international business and investment union

The success of the first Global Dialogue on AI Governance should be measured by its ability to translate principles into concrete, coordinated global action. A key outcome should be the establishment of a shared baseline framework for AI governance that promotes safety, trust, and interoperability, while respecting national regulatory differences. Such a framework should include common definitions, minimum standards, and risk-based approaches to AI deployment. The Dialogue should also ensure inclusive and meaningful participation from all stakeholders, including developing economies, the private sector, and civil society, enabling them to actively contribute to shaping governance models. Equally important is advancing capacity-building initiatives to support countries and institutions in effectively implementing AI governance, particularly in emerging markets. At the same time, it is essential to address emerging risks associated with AI misuse, including disinformation, deepfakes, and manipulation of public opinion. These challenges require coordinated international responses that reinforce transparency, accountability, and human oversight. Finally, the Dialogue should deliver actionable commitments that strengthen public-private collaboration, enabling responsible innovation while mitigating risks, and ensuring that AI continues to support sustainable economic growth and global stability.

• Safe, secure and trustworthy AI
• AI capacity-building
• Interoperability of governance approaches
• Transparency, accountability, and human oversight

Our selected priorities reflect the need for a balanced, pragmatic, and forward-looking approach to AI governance. Safe, secure, and trustworthy AI is fundamental to building global confidence, particularly in cross-border applications, where trust directly impacts adoption and investment flows. AI capacity-building is critical to ensuring that all countries, especially developing economies, are equipped to participate effectively in the global AI ecosystem. Bridging this gap is essential to preventing digital inequality. Interoperability of governance approaches is necessary to avoid regulatory fragmentation. Harmonized frameworks will facilitate international cooperation, enhance cross-border investment, and enable more efficient deployment of AI technologies. Transparency, accountability, and human oversight are central to maintaining alignment between AI systems and societal values, legal standards, and ethical principles. These elements are essential for mitigating risks, including the misuse of AI in areas such as disinformation and content manipulation. Together, these priorities contribute to a globally coordinated, inclusive, and resilient AI governance ecosystem that supports innovation while safeguarding public trust.

Yes, several cross-cutting and emerging issues merit greater attention beyond the listed themes. One critical area is the governance of AI-driven disinformation and synthetic media. The rapid advancement of generative AI has amplified the risks of large-scale manipulation of public opinion, requiring coordinated global standards for detection, disclosure, and accountability. Another key issue is the economic impact of AI on labor markets and the future of work. While AI drives productivity, it also introduces structural shifts that necessitate reskilling strategies, workforce transition frameworks, and inclusive economic policies. Data governance and ownership also remain underdeveloped areas. Clear frameworks are needed to address data sovereignty, cross-border data flows, and fair access to high-quality datasets, particularly for developing economies. In addition, the concentration of AI capabilities within a limited number of global actors raises concerns around market dominance, access to technology, and equitable participation in the AI ecosystem. Finally, the environmental impact of large-scale AI systems, including energy consumption and resource usage, is an emerging challenge that requires sustainable and responsible innovation strategies. Addressing these cross-cutting issues will be essential to ensuring that AI governance remains comprehensive, forward-looking, and aligned with global priorities. This also highlights the importance of continuous international dialogue and adaptive governance frameworks that can evolve alongside rapidly advancing AI technologies.

In the Gulf region, and particularly in the UAE, rapid advancements in AI adoption have created significant opportunities, but also exposed important governance gaps. One of the key challenges is the pace of technological deployment outpacing regulatory frameworks. While governments are proactive, there remains a need for more harmonized and adaptive regulations that can keep up with fast-evolving AI applications, particularly in areas such as financial services, digital trade, and cross-border transactions. Another challenge relates to data governance, especially in the context of cross-border data flows and data sovereignty. As the region positions itself as a global hub for investment and innovation, the absence of fully aligned international data standards can create uncertainty for businesses operating across jurisdictions. In addition, the misuse of AI technologies, including disinformation and synthetic media, presents emerging risks that could impact market confidence and institutional trust if not addressed through coordinated governance measures. However, these developments also present substantial opportunities. The UAE and the wider region are well-positioned to become global leaders in responsible AI adoption, supported by forward-looking policies, strong digital infrastructure, and strategic investment initiatives. There is also a significant opportunity to establish the region as a bridge between developed and emerging markets by promoting interoperable governance frameworks and facilitating cross-border investment in AI-driven sectors. Strengthening public-private partnerships, enhancing regulatory clarity, and investing in AI capacity-building will be key to unlocking sustainable economic growth and reinforcing the region's position in the global AI ecosystem.

The AI Dialogue can play a pivotal role in advancing international cooperation by serving as a neutral, inclusive platform that aligns diverse stakeholders around shared priorities in AI governance. It can facilitate the development of common principles and promote interoperability between national and regional regulatory frameworks, reducing fragmentation and enabling smoother cross-border collaboration. By fostering dialogue between governments, the private sector, and civil society, it can bridge policy gaps and encourage coordinated responses to emerging challenges. The Dialogue can also act as a catalyst for trust-building among countries by promoting transparency, information sharing, and best practices in AI governance. This is particularly important in addressing global risks such as disinformation, cybersecurity threats, and the misuse of AI technologies. In addition, it can support capacity-building efforts by connecting developed and developing economies, enabling knowledge transfer, technical assistance, and collaborative initiatives. Ultimately, the AI Dialogue has the potential to strengthen multilateral cooperation, accelerate responsible innovation, and contribute to the development of a more coherent, inclusive, and resilient global AI governance ecosystem.

