can be more interoperable. This is especially important as countries and institutions are moving at different speeds and with different levels of readiness. Second, the Dialogue can strengthen international cooperation by giving greater visibility to the needs and realities of developing countries. This includes cooperation on AI capacity-building, infrastructure access, institutional readiness, and talent development—areas that are essential for more equitable participation in the global AI ecosystem. Third, it can serve as a bridge between policy discussions and practical collaboration. Beyond exchanging views, the Dialogue can catalyse partnerships, pilot initiatives, and knowledge-sharing platforms that connect global frameworks with real implementation in sectors such as education, water, healthcare, and public service delivery. Finally, the Dialogue can support continuity and collective learning. Through follow-up consultations, iterative stakeholder engagement, and stronger synthesis of contributions, it can evolve into a living process that informs future cooperation rather than a one-time event. Used well, it can help turn broad international interest in AI governance into coordinated action, shared learning, and more inclusive global stewardship of AI.

The AI Dialogue should build on existing initiatives that already provide normative foundations, policy tools, and convening power. In particular, it should connect with UNESCO's Recommendation on the Ethics of AI, which applies to all UNESCO Member States and is already supported by implementation tools such as readiness assessment mechanisms. It should also build on the AI for Good platform led by ITU with UN partners, which already convenes policymakers, experts, and innovators around AI skills, standards, and real-world applications. In addition, the Dialogue can draw from the Global Digital Compact, which provides a broader UN framework for digital cooperation and includes a roadmap for global AI governance, as well as from the OECD AI Principles, which remain an important reference for trustworthy AI and policy interoperability. From our perspective, the added value of the AI Dialogue is not to duplicate these efforts, but to connect them more effectively and make them more inclusive and implementation-oriented. It can serve as the space where existing principles, standards, and readiness tools are translated into coordinated action across countries and sectors. It can also add value by giving stronger voice to developing countries and the Global South, ensuring that international cooperation reflects different levels of institutional readiness, infrastructure access, and development priorities. Finally, the Dialogue can create continuity between existing initiatives by linking high-level discussions with follow-up mechanisms, practical partnerships, and more structured synthesis of stakeholder inputs. In this way, it can act as a bridge between what already exists and what is still needed: stronger coordination, broader inclusion, and more actionable pathways for responsible AI governance.

Different stakeholders can contribute most effectively when the Dialogue is structured not only as a space for statements, but as a platform for co-creation and follow-through. - Member States can contribute by sharing policy priorities, regulatory experiences, and national implementation challenges. - Private sector actors can bring practical lessons on deployment, risk management, technical standards, and scalable innovation. - Academia and research centers can contribute evidence, foresight, independent analysis, and links between research and applied solutions. - Civil society can help ensure that inclusion, rights, equity, and local community realities remain central. - The technical community can support the Dialogue with expertise on model development, safety, interoperability, and open-source ecosystems. - International organizations can help connect existing frameworks, mobilize partnerships, and support continuity across initiatives. To make these contributions meaningful, the format should go beyond plenary exchange. A strong structure could include: 1. High-level plenary sessions to frame priorities and surface shared concerns 2. Thematic multi-stakeholder working groups on key issues such as capacity-building, trustworthy AI, interoperability, and accountability 3. Regional or development-focused segments to ensure stronger voice for developing countries and the Global South 4. Practical case and pilot showcases that connect governance discussions with real implementation examples 5. A structured synthesis and follow-up mechanism so inputs are captured, analysed, and translated into actionable outcomes beyond the event itself The Dialogue will be most valuable if it combines inclusiveness with structure, and broad participation with practical output. In that sense, success depends not only on who joins the conversation, but on whether the format enables genuine collaboration, continuity, and implementation.

