Compute, energy, minerals and governance shaping the AI race

The global race for AI dominance in 2026 is increasingly defined by three critical enablers: compute infrastructure, reliable low-carbon energy, and secure access to critical minerals. These pillars are shaping not only technological advancement but also geopolitics, security, and international cooperation. At the same time, governance frameworks, cyber sovereignty, and norms are determining how these enablers are utilized and protected, adding layers of strategic complexity to the AI race.

Compute Infrastructure: The Shift Toward Regionalization and Sovereignty

Traditionally, control over AI compute resources was concentrated among major tech giants like AWS, Microsoft Azure, and Alibaba Cloud. However, recent developments highlight a paradigm shift toward regionalized and sovereign compute ecosystems driven by geopolitical imperatives. Countries wary of US-China decoupling are investing heavily in domestic data centers, regional cloud infrastructure, and AI hardware to foster autonomous, secure AI environments.

• Localized Compute Hubs: Companies such as CoreWeave and emerging regional cloud providers are establishing localized compute centers to reduce dependence on global giants and bolster data sovereignty.
• National Strategies: Governments see control over AI infrastructure as a matter of national security, leading to aggressive investments in building domestic data centers and AI-specific hardware.
• Development of Domestic LLMs: Leaders like Alibaba are creating homegrown large language models such as Qwen3.5 to ensure technological self-reliance, especially in response to export restrictions and geopolitical decoupling.
• New Alliances and Supply Chain Diversification: Initiatives like IMEC's semiconductor collaborations and India-EU Free Trade Agreements are creating alternative supply corridors, reducing reliance on traditional superpowers and ensuring resilient compute supply chains vital for sustained AI progress.

Energy Infrastructure: Powering AI with Low-Carbon, Reliable Sources

AI's insatiable computational demands make energy infrastructure a strategic focal point. Ensuring reliable, low-carbon energy supplies is essential for sustainability and uninterrupted AI development.

• Emergence of Small Modular Reactors (SMRs): SMRs are gaining prominence as scalable, safe, and low-carbon solutions capable of powering large-scale AI data centers. Countries are investing in SMRs to reduce fossil fuel dependence and secure energy independence.
• Integration of Renewables and Nuclear Power: Advances in solar photovoltaics and nuclear energy are being incorporated into AI infrastructure planning. Hybrid systems combining renewables and nuclear power are increasingly seen as necessary for meeting AI’s exponential energy needs while maintaining cost-effectiveness and resilience.
• Regional Risks and Strategic Policies: Geopolitical instability in regions like the Middle East, Ukraine, and Africa pose risks to energy security. To counter this, nations are prioritizing diversification strategies, renewable investments, and regional energy interconnections to future-proof AI ecosystems.

Securing Critical Minerals and Hardware Supply Chains

AI hardware—semiconductors, chips, and memory modules—relies heavily on critical minerals, notably Rare Earth Elements (REEs) and precious metals.

• Strategic Importance of REEs: These minerals are indispensable for manufacturing high-performance chips. Control over REE supply chains allows nations to influence hardware deployment and AI capacity expansion.
• China’s Dominance: China maintains a near-monopoly over REE processing and refining, giving it significant strategic leverage. Recent export restrictions and diplomatic tensions have exposed vulnerabilities in global supply chains, risking delays and cost increases.
• Diversification and Recycling: Recognizing these vulnerabilities, Australia, Europe, and the US are investing in domestic mineral extraction, processing capabilities, and recycling programs to reduce dependency on Chinese supply chains. Projects like rare earth mining in Australia and European recycling efforts aim to build resilience and self-sufficiency.

Geopolitical Dynamics and International Alliances

The AI infrastructure race is embedded within broader geopolitical shifts:

• India-EU Cooperation: Initiatives like IMEC's collaboration with India and the India-EU Free Trade Agreement are creating new supply chain corridors and technological cooperation frameworks to diversify and strengthen resilience against traditional superpower dominance.
• Japan’s Strategic Recalibration: Japan emphasizes technological independence through domestic mineral sourcing, advanced nuclear energy, and AI hardware innovation, seeking to position itself as a regional AI infrastructure hub.
• China’s Diplomatic Strategies: China leverages the Belt and Road Initiative to secure resource access and technological cooperation across Asia, Africa, and Europe, maintaining its dominance over supply chains vital for AI.
• Regional Risks: Tensions in the Middle East, Eastern Europe, and East Asia threaten energy security, resource availability, and supply chain stability, potentially delaying AI infrastructure expansion.

Governance, Cybersecurity, and Dual-Use Risks

The rapid expansion of AI infrastructure introduces significant vulnerabilities:

• Cyber Threats: AI data centers and supply chains are prime targets for cyber espionage, sabotage, and state-sponsored attacks. Incidents involving industry-government tensions—such as Anthropic’s standoff with the Pentagon—highlight the cyber vulnerabilities.
• Dual-Use and Military AI Risks: The proliferation of autonomous military systems raises escalation risks, miscalculations, and concerns over weaponization. The development of autonomous weapons without robust international norms heightens security tensions.
• International Norms and Resilience: Developing global standards for AI security, export controls, and dual-use regulation is crucial to prevent conflicts, manage proliferation, and protect human rights. The lack of cohesive governance frameworks could lead to misunderstandings and destabilization.

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Implications for 2026 and Beyond

The convergence of these factors underscores that control over compute, energy, and minerals is fundamental to geopolitical influence and technological leadership. Nations investing in resilient supply chains, domestic infrastructure, and international cooperation are positioning themselves as future AI leaders. Conversely, regional tensions, resource dependencies, and security vulnerabilities threaten to hamper progress and exacerbate conflicts.

Resilience and sovereignty will be decisive in sustaining AI innovation, while international norms and governance are essential to prevent misuse and manage risks. As the AI race intensifies, those who secure the foundations—compute, power, and minerals—will shape the geopolitical and technological order of the coming decades.

In summary, the future of AI leadership in 2026 hinges on who controls these critical enablers. The ongoing efforts to regionalize compute, integrate low-carbon energy, and diversify mineral supply chains are not just technological strategies—they are geopolitical imperatives that will define global power dynamics for years to come.