Geopolitics & Coordination

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LLM Summary:Comprehensive analysis of US-China AI competition using 2024-2025 data showing US maintains 12:1 private investment lead but China produces 47% of top AI researchers (vs US 18%) and is rapidly closing capability gaps through state funding and domestic talent retention. Documents declining global AI talent mobility (55% to 42% working abroad) and emergence of 44+ country international governance frameworks with 87% content overlap.

Overview

The geopolitical dimension of AI development significantly shapes both capability trajectories and risk profiles. International competition can accelerate development timelines and reduce safety standards, while effective coordination could enable shared safety measures and governance frameworks.

This page tracks key metrics across:

Capability gaps between major powers
Talent flows and human capital distribution
Cooperation mechanisms and international agreements
Arms race indicators suggesting competitive pressure
Governance effectiveness of international institutions
Technology proliferation to authoritarian regimes

1. US-China AI Capability Gap

Overall Assessment (2024-2025)

Current Status: United States maintains overall lead, but gap is narrowing in specific domains.

Investment Comparison

Metric	United States	China	Ratio
Private AI Investment (2024)	$109.1 billion	$9.3 billion	12:1 US lead
Total VC Funding to AI (2025)	$159 billion (79% of global)	~$125 billion total AI investment	~1.3:1 US lead
Government VC for AI	Limited direct government VC	$184 billion to ~10,000 AI firms (cumulative)	China leads in state funding
2025 AI Capital Spending	Not specified	Up to $98 billion projected	-

Key Finding: The US private sector invests nearly 12x more than China’s private sector, but China’s government-directed investment significantly narrows the total funding gap.

AI Talent Distribution

Metric	United States	China
Top 2% AI talent currently working	57% of global total	28% of global total
Top AI researchers produced (2022)	18% of global	47% of global
Top-tier talent at US institutions (origin)	37% domestic, 38% Chinese-origin	90% retention of domestic graduates
Graduate retention rate	80% of those who studied in US	90% of those who studied in China

Key Finding: The US employs the majority of elite AI talent globally, but China produces more than twice as many top researchers and is increasingly retaining them domestically.

Compute & Hardware

US Advantages:

Dominance in advanced chip design (NVIDIA, AMD)
Leading-edge semiconductor manufacturing access
Export controls limiting China’s access to cutting-edge GPUs

China Challenges & Strategies:

Significant lag in domestic chip fabrication (estimated 2-5 years behind)
Huawei developing AI chips to circumvent US restrictions
Building massive chip clusters with domestic hardware
Government subsidies for electricity costs at data centers using domestic chips
Focus on efficiency and open-source models (e.g., DeepSeek)

CSET Assessment: “China still lags significantly due to constraints imposed by U.S. export restrictions” in semiconductor fabrication, though working to close the gap.

Model Performance

US Leadership: Dominates frontier model development (GPT-4, Claude, Gemini)

China Progress: Rapid advancement in open-source models and specific applications, but generally trailing in cutting-edge capabilities

Competitive Dynamic: While the US focuses on AGI development, China is “outpacing the United States in diffusing AI across its society” according to CSET, though “China has by no means de-emphasized its state-sponsored pursuit of AGI.”

2. AI Talent Migration Patterns

Data primarily from MacroPolo Global AI Talent Tracker 2.0↗ (March 2024 update).

Key Findings

Global Mobility Declining

2019: 55% of top-tier AI researchers worked abroad (foreign nationals) 2022: 42% of top-tier AI researchers worked abroad Change: -13 percentage points, indicating declining mobility

Interpretation: More top-tier talent staying in their home countries rather than migrating.

US as Primary Destination

60% of top AI institutions globally are in the United States
57% of the top 2% of global AI talent works in the United States
75% of top-tier AI talent at US institutions are of American or Chinese origin (up from 58% in 2019)

Composition of US AI Workforce (Top 20%)

Origin	Percentage
United States	37%
China	38%
Other	25%

Critical Dependency: The US AI sector is heavily dependent on foreign talent, with Chinese-origin researchers comprising the single largest group.

