Launch of Global AI Index (Part 4) and AI Industry Ecosystem in Hong Kong

On November 18-19, Deep Knowledge Group published two major analytical projects in coordination with key collaborators that together provide one of the most comprehensive assessments of global and regional artificial intelligence trends released this year. 

The Global AI Competitiveness Index (Part 4) (with  Financial Services Development Council serving as official report Observer) and the AI Industry Ecosystem in Hong Kong Report & Platform in cooperation with FSDC (Observer) and the AI Industry Association of Hong Kong (Supporting Organization) each examine different layers of AI development—global governance on one hand, and regional ecosystem acceleration on the other—offering data-driven insights for policymakers, industry leaders, and the broader innovation community.

Both releases are distinct in their scope and objectives, yet deeply synergistic when taken together. The AI Index provides a bird’s-eye perspective on how nations govern, regulate, fund, and strategically guide AI at the highest levels. The AI in Hong Kong mapping zooms down into the microstructure of a single high-value ecosystem—Hong Kong—showcasing how regional clusters translate those global governance environments into applied innovation, investment flows, research strength, and economic transformation.

These releases speak to two sides of the AI landscape that often remain siloed but are, in reality, deeply interconnected: policy frameworks → shape national capacity → influence regional ecosystems → drive global competitiveness.

(From left to right) Dmitry Kaminskiy, general partner of Deep Knowledge Group; Patrick Glauner, professor of AI at Deggendorf Institute of Technology; and King Au, executive director of the Financial Services Development Council, share the findings from the Global AI Competitiveness Index Part 4 in Hong Kong on Nov 19, 2025

Global AI Competitiveness Index, Part 4: Mapping Policy, Governance, and Regulation Worldwide

Full report: https://www.dkv.global/ai-index/part4

The fourth edition of the Global AI Competitiveness Index deepens the project’s long-term mission: to analyze how countries build, manage, support, and regulate artificial intelligence at a national level. Part 4 shifts focus from science, talent, and enterprise activity (covered in previous editions) to the governance, policy, and regulatory architectures that increasingly shape AI adoption, innovation, and safety.

This edition is informed by the expert perspectives of distinguished AI Committee Members, including Rudolf Scharping (Former Federal Minister of Defence of Germany; Chairman of RSBK AG), Prof. Dr. Rudolf Mellinghoff (Former President of the German Federal Fiscal Court), Volker Römermann (Professor of Law; Managing Director, Römermann Rechtsanwälte), and other global AI governance specialists. The Hong Kong Financial Services Development Council (FSDC) serves as an Observer organization for the Index.

The Global AI Competitiveness Index (Part 4) is the latest installment in a multi-edition analytical series that has, since its inception, become one of the world’s most structured references for comparing and understanding national AI trajectories. While previous editions focused on AI enterprises, talent density, science and technology output, and human capital competitiveness, Part 4 shifts the lens toward the domain that increasingly determines national success: governance and regulation.

Key Themes and Insights

• AI Governance Gap Widens: Countries accelerating deployment (US, China) are diverging from those prioritizing rights-based, compliance-first models (EU).

• Three Macro Models Emerge: State-led (China), innovation-driven (US), and rights-based (EU), each shaping competitive outcomes and cross-border dynamics.

• Policy Maturity as a Competitive Asset: Nations with clear institutional coordination, central AI offices, and multi-ministry frameworks score higher on readiness.

• International AI Diplomacy Expands: Countries with strong engagement in treaties, alliances, and AI standard-setting bodies show increased geopolitical influence.

• Regulatory Acceleration: Dozens of jurisdictions are introducing new AI laws, risk-classification systems, and national safety frameworks—often faster than anticipated.

This edition examines how 25+ countries build institutional capacity around AI, including:

• national AI offices and interministerial bodies

• long-term national strategies

• regulatory systems and risk-classification frameworks

• AI safety oversight

• data governance structures

• international AI diplomacy

• standards-setting participation

• public-sector digital readiness

• institutional coordination

  
  

These factors are now central to global competitiveness. Nations with stronger governance architectures consistently demonstrate a greater ability to scale AI adoption, mobilize investment, and shape international standards.

