Few technologies have promised to reshape the balance of power as profoundly as artificial intelligence. From the steam engine to nuclear weapons, transformative technologies have repeatedly reordered international hierarchies, creating new great powers while diminishing old ones. AI appears poised to join this lineage. The nations that master its development and deployment stand to gain decisive advantages in economic productivity, military capability, and the capacity to shape global norms. It is little wonder that the world’s major powers have made AI leadership a strategic priority.
AI as a Geopolitical Domain¶
Artificial intelligence encompasses a range of technologies that enable machines to perform tasks traditionally requiring human intelligence: pattern recognition, language processing, decision-making, and learning from experience. While AI research dates to the 1950s, recent advances in machine learning, computational power, and data availability have transformed theoretical possibilities into practical applications. These applications span virtually every domain relevant to statecraft.
Economic productivity represents perhaps the most immediate impact. AI systems can optimize supply chains, accelerate drug discovery, automate manufacturing, and enhance services across industries. Nations that effectively deploy AI may achieve sustained productivity growth that compounds into significant economic advantage over competitors. The McKinsey Global Institute has estimated that AI could add thirteen trillion dollars to global output by 2030, but these gains will not be evenly distributed.
Military applications extend from logistics and intelligence analysis to autonomous weapons systems and cyber operations. AI can process reconnaissance data at speeds humans cannot match, coordinate drone swarms, optimize targeting, and detect threats. The integration of AI into military systems promises to accelerate the tempo of conflict and may ultimately reshape the character of warfare itself.
Intelligence and surveillance capabilities expand dramatically with AI. Systems that can process vast quantities of communications, imagery, and open-source data provide unprecedented situational awareness. This power can be directed externally for national security purposes or internally for social control, creating divergent models of AI-enabled governance.
Information environments are increasingly shaped by AI through content recommendation algorithms, synthetic media generation, and automated influence operations. The capacity to shape narratives at scale has become a dimension of hybrid warfare and political competition.
This breadth of application makes AI a general-purpose strategic technology, akin to electricity or computing itself. Unlike domain-specific capabilities, AI’s pervasive potential application means that leadership or dependency in this field will ramify across the entire spectrum of national power.
The US-China Competition¶
The central axis of AI competition runs between the United States and China. Both nations have identified AI as essential to their strategic futures and have mobilized substantial resources accordingly. Their rivalry is shaping the global AI landscape and drawing other nations into alignment decisions.
The United States maintains significant advantages in AI development. American universities and technology companies lead in fundamental research; firms like OpenAI, Google DeepMind, Anthropic, and Meta have produced the most capable AI systems. Silicon Valley’s innovation ecosystem, venture capital abundance, and ability to attract global talent have sustained American technological leadership. The semiconductor supply chain, though geographically dispersed, depends heavily on American design tools and intellectual property.
Yet American advantages face challenges. The private sector drives most AI development, creating coordination difficulties between commercial and national security priorities. Immigration restrictions have sometimes impeded talent acquisition. The open research culture that accelerated American AI progress also enabled knowledge diffusion to competitors. And American political divisions have complicated coherent technology policy.
China has mounted the most ambitious state-directed AI program in history. The 2017 New Generation Artificial Intelligence Development Plan set explicit goals for Chinese AI supremacy by 2030. Beijing has directed massive investments into AI research, subsidized domestic champions, and mandated AI adoption across industries. Chinese firms like Baidu, Alibaba, Tencent, and newer entrants have closed capability gaps in many application domains.
China possesses distinctive advantages: a vast population generating training data, a government capable of mobilizing resources and mandating adoption, fewer constraints on surveillance applications that provide real-world AI deployment experience, and a large technical workforce. State direction enables coordination between civilian and military AI development that the American system does not easily achieve.
However, China faces significant constraints. American export controls on advanced semiconductors and manufacturing equipment have impaired Chinese access to cutting-edge chips essential for training frontier AI models. The “great firewall” that protects domestic firms from foreign competition may also limit their global competitiveness. Authoritarian control may inhibit the creative culture that produces breakthrough research. And China’s demographic trajectory suggests a shrinking workforce even as AI development demands more talent.
