Ipioneer

In my view, the success of the first Global Dialogue on AI Governance should not be measured solely by the number of participating states or high-level declarations issued in Geneva. Its true success will depend on whether it creates a genuinely inclusive governance process in which developing countries are able to shape - rather than adopt — the future rules of artificial intelligence. As a Legal Consultant in AI Governance and Intellectual Property from Egypt and the MENA region, I see a critical gap in current global discussions: the voices of emerging markets, legal practitioners, startups, and underrepresented linguistic communities remain structurally limited within international AI policymaking. A successful Dialogue should therefore ensure that Global South perspectives are substantively reflected in the Co-Chairs' Summary and future governance mechanisms. One of the most important outcomes would be the formal recognition of the intersection between Artificial Intelligence and Intellectual Property as a core governance issue. Questions surrounding AI-generated works, inventorship, training data, copyright, and cross-border enforcement are no longer theoretical concerns; they are already affecting innovators, creators, and startups across developing economies. The Dialogue should also prioritize legal and regulatory capacity-building alongside technical AI development. Many countries are being asked to comply with frameworks they had little role in designing, while lacking the institutional infrastructure necessary for implementation. Finally, I believe the Dialogue would be truly successful if it establishes a long-term, multi-stakeholder process that includes not only governments and major technology companies, but also legal experts, civil society, startups, and regional innovators from Africa, the Arab world, and other underrepresented regions. AI governance must become globally representative if it is to become globally legitimate.

• Social, economic, ethical, cultural, linguistic and technical implications of AI
• Safe, secure and trustworthy AI
• Open-source software, open data and open AI models
• Protection and promotion of human rights

From my perspective as a Legal Consultant in AI Governance and Intellectual Property and Founder of iPioneer in Egypt, these thematic priorities reflect the most urgent governance challenges facing the MENA region and the broader Global South in the age of artificial intelligence. "Safe, secure and trustworthy AI" is a critical priority because many developing countries are rapidly adopting AI systems without sufficiently developed legal, regulatory, or institutional safeguards. Trustworthy AI cannot be achieved through technical standards alone; it also requires transparent governance frameworks, accountability mechanisms, and accessible legal protections for individuals and businesses. I also selected the social, economic, ethical, cultural, linguistic, and technical implications of AI because AI systems are not culturally neutral. Many existing AI models underrepresent Arabic language content and often embed assumptions shaped primarily by Western datasets and governance approaches. This raises important concerns regarding linguistic inclusion, cultural diversity, and equitable participation in the AI-driven digital economy. The protection and promotion of human rights is equally essential. Across many regions, including the MENA region, AI technologies are increasingly influencing access to information, employment, legal services, and digital rights. Ensuring human oversight, transparency, fairness, and due process must remain central to international AI governance discussions. Finally, I selected open-source software, open data, and open AI models because equitable access to AI innovation is fundamental for emerging economies. Open and accessible AI ecosystems can help reduce technological dependency, support local innovation, strengthen research capacity, and enable startups and legal innovators in developing countries to participate more meaningfully in global AI development. Together, these priorities reflect the need for a more inclusive, balanced, and globally representative AI governance framework.

Yes. One important cross-cutting issue that remains insufficiently addressed in current international AI governance discussions is the intersection between Artificial Intelligence and Intellectual Property (AI-IP Governance). While existing thematic areas address safety, human rights, and technical development, they do not fully capture the growing legal uncertainty surrounding ownership, authorship, inventorship, training data rights, and the commercialization of AI-generated outputs. From my perspective as a Legal Consultant in AI Governance and Intellectual Property working in the MENA region, this governance gap is already creating practical challenges for startups, innovators, legal practitioners, and policymakers in developing economies. Questions such as who owns AI-generated content, whether AI-assisted inventions are patentable, and how copyrighted materials may be used in AI model training remain fragmented across jurisdictions and lack internationally coordinated standards. Another emerging issue is the widening "governance divide" between countries that actively shape global AI norms and those that are expected to implement frameworks designed elsewhere. Many developing countries currently lack the legal infrastructure, regulatory capacity, and institutional participation necessary to engage meaningfully in international AI standard-setting processes. As a result, they risk becoming norm-takers rather than norm-makers in the future AI ecosystem. I also believe that linguistic and cultural representation in AI systems deserves stronger recognition as a governance issue rather than solely a technical challenge. Underrepresentation of languages such as Arabic within AI models can affect access to knowledge, digital participation, and cultural preservation for hundreds of millions of people. Addressing these cross-cutting issues will be essential to ensuring that global AI governance frameworks are not only technologically advanced, but also equitable, inclusive, and internationally representative.