China’s Growing Talent Production & Retention

2019: China produced 29% of world’s top AI researchers
2022: China produced 47% of world’s top AI researchers
Current: ~2,000 AI university majors across China

Retention Improvement:

90% of researchers who attended graduate school in China stayed in China
28% of top AI researchers globally now work in China (2022)

Driving Factor: “The growth of the domestic AI sector in China and the job opportunities it has created”

Other Countries

Gaining Ground: United Kingdom, South Korea, continental Europe “slightly raised their game as destinations”

Relative Declines: India and Canada as sources of AI researcher talent

Implications

US Vulnerability: Heavy reliance on foreign talent, particularly from strategic competitor China
China’s Trajectory: Rapidly improving domestic talent pipeline and retention
Decentralization: Global AI talent becoming less concentrated, more distributed
Brain Drain Reversal: Traditional “brain drain” to US showing signs of reversal for Chinese talent

3. Multinational AI Cooperation Agreements

Major Multilateral Initiatives (2024-2025)

GPAI-OECD Integrated Partnership

Status: Launched 2024 Members: 44 countries + European Union Significance: Most comprehensive international AI governance partnership

December 2024: GPAI Belgrade Ministerial Declaration issued

2024 OECD AI Principles Update:

Now endorsed by 47 jurisdictions including EU
Updated to address general-purpose and generative AI
Enhanced focus on safety, privacy, intellectual property, and information integrity
87% content overlap with UNESCO, G7, and UN frameworks (indicating global convergence)

Council of Europe AI Framework Convention

Adopted: May 17, 2024 Signatories: 46 Council of Europe members + 11 non-member states

Non-member signatories include: Argentina, Australia, Canada, Costa Rica, Holy See, Israel, Japan, Mexico, Peru, United States, Uruguay + European Union

Nature: First international AI treaty with legal framework (though implementation mechanisms vary)

UN Global AI Resolution

Adopted: March 2024 Co-sponsors: 122 countries Significance: First global consensus resolution on AI

December 2024: UN General Assembly adopted first resolution specifically on AI in military domain, stressing importance of humanitarian and international human rights law

G7 Hiroshima AI Process

Status: Ongoing Key Outputs:

International Guiding Principles for AI
Voluntary Code of Conduct for AI developers

Bilateral AI Safety & Cooperation Agreements

US-UK AI Safety Partnership

Signed: April 2024 Signatories: US Commerce Secretary Gina Raimondo, UK Technology Secretary Michelle Donelan

Scope:

Joint development of tests for advanced AI models
Align scientific approaches to AI safety evaluation
Accelerate development of robust evaluation suites

Follow-up: July 2025 OpenAI-UK Government MOU for AI-powered growth and innovation

US-Saudi Arabia Strategic AI Partnership

Signed: November 2025 Focus: Strategic cooperation on AI development and deployment

International Governance Infrastructure

OECD AI Policy Observatory

Scale: Tracking over 900 AI policy initiatives across 69 countries

Types: National strategies, action plans, regulatory frameworks, sectoral guidelines

UNESCO Implementation

58 governments conducting Readiness Assessments for AI implementation

African Union Framework (2024)

Focus on trustworthy and inclusive AI development

Effectiveness Assessment

Strengths

High Convergence: 87% overlap in principles across major frameworks suggests genuine consensus
Broad Participation: 122 UN co-sponsors shows wide buy-in
Interoperability: OECD definitions being adopted by EU, Council of Europe, Japan, US, creating common language

Weaknesses

Non-Binding Nature: Most agreements lack enforcement mechanisms
Implementation Gap: OECD notes “concrete guidance for implementation is often lacking”
Monitoring Deficit: “Weak” evaluation mechanisms limit ability to measure outcomes
Capability-Governance Gap: 53 percentage points between AI adoption and governance maturity
Resource Constraints: “Skills shortages, outdated legacy systems, difficulties in data sharing, and financial constraints all hinder scaling”

OECD Assessment (2025): “Although AI use is increasing, AI use in government has not yet made a transformative impact.”

