Global declarations on AI governance abound—but the real test lies in implementation, much of which is unfolding in cities. Yet local initiatives are rarely monitored or shared across jurisdictions. The AI Localism Repository aims to bridge that gap by spotlighting governance mechanisms developed at the city level.

In this post, we highlight six recent additions to the repository that exemplify the diversity and innovation of AI Localism or city-level AI governance. These examples—spanning from Amsterdam to Bogotá—illustrate how local governments are using distinct mechanisms such as resident panels, action plans, synthetic data frameworks, and AI-assisted public deliberation to shape more responsive, inclusive, and future-proof approaches to AI.

Recent Additions

Amsterdam Vision on AI: Community-Led Principles for AI - In November 2024, Amsterdam released The Amsterdam Vision on AI, which outlines five approaches to responsible AI use by all actors within the city: Human Value, Expert Guidance, Intensive Automation, AI Education, and Equal Access. In creating a shared vision for AI grounded in realism, the city’s IT Alderman states that, “We do not see (AI) as a technology that can replace human intelligence, nor as an existential threat.” Based on a series of community dialogues, the city first uncovered concerns that Amsterdam residents hold with AI, including reliability, neutrality, accessibility, climate impact, and justice. Building on these concerns, the Vision develops three guiding principles - human-centricity, reliability, and future-proofing - that will guide AI use. Amsterdam is currently  using the Vision to develop the AI Agenda, a more robust set of policies for AI use by city employees.

Source: Amsterdam Vision on AI

New York City Artificial Intelligence Action Plan: Centralized Strategy - The New York City AI Action Plan packages seven governance initiatives into one centralized plan to direct the city’s use and control of artificial intelligence. The Action Plan’s concrete measures range from establishing governance groups such as a City AI Steering Committee to guidance documents defining AI Principles to training city staff on skills and duties. Within one year, the city reported that 31 of 37 proposed actions had been started or completed.

Source: New York City Artificial Intelligence Action Plan

Dubai Synthetic Data Framework: Structured and Targeted Guidance - In contrast to New York City and Amsterdam, Dubai’s most recent governance measure shares procedural guidance for a specific technology: synthetic data. A series of decision matrices guide data leaders and stewards within Dubai’s governmental authorities on when, how, and why to use synthetic data. The Framework outlines scenarios for the use of synthetic data, associated risks, and recommendations for privacy preservation. The Framework requires coordination with Dubai’s sandbox before the publication and sharing of synthetic data.

Source: Dubai Synthetic Data Framework

Camden Data Charter: Resident Panels for Data Visioning - Camden’s Data Charter outlines principles by which the London Borough of Camden collects and shares data responsibly. Camden Council developed and revised the Data Charter through facilitator-supported Resident Panels. To create the Charter’s Principles, a representative group of residents responded to sample data use scenarios and proposed AI-incorporating activities. The revised principles guide Camden’s future data activities, including all AI use, by highlighting transparency, accountability, oversight, privacy, and outcomes-orientation, among other values. The Charter also establishes governance structures to oversee the Council’s short- and long-term procedural commitments towards putting the Charter into action.

Source: Camden Data Charter

Bogotá’s Data Infrastructure and Governance Model - Bogotá’s data infrastructure decree establishes a governance model for the “data ecosystem” within Colombia’s capital district. The model creates procedures and structures to align data standards and services across the city, as well as guiding principles for cooperation in data collaboration with private companies and public agencies. Aligning with the principles of Colombia’s national model, the model establishes strategic, tactical, and operational roles, as well as an oversight committee. A district-wide data coordinator is charged with making sure that Bogotá’s actions fall in line with national AI plans. Emphasis is placed on privacy and interoperability within the data infrastructure, which covers artificial intelligence technologies. The model governs the actions of AGATA, a public cost-recovering agency that provides artificial intelligence strategy and analysis for public and private stakeholders within the city.

AI for AI? Washington D.C.’s AI Public Listening Session - Washington D.C. is one of the pioneering cities in establishing values that guide and bound the use of artificial intelligence. In order to operationalize these values, Mayor Muriel Bowser established an Advisory Group on AI Values Alignment composed of experts and members of the public. This advisory group holds public listening sessions, and, for the first time on July 15, 2025, used an artificial intelligence tool to gather feedback during the listening session. If deemed successful, the tool, deliberation.io, will be rolled out for use in other agencies to “support large-scale open dialogue between residents and help the district gather feedback." 

Themes and Takeaways

1. Strengthening and Deepening Governance in Pioneer Cities: Pioneer cities such as New York City and Amsterdam are implementing new governance measures to root AI governance in resident’s values while also broadening city-level focus. Amsterdam’s Vision sits on top of a host of narrower governance measures, and New York City’s Action Plan builds on a previous AI primer and AI strategy. 

2. AI Governance Measures Are Not Inflexible: Because artificial intelligence is a dynamic technology and governance practices are still novel, these newest governance measures are designed to be revised frequently. As New York City’s Action Plan states, “As the technology develops further, and as governance measures and regulatory practices begin to emerge across the field, the city’s efforts will need to be iterative and ongoing.” Rather than responding to technology changes, Camden’s Data Charter takes a more resident-led approach that establishes commitments to periodic revision through Resident Panels.

3. AI Governance Measures Incorporate and Foster Engagement: Cities are developing governance measures through varying mechanisms and levels of public engagement. Camden and Amsterdam both used structured dialogues and focus groups to understand community values on technology as well as perceptions and wishes towards artificial intelligence. New York City committed to holding public listening sessions where New Yorkers shared AI-related priorities and concerns. At the same time, cities do differ in their operationalization of “public engagement.” New York and Washington D.C. are focused on socializing AI policies, while Amsterdam and Camden chose design-led engagement in addition to consultative feedback.

These snapshots show how cities of all sizes are setting and refining governance measures for the responsible deployment of artificial intelligence. For a deeper explanation of AI Localism, read our report AI Localism in Practice: Examining How Cities Govern AI. Do you know of an AI Localism measure that should be added to the repository? Use the form on our website to share examples of AI Localism or to express your interest in collaborating with us on the AI Localism program.