Nations are in a digital arms race over AI infrastructure—controlling data pipelines, compute, and models. Sovereign systems like Switzerland’s Apertus and India’s AIRAWAT deliver economic, security, innovation, and cultural dividends that compound over time.  

The metaphor of data as the “new oil” has long dominated discussions about the digital economy, implying that data, like oil, is a raw resource to be extracted, refined, and monetized. Similarly, compute power has been likened to steel—a foundational material enabling industrial progress. These analogies, while evocative, are outdated. In the age of artificial intelligence (AI), infrastructure—encompassing data pipelines, compute clusters, and AI models—has emerged as the new sovereignty. Sovereignty in this context is not merely political but deeply technical: those who control the pipelines that channel data, the clusters that process it, and the models that derive intelligence from it wield unparalleled leverage in the global order. As nations race to secure this leverage, AI infrastructure has become a geopolitical battleground, rivaling the strategic importance of ports, power grids, and satellites.

This article explores why AI infrastructure is a cornerstone of national power, how sovereign and open AI models like Switzerland’s Apertus, India’s AIRAWAT, and the EU’s LEAM offer a path to autonomy, and why the “sovereignty dividend” promises economic, security, innovation, and cultural benefits. It also examines the risks of failing to secure AI sovereignty and outlines a policy playbook for nations to assert control over their digital destinies.

The Strategic Stakes

AI infrastructure is not just a technological asset; it is geopolitical infrastructure, akin to the ports that facilitate trade, the power grids that sustain economies, and the satellites that enable communication and surveillance. Control over AI infrastructure determines a nation’s ability to shape its economic, security, and cultural future. Just as ports once dictated maritime dominance and power grids underpinned industrial revolutions, AI infrastructure—data centers, high-performance computing (HPC) clusters, and foundation models—defines who holds the reins of intelligence in the 21st century.

Proprietary AI models, such as those developed by OpenAI, Anthropic, and Google DeepMind, create dependencies that mirror historical colonial structures. Nations relying on these models face vendor lock-in, where access to AI capabilities is mediated by foreign corporations subject to their own governments’ priorities. This introduces vulnerabilities: API access can be throttled, pricing can shift unpredictably, and models can embed biases or values misaligned with local needs. For example, a nation dependent on a U.S.-based model risks service disruptions if geopolitical tensions lead to sanctions or export controls, as seen in U.S.-China tech rivalries.

In contrast, open and sovereign AI models, such as Switzerland’s Apertus, India’s AIRAWAT, and the EU’s LEAM, offer autonomy and bargaining power. These models, developed with public or national interests in mind, allow countries to control their AI stack—from data to compute to deployment—reducing reliance on foreign providers. By fostering self-sufficiency, sovereign AI infrastructure empowers nations to negotiate global partnerships from a position of strength, much like control over physical infrastructure enabled maritime powers to dictate trade terms centuries ago.

The Sovereignty Dividend

The “sovereignty dividend” refers to the multifaceted benefits that accrue from investing in sovereign AI infrastructure. These benefits span economic, security, innovation, and cultural domains, compounding over time to create a resilient, self-reliant digital ecosystem.

a) Economic Dividend

Sovereign AI infrastructure generates significant economic returns by fostering local industries and retaining value within national borders. Building and maintaining HPC clusters, data centers, and AI training pipelines creates high-skill jobs in areas like data annotation, model optimization, and systems engineering. For instance, India’s AIRAWAT initiative, part of the IndiaAI Mission, is investing in supercomputing and cloud infrastructure, creating opportunities for local engineers and researchers.

Moreover, sovereign AI prevents economic leakage. When nations rely on foreign models, billions in licensing fees, API usage costs, and infrastructure bills flow to overseas providers like Amazon, Microsoft, or Google. By contrast, sovereign models like Apertus, hosted on platforms like Swisscom’s sovereign cloud, ensure that these funds remain within the local economy, supporting domestic innovation and infrastructure development. This retained value can be reinvested into education, research, and startup ecosystems, amplifying economic growth.

b) Security Dividend

AI sovereignty is critical for national security, particularly for defense, critical infrastructure, and intelligence operations. Relying on foreign models introduces risks: proprietary systems are black boxes, potentially embedding backdoors or vulnerabilities exploitable by adversaries. For example, a nation using a foreign AI model for defense analytics could face surveillance or data leaks, compromising sensitive operations. Sovereign models, built and controlled domestically, mitigate these risks by ensuring transparency and control over the AI stack.

Additionally, sovereign AI reduces exposure to geopolitical disruptions. U.S. export controls on advanced chips, as seen in restrictions on China, highlight how dependence on foreign technology can be weaponized. Sovereign infrastructure, such as China’s domestic chip and server manufacturing or the EU’s Gaia-X initiative, ensures continuity of AI capabilities during sanctions or supply chain disruptions. This security dividend is vital for maintaining operational resilience in critical sectors like energy, finance, and transportation.

c) Innovation Dividend

Sovereign AI fosters a vibrant innovation ecosystem by providing open access to critical resources. Unlike proprietary models, which gatekeep access through APIs or restrictive licensing, open models like Apertus—developed by EPFL, ETH Zurich, and CSCS—offer researchers, startups, and universities unrestricted access to model weights, training data, and documentation. This democratizes innovation, enabling local developers to build applications tailored to national needs, from healthcare diagnostics to climate modeling.