4. AI Arms Race Intensity Indicators

Military AI Spending

United States Department of Defense

Fiscal Year	AI R&D Budget
FY 2022	$874 million
FY 2024	$1.8 billion
FY 2025	$1.8 billion (requested)

Additional commitments:

$90 billion: AI data center expansion (Trump administration)
$200 billion: Micron Technology semiconductor manufacturing investment
685+ AI-related projects currently overseen by Pentagon

China (PLA)

Official estimates: Significantly understated Actual estimates: 40-90% higher than publicly announced

Public 2024 defense budget: ~$230 billion
Estimated actual defense spending: $330-450 billion
AI investment portion: Potentially matching or exceeding US DoD spending

Key capabilities: Autonomous military vehicles, drone swarm technology, AI-enhanced command and control

France

€2 billion redirected from 2024-2030 defense budget to AI (March 2024)
€300 million budget for Ministerial Agency for Artificial Intelligence in Defence (MAAID, established May 2024)

Iran

$20 billion National AI action from National Development Fund (2025)

India

Established Indian Army AI Incubation Center
Focus on autonomous platforms, surveillance, predictive maintenance, intelligent decision support

Global Military AI Market

Metric	2024	2030 (Projected)	CAGR
Market Size	$9.31 billion	$19.29 billion	13.0%

Regional Distribution: North America dominated with 32.8% market share (2024)

Context: Global military spending reached $2.4 trillion in 2023 (6.8% increase, steepest since 2009)

Autonomous Weapons Development

Global automated weapon system market: ~$15 billion (2025)

Key developments:

Multiple nations deploying Autonomous Weapon Systems (AWS) with lethal decision-making capability
Ukraine producing ~2 million drones in 2024 (96.2% domestically manufactured)
AI-powered GPS-denied navigation advancing
Drone swarming experiments accelerating

Ukraine as testing ground: Real-world validation of AI military technologies creating rapid capability improvements

Policy Shifts Indicating Intensification

OpenAI: Removed blanket ban on military use from policies (January 2024)
UN Response: First resolution on AI in military domain (December 2024)
Export Controls: US tightening restrictions on advanced chip exports to China
National Security Framing: Increased rhetoric linking AI leadership to national security

Strategic Concerns (RAND Analysis)

Competition Drivers:

“Both the United States’ and China’s military strategists fear falling behind their rivals in harnessing AI”
“This is the kind of dynamic that stokes costly arms races, increases the probability of international crises”
“Makes crises that do occur more likely to escalate to large-scale war”

Command & Control Evolution:

China recognizing need for less-centralized command in AI-era warfare
Could erode traditional US agility advantage
May make Chinese units “more aggressive and unpredictable”

Intensity Assessment

Current Level: Medium-High and Accelerating

Evidence:

Military AI spending growing 15-20% annually
Rapid expansion of autonomous weapons programs
Real-world testing in Ukraine driving iteration
Increasing national security rhetoric
Policy barriers to military AI use being removed
Spending levels still modest relative to total defense budgets, but trajectory is steep

5. International AI Governance Body Effectiveness

Scope of International Governance (2024-2025)

National Strategy Proliferation

89 national AI strategies documented worldwide by end of 2023 (UNCTAD Technology and Innovation Report 2025)

Geographic distribution: Concentrated in developed nations; developing countries face “significant infrastructure and capacity gaps”

Major Governance Bodies & Initiatives

OECD AI Governance

Reach: 47 jurisdictions (including EU) Policy tracking: 900+ initiatives across 69 countries Influence: OECD AI system definitions adopted by EU, Council of Europe, Japan, US

Strengths:

High interoperability across jurisdictions
Comprehensive policy observatory
Regular updates to principles

Limitations:

Non-binding nature
“Flexible and adaptable” principles can mean weak enforcement
Implementation guidance often lacking

UNESCO

Recommendation on Ethics of AI: Adopted by 193 member states Readiness Assessments: 58 governments conducting evaluations

Focus: Ethical frameworks, inclusive development

UN AI Initiatives

March 2024: First global AI resolution (122 co-sponsors) September 2024: Partnership with OECD Office of the Tech Envoy December 2024: First resolution on AI in military domain

Scope: Broad normative frameworks, human rights focus

Limitations: No enforcement mechanisms, slow-moving relative to AI development pace

G7 Hiroshima AI Process

Participants: Major democracies (US, UK, France, Germany, Italy, Canada, Japan) Output: Voluntary code of conduct, guiding principles

