Where will the AI Policy Summit be held?

The AI Policy Summit will take place in Zurich, CHE.

When is the AI Policy Summit scheduled?

The summit is scheduled for the end of September.

What is the primary focus of the AI Policy Summit?

The summit focuses on the governance, ethics, and societal impact of artificial intelligence, aiming to foster international cooperation and develop frameworks for responsible AI development and deployment.

AI Policy Summit 2026

Name: AI Policy Summit 2026
Start: 2026-09-29T00:00:00Z
End: 2026-09-30T00:00:00Z
Location: Zurich

Sep 29–30, 2026Zurich, SwitzerlandIn-person

Registration open

The AI Policy Summit convenes in Zurich, CHE, to address the multifaceted implications of artificial intelligence on global policy. This event serves as a critical forum for policymakers, researchers, and industry leaders to engage in discussions surrounding the governance, ethics, and societal impact of AI technologies. The summit aims to foster international cooperation and develop frameworks for responsible AI development and deployment.

Committees & topics

Topics
Governing the Rise of Artificial Intelligence · Public Policy Frameworks for Emerging Technology · Societal Engagement in AI Decision-Making · International AI Governance Architecture · Digital Rights in the AI Era · Algorithmic Accountability and Redress · AI-Enabled Surveillance and Civil Liberties

Why it matters

The rapid advancement of artificial intelligence presents both unprecedented opportunities and significant challenges for societies worldwide. From economic disruption to national security concerns, the decisions made today regarding AI policy will shape the future trajectory of human development. This summit is crucial because it brings together diverse perspectives to navigate these complex issues, ensuring that AI's evolution is guided by principles of fairness, transparency, and accountability.

Effective AI policy requires a nuanced understanding of technological capabilities, ethical considerations, and geopolitical dynamics. The discussions in Zurich will contribute to shaping international norms and standards, preventing a fragmented regulatory landscape that could hinder innovation or exacerbate global inequalities. By facilitating dialogue among key stakeholders, the summit aims to bridge the gap between technological progress and responsible governance, fostering a future where AI serves humanity's best interests.

How to prepare

Delegates preparing for the AI Policy Summit should focus on understanding the current global landscape of AI regulation, including initiatives and debates in major technological hubs like USA, CHN, and the European Union. A strong grasp of the ethical dilemmas posed by AI, such as bias in algorithms and privacy concerns, will be essential. Reviewing concepts like "data governance" and "algorithmic amplification" from the glossary will provide a solid foundation for discussions.

Consider how different national interests and values might influence approaches to AI policy. For instance, countries with strong data protection laws might advocate for stricter regulations, while those prioritizing innovation might seek more flexible frameworks. Understanding these varying perspectives, as outlined in lessons like "Engagement Strategies" and "Dynamic Analysis," will be key to constructive participation. Delegates should also be prepared to discuss the potential for an "artificial intelligence arms race" and its implications for international stability.

Country perspectives

Where the most-relevant 5 countries stand on the core issues in play. Click through for the full country profile.

United States

Advocates for innovation-friendly regulation while addressing ethical concerns and national security implications.

Role in topic

A leading developer of AI technology, the USA is focused on maintaining its competitive edge while also grappling with the societal impacts and the need for responsible AI development. Its approach often involves public-private partnerships and sector-specific guidance rather than broad, overarching legislation.

China

Prioritizes national strategic advantage in AI, integrating it into national development plans and surveillance capabilities.

Role in topic

CHN is a major global player in AI development and application, with significant government investment and a focus on integrating AI into various sectors, including public security and economic growth. Its policy approach emphasizes national leadership and data-driven governance.

Switzerland

Promotes a balanced approach, fostering innovation while emphasizing ethical guidelines and international cooperation.

Role in topic

As the host nation, CHE plays a crucial role in facilitating international dialogue on AI policy. Known for its neutrality and strong research institutions, CHE is well-positioned to encourage collaborative efforts in developing ethical and responsible AI frameworks.

United Kingdom

Seeks to become a global leader in responsible AI, balancing economic growth with ethical considerations and public trust.

Role in topic

The GBR has outlined strategies to position itself as a global hub for AI innovation and governance. Its policy focuses on creating a regulatory environment that supports technological advancement while ensuring public trust and addressing potential risks.

Germany

Emphasizes human-centric AI development, focusing on ethical principles, data protection, and social impact.

Role in topic

DEU, as a key member of the European Union, contributes significantly to the bloc's efforts to establish comprehensive AI regulations. Its national strategy prioritizes ethical considerations, data privacy, and the responsible integration of AI into industry and society.

Topics & background

The background behind each topic and the actors that shape it.

Governing the Rise of Artificial Intelligence

Artificial intelligence has moved from a niche research field into a general-purpose technology shaping economies, militaries, and public discourse. The release of large-scale generative models from 2022 onward accelerated regulatory attention, prompting the EU's AI Act (adopted 2024), the U.S. Executive Order 14110 on Safe, Secure, and Trustworthy AI (2023), China's Interim Measures for Generative AI Services (2023), and the UK-hosted Bletchley and Seoul AI Safety Summits (2023-2024). UNESCO's 2021 Recommendation on the Ethics of AI and the 2024 UN General Assembly resolution on safe, secure, and trustworthy AI established the first multilateral baselines. The core disputes concern who sets the rules for frontier models, how to balance innovation against systemic risk, and how compute, data, and talent should be distributed globally. Wealthier states with domestic frontier labs favor voluntary safety commitments and export controls, while many developing countries warn of a widening AI divide. Today states are negotiating whether AI should be governed through existing bodies (ITU, UNESCO, OECD), a new dedicated agency as proposed by the UN High-Level Advisory Body on AI, or sector-specific instruments.

