Technology and International Affairs in 2026: How AI, Cybersecurity, and Geopolitics Are Reshaping the Global Order

The New Great Power Competition: How the US-China AI Race Is Redefining Global Strategy

The artificial intelligence competition between the United States and China has evolved from an economic rivalry into a defining feature of 21st-century geopolitics. According to the Carnegie Endowment for International Peace’s comprehensive analysis of technology and international affairs, this competition is reshaping global strategic thinking across multiple dimensions.

The Carnegie Endowment’s research, spanning over 514 published results across 20 topics and 43 regions, reveals that the AI race has moved beyond simple technological advancement to encompass questions of national security, economic competitiveness, and global governance. The competition is particularly intense in areas where AI intersects with traditional security concerns, including military applications, critical infrastructure protection, and information warfare capabilities.

What makes this competition particularly complex is how it’s forcing allied nations and middle powers to make increasingly difficult choices. Unlike previous technological competitions that could be compartmentalized, AI development touches virtually every aspect of modern society and governance. Nations find themselves having to choose not just trading partners, but entire technological ecosystems that will shape their digital futures.

The strategic implications extend beyond the immediate participants. As the evolution of AI policy frameworks demonstrates, the US-China competition is driving rapid policy development worldwide as nations seek to position themselves advantageously in this new landscape.

DeepSeek and Beyond — China’s Emerging AI Surprises and What They Mean for the West

China’s release of DeepSeek represents what Carnegie analysts describe as a “warning shot” in the AI competition—a demonstration that Chinese AI capabilities may be advancing faster and more independently than Western intelligence assessments suggested. This development has profound implications for how the West understands Chinese AI strategy and capabilities.

DeepSeek’s emergence highlights China’s dual-track approach to AI development. While Western observers focused on China’s investments in large language models competing directly with GPT-4 and similar systems, Chinese researchers were simultaneously developing alternative architectures and training methodologies that could potentially bypass some Western technological advantages.

The geopolitical significance of DeepSeek extends beyond its technical capabilities. It signals China’s growing confidence in challenging Western AI dominance directly, rather than simply pursuing separate development paths. This represents a shift from China’s earlier strategy of building parallel systems to a more confrontational approach of developing superior alternatives to Western technologies.

For Western policymakers, DeepSeek raises difficult questions about the effectiveness of current export controls and technology transfer restrictions. If China can develop competitive AI systems with limited access to cutting-edge Western chips and software, the entire premise of technological containment strategies may need fundamental revision.

Embodied AI and Smart Robotics: The Next Frontier of Strategic Competition

While much attention has focused on large language models and generative AI, Carnegie researchers identify embodied AI and smart robotics as the next critical battleground in technological competition. China’s substantial investments in this area represent a strategic bet on the physical manifestation of artificial intelligence.

Embodied AI—artificial intelligence systems that interact with the physical world through robotic platforms—represents a convergence of AI software capabilities with advanced manufacturing and engineering. This fusion creates new categories of economic and military applications that extend far beyond traditional computing environments.

China’s approach to embodied AI development emphasizes integration across the full technology stack, from semiconductor design to robotic hardware to AI software. This holistic approach potentially gives China advantages in developing general-purpose robotics platforms that could have broad commercial and military applications.

European competitiveness in this space appears particularly challenged, according to Carnegie analysis. While Europe maintains strengths in precision manufacturing and industrial automation, the integration of advanced AI capabilities with robotics platforms may require the kind of large-scale investment and coordination that has proven difficult within the European Union’s fragmented technology ecosystem.

The AI Divide: Why Low- and Middle-Income Countries Risk Being Left Behind

The concept of an “AI divide” has emerged as one of the most significant concerns in international technology policy. As outlined in Foreign Affairs research cited by Carnegie, this divide threatens to create new forms of technological dependency that could reshape global power dynamics for decades.

Historical patterns of technological revolution suggest that nations unable to participate meaningfully in the development and deployment of transformative technologies often find themselves permanently disadvantaged. The AI revolution appears to be following this pattern, with a small number of frontier nations—primarily the United States and China—pulling ahead of the rest of the world in terms of both capabilities and resources.

The barriers to AI participation are particularly high for developing nations. Advanced AI development requires not just financial resources, but also technical expertise, computational infrastructure, and access to large datasets. These requirements create multiple layers of exclusion that can be difficult to overcome even with international assistance.