From the perspective of the MENA region and my work as a Legal Consultant in AI Governance and Intellectual Property, the current gaps in global AI governance are already having visible legal, economic, and institutional impacts across emerging markets. One of the most significant challenges is the absence of clear and harmonized legal frameworks governing AI-generated works, AI-assisted inventions, data usage, and accountability mechanisms. Many startups and innovators in Egypt and the broader MENA region are rapidly adopting AI technologies while operating in an environment of regulatory uncertainty. This creates barriers to investment, limits trust in AI-driven innovation, and leaves businesses exposed to cross-border legal risks when interacting with international markets. Another major challenge is the governance imbalance between developed and developing economies. AI governance frameworks are increasingly being shaped in jurisdictions such as the European Union and the United States, while many countries in the Global South have limited participation in standard-setting discussions despite being directly affected by these rules. As a result, businesses and policymakers in the region are often required to comply with external frameworks they had little role in designing. The underrepresentation of Arabic language datasets and culturally relevant AI systems also remains a significant concern. This affects not only technical performance, but also digital inclusion, access to knowledge, and cultural representation within AI ecosystems. At the same time, these developments present important opportunities. The MENA region has a young, digitally engaged population and rapidly growing technology ecosystems. With the right governance frameworks, legal infrastructure, and regional cooperation, AI can become a catalyst for innovation, entrepreneurship, legal modernization, and economic diversification across the region. In my view, the current moment represents a critical opportunity for developing countries to participate more actively in shaping inclusive and globally representative AI governance frameworks rather than adapting to them after they are established.

The Global Dialogue on AI Governance is uniquely positioned to serve as the world's first truly inclusive multilateral platform for AI governance — not simply another forum dominated by technologically advanced nations, but a space where the Global South genuinely shapes the rules governing a technology that affects every country on earth. From the perspective of Egypt and the MENA region, the Dialogue can advance international cooperation in three concrete ways. First, as a norm-bridging platform. Dozens of national and regional AI governance frameworks currently exist in parallel — the EU AI Act, GCC regulatory initiatives, African Union frameworks, and others — with minimal interoperability. The Dialogue can serve as the connective tissue that identifies commonalities, surfaces contradictions, and builds shared understanding across these frameworks, reducing the compliance burden on innovators in developing countries who must navigate multiple systems simultaneously. Second, as a standard-setting initiator. Critical governance gaps — particularly at the intersection of AI and intellectual property — remain unaddressed by any single body. The Dialogue can formally mandate cross-agency workstreams, inviting WIPO, UNESCO, and ITU to jointly develop frameworks on AI-generated works, inventorship, and training data rights. No existing forum currently owns this mandate. Third, as a trust-building mechanism. Meaningful international cooperation on AI governance requires trust — and trust requires that developing countries not merely receive governance frameworks designed elsewhere, but actively participate in designing them. The Dialogue can institutionalize this by ensuring that the Co-Chairs' summaries reflect Global South priorities, that capacity-building includes legal and regulatory expertise alongside technical skills, and that future editions expand representation from underrepresented regions including the Arab world and Africa.