The competition is not merely bilateral. Both powers seek to draw others into their technological ecosystems, creating pressures toward bloc formation. Nations must increasingly choose whose AI systems to deploy, whose standards to adopt, and whose regulations to follow.
Military Transformation¶
Defense establishments worldwide are racing to integrate AI into military systems, recognizing that AI capabilities may prove as consequential as earlier revolutions in military affairs.
Intelligence, surveillance, and reconnaissance represent the most mature military AI applications. Systems that can analyze satellite imagery, intercept communications, and process open-source intelligence at scale provide decision-makers with unprecedented information. Project Maven, the controversial Pentagon program that applied AI to drone footage analysis, exemplified early military AI deployment.
Autonomous systems raise the most profound questions. Drones that can identify and engage targets without human intervention, naval vessels that operate independently, and cyber weapons that autonomously propagate all challenge existing frameworks of command responsibility and international humanitarian law. The degree of human control required over lethal autonomous weapons systems remains fiercely debated.
Command and control acceleration through AI decision support could compress the timeline for military decisions from hours to seconds. This tempo advantage could prove decisive, but also risks catastrophic miscalculation. When AI systems on both sides of a conflict recommend rapid escalation, human judgment may be bypassed entirely.
Nuclear stability represents perhaps the gravest concern. AI-enabled advances in sensing and targeting might undermine second-strike capabilities that have maintained nuclear deterrence. If one side believes it can locate and destroy the other’s nuclear forces before retaliation, the calculus of deterrence changes dangerously. Scholars have warned that AI could destabilize the nuclear balance that has prevented great power war for eight decades.
Cyber operations increasingly incorporate AI for both offense and defense. AI systems can identify vulnerabilities, craft intrusion tools, and respond to attacks faster than human operators. The result may be a persistent, low-level cyber conflict in which AI systems continually probe and defend network perimeters.
These military applications ensure that AI development will remain a national security priority regardless of commercial dynamics. No major power will accept strategic dependence on rivals for military-relevant AI capabilities.
The European Approach¶
The European Union has charted a distinctive path in AI governance, emphasizing regulation and rights protection over raw capability development. This approach reflects both European values and the practical reality that Europe lacks AI champions comparable to American or Chinese firms.
The AI Act, adopted in 2024, represents the world’s most comprehensive AI regulatory framework. It establishes risk-based categories for AI systems, with strict requirements for high-risk applications in areas like biometric identification, critical infrastructure, and employment decisions. Prohibited applications include social scoring systems and certain forms of predictive policing. The Act aims to ensure AI deployment consistent with fundamental rights and democratic values.
The Brussels effect may extend European influence beyond its borders. As with the General Data Protection Regulation (GDPR), companies seeking access to the European market may adopt EU AI standards globally rather than maintain separate systems. Europe thus wields regulatory power even without producing leading AI firms.
Strategic autonomy concerns motivate European efforts to reduce dependence on American and Chinese AI systems. Initiatives like GAIA-X for cloud infrastructure and various AI research programs aim to develop European capabilities. Yet Europe faces structural challenges: fragmented national markets, insufficient venture capital, and difficulty retaining technical talent drawn to American opportunities.
Ethical leadership represents an alternative form of influence. By establishing norms around trustworthy AI, Europe positions itself as the standard-setter for responsible development. Whether this leadership proves influential or merely marginal to the main competition remains to be seen.
The European approach offers a potential model for nations seeking to deploy AI benefits while limiting harms, but it does not resolve the fundamental challenge of capability dependence on external powers.
The Competition for Talent¶
AI development depends ultimately on human expertise, making talent competition a critical dimension of the geopolitical contest. The supply of researchers capable of advancing frontier AI remains limited, and their geographic distribution shapes national capabilities.
American universities have trained a disproportionate share of leading AI researchers, including many from China and other nations. This training pipeline has historically benefited American AI development as many graduates remained to work in US industry and academia. Immigration policy thus directly affects AI capability.