What makes the AI divide particularly concerning is how it could compound existing inequalities. Nations excluded from AI development may find themselves not just economically disadvantaged, but also unable to participate meaningfully in setting global AI governance standards. This creates a feedback loop where technological exclusion leads to political marginalization, which in turn reinforces technological exclusion.

Middle Powers in the Crossfire: Navigating Between Competing AI Ecosystems

Carnegie research identifies middle powers as facing perhaps the most complex strategic decisions in the current AI landscape. Unlike developing nations that may have limited choices, middle powers often possess sufficient resources to pursue multiple technological partnerships, but must navigate increasingly incompatible ecosystem requirements.

The challenge for middle powers extends beyond simple technology procurement decisions. AI ecosystems include not just hardware and software, but also data governance frameworks, regulatory standards, and security protocols. Choosing one ecosystem over another can have long-term implications for a nation’s digital sovereignty and strategic autonomy.

Several middle powers are pursuing hedging strategies that attempt to maintain relationships with both US and Chinese technology ecosystems. However, as export controls and technology transfer restrictions become more stringent, such hedging may become increasingly difficult or impossible.

The NIST AI standards development process represents one attempt to create international technical standards that could provide middle powers with alternatives to choosing sides completely. However, the effectiveness of such multilateral approaches remains unclear in an increasingly polarized technological environment.

From Chips to Data Centers: How Physical Infrastructure Became a Geopolitical Battleground

The targeting of data centers in recent conflicts marks a significant shift in how physical infrastructure intersects with digital operations and international security. Carnegie analysis highlights how the Iran conflict demonstrated the vulnerability of what was previously considered relatively protected civilian infrastructure.

Data centers represent a unique category of critical infrastructure because they simultaneously serve civilian and military functions, often without clear distinctions. A data center supporting civilian cloud services may also host applications critical to national security, creating complex questions about legitimate targeting in conflicts.

The semiconductor supply chain represents another critical vulnerability highlighted in Carnegie research. The Nexperia crisis demonstrated how export controls affecting single companies can have cascade effects throughout global technology supply chains, particularly when those companies control critical chokepoints in semiconductor manufacturing.

These infrastructure vulnerabilities create new requirements for international coordination on protection of critical technology assets. However, such coordination is complicated by the dual-use nature of many technologies and the competitive dynamics between major powers.

Governing the Ungovernable: The State of AI Regulation at International, National, and Subnational Levels

AI governance in 2026 represents what Carnegie researchers describe as a complex multilevel challenge, with regulatory initiatives proceeding simultaneously at international, national, and subnational levels without clear coordination mechanisms. This fragmented approach creates both opportunities and risks for effective AI governance.

At the international level, the International AI Safety Report 2026 represents the most comprehensive attempt to date to establish global AI governance frameworks. However, the effectiveness of international coordination remains limited by fundamental disagreements between major powers about the appropriate scope and mechanisms for AI regulation.

National-level AI regulation has proceeded more rapidly, but with significant variation in approaches and priorities. The United States has seen particularly active development at the state level, with New York’s RAISE Act aligning with California’s existing frameworks to create an emerging subnational consensus on frontier AI regulation.

China’s approach to AI regulation has focused particularly on anthropomorphic AI and AI companions, reflecting different cultural and political priorities compared to Western regulatory frameworks. This divergence in regulatory approaches could lead to further fragmentation of global AI governance standards.

AI-Orchestrated Hacking and the New Cyber Threat Landscape

The emergence of AI-orchestrated hacking represents a fundamental shift in the cyber threat landscape, lowering barriers to sophisticated attacks and enabling actors with limited technical capabilities to conduct operations previously requiring nation-state resources. Carnegie analysis identifies this as one of the most concerning near-term developments in cybersecurity.

AI-orchestrated attacks differ from traditional automated hacking in their ability to adapt and respond to defensive measures in real-time. These systems can potentially conduct reconnaissance, develop exploits, and execute attacks with minimal human supervision, dramatically accelerating attack timelines and complicating attribution efforts.

The proliferation of AI-enabled cyber capabilities raises particular concerns about escalation dynamics in international conflicts. When attacks can be conducted rapidly and anonymously by a wide range of actors, traditional concepts of deterrence and response become much more complex to implement.

