The UAE has been ranked 9th globally in the Global AI for Finance Competitiveness Index (GAICI)
- UAE emerges as the Gulf’s most AI-deployable financial hub
- As a “system builder,” the UAE competes not on the sheer volume of research output but on its speed of AI adoption, regulatory modernization, and efficient deployment pathways
- From AI policy to finance execution, the UAE is structurally advantaged
The UAE has been ranked 9th in the Global AI for Finance Competitiveness Index (GAICI), which was released today by Deep Knowledge Group with the Hong Kong Financial Services Development Council (FSDC) serving as an observer.
Dubai ranked 14th, serving as a global bridge hub where AI seamlessly integrates into financial markets, while Abu Dhabi, in the 17th place, leverages its capital strength and institutional governance to deploy AI at scale in regulated environments.
The index provides a benchmark analysing AI competitiveness from a finance, economy and financial services perspective. It combines a global landscape overview of AI adoption in finance with an indicator-based competitiveness index that ranks 20 countries and 15 city-level finance hubs on AI-for-Finance capability and maturity.
The UAE stands out not only for its technological capability but also for its ability to turn AI potential into operational financial systems. This unique combination of state-driven AI development, a globally oriented financial ecosystem, and robust institutional execution makes the UAE a front-runner in deploying AI in regulated financial markets. As a “system builder,” the UAE competes not on the sheer volume of research output but on its speed of AI adoption, regulatory modernization, and efficient deployment pathways. Its ability to rapidly implement AI programs, set clear regulatory frameworks, and scale AI-powered financial tools has positioned it as a global testbed for finance-grade AI.
Dubai, ranked 14th globally, has carved out a leading role as the Gulf’s most internationally connected financial hub. Its strength lies not in raw AI capability but in its capacity to integrate AI into real-world financial operations. As a bridge hub between global finance centers and the Gulf region, Dubai offers the infrastructure and ecosystem needed to foster AI deployment. Its financial market-facing approach ensures that AI systems can seamlessly be piloted, tested, and deployed in regulated environments. Dubai’s competitive edge lies in its readiness to enable AI adoption, positioning itself as the primary entry point for international financial actors seeking to tap into the Gulf’s AI-driven finance landscape.
Abu Dhabi, ranked 17th, serves as the institutional backbone for AI in finance within the UAE. Its advantage is not rooted in fintech density but in its sovereign-scale capital strength and institutional governance. Abu Dhabi’s competitive positioning is built on deploying AI at a larger scale across institutional finance, asset pools, and market infrastructure. It stands out for its ability to execute AI within stringent regulatory frameworks, focusing on high-value areas like risk modeling, portfolio analytics, and institutional compliance. While Abu Dhabi is still expanding its AI ecosystem and deepening its market presence, its strategic focus on capital-backed AI deployment sets it apart as a critical player in the global financial AI landscape.
Dmitry Kaminskiy, General Partner of Deep Knowledge Group stated: “The UAE’s unique position in the AI for Finance Index highlights its ability to not just innovate but to efficiently deploy AI systems that meet the rigorous demands of regulated financial markets. This makes the UAE a key player in shaping the future of finance through AI across the globe.”
The index is led by the United States (98.84) and China (83.41), followed by the United Kingdom (78.26) and Switzerland (73.09), with Singapore (69.12) next. The leaders are not defined by a single strength, but by multi-pillar performance that supports production-grade AI in finance—including deployment readiness, institutional capacity, and ecosystem breadth. The U.S. leads with large-scale capability across AI, capital markets, and financial services adoption. China ranks second on the strength of ecosystem scale and rapid implementation dynamics in AI-enabled financial services. The U.K. and Switzerland follow as high-performing financial centres where strong institutional environments and finance-grade expectations—governance, accountability, and risk discipline—support consistent AI adoption. Singapore rounds out the top tier, reflecting strong ecosystem coordination and high deployment readiness relative to its size.
“The leaders in this index are not simply ‘AI-strong’; they are strong at converting AI capacity into deployed financial systems—where governance, resilience, and market integrity are non-negotiable,” Kaminskiy continued.
Meanwhile, city-hub ranking places New York (99) and London (81) first and second, with Hong Kong (76) third—reflecting their combined advantages in market connectivity, institutional concentration, and capital formation for AI-enabled financial activity. The next positions—San Francisco (70) and Shanghai (67)—reflect the interaction between AI capability and financial-market pull. Mid-table hubs (e.g., Toronto, Singapore, Tokyo, Chicago, Riyadh) typically show strengths in one or two dimensions but less complete end-to-end breadth. Lower-ranked hubs are often constrained by thinner ecosystem density, fewer scalable deployment pathways into regulated institutions, or weaker global market connectivity. Moving up the ranking generally requires (i) strengthening capital-formation and listing pathways, (ii) expanding production-grade adoption mechanisms across regulated institutions, and (iii) increasing ecosystem breadth so that AI capabilities translate into repeatable, auditable deployments rather than isolated pilots.
Dr King Au, Executive Director of the FSDC, remarked, “Hong Kong’s ranking among leading global finance hubs reflects the city’s excellent market connectivity and top-notch institutional quality—two conditions that matter when AI for finance must operate under finance-grade expectations.”
Dr Patrick Glauner, Professor of AI at Deggendorf Institute of Technology, a co-author of the report, noted, “In finance, competitive advantage comes from trustworthy AI—models that are explainable, auditable, and robust under real-world constraints. The index makes clear that deployment quality matters as much as innovation.”
Additional Key Findings
1. AI for finance is shifting from novelty to infrastructure: competitive advantage now reflects repeatable deployment in regulated workflows.
2. Top-ranked countries pair ecosystem scale with execution capacity: strong performance typically requires strength across multiple pillars, not one-off advantages.
3. The hub ranking underscores concentration: AI-for-finance activity clusters in a limited set of global financial centres with strong market infrastructure.
4. Model governance and assurance are central: monitoring, auditability, and operational resilience are becoming baseline expectations.
5. Data exchange and interoperability remain most common bottlenecks in mid-tier markets.
6. Strategic takeaway: the next phase of competition is about institutionalisation—turning tools into operating systems.
