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A successful first Global Dialogue on AI Governance must transcend theoretical frameworks and deliver tangible, actionable outcomes that bridge the gap between Global North and Global South. In my view, success would be defined by the following three pillars:1. Inclusive Multistakeholder Alignment: Beyond high-level principles, success means establishing a formal mechanism for ongoing participation of civil society and academia from the MENA and SWANA regions. As an AI Governance expert, I believe true success is achieving a 'Global Consensus' that reflects the cultural and socio-political nuances of non-Western contexts, ensuring AI ethics are not one-size-fits-all but human-centric and globally representative. 2. Operationalization of Ethics (The GRC Bridge): The dialogue succeeds if it moves from 'What' to 'How.' A concrete outcome would be a unified roadmap for operationalizing AI Governance, Risk, and Compliance (GRC) standards that SMEs and emerging startups in developing nations can realistically implement. This includes practical tools for algorithmic bias mitigation and technical transparency that are accessible and scalable. 3. Accountability and Safeguards for Vulnerable Populations: Success is measured by the establishment of robust safeguards for high-impact AI use cases in healthcare and education. The dialogue should result in a commitment to 'Responsible Innovation' that protects digital rights and prevents the deepening of the geographic digital divide.Ultimately, the dialogue will be a success if it creates a permanent, transparent platform for knowledge sharing, like an 'AI Governance Repository', that empowers local experts to lead the implementation of ethical AI within their own sovereign borders.

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

Based on my professional trajectory and current academic focus, my selection is driven by the necessity to move from high-level AI principles to measurable, human-centric implementation.Transparency, Accountability, and Human Oversight: As an expert in AI GRC, my primary focus is operationalizing governance. I currently translate complex ethical requirements into actionable Codes of Conduct and conduct algorithmic bias audits to ensure technical transparency and rigorous oversight in enterprise AI deployment.AI Capacity-Building: Bridging the geographic representation gap is central to my work. Through AI Minds Academy, I have trained over 450 learners in the MENA region, and as an Academic Lecturer, I develop curricula that empower students to navigate the societal implications of AI.Social, Economic, Ethical, Cultural, Linguistic, and Technical Implications: My research, including collaborations with Columbia University, analyzes the socio-technical impacts of AI on vulnerable populations. I prioritize aligning AI development with the specific socio-political and linguistic contexts of the SWANA region to ensure cultural relevance and equity.Protection and Promotion of Human Rights: My career is rooted in advocacy and the alignment of technology with human rights principles. Whether evaluating national AI strategies in Qatar or researching digital sovereignty, I focus on ensuring that AI serves as a tool for restoring rights rather than exacerbating existing inequalities.These areas represent the intersection of my technical expertise in risk management and my commitment to inclusive, responsible innovation.

As an expert in AI Governance with a Ph.D. in AI Management, I believe several critical emerging issues require more focused attention to ensure a truly global and equitable governance framework.1. AI Sovereignty and Digital ColonialismCurrent global dialogues often overlook the risk of "digital colonialism," where the Global South provides data and labor while the Global North retains intellectual property and strategic control. True success in governance must include the right to AI Sovereignty, allowing nations to develop and govern AI systems that reflect their specific cultural, linguistic, and socio-political values without being entirely dependent on external proprietary models.2. Environmental Sustainability and Resource EquityThe environmental cost of training and maintaining Large Language Models (LLMs) including massive water consumption for cooling and high energy demands is a cross-cutting crisis. Governance must address the "sustainability gap," ensuring that the environmental burden of AI does not disproportionately fall on developing regions that may not yet fully benefit from the technology's economic outputs.3. Crisis-Specific AI GovernanceBased on my research into AI's role in conflict zones and humanitarian crises, there is an urgent need for protocols governing AI in high-stakes, unstable environments. This includes preventing the use of AI for automated misinformation or surveillance in vulnerable regions and ensuring that AI serves as a tool for restoring rights and providing essential services during crises.4. Algorithmic Redress and Recourse MechanismsWhile accountability is often discussed, we lack global standards for effective recourse. When an automated system denies a person a visa, a medical treatment, or a job, there must be a clear, cross-border mechanism for human-led appeal and redress that is accessible to individuals regardless of their technical literacy or geographic location.

