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A successful Global Dialogue on AI Governance should go beyond high-level discussions and provide practical direction that supports inclusive and real-world adoption of AI across different sectors. Firstly, success would mean ensuring that diverse voices are meaningfully represented, particularly from non-technical stakeholders, educators, and communities that experience the everyday impact of AI systems. Inclusive participation is essential to avoid governance approaches that are disconnected from real-world use. Secondly, the dialogue should produce clear and actionable principles that organisations can use to apply AI responsibly. These principles should be practical enough to support implementation, not just theoretical guidance. Another important outcome would be increased awareness and understanding of AI beyond technical communities. Many barriers to adoption are conceptual rather than technical and the dialogue should help bridge this gap by promoting accessible ways of engaging with AI. Finally, success would involve establishing ongoing collaboration mechanisms across regions, ensuring that insights and best practices are continuously shared, adapted and applied in different contexts.

• AI capacity-building
• Social, economic, ethical, cultural, linguistic and technical implications of AI
• Transparency, accountability, and human oversight
• Protection and promotion of human rights

These priorities reflect the need to ensure that AI is not only developed responsibly, but also understood and applied effectively across different contexts. AI capacity-building is critical, particularly for individuals and organisations without strong technical backgrounds. Many barriers to adoption stem from uncertainty and lack of confidence, rather than a lack of available tools. The social, economic and cultural implications of AI are equally important, as these systems increasingly influence everyday decision-making. Without diverse participation, there is a risk of reinforcing existing inequalities or overlooking important perspectives. Transparency, accountability and human oversight are essential to building trust. Users need to understand how decisions are made and retain the ability to question and interpret outcomes. Finally, the protection and promotion of human rights must remain central to any governance approach. AI systems should support fairness, inclusion and accessibility, rather than create additional barriers.

One important cross-cutting issue is the gap between awareness and the practical application of AI. Many individuals and organisations are aware of AI but struggle to translate that awareness into meaningful use. This is often not due to technical limitations, but rather a lack of structured guidance on how to apply AI in real-world tasks. There is also a need to better recognise the role of everyday users in shaping AI systems. Governance discussions often focus on developers and policymakers, yet the way AI is used in practice is significantly influenced by non-technical users. Their behaviours, inputs and decisions directly impact outcomes. Another emerging issue is the fragmentation of how information and insights are captured across different environments, particularly in sectors such as education. Without structured and consistent approaches, it becomes difficult to interpret progress or make informed decisions using AI-supported systems. Addressing these gaps would help ensure that AI governance is not only well-defined at a policy level, but also effective in everyday application.

Governance gaps in AI are increasingly visible at the level of everyday use, particularly in sectors such as education and among small organisations that are beginning to adopt AI without structured guidance. One of the most significant challenges is the lack of clarity around how AI should be applied in real-world tasks. While tools are widely available, many individuals and organisations remain uncertain about how to use them responsibly and effectively. This often leads to inconsistent use, over-reliance on outputs without sufficient interpretation or hesitation to adopt AI altogether. Another challenge is the fragmentation of data and information across different stakeholders and environments. Without consistent approaches to capturing and interpreting information, it becomes difficult to apply AI in a way that supports clear decision-making or meaningful progress tracking. At the same time, there are important opportunities. AI has the potential to significantly improve how information is structured, interpreted, and used to support decision-making, particularly in education and operational contexts. It can also support more inclusive participation by enabling non-technical users to engage with complex tasks in more accessible ways. Addressing governance gaps through practical guidance, capacity-building, and inclusive participation would help unlock these opportunities while ensuring responsible and effective use.

The AI Dialogue can play a critical role in advancing international cooperation by creating a shared platform for inclusive and practical engagement across different regions and sectors. One of its most important functions is to bring together diverse stakeholders, including governments, private sector actors, educators, and non-technical users, to ensure that AI governance reflects real-world use, not just policy or technical perspectives. This helps promote more balanced and context-aware approaches to governance. The Dialogue can also support the alignment of principles and practices across regions. While different countries may adopt varying approaches to AI governance, there is value in establishing common foundations around responsible use, transparency, and inclusion. This can reduce fragmentation and support more consistent application of AI across borders. In addition, the AI Dialogue can facilitate knowledge-sharing by highlighting best practices, lessons learned, and practical approaches to implementation. This is particularly important for regions and organisations that are still developing their capacity to engage with AI effectively. By promoting ongoing collaboration, rather than one-time discussions, the Dialogue can help ensure that international cooperation remains responsive to the rapid pace of AI development.