The AI Dialogue should build upon and connect with existing international initiatives and frameworks, including those led by the United Nations, the OECD, the G20, and regional regulatory efforts such as the European Union's AI Act. It should also engage with multi-stakeholder platforms such as the Global Partnership on AI (GPAI), as well as industry-led initiatives that promote responsible AI development and standards. The added value of the AI Dialogue lies in its ability to act as a coordinating mechanism that bridges these efforts, reduces duplication, and enhances coherence across different governance frameworks. Rather than creating parallel structures, it can serve as a convergence point for aligning global standards and facilitating practical implementation. Furthermore, the Dialogue can bring greater inclusivity by ensuring that developing economies and underrepresented stakeholders have a meaningful voice in shaping global AI governance. It can also introduce more flexible and adaptive approaches to governance, allowing frameworks to evolve alongside technological advancements. By connecting existing initiatives and focusing on practical outcomes, the AI Dialogue can strengthen global cooperation, support cross-border investment, and accelerate the responsible deployment of AI technologies.

Different stakeholders can contribute most effectively to the AI Dialogue through a structured, multi-layered engagement model. Governments should provide regulatory direction, align national strategies, and contribute to the development of interoperable frameworks. The private sector should offer practical insights, innovation perspectives, and implementation experience, particularly in high-impact sectors such as finance, healthcare, and digital infrastructure. Civil society and academia should play a critical role in ensuring ethical considerations, social impact assessments, and independent research contributions. To maximize impact, the AI Dialogue should adopt a modular structure combining high-level plenary sessions with specialized working groups focused on key thematic areas. These working groups should produce actionable outputs, such as policy recommendations, best-practice guidelines, and implementation roadmaps. In addition, the Dialogue should establish continuous engagement mechanisms beyond annual meetings, including digital collaboration platforms, regional forums, and public-private task forces. This would ensure that discussions translate into sustained action. A results-oriented structure, supported by measurable outcomes and follow-up mechanisms, will be essential to ensure that stakeholder contributions lead to tangible progress in global AI governance.

Several important voices remain underrepresented in global AI governance discussions. These include developing and emerging economies, particularly in Africa, parts of Asia, and Latin America, where participation is often limited despite being significantly impacted by global AI developments. Small and medium-sized enterprises (SMEs) are also underrepresented, even though they are key drivers of innovation and economic growth. Additionally, perspectives from the Global South, youth communities, and non-technical stakeholders—including legal professionals, policymakers at local levels, and social sector organizations—are often not sufficiently integrated into the conversation. To address this, the AI Dialogue should adopt more inclusive participation mechanisms, such as targeted outreach, regional representation quotas, and capacity-building initiatives that enable meaningful engagement. Providing multilingual platforms, financial support for participation, and accessible digital engagement tools will also be essential to lowering barriers to entry. Ensuring that these voices are included will strengthen the legitimacy, relevance, and effectiveness of global AI governance frameworks.

Innovative engagement formats are essential to foster meaningful and dynamic participation in the AI Dialogue. Hybrid participation models that combine in-person and virtual engagement can significantly expand accessibility and inclusivity. Interactive formats such as real-time policy labs, scenario-based simulations, and multi-stakeholder roundtables can enable participants to collaboratively address complex governance challenges. The use of digital platforms for continuous engagement—such as AI-powered consultation tools, crowdsourced policy input systems, and open feedback mechanisms—can enhance transparency and broaden participation beyond traditional stakeholders. In addition, structured "policy sprints" or time-bound working sessions can accelerate the development of practical solutions and actionable recommendations. Regional dialogue hubs can also play a key role in contextualizing global discussions and ensuring that local perspectives are effectively integrated into global frameworks. By adopting flexible, technology-enabled, and outcome-driven engagement formats, the AI Dialogue can ensure more inclusive, responsive, and impactful global participation.

Effective AI governance is best supported through a combination of regulatory frameworks, practical implementation tools, and multi-stakeholder collaboration models. One notable example is the European Union's AI Act, which adopts a risk-based approach by categorizing AI systems based on their potential impact and applying proportionate regulatory requirements. This model provides clarity for businesses while ensuring safeguards for high-risk applications. Similarly, the OECD AI Principles offer a widely recognized framework that promotes responsible AI development, emphasizing transparency, accountability, and human-centered values. These principles have been instrumental in aligning international policy discussions. In practice, regulatory sandboxes have proven to be highly effective in enabling innovation while maintaining oversight. By allowing controlled testing of AI systems in real-world environments, they help regulators and businesses better understand risks and refine governance approaches. In addition, industry-led initiatives focused on AI ethics, auditing, and standards development play a critical role in complementing formal regulations. These include internal governance frameworks, algorithmic audits, and responsible AI guidelines adopted by leading technology firms. Digital platforms that support transparency-such as AI registries, model documentation standards, and disclosure mechanisms-also contribute to building trust and accountability. A key best practice is the integration of public-private partnerships, which facilitate knowledge exchange, accelerate implementation, and ensure that governance frameworks remain practical and adaptable. Combining regulatory clarity, flexible innovation mechanisms, and collaborative governance models is essential to developing effective, scalable, and future-ready AI governance systems.