# Computational Sovereignty: Structural Economic Risks for European Competitiveness in AI-Mediated Markets **Structural Risks, Representation Capital, and Computational Market Infrastructure** > **⚠️ Evidence Status:** Proposed hypothesis — not yet tested > > This publication presents a conceptual hypothesis awaiting empirical validation. --- **Publication Date**: 2026-07-06 **Authors**: Marco Patrone **Institution**: HomeSelf Research **Category**: working_paper **Evidence Status**: hypothesis — Proposed hypothesis — not yet tested **Version**: v1.0 --- ## Abstract This working paper examines whether the transition from human-mediated to AI-mediated markets creates new structural risks for European competitiveness. It introduces Computational Sovereignty as the capacity of firms, assets, and institutions to remain discoverable, interpretable, comparable, and actionable by AI systems that increasingly mediate economic demand. The paper develops Representation Capital as a proposed production factor in AI-mediated economies, formulates the Law of Computational Visibility, and introduces the Computational Transmission Mechanism as a complement to traditional monetary and industrial policy channels. It argues that European competitiveness may increasingly depend not only on capital, innovation, energy, and digital infrastructure, but also on computational market infrastructure: the layer through which economic entities become machine-readable, verifiable, and eligible for AI-mediated discovery and transaction. The analysis is theoretical and policy-oriented. It positions Computational Sovereignty as a complementary framework to existing European policy debates on digital sovereignty, the Capital Markets Union, the Digital Euro, AI governance, and competitiveness. The paper does not present empirical validation; instead, it offers hypotheses, indicators, scenarios, and a roadmap for further measurement, institutional testing, and policy discussion. ## Executive Summary ### Background European competitiveness frameworks have traditionally focused on capital, innovation, energy, and digital infrastructure. As AI systems increasingly mediate market discovery, comparison, and selection, a new structural layer may be emerging: computational market infrastructure. This layer determines whether economic entities can be discovered, interpreted, and acted upon by AI systems. ### Objectives - Introduce Computational Sovereignty as a framework for analyzing structural risks in AI-mediated markets - Develop Representation Capital as a proposed production factor in AI-mediated economies - Formulate the Law of Computational Visibility as a theoretical construct - Introduce the Computational Transmission Mechanism as a complement to monetary transmission - Position computational market infrastructure as a proposed fifth pillar of European competitiveness - Connect the framework to existing European policy debates on digital sovereignty, Capital Markets Union, and AI governance ### Approach Theoretical and policy-oriented analysis drawing from computational economics, infrastructure theory, and European policy frameworks. The paper proposes concepts, hypotheses, and indicators for empirical validation. It does not present empirical findings or claim measured effects. ### Main Findings - Computational Sovereignty is proposed as the capacity of entities to remain discoverable, interpretable, comparable, and actionable by AI systems - Representation Capital is proposed as a production factor affecting allocative outcomes in AI-mediated markets - The Law of Computational Visibility states that allocative outcomes increasingly depend on computational representation quality - The Computational Transmission Mechanism is proposed as a channel through which representation affects economic outcomes - Computational market infrastructure may be emerging as a fifth pillar of European competitiveness - All constructs are theoretical and require empirical validation before policy application ### Conclusions - The transition to AI-mediated markets may create new structural risks for European competitiveness - Computational Sovereignty provides a framework for analyzing these proposed risks - Representation Capital may emerge as a strategic asset in AI-mediated economies - Policy frameworks may require extension to account for computational market infrastructure - Further research should focus on empirical validation of the hypotheses presented - The analysis is theoretical and not intended as immediate policy prescription ## Methodology **Research Type**: theoretical analysis Theoretical and policy-oriented framework development. The analysis introduces conceptual frameworks, formulates theoretical constructs, and proposes indicators for empirical validation. It does not present empirical findings, experimental results, or measured effects. The paper is positioned as a starting point for further research, policy discussion, and institutional testing. **Data Sources**: synthetic, literature based **Confidence Level**: low ### Limitations - All constructs are theoretical hypotheses requiring empirical validation - No empirical data is presented to support the proposed frameworks - The analysis is policy-oriented and not intended as immediate policy prescription - Alternative explanations for observed phenomena exist - Measurement challenges may impede validation of proposed constructs - The framework is conceptual and requires further development and testing ## Key Findings ### Computational Sovereignty is proposed as the capacity of entities to remain discoverable, interpretable, comparable, and actionable by AI systems. **Evidence**: Theoretical analysis demonstrates that as AI systems increasingly mediate economic demand, the capacity of firms, assets, and institutions to be discovered, interpreted, compared, and acted upon may become a critical determinant of economic participation. **Evidence Status**: hypothesis **Confidence**: low **Implications**: - Computational Sovereignty may emerge as a strategic asset in AI-mediated economies - Entities with low Computational Sovereignty may face structural exclusion risks - Policy frameworks may require extension to account for computational market infrastructure ### Representation Capital is proposed as a production factor in AI-mediated economies. **Evidence**: The framework develops Representation Capital as the accumulated advantage conferred by machine-readable representation quality, measured as the delta in inclusion probability for AI-mediated consideration sets. **Evidence Status**: hypothesis **Confidence**: low **Implications**: - Representation Capital may affect allocative outcomes in AI-mediated markets - Traditional competitive advantages may require supplementation with computational representation advantages - Investment frameworks may need to incorporate representation quality metrics ### The Law of Computational Visibility states that allocative outcomes increasingly depend on computational representation quality. **Evidence**: Theoretical analysis suggests that in AI-mediated markets, allocative outcomes may increasingly depend on whether entities can be discovered, interpreted, compared, and acted upon by AI systems—regardless of traditional quality or price metrics. **Evidence Status**: hypothesis **Confidence**: low **Implications**: - Visibility may no longer guarantee consideration or participation in AI-mediated markets - Traditional marketing and visibility strategies may be insufficient for AI-mediated discovery - Computational representation quality may become a prerequisite for market participation ### The Computational Transmission Mechanism is proposed as a complement to traditional monetary transmission. **Evidence**: The framework introduces the Computational Transmission Mechanism as a channel through which changes in computational representation and market infrastructure may affect allocative outcomes, firm valuation, and economic activity. **Evidence Status**: hypothesis **Confidence**: low **Implications**: - Central banks and monetary authorities may need to account for computational intermediation channels - Computational market infrastructure may become a fifth pillar of economic policy - Industrial and competitiveness policy may require extension for computational allocation effects ## Citation ``` Patrone, M. (2026). Computational Sovereignty: Structural Economic Risks for European Competitiveness in AI-Mediated Markets. HomeSelf Research Series, Working Paper Version 1.0. Zenodo. DOI: 10.5281/zenodo.21215504. ``` --- **Links**: - **Original**: https://homeself.ai/research/computational-sovereignty-structural-risks-ai-mediated-markets - **JSON-LD**: https://homeself.ai/api/research/computational-sovereignty-structural-risks-ai-mediated-markets.jsonld