Several voices remain underrepresented in global discussions on AI governance, even when multi-stakeholder participation is formally encouraged. In particular, there is still insufficient representation from developing countries and the Global South, especially practitioners working at the level of implementation rather than only high-level policy. This includes public sector implementers, local innovators, SMEs, startup ecosystems, applied researchers, and institutions working in contexts with infrastructure, funding, and capacity constraints. The consultation materials clearly emphasize inclusion, capacity gaps, and the need to close digital divides, which makes this an especially important gap to address in practice. Also underrepresented are local-language communities, universities and research centers from emerging economies, civil society actors working close to affected communities, and sectors such as education, agriculture, water, and public service delivery, where AI governance questions are becoming increasingly important but are often less visible in global forums. To include these perspectives more meaningfully, representation should be built into the structure of the Dialogue itself. This can include dedicated regional segments, balanced speaking roles across regions, targeted outreach to implementation-focused institutions, and stronger participation pathways for universities, research centers, and innovation ecosystems from developing countries. The Dialogue should also include practical working groups and case-based sessions, not only plenary interventions, so that participants with applied experience can contribute concrete insights. In addition, follow-up mechanisms such as written inputs, iterative consultations, and structured synthesis of contributions can help ensure that underrepresented voices do not appear only once, but continue shaping outcomes over time.

To foster meaningful and dynamic engagement, the AI Dialogue should combine formal plenary discussion with more interactive, problem-solving formats. The consultation materials already emphasize the need for practical cooperation, dynamic engagement, and actionable policy discussion, which creates a strong basis for more innovative design. One effective format would be multi-stakeholder thematic working labs, where policymakers, technical experts, private sector actors, academia, and civil society work together on specific governance questions such as capacity-building, trustworthy AI, interoperability, or accountability. These sessions could be designed around concrete scenarios and end with short, practical recommendations. A second useful format would be regional or development-focused roundtables, giving stronger voice to developing countries and the Global South on issues such as infrastructure access, institutional readiness, local-language AI, and research-to-deployment gaps. This would help ensure that the Dialogue reflects different realities, not only the perspectives of the most advanced ecosystems. A third format could be case-based implementation showcases, where institutions present real examples of AI governance in action across sectors such as education, healthcare, water, or public services. This would help connect principles with practice and make the discussions more grounded. In addition, interactive polling and live prioritisation tools could be used during and after sessions to capture stakeholder views on key recommendations, areas of convergence, and unresolved issues. This would make engagement more participatory and create useful input for follow-up. Finally, the Dialogue would benefit from an AI-supported synthesis mechanism that analyses pooled interventions and identifies patterns, recurring priorities, and opportunities for cooperation. Combined with working groups and interactive sessions, this would help transform diverse contributions into a more cohesive and actionable outcome.

Examples that promote effective AI governance should combine policy direction, institutional readiness, and practical multi-stakeholder engagement. At the global level, UNESCO's Recommendation on the Ethics of AI remains a strong normative foundation for trustworthy, human-centered AI, while the EU AI Act offers an important regulatory model by translating risk-based governance into concrete legal obligations for different categories of AI systems. Together, they are valuable because they move the discussion from broad principles toward more operational governance approaches. A second important example is AI for Good, led by ITU with UN partners, which creates an action-oriented platform linking AI governance to skills, standards, partnerships, and real-world SDG applications. Its strength is that it connects dialogue with implementation and can help sustain engagement beyond one-off consultations. At the regional level, the MENA Observatory on Responsible AI at AUC is also highly relevant. As a locally driven platform, it helps surface research, regional evidence, and context-specific perspectives on responsible AI in both English and Arabic. This is especially valuable for ensuring that AI governance reflects MENA realities and contributes Global South perspectives to broader international discussions. From ACG's side, the Leadership X Roundtables Initiative offers a practical governance-focused approach by engaging senior executives and decision-makers around AI leadership, risk, governance, and responsible adoption. Its added value lies in helping translate governance from policy language into executive understanding, institutional readiness, and practical implementation. Overall, the most effective approaches are those that connect global frameworks, regional knowledge platforms, and executive-level action. In practice, this means combining regulation, ethics, research, leadership engagement, and cross-sector collaboration so that AI governance becomes actionable, locally relevant, and scalable.