Several existing initiatives provide important foundations that the Dialogue should connect with rather than duplicate. UNESCO's Recommendation on the Ethics of Artificial Intelligence (2021) is the first globally adopted normative framework on AI ethics, emphasizing cultural diversity, inclusiveness, and equitable participation. The Dialogue should actively build on this foundation, translating its principles into concrete governance mechanisms — particularly for underrepresented regions and languages. WIPO's ongoing conversations on generative AI and intellectual property address the critical and growing gap around AI-generated works, inventorship, and training data rights. The Dialogue adds value here by providing the political mandate and multi-stakeholder legitimacy to accelerate WIPO's work into binding or harmonized international frameworks — something WIPO alone cannot compel. The UN Global Digital Compact establishes high-level commitments on digital inclusion and AI governance. The Dialogue serves as the primary implementation pathway for translating those commitments into actionable cooperation — particularly for developing countries that lack the institutional capacity to implement the Compact's principles unilaterally. The OECD AI Policy Observatory provides valuable comparative data on national AI governance approaches. The Dialogue adds value by extending this work to non-OECD countries — particularly in Africa and the Arab world — ensuring that comparative governance analysis reflects the full spectrum of global realities, not only advanced economies. The ITU AI for Good Summit, held alongside the Dialogue, offers a natural bridge between technical innovation and policy governance. This co-location should be leveraged deliberately — not just logistically — by ensuring that technical insights from AI for Good directly inform the Dialogue's thematic discussions. The Dialogue's unique added value lies in its universality: it is the only forum with the mandate, convening power, and legitimacy to bring all of these threads together under a single UN roof.

Meaningful multi-stakeholder contribution requires more than open-door access — it requires deliberate structural design that enables substantive input from actors with very different capacities, time zones, languages, and institutional resources. On stakeholder roles: Governments bring legislative authority and national mandates. The private sector — particularly Legal Tech and AI platform builders like IPioneer — brings implementation experience and direct visibility into where governance frameworks succeed or fail on the ground. Civil society represents the populations most affected by AI deployment. Academia provides independent evidence. The technical community translates policy intent into technical standards. Each of these roles is distinct and the Dialogue's format should preserve space for all of them — not flatten them into a single "stakeholder" category during plenary sessions. On format recommendations: The Dialogue should adopt a pre-Dialogue written input process — as it has done — but go further by publishing synthesized summaries of submissions before the event so that in-person discussions build on, rather than repeat, what stakeholders have already submitted. Thematic breakout sessions should be co-chaired by a developing country representative and a non-governmental stakeholder — not merely moderated by them. This signals genuine co-ownership rather than symbolic inclusion. A dedicated Legal and Regulatory track should be introduced alongside the existing technical and policy tracks. AI governance is fundamentally a legal challenge, yet legal practitioners, IP specialists, and regulatory experts from developing countries are systematically absent from current AI governance forums. Finally, the Dialogue should commit to publishing a multilingual summary of outcomes — at minimum in the six UN languages — within 30 days of the event. Governance that cannot be read by those it governs is not inclusive governance.

The most significant representation gap in global AI governance is not simply geographic — it is structural. The voices missing are not just from certain countries; they are from certain types of actors within those countries. Legal practitioners and IP specialists from the Global South are almost entirely absent from AI governance forums. Yet AI's most consequential governance questions — who owns AI-generated works, who is liable when AI causes harm, how contracts and regulations apply to autonomous systems — are fundamentally legal questions. The absence of lawyers, judges, and IP professionals from developing countries means that the frameworks being designed will be unimplementable in their legal systems. Arabic, Swahili, Hindi, and other non-English speaking communities are structurally excluded by the language of AI governance itself. With more than 400 million Arabic speakers globally and Arabic severely underrepresented in AI training datasets, Arab communities are simultaneously the most affected by AI's linguistic gaps and the least represented in discussions about fixing them. Inclusion requires not just translation of documents, but Arabic-language consultation processes, Arabic-speaking panelists, and Arabic-language AI governance resources. Small and medium enterprises (SMEs) and startups in emerging markets are the entities most directly shaped by AI governance decisions — and least represented in making them. Platforms like iPioneer exist precisely to bridge this gap, translating global governance frameworks into actionable guidance for innovators who cannot afford to engage international policy processes directly. Concrete inclusion mechanisms: regional pre-consultations in Arabic, French, and Swahili before each Dialogue edition; travel fellowships explicitly reserved for legal and IP practitioners from developing countries; a permanent stakeholder advisory group with mandatory seats for Global South civil society and Legal Tech innovators.