Key players

Public Policy Frameworks for Emerging Technology

States have historically regulated technology reactively, addressing harms after deployment. The pace of AI diffusion has forced governments to develop anticipatory public policy instruments — risk-tiered regulation, regulatory sandboxes, mandatory model evaluations, and public procurement standards. The OECD AI Principles (2019, updated 2024) and the G7 Hiroshima Process Code of Conduct have provided soft-law scaffolding, while the EU AI Act offers the first binding horizontal regime. Key policy disputes include whether to regulate AI applications by sectoral risk or to impose obligations on foundational models themselves, how to align competition policy with concentrated compute markets, and how to fund public-interest AI capacity. Industrial policy has re-emerged as a central tool: the U.S. CHIPS and Science Act, the EU Chips Act, and similar measures in Japan and South Korea reflect a turn toward strategic technology statecraft. Committees are now weighing how to share regulatory learning across jurisdictions and avoid fragmentation that would burden smaller economies.

Key players

Societal Engagement in AI Decision-Making

Concerns that AI policy is being shaped by a narrow set of corporate and technical actors have driven calls for broader societal engagement. UNESCO's Recommendation on the Ethics of AI emphasizes multi-stakeholder participation, and the UN Global Digital Compact (2024) commits members to inclusive digital governance. National experiments include France's Conférence Citoyenne on AI, the UK's public deliberation pilots run by the Ada Lovelace Institute, and Taiwan's vTaiwan and Polis-based consultations. Debate centers on whether participatory mechanisms — citizens' assemblies, red-teaming with affected communities, and worker consultation requirements — should be embedded in binding law or remain advisory. Civil society groups argue that without enforceable engagement requirements, public consultation risks becoming legitimation theater. Developing countries additionally push for meaningful representation in standard-setting bodies such as ISO/IEC JTC 1/SC 42, where participation is currently skewed toward wealthier states.

Key players

International AI Governance Architecture

There is no single international institution responsible for AI. Governance is distributed across the OECD, G7 Hiroshima Process, G20, UNESCO, ITU's AI for Good, the Council of Europe Framework Convention on AI (opened for signature 2024), and the UN system, which in 2024 created a High-Level Advisory Body on AI and adopted the Global Digital Compact. The first UN General Assembly resolutions on AI in 2024 were sponsored by the United States and China respectively, signaling that both powers seek to anchor norms within the UN. The central dispute is institutional: whether to build a new dedicated body (variously framed as an "IAEA for AI," an IPCC-style scientific panel, or a CERN-style research consortium), to strengthen existing agencies, or to rely on plurilateral coalitions. Underlying tensions include U.S.-China strategic competition, EU regulatory leadership versus U.S. innovation primacy, and Global South demands for capacity-building, technology transfer, and equitable governance seats. The Council of Europe's binding treaty and the UN advisory body's recommendations on a global AI fund and data framework are central reference points.

Key players

Digital Rights in the AI Era

Digital rights — privacy, freedom of expression, non-discrimination, and due process online — predate AI but are being stress-tested by it. The ICCPR, the EU Charter of Fundamental Rights, and instruments such as the GDPR and the Council of Europe's Convention 108+ provide the existing baseline. The 2024 OHCHR report on the human rights implications of new and emerging technologies, and successive Human Rights Council resolutions on privacy in the digital age (most recently A/HRC/RES/54/21), have extended these protections to AI-driven systems. Live disputes include whether biometric mass identification should be prohibited, how to enforce data protection extraterritorially, the legality of generative AI training on copyrighted and personal data, and how to safeguard expression against AI-enabled content moderation at scale. Authoritarian and democratic states diverge sharply on whether "digital sovereignty" justifies content controls. Civil society pushes for an explicit right to human review of automated decisions and for cross-border remedies when AI systems cause harm.

Key players

Algorithmic Accountability and Redress

Algorithmic systems now determine access to credit, welfare, housing, employment, and policing. High-profile failures — including the Dutch childcare benefits (toeslagenaffaire) scandal that brought down the Rutte government in 2021, the UK's A-level grading algorithm in 2020, and documented bias in U.S. risk-assessment tools — have made algorithmic accountability a core governance question. The EU AI Act, New York City's Local Law 144 on automated employment decisions, and Canada's Directive on Automated Decision-Making represent first-generation accountability regimes. Debates focus on what accountability concretely requires: mandatory impact assessments, third-party audits, public algorithm registers, explainability standards, liability allocation between developers and deployers, and whistleblower protections for AI workers. The OECD AI incidents monitor and NIST's AI Risk Management Framework offer common vocabularies but are non-binding. A central unresolved question is enforcement — whether existing data-protection and consumer authorities can effectively audit complex models, or whether new specialized regulators are needed.

Key players

AI-Enabled Surveillance and Civil Liberties

AI has expanded the scale, accuracy, and affordability of surveillance. Facial recognition, gait analysis, predictive policing, social-media monitoring, and AI-assisted lawful interception tools have proliferated through state procurement and a global export market. UN Special Rapporteurs have documented misuse of commercial spyware such as Pegasus against journalists and dissidents, and HRC resolutions on the right to privacy in the digital age (A/HRC/RES/42/15 onward) have called for moratoria on certain technologies pending human-rights safeguards. The central disputes concern export controls on surveillance technology (the Wassenaar Arrangement and the U.S.-led Joint Statement on Commercial Spyware signed in 2023), the legitimacy of remote biometric identification in public spaces, the boundary between national-security exemptions and rights protections, and accountability for cross-border surveillance abuses. The EU AI Act's restrictions on real-time biometric identification, China's wide deployment of public-space recognition systems, and ongoing concerns about surveillance in Xinjiang and elsewhere mark the poles of the debate.

Key players