Globe Telecom Inc.

A successful first Global Dialogue on AI Governance should move beyond alignment in principle and deliver clear, actionable direction that reflects global realities not just dominant perspectives. 1. Success means meaningful inclusion of the Global South not just in participation, but in influence. This includes concrete commitments to fund, support, and institutionalize representation across regions, ensuring that governance frameworks reflect diverse socio-economic, cultural, and technological contexts. 2. It should produce practical pathways for operationalizing global principles locally. High-level frameworks must be translated into adaptable, grounded, real-world playbooks that countries and organizations at varying levels of digital maturity can implement without being excluded from progress. 3. The dialogue should establish a shared baseline for "minimum viable governance" a set of essential safeguards (risk identification, accountability, human rights considerations, impact to environment/ society) that enable safe AI adoption while allowing flexibility for innovation and scaling. 4. Success would include mechanisms for continuous, cross-border collaboration, such as regulatory sandboxes, knowledge-sharing platforms, and real-time learning exchanges. Governance must evolve alongside AI, and this requires sustained cooperation not one-time dialogue. 5. There should be alignment on shared risks, even if regulatory approaches differ. Issues like bias, misuse, exclusion, and harm are universal, and global consensus on these risks can serve as a foundation for coordinated action. 6. The dialogue must clarify the role of the private sector as active co-shapers of governance, not just implementers. Given their role in building and deploying AI systems, their engagement is critical to ensuring that policies are both practical and effective. Success is not measured by the dialogue itself but by whether it leads to more inclusive, implementable, and trusted AI governance worldwide.

• Safe, secure and trustworthy AI
• Interoperability of governance approaches
• AI capacity-building
• Protection and promotion of human rights

To move AI governance forward, we need to anchor on what truly enables global trust and participation not just technical alignment. (people not just tools and technology) 1. safe, secure, and trustworthy AI must remain the foundation. Without trust, adoption will always be limited, regardless of how advanced the technology becomes. 2. AI capacity-building is important esp for the Global South. Governance cannot be effective if entire regions are unable to meaningfully participate due to gaps in skills, infrastructure, or access. Inclusion starts with capability. 3. we need interoperability of governance approaches. AI operates across borders, but governance remains fragmented. Aligning on common principles, standards and enabling systems to work across jurisdictions is essential to avoid regulatory silos and inefficiencies. 4. lastly, human rights must be non-negotiable. These cannot be treated as an add-on or secondary consideration. They must be embedded by design, serving as the baseline for how AI systems are developed, deployed, and governed. Together, these priorities reflect a simple but critical shift, and that is AI governance must move from being fragmented and reactive to being inclusive, practical, and globally coherent. Because if we are building AI for the world, then governance must ensure the world can shape it and be protected by it if not, we will be shaped by it.

While these priorities are critical, one area that remains underrepresented is sustainability, ensuring that AI systems are not only safe and inclusive today, but viable and responsible in the long term. as convenor in ISO's Joint advisory group, AI and Sustainability is what we are also pushing forward.

The urgency of these priorities is very real for the Philippines and the broader Global South. 1. Safe, secure, and trustworthy AI directly affects public trust. In markets where digital scams (a lot right now), misinformation (masssively used), and data misuse are rising, weak safeguards can quickly erode confidence and slow adoption. 2. AI capacity-building is foundational. Many countries in the Global South face gaps in skills, infrastructure, and access. Without deliberate investment, they risk becoming passive consumers of AI rather than active contributors shaping its development. 3. Interoperability of governance approaches matters because economies like the Philippines operate across global systems, BPO, telecom, digital services. Fragmented regulations create compliance burdens and limit participation in global AI ecosystems. 4. Human rights as a baseline is critical. In diverse and rapidly digitizing societies, risks around bias, exclusion, and misuse can disproportionately impact vulnerable populations if not addressed early.This further increases the digital divide. Overlaying all of this is sustainability. The Global South is more exposed to resource constraints and climate risks, yet often has less influence over how AI systems are scaled. Without sustainable AI practices, we risk widening inequality, economically, digitally, and environmentally. Together, these priorities amplifies the layer of divide and discrimination.

3 things where AI dialogue can help: 1. the AI Dialogue can act as a neutral convening platform bringing governments, industry, and civil society together to build trust and reduce fragmentation. This is especially important in a space where geopolitical interests often compete. 2. it can drive alignment on shared risks and principles, even if countries take different regulatory approaches. Agreeing on what needs to be protected human rights, safety, accountability, creates a common foundation for cooperation. 3. it can enable practical collaboration, not just discussion through shared frameworks, cross-border sandboxes, and real-time knowledge exchange. This helps translate global intent into local action. overall, its role is to move AI governance from isolated efforts to coordinated, inclusive, and action-driven cooperation.

There's a lot of key foundations that exists, OECD, ISO, ITU, IEEE. The added value of the AI Dialogue is not to create new principles or frameworks, but to connect, align, and operationalize what already exists. To act as bridge, translator and someone who will execute. Making the foundations connected, practical, and globally inclusive.

Governments should lead in setting risk-based policies and enabling environments, while remaining open to alignment with global standards. Private sector organizations must step up as co-creators of governance, not just compliance actors and this is what Globe is currently doing now as part of ISO, where PH now holds its first convenor role under JAG on AI and Sustainability. Academia and research institutions can ground the Dialogue in evidence and foresight, but this needs to be pragmatic. Civil society and advocacy groups play a critical role in ensuring accountability and representation. International organizations and standards bodies (UN, ISO) should act as connectors and harmonizers, aligning existing frameworks and promoting interoperability across regions. Global South stakeholders must be enabled to move from consultation to active participation and leadership, through funding, platforms, and deliberate inclusion.

Global South like from the Philippines, small and developing countries must be enabled to move from consultation to active participation and leadership, through funding, platforms, and deliberate inclusion. We are often impacted, but not shaping the rules and policies. Non-English and non-Western perspectives, language alone is a barrier to participation. If we're serious about global AI governance, then representation can't be performative. It has to be designed, resourced, and sustained.

1. Cross-Border Policy Labs (working sessions, not panels), small, diverse groups (government, industry, civil society, Global South reps) co-develop solutions to a specific issue (bias, AI safety). Output: draft playbooks or recommendations not just discussion. 2. Reverse Panels (Voices from the Ground First). start with frontline voices SMEs, affected communities, Global South practitioners before policymakers respond. This flips the usual power dynamic. 3. Participants simulate real AI deployment scenarios (launching an AI tool across regions) and work through governance decisions in real time. This makes trade-offs visible and practical. 4. Run parallel regional dialogues (ASEAN, Africa, LATAM), then bring synthesized insights into the global stage. Ensures local realities shape global outcomes.

Something that is practical, embedded, and continuously tested and improved, not on slides, and whitepapers. 1. Minimum Viable Governance (MVG)- instead of waiting for perfect frameworks, start with essential controls, risk identification, human oversight, and accountability, then scale. we've applied this in enterprise settings to enable teams to move fast, while still staying within guardrails. 2. Embedded Governance ("Shift-Left")- governance works best when it's built into the workflow, not reviewed at the end. Examples include integrating Responsible AI checklists into project intake, linking AI use cases to registries, and aligning with existing processes like privacy and vendor assessments. 3. Multi-Stakeholder Sandboxes- real progress happens when policies are tested, not just written. Cross-sector sandboxes where regulators, companies, and communities test AI use cases together help surface real risks, trade-offs, and what actually works across contexts.