For example, Switzerland’s Apertus, trained on 15 trillion tokens across 1,000+ languages, allows developers to create chatbots, translation tools, and educational platforms without relying on foreign APIs. Similarly, India’s Bhashini platform, which supports AI-driven language processing for Indian languages, empowers startups to develop localized solutions, fostering a competitive domestic AI sector. This innovation dividend ensures that nations can cultivate their own tech ecosystems, reducing dependence on Silicon Valley giants.

d) Cultural Dividend

AI models trained on local datasets preserve linguistic and cultural memory, countering the risk of an English-centric AI future. Proprietary models, often trained predominantly on English data, embed Anglo-Saxon cultural biases, marginalizing non-English-speaking communities. Sovereign models like Apertus, with 40% of its training data in non-English languages including Swiss German and Romansh, ensure that AI reflects local dialects, histories, and norms.

India’s AIRAWAT and Bhashini initiatives similarly prioritize regional languages, enabling AI applications that resonate with India’s diverse cultural landscape. This cultural dividend preserves national identity in the digital age, ensuring that AI serves as a tool for cultural expression rather than homogenization. It also enhances user trust, as citizens interact with systems that understand their linguistic and cultural nuances.

Case Studies / Signals

Several nations are leading the charge in building sovereign AI ecosystems, each tailored to their strategic priorities:

• Switzerland: Apertus, developed by EPFL, ETH Zurich, and CSCS, is a fully open AI model trained on Switzerland’s Alps supercomputer. Available in 8-billion and 70-billion parameter versions, it supports over 1,000 languages and is hosted on Hugging Face and Swisscom’s sovereign cloud. Apertus embodies Switzerland’s commitment to transparency and public infrastructure, positioning it as a global leader in open AI.

• India: The IndiaAI Mission, including AIRAWAT and Bhashini, focuses on building sovereign compute infrastructure and language models for India’s 1,200+ dialects. By investing in supercomputing and digital public goods, India is reducing reliance on foreign providers while fostering local innovation.

• European Union: The EU’s AI Act and Gaia-X initiative prioritize data sovereignty and regulatory autonomy. The LEAM model, designed for European languages and values, complements these efforts, ensuring that AI aligns with GDPR and local ethical standards.

• China: China’s fully domestic AI stack, including chips from Huawei and models like DeepSeek, reflects a state-driven approach to sovereignty. By banning foreign models like OpenAI’s, China ensures control over its AI ecosystem, aligning it with national priorities.

These case studies illustrate diverse approaches to AI sovereignty, from Switzerland’s open-source model to China’s state-controlled ecosystem, each leveraging national strengths to secure strategic autonomy.

Risks of Non-Sovereignty

Failure to invest in sovereign AI infrastructure risks what some scholars call “AI colonialism.” Nations without their own AI capabilities become data extractors for foreign models, feeding raw data to companies like OpenAI or Google while receiving processed intelligence at a premium. This creates economic leakage, with billions in API fees and cloud costs flowing to foreign providers, draining national economies.

Moreover, non-sovereignty erodes policy autonomy. Foreign models embed external ethical frameworks and governance norms, which may conflict with local laws or values. For example, a nation using a U.S.-based model may inadvertently adopt American data privacy standards, undermining local regulations like GDPR or India’s DPDP. This loss of control extends to cultural erosion, as English-centric models marginalize local languages and histories, creating a homogenized digital future.

Geopolitically, dependence on foreign AI introduces vulnerabilities to sanctions, surveillance, or service disruptions. As seen in U.S. chip export controls, reliance on foreign infrastructure can be leveraged as a geopolitical weapon, leaving nations without sovereign AI at the mercy of global powers.

The Policy Playbook

To secure the sovereignty dividend, nations must adopt a strategic policy framework:

1. Invest in Compute Capacity: Building supercomputers and sovereign cloud infrastructure is critical. Switzerland’s Alps supercomputer and India’s AIRAWAT demonstrate how national investments in HPC can power sovereign AI. Governments should prioritize funding for data centers and renewable energy to support AI workloads.

2. Build Sovereign Datasets: Curating national datasets in finance, healthcare, law, and language ensures that AI models reflect local priorities. India’s Bhashini, with its focus on regional languages, is a model for creating inclusive datasets that preserve cultural identity.

3. Incentivize Open Models: Open-source models like Apertus and Falcon (developed by the UAE) reduce barriers to innovation. Governments should fund open AI research and provide incentives for startups to build on these models, fostering local ecosystems.

4. Forge Regional Alliances: No nation can achieve full AI sovereignty alone. Regional consortia, like the EU’s Gaia-X or the India-EU-G20 partnerships, allow cost-sharing and resource pooling. The JAIS initiative in the Arab world exemplifies how multilateral alliances can enhance sovereignty without isolation.

5. Embed Ethics in Infrastructure: Trust is a competitive edge. By integrating ethical guidelines into AI development—as Switzerland does with Apertus’s compliance with Swiss and EU laws—nations can build systems that align with local values, enhancing public confidence and global credibility.

The sovereignty dividend is not just a defensive strategy; it is a long-term investment that compounds over decades. Nations that control their AI infrastructure—data, compute, and models—reap economic, security, innovation, and cultural benefits that strengthen their global standing. Conversely, those that rely on foreign providers risk becoming tenants in someone else’s intelligence ecosystem, paying rent in the form of data, fees, and lost autonomy.

The choice is stark: nations can invest in sovereign AI to harvest dividends for generations, or they can remain mere users in a global operating system controlled by a handful of tech giants. As AI reshapes geopolitics, the window to act is narrowing. Nations that miss this opportunity risk being relegated to the periphery of the intelligence economy, forever dependent on foreign landlords. The time to build sovereign AI infrastructure is now—because in the digital age, those who own the infrastructure own the future.