International coordination on AI cybersecurity presents unique challenges because the same technologies that enable defensive AI capabilities can also be used for offensive purposes. This dual-use problem makes traditional arms control approaches difficult to apply to AI-enabled cyber weapons.

Drones, Nuclear Deterrence, and AI: The Evolving Security Implications of Autonomous Technology

The intersection of autonomous technology with traditional security domains is creating new categories of strategic challenges, particularly visible in the proliferation of drone warfare capabilities and their potential interaction with nuclear deterrence systems. Carnegie research highlights how conflicts in Sudan and Ukraine have demonstrated the rapid evolution of autonomous weapons capabilities.

Drone proliferation represents a democratization of precision strike capabilities that was previously limited to major military powers. The integration of AI systems with drone platforms enables autonomous target selection and engagement capabilities that could fundamentally alter the character of conflicts.

Perhaps most concerning is the potential interaction between AI-enabled autonomous systems and nuclear command and control systems. While major nuclear powers have generally maintained human control over nuclear weapons decisions, the increasing speed of AI-enabled conflicts could create pressure to delegate more decision-making authority to autonomous systems.

The development of cybersecurity frameworks for autonomous systems represents a critical challenge for maintaining strategic stability in an era of increasing automation of security decisions.

Information Integrity Under Siege: Deepfakes, Influence Operations, and the Crisis of Trust

The Carnegie Endowment’s analysis of information integrity challenges highlights a fundamental shift in how societies understand and verify information. The emergence of sophisticated deepfake technologies and AI-enabled influence operations has created what researchers describe as an environment where “seeing is no longer believing.”

Deepfake technology has evolved from a novelty to a practical tool for disinformation that can be deployed at scale by both state and non-state actors. The democratization of these capabilities means that sophisticated information manipulation is no longer limited to well-resourced intelligence agencies.

AI-enabled influence operations can now adapt their messaging and targeting in real-time based on audience responses, making them much more effective than traditional propaganda techniques. These systems can potentially conduct A/B testing on disinformation campaigns to optimize their impact across different demographic and political segments.

The challenge for democratic societies is developing technological and institutional responses to these threats without undermining fundamental principles of free expression and open information sharing. This balance becomes particularly difficult when the same AI technologies that enable disinformation can also be used to detect and counter it.

South-South Cooperation and the Path to Inclusive AI Development

Carnegie research identifies South-South cooperation as potentially offering alternative pathways for AI development that could help address the growing AI divide. Rather than simply accepting technological dependency on major powers, developing nations are exploring collaborative approaches to AI development and deployment.

South-South cooperation in AI development offers several potential advantages, including shared development costs, pooled technical expertise, and governance frameworks that reflect the priorities and constraints of developing nations rather than major powers. These collaborations could potentially create alternative AI ecosystems that are more accessible and appropriate for developing country contexts.

However, South-South AI cooperation also faces significant challenges, including limited resources, competition for scarce technical talent, and pressure from major powers to choose sides in the broader AI competition. The success of such initiatives may depend on their ability to maintain strategic autonomy while engaging productively with existing AI ecosystems.

What’s Next — Key Trends That Will Shape Technology Policy Through 2026 and Beyond

Looking toward the remainder of 2026 and beyond, Carnegie researchers identify several key trends that will likely shape the intersection of technology and international affairs. Understanding these trends is crucial for policymakers, business leaders, and civil society organizations working to navigate an increasingly complex technological landscape.

The fragmentation of global AI governance is likely to continue, with different regions and nations pursuing increasingly divergent approaches to AI regulation and development. This fragmentation could lead to the emergence of distinct technological spheres of influence, similar to the internet balkanization that some observers have predicted.

Physical infrastructure protection will become an increasingly important aspect of national security strategy, as the targeting of data centers and semiconductor facilities demonstrates the vulnerability of critical technology assets. Nations will need to develop new frameworks for protecting civilian infrastructure that also serves security functions.

The role of middle powers in technology governance may become increasingly important as they develop hedging strategies and alternative partnerships that could provide models for other nations seeking to maintain strategic autonomy in an increasingly polarized technological environment.

Finally, the intersection of AI with traditional security domains—from nuclear deterrence to conventional warfare—will require new forms of international coordination and arms control that can address the dual-use nature of AI technologies while maintaining strategic stability. The development of these frameworks represents one of the most significant challenges in contemporary international relations.