In my sector (AI GRC and Academia) and the MENA region, the current governance gaps create a dichotomy between rapid technological adoption and lagging regulatory maturity.Significant ChallengesOperationalization Gap: While high-level ethical principles exist, there is a lack of technical standards to translate them into practice. In my work with the Global AI Responsible Index, I have observed that organizations often struggle to move from "ethical intent" to "algorithmic accountability," leaving high-impact sectors like healthcare and education vulnerable to unmitigated bias.Geographic and Linguistic Underrepresentation: Most governance frameworks are developed in the Global North, often failing to account for the socio-political and linguistic nuances of the SWANA region. This leads to "imported" ethics that may not address local risks such as digital sovereignty or regional misinformation.Capacity Deficit: There is a critical shortage of professionals who can navigate the intersection of law, policy, and AI technicalities, which hinders the effective implementation of risk controls.Strategic OpportunitiesRegional Leadership: Countries like Qatar and Oman are actively seeking to align their AI strategies with global standards while maintaining national visions (e.g., Oman Vision 2040), creating a unique opportunity for bespoke governance models.Academic-Industry Synergy: My work at AI Minds Academy and Yeni Yüzyıl University demonstrates a growing appetite for specialized AI literacy. This represents an opportunity to build a "bottom-up" governance culture where fairness and transparency are integrated into the workforce's DNA.Standardization as a Catalyst: Closing these gaps through interoperable frameworks can turn responsible AI into a competitive advantage, fostering trust and accelerating the safe deployment of proprietary LLMs across the region.

The AI Dialogue serves as a critical bridge between high-level international policy and the localized, technical implementation of AI governance. Drawing from my experience in the MENA region and my research collaborations, I believe the Dialogue can advance international cooperation through three primary functions:Standardizing "Operational" Governance: The Dialogue can move global discourse beyond abstract ethics toward a unified framework for AI Governance, Risk, and Compliance (GRC). By establishing interoperable standards for bias mitigation and technical transparency, it allows organizations in different jurisdictions to align their proprietary LLM development with a common global baseline.Fostering Knowledge Equity: It provides a platform to bridge the "representation gap" by integrating insights from diverse regions, such as the SWANA and MENA contexts. This ensures that international cooperation is not a top-down mandate but a collaborative exchange where regional experts share best practices on digital sovereignty and socio-technical impacts.Formalizing Multi-Stakeholder Accountability: The Dialogue can institutionalize cooperation between academia, industry, and government. For example, my work with the Global AI Responsible Index demonstrates how independent evaluation of governmental AI initiatives can drive national policy toward global ethical alignment.Ultimately, the AI Dialogue can transform fragmented national strategies into a cohesive global roadmap, ensuring that AI development remains human-centered and accountable across all borders

The AI Dialogue should strategically converge with existing frameworks to avoid duplication and enhance global interoperability. Based on my professional experience in AI GRC and regional strategy, the Dialogue should build upon the following:Core Initiatives to Build UponThe Global AI Responsible Index (GIRAI): Having served as a consultant for GIRAI in Qatar, I have seen how this mechanism provides a data-driven baseline for evaluating governmental and non-governmental AI maturity. The Dialogue can use these indices to identify specific governance gaps in the Global South.OECD AI Principles & EU AI Act: These serve as the current "gold standard" for risk-based classification. The Dialogue should connect these with regional frameworks like Oman Vision 2040 to ensure global standards are culturally and economically scalable.UNESCO Recommendation on the Ethics of AI: This is vital for its focus on human rights and dignity, which aligns with my research on AI's impact on vulnerable populations in the MENA region.Academic-Private Partnerships: Initiatives like my collaboration with the Columbia University Research Center provide the socio-technical evidence needed to ground policy in reality.The Added Value of the AI DialogueThe unique value of this Dialogue lies in its ability to act as a Global Operationalizer. While existing forums often remain at the "principle" level, the AI Dialogue can:Harmonize LLM Governance: Create a unified approach to the risks associated with proprietary and open-source Large Language Models.Democratize Participation: Provide a formal seat for entities like AI Minds Academy, ensuring that practitioners from underrepresented regions influence the global roadmap.Cross-Sectoral Synthesis: Bridge the gap between media, law, and technical engineering sectors I currently navigate as an academic lecturerm to create a holistic governance language

To ensure the Global Dialogue on AI Governance is truly inclusive and impactful, the format must shift from a traditional top-down assembly to a collaborative, multi-layered ecosystem. Drawing from my dual experience as an Academic Lecturer and an AI GRC expert, I recommend the following structure:Stakeholder ContributionsAcademia & Research: Should provide the socio-technical evidence base. For example, my research with Columbia University on AI in healthcare and education highlights how localized data can inform global ethics.Private Sector & SMEs: Must focus on the operationalization of GRC. Small enterprises and startups from regions like MENA need a platform to discuss the practicalities of compliance without stifling innovation.Civil Society: Acts as the human rights watchdog, ensuring that governance frameworks prioritize the protection of vulnerable populations and digital sovereignty.Recommended Format and StructureHybrid "Living Labs" Sessions: Move beyond speeches to interactive workshops. Utilizing the "Living Lab" model which I have engaged with through AI Minds Academy's partnerships allows stakeholders to co-create policy prototypes in real-time.Regional Technical Briefings: Before the Geneva session, the Dialogue should hold virtual regional consultations (e.g., SWANA-specific tracks) to ensure that linguistic and cultural nuances are integrated into the final report.The "Governance Repository" Track: A dedicated stream for sharing Open-Source Governance Tools. As someone who created a repository for 3,450 organizations, I believe a shared digital library of "Ethical Codes of Conduct" would provide immediate value to developing nations.Intergenerational Panels: Include youth and learners, such as the 450+ individuals trained at my academy, to ensure the dialogue addresses the long-term educational and economic shifts caused by AI