The risk with a two-day high-level dialogue is that it becomes a series of prepared statements with little genuine exchange. Avoiding this requires deliberate innovation in format — not just in content. Governance stress-testing sessions: Rather than panel discussions where speakers present polished positions, the Dialogue should introduce structured scenario exercises where participants — governments, civil society, industry, and legal experts — are presented with a concrete AI governance dilemma and asked to work through it in real time. For example: "An AI system developed in China is deployed in Egypt and causes harm to a Sudanese citizen. Which governance framework applies? Who is liable? What international mechanism resolves this?" These sessions surface real disagreements and produce more actionable insights than abstract position statements. Global South solution showcases: Allocate dedicated time — not as a side event, but in the main programme — for innovators, legal practitioners, and policymakers from developing countries to present governance solutions they have developed locally. iPioneer's AI–IP advisory framework for MENA startups is one example of a ground-up governance innovation that deserves main-stage visibility. This inverts the usual dynamic where Global South participants respond to frameworks designed elsewhere. Structured cross-regional peer dialogue: Pair delegations from different regions — for example, Egypt with a Southeast Asian country, or Nigeria with a Latin American nation — for facilitated bilateral exchanges on shared governance challenges. These conversations often generate more genuine learning than large plenary sessions. A live gap-mapping exercise: On Day 2, convene a moderated session where participants collectively map the governance gaps that the Dialogue has identified but not yet resolved — creating a transparent, publicly available "unfinished business" document that directly shapes the 2027 agenda. This transforms the Dialogue from a one-time event into a living, accountable process.

Effective AI governance does not emerge from declarations alone - it requires concrete policies, operational platforms, and on-the-ground practices that translate principles into implementation. The following examples, drawn from global and regional experience, illustrate what works and why. The EU AI Act (2024) represents the most comprehensive binding regulatory framework for AI to date, introducing a risk-based tiered approach that distinguishes between unacceptable, high, limited, and minimal risk AI applications. Its value lies in forcing regulators to be specific rather than aspirational. However, its implementation burden disproportionately affects smaller jurisdictions and developing countries that must comply without equivalent institutional capacity - a lesson the Global Dialogue must internalize. The UNESCO Recommendation on the Ethics of AI offers the first globally adopted normative framework, emphasizing cultural diversity, human rights, and equitable participation. Unlike binding treaties, its soft-law nature has enabled broader adoption - including by MENA countries - making it the most geographically inclusive AI governance instrument currently in existence. The OECD AI Policy Observatory provides a practical comparative platform tracking national AI strategies, regulations, and incidents. Its value is transparency and benchmarking - enabling policymakers to learn from peers. Extending this observatory's scope to fully include African and Arab countries would significantly enhance its global utility. iPioneer - Egypt / MENA Region offers a ground-up example of AI governance in practice: a Legal Tech platform that translates complex AI regulatory frameworks into accessible legal intelligence tools for startups and SMEs in emerging markets. By bridging the gap between international governance principles and local legal realities - covering AI-generated IP ownership, cross-border compliance, and Arabic-language regulatory guidance - iPioneer demonstrates that effective governance requires implementation layers that international bodies alone cannot provide. These examples collectively illustrate that effective AI governance requires diversity of approaches: binding regulation, normative frameworks, comparative observatories, and practical implementation platforms - working in concert.