Why This Matters

AI competitiveness is increasingly defined not only by technical capability and talent, but by the ability of governments to create structured, consistent, forward-looking policy environments. Part 4 provides governments, regulators, and industry bodies with a comparative analytical framework to understand global trajectories and benchmark their own governance readiness.

Key Findings From Part 4: A World of Diverging AI Governance Models

The AI Governance Gap is Widening

Countries that aggressively deploy AI in industry, government services, and national-scale platforms are moving faster than those emphasizing compliance-first, rights-based frameworks. This divergence creates increasing global asymmetry in:

• AI adoption rates

• innovation diffusion

• commercialization of research

• deployment of AI in government services

• AI diplomacy influence

Three Global Governance Archetypes Continue to Solidify

1. State-Led (China and similar jurisdictions) Characterized by strong central coordination, national AI missions, and integrated regulatory ecosystems.

2. Innovation-Driven (United States and similar) Market-first development supported by a flexible regulatory environment and private-sector dominance.

3. Rights-Based (European Union) A compliance-forward model centered on risk classification, safety, ethics, and harmonized digital rights frameworks.

These models are not ranked, but contextualized to explain strategic strengths and constraints.

Institutions Are the New Competitive Infrastructure

Countries with multi-agency governance bodies—e.g., national AI councils, AI safety institutes, centralized data governance authorities—demonstrate:

• higher regulatory readiness

• stronger ability to coordinate between ministries

• improved national AI deployment

• greater AI diplomatic leverage

AI Diplomacy is Becoming a Strategic Theater

Countries engaged in global alliances, safety summits, standards bodies, and multilateral AI initiatives exhibit stronger geopolitical influence over the emerging AI order.

AI Industry Ecosystem in Hong Kong: A Growing Innovation Hub

Alongside the AI Index release, Deep Knowledge Group also unveiled the AI Industry Ecosystem in Hong Kong Report and Interactive Platform, co-produced with the AI Industry Association of Hong Kong (AIHK). This initiative provides the most comprehensive mapping of Hong Kong’s AI landscape ever produced, capturing the structure, momentum, and economic relevance of a region that is rapidly becoming one of Asia’s most dynamic AI hubs.

Full report and interactive platform: https://www.hk-ecosystem.tech/ai

The report and platform provide the most comprehensive mapping to date of Hong Kong’s AI sector. With 500 organizations, 290 AI companies, and 180 investors, the city is rapidly asserting itself as one of Asia’s most dynamic AI ecosystems.

The report and interactive platform reflect a coordinated effort to analyze and visualize the full structure of Hong Kong’s AI landscape—spanning startups, corporates, accelerators, universities, research institutes, investment firms, hubs, government bodies, and cross-border innovation corridors.

Key Findings

• AI-Driven IPO Momentum: The Hong Kong Stock Exchange recorded a 23% increase in IPO volume in Q1 2025, with AI companies being one of the major drivers.

• Finance Leads the Way: Banks, insurers, and fintech companies are rapidly adopting AI—enhancing trading, risk management, compliance automation, customer analytics, and digital asset operations.

• Deepening R&D Strength: University-led research, cross-border innovation zones, and industry–academia partnerships continue to expand Hong Kong’s scientific foundation.

• Growing Capital Environment: With 180 active AI investors, the city now facilitates one of Asia’s most international sets of cross-border innovation and financing relationships.

• Platform-Based Visibility: The interactive knowledgebase allows users to explore the ecosystem through dynamic mindmaps, sector maps, profile cards, and institutional networks.

  
  

Why Hong Kong’s Story Matters

Unlike many global hubs competing on raw scale, Hong Kong’s differentiated AI identity emerges from:

• strong regulatory clarity,

• financial-sector application depth,

• cross-border science and talent pipelines,

• and a uniquely international capital environment.

  
  

In addition, Hong Kong’s institutional ecosystem—featuring Science Park, Cyberport, HKMA, the Insurance Authority, leading universities, and emerging AI clusters—plays a crucial role in steering the sector toward maturity.

