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The following outcomes would make the first Global Dialogue on AI Governance a success: (a) Ensure inclusive and meaningful participation from developed and developing countries, alongside key stakeholders such as scientists, technology sector, industry leaders, policymakers, civil society organisations and affected individuals including women, children and elderly who may be directly or indirectly impacted by AI-related harms. (b) Sharing regular updates and initiatives on social media platforms can facilitate the AI dialogue engaging with broader public and promote transparency. The exchange of best practices and strengthening of global cooperation would demonstrate the effectiveness of AI Dialogue in addressing AI challenges. Not everyone has access to digital platforms, therefore in-person engagement such as community meetings, workshops, multilingual and accessible formats as well as collaboration with civil society organisations, will be required to ensure inclusive participation.

• Safe, secure and trustworthy AI
• Social, economic, ethical, cultural, linguistic and technical implications of AI
• Protection and promotion of human rights
• Transparency, accountability, and human oversight

(i) Safe, Secure and Trustworthy AI- Inadequate coordination among governments, technology platforms and civil society organisations undermines the effective enforcement of online safety measures. Consequently, policies frequently fail to reflect or address the real experiences of those most affected, particularly women and children facing digital violence. (ii) Social, economic, ethnic, cultural, linguistic and technical implications of AI-AI data practices often suffer from unclear accountability, lack of transparency in privacy disclosures and risk of data misuse. Generally, privacy policies are often complex and fail to provide meaningful clarity for users. Furthermore, the development and deployment of AI systems may result in biased algorithmic outcomes, particularly due to the underrepresentation of marginalized groups in training data. This lack of inclusivity combined with weak digital safety safeguards, thus increases the risk of algorithmic AI-related harm. (iii) Protection and promotion of human rights- The absence of human rights protection in AI Governance along with critical appointments such as Special Rapporteur on AI supported by a multi-advisory committee (covering human rights, environmental protection, economic security and space governance), an AI Grievance Redressal Officer distinct from a Data Protection Officer and an Independent AI Ombudsman for compliance oversight and cross-border complaints can lead to bias, discrimination, privacy violations and threats to human dignity. (iv) Transparency, accountability and human oversight -Emphasis should be placed on Corporate Accountability within established legal frameworks, rather than on voluntary Corporate Social Responsibility (CSR) initiatives, to ensure binding accountability in AI Governance with stringent penalties for non-compliance and clearly defining roles among providers, deployers and other relevant actors to prevent ambiguity and gaps in liability. This will ensure transparency, establish enforceable accountability and mandate effective human oversight across at all stages of AI development and deployment.

(a) AI Governance in Space: Robust AI Governance in Space is essential to ensure safety, prevent conflict and protect shared resources. (b) Labour Displacement and Replacement due to AI: AI should enhance productivity and empower employees, not replace them. However, presently many companies across the world are replacing staff with cost-saving AI. (c) Gender biasness in Datasets: Unfair outcomes may arise, despite widespread discussion on AI fairness, as practical solutions remain challenging. This makes it essential to address gender bias with equal priority within governance frameworks. (d) Environmental concerns of AI: Energy consumption and water use in AI development and deployment are emerging as important environmental considerations, with potential impacts on carbon emissions and local water resources. As highlighted in discussions such as the World Bank's Water Forward session at 2026 Spring Meetings, there is an urgent need for coordinated and effective measures to protect global water resources. At the same time, sustainability claims in AI should be transparent and evidence-based and not contribute to greenwashing. (e) Monitoring, Evaluation & Implementation (MEI) Approach: All these three together should constitute the core pillars of effective AI Governance, ensuring that relevant guidelines are clearly defined, consistently upheld and continuously improved in practice. This process should be continuous and not occasional.

Across different jurisdictions, entitles engaged in development and deployment of AI systems rely on voluntary Corporate Social Responsibility (CSR), which creates governance gaps, makes accountability unclear and difficult to define liability. Without strict legal frameworks and penalties, risks like bias and data breaches persist. However, these gaps create an opportunity to implement binding regulations that clearly assign responsibility and ensure ethical, transparent AI practices.

Fragmented global frameworks on AI Governance may create legal ambiguity and hinder international collaboration. AI Dialogue can play a crucial role for advancing international co-operation in AI governance by helping countries identify shared goals, align regulations, foster multilateral dialogues and develop global standards that ensure consistency and co-operation. AI innovation for progress is most meaningful when it aligns with respect for human rights and environment sustainability.

AI Dialogue could build on initiatives, partnerships and mechanisms such as research collaborations between universities and industry that promote innovation alongside responsible development, multi-stakeholder governance bodies comprising governments, industry and civil society organisations that contribute to policy development and regulatory oversight and cross-border AI research dialogues that enable international co-operation through the sharing of knowledge and expertise. Its value lies in bringing diverse stakeholders together, translating AI principles into practical outcomes and enabling responsible, inclusive and sustainable innovation at scale.

Stakeholders such as governments, technology sector, industry, legal experts, civil society organisations, academia, subject matter expertise on environment, space etc. and affected individuals will bring differing and value perspectives to the AI Dialogue. It should prioritise accessibility by offering sign language interpretation, live captioning, translated materials and accessible venues to ensure full participation of individuals. Structured forums such as roundtable discussions, public consultations and collaborative workshops should be designed to promote inclusive participation for all stakeholders.

Global discussions may at times overlook certain groups such as women, children, persons with disabilities, the elderly and persons with limited proficiency in official or working languages. To improve inclusivity, it is essential to create accessible forums, provide multilingual support so that no one is left behind and use technology to ensure broader participation. These measures can support more inclusive and effective outcomes.

Interactive workshops, real-life examples used as case studies, brainstorming sessions and discussions of relevant court orders and judgments can foster meaningful engagement during the AI Dialogue. These formats encourage collaboration, diverse perspectives and innovative solutions.

Effective AI Governance ensures transparency, accountability and ethical use of technology. Policies like AI ethics guidelines, data protection laws combined with practices such as impact assessments, stakeholder consultations, periodic monitoring and evaluation help entities to use AI responsibly, mitigate risks and build public trust.