Chinese talent development has accelerated dramatically. Chinese universities now produce more STEM graduates than any other nation, and returning diaspora researchers have strengthened domestic institutions. State support for AI education aims to reduce dependence on foreign training.
Global competition for AI talent has intensified. Nations including Canada, the United Kingdom, France, and others have implemented visa programs and research funding specifically to attract AI researchers. The concentration of talent in a few global hubs creates vulnerabilities; the relocation of even a small number of leading researchers can shift capability balances.
Salary disparities between academic and industry positions, and between nations, shape talent flows. American technology firms can offer compensation that few academic institutions or foreign employers can match. This economic pull concentrates capability in private American hands.
The talent dimension illustrates how AI competition involves not merely technology policy but immigration, education, and labor market dynamics. Nations cannot develop AI capabilities without the people to do so.
Governance Challenges¶
The rapid advancement of AI capabilities has outpaced the development of governance frameworks, creating regulatory gaps that both enable innovation and risk harm.
International coordination on AI governance remains nascent. No equivalent to nuclear non-proliferation treaties or climate agreements governs AI development. The Bletchley Declaration of 2023 brought together major AI powers to acknowledge risks, but established no binding commitments. Fundamental disagreements between democratic and authoritarian approaches to AI governance impede consensus.
Dual-use characteristics complicate control regimes. The same AI systems that optimize logistics can coordinate military operations; the same language models that assist writing can generate disinformation. Unlike nuclear materials, AI capabilities cannot be physically secured or easily monitored. Export controls on semiconductors represent an attempt to limit capability diffusion through hardware restrictions, but their long-term effectiveness remains uncertain.
Safety concerns have grown alongside capability advances. Leading AI researchers have warned that advanced AI systems could pose existential risks if their objectives diverge from human values. Whether such risks are imminent or speculative is debated, but the possibility has motivated both voluntary industry commitments and preliminary regulatory attention.
Accountability gaps emerge when AI systems cause harm. When an autonomous vehicle causes an accident or an AI hiring system discriminates, determining responsibility across developers, deployers, and users proves difficult. Existing legal frameworks designed for human decision-makers fit AI systems poorly.
Standards competition mirrors broader technological rivalry. China has sought to shape international AI standards through bodies like the International Telecommunication Union, sometimes advancing approaches that embed authoritarian values. Democratic nations have countered with alternative frameworks emphasizing rights protection and transparency.
These governance challenges will not be resolved quickly. The speed of AI development, the diversity of applications, the commercial and strategic interests at stake, and the ideological differences between major powers all impede comprehensive governance solutions.
Implications for the International Order¶
The AI competition is not merely a technological race but a contest to shape the international order itself.
Power distribution may shift as AI capability concentrates. Nations that lead in AI will enjoy compounding advantages across economic, military, and informational dimensions. Those that fall behind risk technological dependency resembling colonial-era raw material extraction, providing data and labor while value accrues elsewhere.
Geoeconomic competition increasingly centers on AI-related supply chains. Control over semiconductors, training data, and AI infrastructure provides leverage that states can wield for strategic purposes. Weaponized interdependence extends naturally to AI dependencies.
Democratic governance faces distinctive AI challenges. Surveillance capabilities that authoritarian states embrace may be incompatible with democratic values. Yet democracies that forswear such tools may find themselves at a competitive disadvantage. Navigating this tension will test democratic societies.
Developing nations face difficult choices. Adopting Chinese or American AI systems creates dependencies on external powers; developing indigenous capabilities requires resources few possess. The AI divide may reinforce existing global inequalities even as the technology promises productivity gains.
The geopolitics of artificial intelligence will unfold over decades, shaped by technological breakthroughs, policy choices, and contingent events that cannot be predicted. What seems certain is that AI has joined territory, resources, and military power as a fundamental dimension of statecraft. Understanding the strategic dynamics of AI competition has become essential for comprehending the international order now emerging.