Sovereign AI: Rethinking Autonomy in the Age of Global Interdependence

2025-11-18

AI Summary

Amid globalization and technological interdependence, AI sovereignty faces tension between “autonomous controllability” and “open collaboration.” Method: This paper proposes the “Sovereign AI Continuum” framework—moving beyond binary conceptions—to conceptualize sovereignty as a dynamic equilibrium across four dimensions: data, compute, models, and norms. It develops a marginal-return equilibrium model, introduces the “openness–risk parity” policy heuristic, and integrates classical theory, historical analogies, and networked self-governance analysis to formulate a ModelOps-oriented decision-support and lifecycle governance mechanism for policymakers. Contribution/Results: Empirical validation via India and Middle Eastern cases demonstrates that a “moderately open, guardrailed” strategy optimizes co-investment in data and compute infrastructure. The framework offers actionable, context-sensitive AI governance pathways tailored for Global South nations.

Technology Category

• Philosophy and Ethics of AI: Bias, Fairness & Equity
• Humans and AI: Planning and Decision Support for Human-Machine Teams
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Security and Privacy: Data transparency and provenance
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI

Abstract

Artificial intelligence (AI) is emerging as a foundational general-purpose technology, raising new dilemmas of sovereignty in an interconnected world. While governments seek greater control over it, the very foundations of AI--global data pipelines, semiconductor supply chains, open-source ecosystems, and international standards--resist enclosure. This paper develops a conceptual and formal framework for understanding sovereign AI as a continuum rather than a binary condition, balancing autonomy with interdependence. Drawing on classical theories, historical analogies, and contemporary debates on networked autonomy, we present a planner's model that identifies two policy heuristics: equalizing marginal returns across the four sovereignty pillars and setting openness where global benefits equal exposure risks. We apply the model to India, highlighting sovereign footholds in data, compute, and norms but weaker model autonomy. The near-term challenge is integration via coupled Data x Compute investment, lifecycle governance (ModelOps), and safeguarded procurement. We then apply the model to the Middle East (Saudi Arabia and the UAE), where large public investment in Arabic-first models and sovereign cloud implies high sovereignty weights, lower effective fiscal constraints, and strong Data x Compute complementarities. An interior openness setting with guardrails emerges as optimal. Across contexts, the lesson is that sovereignty in AI needs managed interdependence, not isolation.

Problem

• Developing a conceptual framework for sovereign AI as a continuum
• Balancing national autonomy with global interdependence in AI systems
• Identifying policy heuristics for managing AI sovereignty across nations

Innovation

• Sovereign AI as a continuum balancing autonomy
• Policy heuristics equalizing marginal returns across pillars
• Managed interdependence with guardrails for optimal openness