A Full-Ecosystem Analysis Covering More Than 500 Organizations

The project profiles:

• 290 AI companies (from fintech AI to robotics to enterprise intelligence)

• 180 investors

• 40+ government bodies and public institutions

• 50+ research institutes and universities

• major hubs such as Cyberport, Hong Kong Science and Technology Parks (HKSTP), and sector-specific innovation accelerators

The result is a unified, data-driven view of the entire AI environment in Hong Kong.

A Multi-Layered Mapping Framework

The ecosystem is analyzed across:

• sector clusters

• investment flow networks

• founder networks

• institutional linkages

• cross-border innovation corridors

• IPO activity

• R&D and scientific output

• AI adoption maturity across industries

• startup–corporate collaboration pathways

  
  

The project’s interactive platform allows users to explore this environment dynamically, with search layers, mindmaps, profile cards, and ecosystem-level visualizations.

Key Findings From the Hong Kong Ecosystem Mapping

Hong Kong’s AI Sector Is Expanding Rapidly

The report documents Hong Kong’s emergence as a high-momentum AI hub, with:

• 500+ ecosystem entities

• surging investor participation

• mature finance-sector AI adoption

• credentialed university research centers

• high cross-border integration with the Greater Bay Area

AI-Driven IPO Activity Increasing

One of the report’s most notable insights is the 23% increase in IPO volume on HKEX in Q1 2025, driven significantly by AI-associated companies.

This reinforces Hong Kong’s position as a global financial gateway for AI firms seeking international capital access.

A Strong Finance & RegTech AI Base

Hong Kong’s banks, insurers, asset managers, and fintech players have rapidly become some of the most aggressive adopters of:

• AI-driven risk systems

• regulatory automation

• AML/KYC intelligence

• portfolio optimization

• digital asset infrastructure

• fraud analytics

• smart customer automation

• GenAI-enabled compliance and advisory tools

The city’s identity as a global financial center gives it a natural competitive advantage in finance-focused AI applications.

R&D Depth Strengthening

Hong Kong’s universities—including HKU, CUHK, HKUST, CityU, and PolyU—continue to build internationally recognized AI labs, research centers, and interdisciplinary AI programs. These institutions function as the scientific backbone of Hong Kong’s AI ecosystem.

An International Capital Environment

With 180 AI investors, Hong Kong hosts one of the most internationalized investment communities in Asia, with strong cross-border capital flow between Hong Kong, mainland China, Southeast Asia, the Middle East, Europe, and the US.

5. Why These Two Releases Matter Together

Although global in one case and regional in the other, the two projects reflect a common message: AI competitiveness now depends equally on strong governance frameworks and vibrant innovation ecosystems.

Part 4 of the AI Index shows the macro picture:

• How countries govern AI

• How they structure national strategies

• How they regulate safety, risk, and deployment

• How they participate in the global AI diplomatic sphere

  
  

The Hong Kong ecosystem mapping shows the micro picture:

• How a region operationalizes AI

• How capital formation accelerates innovation

• How institutions, research centers, hubs, and corporates form a unified growth engine

• How cross-border technology corridors create competitive advantage

How the Two Projects Connect

While global in scope and regional in focus respectively, the two releases reinforce a shared narrative:

• Nations with clear AI policy direction are advancing most rapidly.

• Cities like Hong Kong, with strong regulatory infrastructure and financial-sector depth, are well-positioned to become bridge nodes in global AI development.

• Policymaking and ecosystem-building are now inseparable from the competitiveness equation.

  
  

Together, these two projects demonstrate how global AI governance architectures and local innovation ecosystems interact to shape the broader technological landscape.

A Foundation for Future Analysis

These two releases mark the continuation of Deep Knowledge Group’s long-term commitment to producing data-driven, multi-edition analytical projects covering global AI competitiveness, national strategic capabilities, and the structural evolution of regional innovation ecosystems.

With Part 5 of the Global AI Index and additional regional ecosystem mappings already in development, the coming year will bring even deeper insights into the evolving architecture of global artificial intelligence.