DEPARTMENT OF INFORMATION AND COMMUNICATIONS TECHNOLOGY - CYBERCRIME INVESTIGATION AND COORDINATING CENTER

A successful first Global Dialogue on AI Governance should produce concrete, inclusive, and actionable outcomes rather than purely aspirational statements. First, it should establish a shared baseline of principles on safe, secure, and trustworthy AI that are endorsed across regions, including the Global South. These principles must go beyond ethics and translate into operational guidance for governments and institutions. Second, the Dialogue should deliver a roadmap for capacity-building, particularly for developing countries, ensuring equitable participation in AI development, governance, and benefits. This includes commitments on funding, knowledge-sharing, and technical assistance. Third, success would mean creating a multi-stakeholder coordination mechanism that brings together governments, academia, civil society, and the private sector, with clear roles and sustained engagement beyond the Dialogue. Fourth, the Dialogue should initiate interoperability pathways across existing AI governance frameworks to reduce fragmentation and regulatory arbitrage, while respecting national contexts. Finally, it should produce measurable follow-up actions, such as pilot initiatives, reporting mechanisms, or working groups focused on priority issues. Without accountability and continuity, the Dialogue risks becoming symbolic. A successful outcome is one that translates global consensus into implementable national and regional action, especially for countries with emerging AI ecosystems.

• Safe, secure and trustworthy AI
• AI capacity-building
• Social, economic, ethical, cultural, linguistic and technical implications of AI
• Interoperability of governance approaches

Safe, secure, and trustworthy AI is foundational. Ensuring AI systems are transparent, accountable, and aligned with human rights is critical to building public trust and preventing harm, particularly in high-risk applications such as healthcare, governance, and security. AI capacity-building is essential to address global inequalities. Many developing countries, including those in ASEAN, face gaps in infrastructure, skills, and regulatory readiness. Strengthening institutional and human capacity enables meaningful participation in AI governance and innovation. Social, economic, ethical, cultural, linguistic, and technical implications of AI highlight the need for context-sensitive governance. AI systems can reinforce biases, marginalize local languages, and disrupt labor markets. Addressing these implications ensures AI development is inclusive and culturally responsive. Interoperability of governance approaches is crucial in a fragmented regulatory landscape. Aligning standards and frameworks across jurisdictions promotes consistency, reduces compliance burdens, and supports cross-border collaboration while allowing flexibility for local adaptation. Together, these priorities emphasize that AI governance must be inclusive, context-aware, and globally coordinated, ensuring that technological advancement benefits all and does not exacerbate existing inequalities.

Yes, several critical cross-cutting and emerging issues require greater emphasis: Data governance and sovereignty remain underexplored. Questions around data ownership, access, localization, and cross-border flows are central to AI development and equity. Without fair data governance, developing countries risk becoming mere data providers rather than value creators. Environmental and energy impacts of AI are increasingly urgent. The growing computational demands of AI systems contribute to carbon emissions and resource consumption. Sustainable AI must be integrated into governance discussions. Labor displacement and just transition is another key issue. While AI creates opportunities, it also disrupts employment. There is a need for global strategies on reskilling, social protection, and inclusive digital economies. Concentration of AI power among a few large technology actors raises concerns about market dominance, access, and influence over global standards. Addressing this requires stronger competition frameworks and equitable access to AI infrastructure. Misinformation and information integrity, especially in democratic contexts, is an emerging risk amplified by generative AI. Governance must address safeguards without undermining freedom of expression. Lastly, meaningful youth and Global South participation should be treated as a cross-cutting principle, not an afterthought. Inclusive governance ensures that diverse perspectives shape AI systems that affect all. These issues highlight the need for AI governance to be holistic, forward-looking, and grounded in equity and sustainability.

In the Philippines, governance gaps in AI are shaped by uneven capacity, fragmented regulation, and limited technical infrastructure, but recent developments signal growing momentum. A major challenge is the absence of a comprehensive national AI governance framework. While sectoral policies exist, coordination across agencies remains limited, creating regulatory uncertainty—particularly on accountability, safety standards, and ethical use. This affects sectors such as public service delivery, education, and digital finance, where AI adoption is increasing without consistent safeguards. Second, capacity constraints are significant. Many government institutions and local governments lack technical expertise to procure, regulate, or audit AI systems. This widens the gap between policy ambition and implementation, especially outside major urban centers. Third, data governance and quality issues hinder trustworthy AI. Fragmented data systems and limited interoperability reduce the effectiveness of AI solutions, while raising privacy and security concerns. However, there are key opportunities. The country's strong digital workforce and BPO sector position it well for AI-enabled services. Growing interest in AI within government and academia also opens pathways for capacity-building and regional leadership in ASEAN. Efforts to strengthen inclusive and culturally responsive AI, including support for local languages and community-based applications, present an opportunity to ensure AI benefits underserved populations. Overall, the Philippines stands at a critical juncture: addressing governance gaps can enable responsible innovation, while failure to act risks deepening inequalities and exposure to harm.