Strength: Alignment among major AI developers Limitation: Excludes China and other major players

Global Partnership on AI (GPAI)

Merged with OECD in 2024 Members: 44 countries

Focus: Multistakeholder approach, working groups on key challenges

Effectiveness Metrics

Coverage

✅ Strong: Geographic reach (122-193 countries in various initiatives) ✅ Strong: Policy tracking and documentation (900+ initiatives) ⚠️ Moderate: Inclusion of key players (China participates in some but not all)

Convergence

✅ Strong: 87% content overlap across major frameworks ✅ Strong: OECD definitions being adopted across jurisdictions

Implementation

❌ Weak: “Concrete guidance for implementation is often lacking” (OECD) ❌ Weak: 53 percentage point gap between AI adoption and governance maturity ❌ Weak: “Monitoring and evaluation mechanisms are also weak, limiting the ability to measure outcomes or detect risks effectively”

Enforcement

❌ Very Weak: Most frameworks are non-binding ❌ Very Weak: No meaningful sanctions for non-compliance ⚠️ EU Exception: AI Act has enforcement mechanisms (fines up to €35 million or 7% of global turnover)

Speed & Responsiveness

⚠️ Moderate: 2024 OECD principles updated 5 years after initial adoption ❌ Weak: Traditional intergovernmental processes lag AI development by years ✅ Strong: Some initiatives (G7 Hiroshima Process) moving on accelerated timelines

Impact Assessment

OECD Finding (2025): “Although AI use is increasing, AI use in government has not yet made a transformative impact.”

Key Challenges Identified:

Skills shortages in government
Outdated legacy systems
Difficulties in data sharing
Financial constraints
Gap between strategy and implementation

Overall Effectiveness Rating

Normative Frameworks: 7/10 (Strong convergence, broad participation) Technical Standards: 6/10 (Good interoperability, but implementation lags) Enforcement & Compliance: 2/10 (Mostly voluntary, weak monitoring) Speed & Adaptability: 4/10 (Improving, but still lags technology) Practical Impact: 3/10 (Limited transformation of actual practices)

Composite Score: 4.4/10 (Moderate-Low Effectiveness)

Trajectory: Improving infrastructure and convergence, but implementation gap remains critical weakness

6. Technology Transfer to Authoritarian Regimes

China-Russia AI Cooperation

Sino-Russian Innovation Dialogue

Established: 2017 (annual since then) Participants: China’s Ministry of Science and Technology + Russia’s Ministry of Economic Development

2019-2024 Work Plan: Combines “China’s industry, capital and market with the resources, technology and talents of Russia”

Russia’s AI Dependence on China

LLM Sources: ~40% of all LLMs globally originate from China Russia’s AI Funding: 5.2 billion rubles ($57 million) in 2024 US Comparison: US government allocated 50x more than Russia in 2022

Implication: Russia increasingly dependent on Chinese AI models and technology given funding constraints and Western sanctions

Global Spread of Chinese Surveillance AI

Geographic Reach

80+ countries have received PRC-sourced AI-for-surveillance solutions Recipients include: Both authoritarian regimes and democracies

Market Dominance in Surveillance

Hikvision + Dahua combined: ~34% of global surveillance camera market (2024, first 3 quarters)

Capabilities: Advanced facial recognition, behavioral analysis, mass monitoring

Dual-Use Technology Proliferation

Export Advantage: China exports AI technology to nearly twice as many countries as the United States

Target Markets: Focus on “autocracies and weak democracies”

Strategic Intent: “Spread its ideology and facilitate the adoption of techno-authoritarian practices”

Weaponization of AI for Disinformation

State Actors Using Generative AI

Iran, Russia, Venezuela: “Purposefully experimenting with and weaponizing generative AI to manipulate the information space and undermine democracy”

2024 US Election: AI-generated fake images and deepfakes “flooding social media platforms”

Scale: Enabled by ~40% of LLMs originating from China that “can be made to adhere to the standards of authoritarian regimes”

Technology Transfer Mechanisms

Commercial Exports

Surveillance cameras and software
Facial recognition systems
Smart city infrastructure packages

