Navigating the New Geopolitical Era of AI Sovereignty: Critical Minerals, Military Competition, and Middle Power Strategies

As artificial intelligence (AI) continues to reshape the global landscape—spanning economic, strategic, and normative domains—the geopolitical stakes surrounding this transformative technology have escalated dramatically. The competition is no longer confined to innovation alone but now hinges critically on control over vital resources, supply chains, and the normative frameworks that will govern future deployment. Recent developments underscore a complex, evolving terrain where US–China rivalry, resource diplomacy, and middle power resilience intersect, with profound implications for global stability and technological sovereignty.

The Geopolitical Stakes: Semiconductors, Critical Minerals, and Supply Chain Control

At the heart of AI’s rapid advancement lie interwoven supply chains reliant on semiconductors, advanced manufacturing, and critical mineral resources such as lithium, cobalt, and rare earth elements. These components are essential for producing AI hardware—particularly GPUs, processors, and specialized chips that power large AI models.

• Semiconductors and GPUs: Leading AI models demand high-performance chips, predominantly supplied by companies like Nvidia, whose GPUs are fabricated through TSMC’s state-of-the-art process nodes. The US has recently imposed export restrictions targeting high-end chip technologies to limit China’s access to critical manufacturing capabilities, aiming to curb Beijing’s AI ambitions. Meanwhile, China is aggressively pursuing indigenous semiconductor industries to achieve self-reliance, exemplifying a strategic push for technological sovereignty.

• Resource Diplomacy and Critical Minerals: Control over lithium, cobalt, and rare earths has become a dominant strategic consideration. Countries like Greenland, with vast deposits of rare earth elements, have become focal points in resource geopolitics. Major powers are engaging diplomatically and economically to secure extraction rights, understanding that resource dominance could reshape regional influence.

Recent Developments

• Greenland’s mineral deposits—once seen as peripheral—have surged in strategic importance, with global powers vying to invest in and secure access to its rare earth reserves. Diplomatic negotiations and strategic investments are intensifying, with Greenland emerging as a critical node in the AI hardware supply chain.

• China’s indigenization efforts are accelerating, with government-backed projects establishing regional supply chains for rare earths and semiconductor materials. These initiatives aim to bypass Western sanctions, strengthen self-sufficiency, and position China as a dominant player in critical resources and high-tech manufacturing.

• The US, through initiatives like the CHIPS Act, is incentivizing domestic fabrication and research & development to counterbalance China’s technological rise. This strategic move aims to secure supply chains, support innovation, and maintain technological leadership.

Middle Powers: Resilience through Alliances and Sovereignty Measures

Amid the fierce US–China competition, middle powers are adopting strategies emphasizing autonomy and digital sovereignty:

• India has become a key regional actor, exemplified by its signing of Pax Silica, a strategic agreement with the US aimed at countering China’s influence over critical minerals and AI infrastructure. India’s approach balances economic growth with independent policymaking, seeking to avoid over-reliance on any single power.

• Countries like Vietnam and nations within the Middle East are developing AI ecosystems through sovereign cloud partnerships and local AI initiatives. Firms such as G42 are working to insulate regional digital infrastructure, fostering resilient, autonomous ecosystems less vulnerable to external disruptions.

• The EU-India partnership seeks to set global AI standards and develop normative frameworks. However, diverging visions and regulatory approaches threaten to cause fragmentation, complicating efforts toward interoperability and trustworthiness of AI systems internationally.

Diverging Approaches to AI Governance: Fragmentation versus Harmonization

Countries are adopting contrasting models for AI regulation, reflecting their underlying priorities:

• The European Union emphasizes comprehensive frameworks such as the EU AI Act, stressing safety, transparency, and accountability. Its goal is to set international standards that could influence global norms.

• The United States prefers industry-driven oversight and flexible liability regimes, aiming to foster innovation while managing risks through adaptive regulation. Recent legislative proposals aim to embed liability laws as primary governance tools, prioritizing regulatory agility.

• China pursues a deployment-focused approach, rapidly integrating AI into industry, governance, and military applications. Its strategy emphasizes economic power projection and soft influence but risks standard divergence and trust deficits internationally.

This divergence is contributing to a fragmented global AI ecosystem, raising concerns over interoperability, trustworthiness, and security, especially as norms and standards evolve independently.

Military and Security Dimensions: AI as a Strategic Asset

AI’s integration into military systems introduces new strategic risks:

• Autonomous weapons systems, AI-enabled defense platforms, and surveillance technologies are central to the modern militarization of AI. Both the US and China are advancing autonomous capabilities, intensifying arms race dynamics.

• China’s rapid development in autonomous systems, missile guidance, and surveillance heightens fears of strategic instability. The deployment of AI-driven military assets raises urgent questions about arms control and rules of engagement.

• Recent military summits—such as the AIDEF 2026—highlight AI’s strategic importance, with experts like Theo Franken and Jerome Leclanche discussing ethical challenges and technological innovations in defense AI. Discussions include autonomous nuclear systems and combat AI ethics, signaling the heightened stakes.

Corporate and Geopolitical Actors: Private Firms as Strategic Stakeholders

Private technology companies are increasingly acting as strategic actors:

• Nvidia remains at the center of the AI hardware ecosystem, with its leading GPU architectures underpinning global AI development. The recent investor anticipation around Nvidia’s earnings underscores its critical role.

• Anthropic, a major AI firm, recently loosened safety policies to accelerate development, signaling tensions between innovation and safety. As reported by Bloomberg on February 25, 2026, “Anthropic’s policy shift reflects a broader industry trend toward balancing rapid AI deployment with ethical considerations,” but it also raises concerns over safety and regulatory oversight.

• Governments are leveraging public-private partnerships and strategic investments to shape AI development, especially in middle-power contexts like India and Taiwan, aiming to secure critical infrastructure and counter dominant players.

Diplomatic and Normative Initiatives: US and Regional Models

A notable recent development involves the US diplomatic effort to counter foreign data sovereignty laws. The Trump administration directed diplomats to lobby against restrictions on US-based data flows, aiming to maintain open digital ecosystems. This approach has implications:

• It challenges international data governance, risking fragmentation of global data flows.
• It undermines international cooperation on AI security and standards.

In parallel, Taiwan’s passage of the AI Basic Act (December 2025, enacted January 2026) exemplifies a regional regulatory model emphasizing ethical standards, regulatory clarity, and public-private collaboration. Taiwan’s approach positions it as an emerging leader in AI governance within Asia, providing a potential blueprint for balancing innovation and regulation amid regional competition.

Current Status and Future Outlook

The landscape today is marked by rising resource dependencies, regulatory divergence, and military competition, all fueled by the US–China rivalry. Middle powers are actively diversifying resources, strengthening regional alliances, and advancing normative frameworks to safeguard sovereignty and resilience.

However, fragmentation presents significant risks:

• Diverging standards threaten interoperability.
• Resource control could shift regional power balances.
• Military AI escalation risks strategic instability and miscalculation.

The key challenge moving forward revolves around balancing sovereignty with international cooperation. Developing autonomous, resilient ecosystems, fostering normative dialogue, and ensuring diverse resource access will be critical for middle powers seeking to navigate this complex environment.

In conclusion, the decisions made today will determine whether AI becomes a catalyst for shared progress or deepens global divisions—with profound consequences for stability, security, and human welfare in the decades ahead. Maintaining a delicate balance between autonomy and cooperation is essential to avoid a fractured future and to promote a sustainable, secure, and inclusive AI-driven world.