The AI Dialogue can serve as a neutral, inclusive platform to bridge divides between countries at different stages of AI development and governance maturity. First, it can facilitate consensus-building on minimum global standards, particularly on safety, security, and trustworthiness, while allowing flexibility for national contexts. This helps reduce fragmentation and promotes interoperability across regulatory approaches. Second, the Dialogue can advance equitable capacity-building, ensuring that developing countries are not left behind. By mobilizing technical assistance, funding, and knowledge-sharing, it can strengthen institutional readiness and human capital. Third, it can support policy coherence and coordination by connecting existing initiatives and avoiding duplication. This includes fostering alignment between regional and global frameworks. Fourth, the Dialogue can act as a platform for multi-stakeholder engagement, ensuring that governments, private sector actors, academia, and civil society collaboratively shape AI governance. Finally, it can promote accountability and follow-through by establishing monitoring mechanisms, voluntary commitments, or thematic working groups. For countries like the Philippines, the Dialogue is an opportunity to amplify Global South perspectives, access expertise, and co-develop solutions that reflect local realities. Its value lies in translating global cooperation into practical, inclusive, and sustained action.

The AI Dialogue should build upon and connect with existing global and regional efforts. At the global level, initiatives such as the UNESCO Recommendation on the Ethics of AI, the OECD AI Principles, and emerging discussions within the UN system provide foundational norms. At the regional level, ASEAN's work on digital transformation and AI governance offers context-specific approaches relevant to countries like the Philippines. Nationally, the Philippines' National AI Strategy Roadmap and data privacy framework provide starting points, though further development is needed. The added value of the AI Dialogue lies in integration and action. Rather than creating new principles, it can align and operationalize existing ones through shared tools, benchmarks, and implementation support. It can also fill gaps by focusing on interoperability across frameworks, ensuring that countries can navigate multiple standards without duplication or conflict. Another key contribution is elevating underrepresented perspectives, particularly from developing countries, and embedding them into global norm-setting processes. Finally, the Dialogue can catalyze practical collaboration, such as joint pilot projects, regional capacity-building programs, and knowledge exchanges. In essence, its value is not in replacing existing initiatives, but in connecting, strengthening, and translating them into measurable outcomes.

Different stakeholders can contribute distinct and complementary roles: Governments should provide policy leadership and regulatory direction. The private sector can share technical expertise and innovation insights, while academia contributes research and evidence-based analysis. Civil society plays a critical role in advocating for rights, inclusion, and accountability, and youth bring future-oriented perspectives and digital fluency. To ensure meaningful participation, the AI Dialogue should adopt a multi-layered format: High-level plenaries for political commitment and agenda-setting Thematic working groups aligned with priority areas Regional consultations to capture context-specific inputs Multi-stakeholder roundtables to encourage dialogue across sectors The structure should also include pre-Dialogue consultations and post-Dialogue follow-ups, ensuring continuity and impact. Digital participation mechanisms are essential to enable broad and equitable access, particularly for stakeholders from developing countries. Clear documentation, transparent processes, and opportunities for co-creation of outputs will strengthen ownership and legitimacy. Ultimately, an inclusive Dialogue is one that moves beyond representation to meaningful influence in decision-making.

Several voices remain underrepresented in global AI governance discussions: Developing countries, particularly from the Global South, often have limited representation despite being significantly affected by AI systems. Local communities and indigenous peoples are frequently excluded, even though AI systems can impact their cultural practices, data rights, and knowledge systems. Youth are underrepresented in decision-making processes, despite being primary users and future leaders in AI-driven societies. Workers and informal sector participants are also often overlooked, even as AI reshapes labor markets and livelihoods. To address this, inclusion must go beyond invitations. It requires targeted support, such as funding for participation, capacity-building, and accessible platforms. The Dialogue should incorporate localized consultations, partnerships with community organizations, and mechanisms to integrate grassroots perspectives into global discussions. Language accessibility and culturally sensitive approaches are also critical to ensure meaningful engagement. Embedding inclusion as a core design principle, rather than an add-on, will result in more legitimate, equitable, and effective AI governance outcomes.

To foster meaningful and dynamic engagement, the AI Dialogue should move beyond traditional conference formats. Interactive policy labs can allow participants to co-develop solutions to real-world challenges, producing actionable outputs. Scenario-based simulations can help stakeholders explore the implications of AI governance decisions in areas such as public services or crisis response. Multi-stakeholder hackathons can generate practical tools, prototypes, or policy ideas within a short timeframe. Deliberative dialogues, such as citizens' assemblies or youth forums, can bring diverse perspectives into structured discussions. Hybrid formats combining in-person and digital participation can expand access and inclusivity. The Dialogue can also use real-time polling and collaborative platforms to capture inputs and build consensus during sessions. Storytelling and case-based discussions can make complex issues more accessible and grounded in lived experiences. Finally, establishing ongoing virtual communities of practice can sustain engagement beyond the event. These approaches ensure that the Dialogue is not only informative, but also participatory, solution-oriented, and impactful.

Several practices offer valuable lessons for effective AI governance: Adopting risk-based regulatory approaches allows governments to focus oversight on high-impact AI systems while enabling innovation in lower-risk areas. Embedding ethics-by-design principles ensures that safety, fairness, and accountability are integrated throughout the AI lifecycle. Developing national AI strategies with clear implementation plans helps align stakeholders and set priorities, particularly when linked to broader development goals. Investing in AI capacity-building, including education, training, and institutional strengthening, is critical for sustainable governance. Promoting data governance frameworks that balance innovation with privacy and security enhances trust in AI systems. Multi-stakeholder collaboration platforms can improve transparency and accountability while fostering innovation. In the Philippine context, strengthening inter-agency coordination, enhancing local government capacity, and supporting inclusive, language-sensitive AI applications are particularly important. Internationally, sharing best practices and developing interoperable standards can help countries learn from each other and avoid fragmentation. Effective AI governance ultimately requires a balance between innovation, regulation, and inclusion, supported by practical tools and sustained collaboration.