The AI Dialogue can build upon existing international and regional initiatives that focus on responsible AI, capacity-building, and multi-stakeholder engagement. These include efforts by international organisations, public-private partnerships, and academic collaborations that are already exploring AI governance frameworks, ethical guidelines, and best practices. However, many of these initiatives operate in fragmented ways, with limited coordination across regions and sectors. The AI Dialogue has the opportunity to act as a unifying platform, connecting these efforts and making it easier to share insights, align priorities, and avoid duplication. One important area of added value is the ability to bridge the gap between policy discussions and real-world application. While many initiatives focus on high-level principles, there is often less emphasis on how these principles are implemented in everyday contexts. The Dialogue can help address this by encouraging contributions from practitioners and non-technical users. Additionally, the AI Dialogue can strengthen inclusivity by ensuring that perspectives from underrepresented regions and sectors are incorporated into global discussions. This would support more balanced and globally relevant governance outcomes. By connecting existing efforts and focusing on practical implementation, the AI Dialogue can enhance both the coherence and impact of AI governance initiatives.

Different stakeholders can contribute to the AI Dialogue by bringing both policy perspectives and practical, real-world insights into the discussion. Governments can provide regulatory direction and help align national approaches, while the private sector can share lessons from implementation, innovation and operational challenges. Academic institutions can contribute research, evidence and critical analysis, while civil society organisations can highlight the societal impact of AI, particularly on vulnerable or underrepresented groups. Equally important is the inclusion of practitioners and non-technical users who engage with AI in everyday contexts. Their experiences provide valuable insight into how AI systems are actually used, interpreted and applied in practice. To support meaningful contributions, the Dialogue should adopt a structured yet flexible format. This could include a combination of plenary sessions for high-level discussions and smaller, thematic working groups focused on specific areas such as application, capacity-building and inclusion. In addition, mechanisms for written submissions, case studies and practical examples should be incorporated, allowing stakeholders to share real-world experiences beyond formal discussions. A well-designed structure that balances policy dialogue with practical input would help ensure that contributions are both inclusive and actionable.

Several voices remain underrepresented in global discussions on AI governance, particularly those of non-technical users, educators, small organisations and communities in developing or resource-constrained environments. While discussions often focus on policymakers, researchers and large technology organisations, there is less representation from individuals who interact with AI systems in everyday settings. These users play a critical role in shaping how AI is applied, yet their experiences are not always reflected in governance conversations. Educators and practitioners in sectors such as education, healthcare and social services are also underrepresented, despite being directly impacted by how AI systems influence decision-making and outcomes. To address this, the AI Dialogue should create accessible pathways for participation. This could include simplified submission processes, regional consultations and opportunities for individuals and smaller organisations to contribute without requiring extensive technical expertise. In addition, efforts should be made to include perspectives from different cultural and linguistic backgrounds, ensuring that governance approaches are globally relevant and not limited to a narrow set of contexts. By actively including these voices, the Dialogue can better reflect the diversity of AI use and support more inclusive and effective governance outcomes.

To foster meaningful and dynamic engagement, the AI Dialogue should move beyond traditional conference-style formats and incorporate more interactive and participatory approaches. One effective format would be scenario-based discussions, where participants are presented with real-world situations involving AI use and invited to explore challenges, decisions and outcomes collaboratively. This helps ground discussions in practical realities rather than abstract concepts. Interactive workshops and small-group sessions can also encourage deeper engagement by allowing participants to share experiences, compare perspectives and co-develop ideas in a more focused setting. Another valuable approach would be the use of case study exchanges, where stakeholders present real examples of AI application, including both successes and challenges. This can support knowledge-sharing and provide practical insights that others can learn from. In addition, digital participation tools, such as virtual breakout sessions and structured online contributions, can help ensure broader global participation, particularly for those who may not be able to attend in person. By combining structured dialogue with interactive and experience-driven formats, the AI Dialogue can create a more inclusive, engaging and impactful environment for collaboration.

Effective AI governance is best supported by approaches that combine clear principles with practical implementation. One important example is the use of human-in-the-loop practices, where AI outputs are reviewed and interpreted by individuals rather than used in isolation. This helps ensure that decisions remain contextual, accountable and aligned with real-world needs. Another effective approach is the development of structured frameworks for capturing and interpreting information. In many environments, particularly in sectors such as education and small organisations, data is often recorded in fragmented or inconsistent ways.Establishing more structured and consistent approaches can improve how information is understood and support more reliable AI-assisted decision-making. Capacity-building initiatives also play a critical role. Providing accessible training and guidance helps individuals and organisations move beyond basic awareness to practical application, enabling more responsible and confident use of AI. In addition, collaborative platforms that enable knowledge-sharing across sectors and regions are valuable. These platforms allow stakeholders to exchange best practices, learn from real-world experiences and adapt approaches to different contexts. Finally, policy approaches that prioritise transparency, accountability and inclusivity help ensure that AI systems are developed and applied in ways that are fair, understandable and accessible to a wide range of users. Together, these practices support a more balanced approach to AI governance that connects policy with practical use.