Government-to-Government

Belt and Road Initiative technology components
Bilateral cooperation agreements
Training programs for foreign officials

Open Source & Indirect

Open-source AI models usable by any regime
Academic collaborations
Commercial AI services available globally

Democratic Responses

Export Controls & Investment Screening

US & Australia leading coordination on:

Export controls for sensitive AI technologies
Investment screening mechanisms
Restrictions on collaboration with military-linked Chinese institutions

Challenge: Difficult to control dual-use technologies with legitimate commercial applications

EU AI Act (2024)

Approved: December 2023, passed March 2024 Scope: “Protect fundamental rights, democracy, the rule of law and environmental sustainability” Approach: Risk-based framework with stricter rules for high-risk applications

Impact on exports: Sets baseline for AI systems sold in EU market

Multilateral Coordination

April 2024 Workshop: Hoover Institution, Stanford Global Digital Policy Incubator, National Endowment for Democracy

Focus: “Map the expanding frontiers of digital authoritarianism” and “discuss the diffusion of authoritarian technologies”

Scale of Technology Transfer

Surveillance Technology

Conservative Estimate: 80+ countries with PRC AI surveillance Market Value: Hikvision + Dahua represent billions in annual surveillance equipment sales

AI Models & Services

Accessibility: Chinese LLMs and AI services available to most countries globally Control: Minimal restrictions on export of general-purpose AI models

Smart City Projects

Hundreds of projects in developing countries incorporating Chinese AI surveillance and management systems

Assessment

Current Risk Level: High

Evidence:

Dominant market share in surveillance technology (34%)
Deployment in 80+ countries
Explicit weaponization by Iran, Russia, Venezuela for disinformation
Rapid proliferation of generative AI capabilities
Limited effective controls on dual-use technology exports

Trend: Accelerating

Proliferation outpacing development of effective control mechanisms. Open-source AI development further complicates restriction efforts.

Key Takeaways

Competition vs. Cooperation Balance

Competition Indicators: Dominant

12:1 US private investment advantage, but China government investment competitive
Military AI spending growing 15-20%+ annually
Autonomous weapons proliferation accelerating
Technology transfer to rivals ongoing

Cooperation Indicators: Present but Weak

87% convergence across governance frameworks
47 countries signed onto OECD principles
Multiple bilateral safety agreements
BUT: mostly non-binding, weak enforcement, significant implementation gap

Critical Vulnerabilities

US Talent Dependence: 38% of top US AI researchers from China
Declining Mobility: Global talent staying home more (13 percentage point drop)
Governance-Capability Gap: 53 percentage point gap between AI adoption and governance maturity
Surveillance Proliferation: Chinese AI surveillance in 80+ countries
Military AI Testing: Ukraine conflict accelerating autonomous weapons development

Trajectories

Near-term (1-3 years):

US maintains overall capability lead but gap narrows
Military AI spending continues rapid growth
Governance frameworks proliferate but remain weak
Technology transfer to authoritarian regimes continues

Medium-term (3-7 years):

China could achieve parity in specific AI domains
Autonomous weapons become standard military capability
International governance either strengthens significantly or fragments
Competition vs. cooperation balance likely determines AI risk landscape

Data Sources

Primary Sources

Additional Context

Limitations & Data Quality

Strengths

Investment data from multiple authoritative sources (KPMG, EY, Stanford)
Talent data from rigorous academic tracking (MacroPolo)
Government spending from official budgets where available
Think tank analysis from CSET, RAND, Carnegie

Limitations

China data opacity: Actual military spending and government AI investment likely understated by 40-90%
Talent attribution: Based on undergraduate institution, may not perfectly reflect current national affiliation
Technology transfer: Difficult to quantify; much occurs through commercial channels
Governance effectiveness: Largely qualitative assessment, hard to measure concrete impact
Rapid change: AI landscape evolving faster than data collection cycles

Update Frequency

Investment data: Quarterly to annual
Talent flows: Major update every 3 years (MacroPolo)
Military spending: Annual budget cycles
Governance: Ongoing policy tracking, major reports annual
Technology proliferation: Ad hoc reporting, no systematic tracking

Last Updated: December 2025 (using latest available 2024-2025 data)