Drawing from my eight years of experience bridging the geographic representation gap, I believe the most significant underrepresented perspectives are those from the Global South, particularly the SWANA (South West Asia and North Africa) region.Underrepresented PerspectivesNon-Western Cultural and Linguistic Frameworks: Current global AI ethics are often "one-size-fits-all" and fail to account for the specific socio-political and linguistic nuances of the Arab world.Vulnerable Populations in Conflict Zones: There is a lack of discourse on the socio-technical impacts of AI on marginalized groups in high-stakes environments, such as healthcare and education in Gaza.Local AI Practitioners and SMEs: Small-to-medium enterprises in developing economies are often excluded from high-level GRC (Governance, Risk, and Compliance) discussions, despite being the primary implementers of these technologies.Women and Gender-Diverse Groups in Emerging Tech: My research on gender bias in AI highlights a persistent gap in how AI governance addresses the unique risks faced by women in the era of automated decision-making.Pathways for InclusionRegionalized Governance "Living Labs": Establishing localized hubs, similar to my work with AI Minds Academy, to co-create policy prototypes that reflect sovereign digital rights.Formalized Knowledge Repositories: Creating accessible platforms for regional experts to contribute data-driven insights, ensuring that "Responsible AI" is not a top-down mandate but a collaborative global standard.Multilingual Participation Tracks: Offering the Dialogue in native languages like Arabic and Turkish to dismantle linguistic barriers that prevent local academics and civil society leaders from engaging in global forums.By moving beyond symbolic inclusion toward structural participation, the AI Dialogue can ensure that the future of technology is truly human-centered and globally equitable.

To foster dynamic and meaningful engagement, the AI Dialogue should move away from static presentations and toward iterative, collaborative formats that bridge the gap between policy and practice. Drawing from my experience in establishing AI Minds Academy and my work with Living Labs, I recommend the following innovative formats:Policy "Living Labs" & Sandboxes: Instead of theoretical debates, stakeholders can engage in real-time "regulatory simulation" exercises. These sessions allow participants to apply draft governance frameworks to hypothetical high-impact AI use cases in sectors like healthcare or education to identify unforeseen ethical risks before finalization."Reverse Pitching" for Governance: Traditional panels can be replaced by sessions where policymakers "pitch" a governance challenge (e.g., mitigating algorithmic bias) to a diverse group of technical experts and civil society leaders, who then provide rapid, multi-perspective solutions.Decentralized Regional Hubs (The Hybrid Model): Utilizing virtual "satellite" sessions in native languages—such as Arabic or Turkish—ensures that the Dialogue is not limited by geography or language, allowing local practitioners to contribute directly to the Geneva plenary.The "Governance Repository" Hackathon: A dedicated track where participants co-create open-source tools, such as standardized Ethical Codes of Conduct or GRC templates, providing immediate, tangible value for SMEs and developing nations.Intergenerational "Visioning" Circles: Facilitating structured dialogues between senior leaders and the "AI generation" students and young learners to ensure long-term accountability and focus on the future of human-centered technology.These formats transform the Dialogue from a one-time event into a continuous, participatory ecosystem that reflects the fast-paced nature of AI evolution.

Effective AI governance requires a transition from high-level principles to practical, risk-based frameworks that account for regional specificities. Based on my work in the MENA region and AI GRC, the following examples offer concrete solutions:National AI Maturity Assessments (GIRAI): During my consultancy for the Global AI Responsible Index in Qatar, I utilized a structured methodology to evaluate governmental AI initiatives against ethical benchmarks. This practice identifies specific "maturity gaps" in oversight and accountability, providing a roadmap for policy updates.Operationalizing Ethical Codes of Conduct: In my current role, I translate abstract governance requirements into actionable operational policies. By conducting algorithmic bias audits and ethical impact evaluations, organizations can mitigate risks during the deployment of proprietary LLMs.Capacity-Building via "Living Labs": Through AI Minds Academy, I have leveraged partnerships with the European Network of Living Labs to foster AI literacy. This "bottom-up" approach ensures that practitioners understand the socio-technical impacts of AI before deployment.Multistakeholder Research Collaborations: My collaboration with Columbia University serves as a model for grounding AI policy in evidence-based research, specifically focusing on the healthcare and education sectors within the SWANA region.Sector-Specific Regulatory Sandboxes: My experience at Yeni Yüzyıl University involves teaching students how to apply regulatory frameworks to media and law, demonstrating that governance must be tailored to the unique risks of each sector.These practices demonstrate that effective governance is achieved through a combination of independent evaluation, technical auditing, and inclusive education.