City AI Readiness: 
A Deep Dive into Abu Dhabi  
and the Global Landscape

City AI Readiness

Cities are where the impact of AI on everyday life is felt most directly.

Yet efforts to assess AI readiness remain largely focused on national governments. This report asks what AI readiness looks like at the city level, and what cities can learn from one another.

To answer these questions, we took Abu Dhabi as our primary case study: an emirate with the stated ambition of becoming the world’s first AI-native government by 2027. Drawing on in-depth interviews, we examined its AI ecosystem through a six-pillar framework: Vision & Governance, Innovation Culture, Innovation Ecosystem, Funding & Financing, Human Capital, and Data & Infrastructure.

We then applied the framework to five further cities: Tallinn, Seoul, London, Montreal and Helsinki. The six pillars proved relevant in every context. Where cities diverged was in the paths they took towards AI readiness.

These paths are shaped in part by structural conditions, such as autonomy, fiscal capacity and institutional arrangements. They are equally shaped by strategic choice: deliberate decisions about how AI can serve each city’s wider ambitions.

The report captures these differences in four city archetypes: the Platform City, the Strategic City, the Delivery City and the Cognitive City. No archetype is inherently superior, and cities may move between them as their priorities evolve.

The findings lay the groundwork for the City AI Readiness Index, a framework designed to make city-level AI readiness measurable and comparable over time.

Our Framework

Exploring AI Readiness at the City Level

The report uses a six-pillar framework that captures the conditions determining whether a city can harness AI to benefit its residents and economy.

It began as a set of initial assumptions about what readiness looks like at the city level. We then tested and refined those assumptions through the Abu Dhabi deep dive and the five international case studies, and the findings shaped its final structure.

Vision & Governance: Whether the city has a clear vision for AI and the governance and policy capacity to deliver it.
Innovation Culture: Whether the city government has the capabilities and appetite to enable and adopt AI.
Innovation Ecosystem: Whether the city has a thriving and innovative AI economy.
Funding & Financing: Whether the city can draw on a diverse set of funding mechanisms to move from strategy to deployment.
Human Capital: Whether the city has the AI talent and skills programmes needed to enable development and adoption.
Data & Infrastructure: Whether the city has the infrastructure to support both the development and deployment of AI, alongside quality, safe and interoperable data.

Abu Dhabi Deep Dive

Why Abu Dhabi?

The Emirate has made AI a priority and has pursued it with sustained institutional and financial commitment. This makes it a useful case for examining city-level AI readiness. Several of the questions that other cities are beginning to consider are already being addressed there, which allows the research to observe readiness as it develops.

The AI Ecosystem in Abu Dhabi

The AI Ecosystem
in Abu Dhabi

Abu Dhabi combines a clear ambition — to become the world’s first AI-native government by 2027 — with the institutional setup, infrastructure, and capital to pursue it with coherence. Several components position the emirate strongly.

A coordinated ecosystem

Across the interviews conducted for this report, a consistent picture emerged of government departments, companies, sovereign investors, universities, and accelerators working with a high degree of coordination. This alignment extends beyond strategy into day-to-day implementation.

The government as active actor in the ecosystem

In many contexts, the public sector acts primarily as a regulator or late-stage adopter. In Abu Dhabi, it also plays an active role as a user and procurer of AI systems. For example, TAMM, Abu Dhabi’s unified government services platform, handled over 22.5 million transactions in the 12 months to 30 September 2026, generating demand for AI-enabled services. More broadly, a clear policy direction and governance structures provide a degree of predictability for ecosystem actors.

The infrastructure base is highly advanced

AI innovators in Abu Dhabi have access to strong compute capacity and a sovereign cloud. The Stargate UAE data centre campus, a $30 billion investment being built by G42 and operated by OpenAI and Oracle, will expand that capacity significantly when its first phase comes online in 2026. For international companies weighing where to establish a regional presence, access to this infrastructure stack is a material factor in the decision.

A vibrant AI ecosystem is taking rapid shape

Abu Dhabi’s financing landscape spans sovereign wealth at Mubadala’s scale, dedicated AI investment through MGX, and local banks increasingly active in AI. Alongside them sits Hub71, Abu Dhabi’s global tech ecosystem, whose Hub71+ AI vertical, launched in December 2024, connects AI startups to capital, compute and commercial partners. Together, these provide a largely continuous pathway from early-stage support to later-stage scaling. Furthermore, both the Mohamed bin Zayed University of Artificial Intelligence and Khalifa University underpin a robust talent pipeline, collaborating to generate pioneering research and advanced training. In addition to international talent attraction policies, these institutions support a growing pool of AI-related skills.

An outcomes-focused approach

There is a stated focus on outcomes, risk management, and longer-term resilience. That ambition extends to how AI is governed: responsible AI principles are embedded at the builder level and reinforced through layered government approval processes. For example, there are multiple AI safety checkpoints within G42’s product teams and Inception42’s delivery workflows. Similarly, the risks brought by AI, such as energy demand, workforce transition, and AI safety are ones Abu Dhabi is already working to anticipate.

The Ecosystem

Mapping Abu Dhabi's AI Ecosystem

AI readiness depends partly on whether the links between policy, capital, infrastructure, research and deployment are systemic or fragmented. In Abu Dhabi, the research found a high degree of integration.

Sovereign investors fund the infrastructure on which technology companies build. Government deploys these companies’ tools, which generates the data and demand that attract further investment and talent. Research institutions supply expertise and foundational models. Governance cuts across this cycle. It is coordinated not by a single ministry but by interlocking institutions led by the AIATC and the DGE.

We mapped these actors across four interdependent layers of the AI Public Value Chain:

Foundations: compute, connectivity, data, capital and talent.
Enablers: where these resources become usable AI capability.
Adoption & Deployment: where AI reaches public services and the wider economy.
Governance & Policy: present throughout all three of the other layers.

The International Landscape

Exploring the international landscape

A framework shaped by Abu Dhabi’s political structures, governance arrangements and resources cannot, on its own, speak for all cities. To test whether it holds across different contexts, we applied the same six pillars to five further cities with contrasting institutional forms and approaches to AI: Tallinn, Seoul, London, Montreal and Helsinki. The pillars proved relevant in every case, but each city pursued them in its own way. These differences reflect both structural conditions, such as autonomy, fiscal capacity and institutional arrangements, and deliberate choices about how AI can serve each city’s wider ambitions. We captured these differences in four city archetypes, explored below.

Tallinn

Estonia

Tallinn’s AI readiness is closely tied to Estonia’s. In a small country whose capital is also its main economic and institutional centre, the national digital platform effectively serves as the city’s platform. AI is being built on more than two decades of digital foundations, including X-Road, digital identity and near-universal online public services. Through Test in Tallinn, the city adds access rather than capital, inviting companies to pilot AI in real urban conditions. The open question is whether this model can grow a deeper AI-native ecosystem, so that Tallinn becomes a producer of AI as well as a strong adopter.

Read the full case study in our report.