https://repository.hneu.edu.ua/handle/123456789/99 2026-08-29T07:35:00Z https://repository.hneu.edu.ua/handle/123456789/41653 Назва: Data Sovereignty as a Marketing Differentiator: the Rise of Privacy-First Positioning Автори: Prokopenko S. O. Короткий огляд (реферат): Over the past several years, data sovereignty has migrated from the vocabulary of regulators and IT architects to that of brand managers. What once denoted a purely technical or jurisdictional condition, where data physically resides, under which legal regime it is processed, and who may compel access to [3,8] it is now routinely deployed as a positioning: a promise addressed not to auditors but to customers. This paper examines the emergence of “privacy-first” and “sovereign” branding as a marketing differentiator in the technology sector, with particular attention to the wave of European sovereign artificial intelligence and large language model (LLM) initiatives that have intensified public debate about who controls the infrastructure behind everyday digital services. The paper argues that data sovereignty functions today as a differentiation strategy in the classical sense theorized by positioning and competitive-strategy scholarship, while simultaneously carrying risks familiar from other “virtue label” markets, most notably the risk of privacy-washing. 2026-01-01T00:00:00Z https://repository.hneu.edu.ua/handle/123456789/41652 Назва: How AI-Generated Content Undermines the Epistemic Resilience of Brands Автори: Prokopenko S. O. Короткий огляд (реферат): The rapid diffusion of generative artificial intelligence has turned brand communication into a site of large-scale, largely unsupervised production of text, images, and videos. This article examines how AI-generated content undermines the epistemic resilience of brands as their capacity to sustain reliable, trusted, and internally consistent knowledge about themselves within a contested information environment. Drawing on recent empirical and theoretical literature, the article identifies five interacting mechanisms of erosion: the AI penalty and disclosure paradox in audience perception; authenticity discounting in influencer and social content; hallucination and the self-reinforcing "AI slop loop" in generative search; model collapse as a long-term contamination of the shared information commons; and the homogenization of brand voice under algorithmic optimization. The article argues that these mechanisms operate cumulatively rather than in isolation, converting short-term efficiency gains into long-term reputational and epistemic liabilities. It concludes with a governance framework built on provenance, human epistemic authority, and transparent disclosure practices that brands and researchers alike can use to preserve trust in AI-mediated communication. 2026-01-01T00:00:00Z https://repository.hneu.edu.ua/handle/123456789/41650 Назва: Sovereign AI and Epistemic Resilience: Governing National Algorithmic Infrastructures Автори: Prokopenko S. O. Короткий огляд (реферат): This paper examines "sovereign AI" as nationally controlled large language models and domestic algorithmic infrastructure through the lens of epistemic resilience, arguing that reducing external technological dependence may simultaneously institutionalize domestic epistemic biases and produce new forms of epistemic closure. Drawing on structuration theory and resilience theory, AI systems are conceptualized as recursive infrastructures that codify norms of relevance and credibility, reinforcing dominant narratives through feedback loops between training, deployment, and institutional uptake. The paper identifies a dual risk structure: external epistemic vulnerability stemming from reliance on foreign AI, and internal homogenization as sovereign systems narrow domestic epistemic diversity. Using a qualitative multi-case comparison of AI governance in the EU, US, China, and smaller powers, the paper builds a framework of epistemic resilience as the capacity to detect, counterbalance, and pluralize algorithmic bias, deriving three governance implications: plural model architectures, cross-border epistemic interoperability, and institutionalized reflexivity through independent audit mechanisms. It concludes that sovereign AI governance should shift from a narrow focus on strategic autonomy to the preservation of pluralism and democratic cognition within national epistemic ecosystems. 2026-01-01T00:00:00Z https://repository.hneu.edu.ua/handle/123456789/41649 Назва: Organizational Resilience in the Times of Algorithmic Decision Support Автори: Prokopenko S. O. Короткий огляд (реферат): This paper examines how the growing integration of algorithmic decision-support systems into core organizational functions as forecasting, workforce scheduling, credit scoring, and pricing, affects an organization's capacity for resilience. Drawing on comparative illustrations from supply chain forecasting, workforce scheduling, and credit underwriting, the paper further argues that sector-wide standardization of algorithmic architectures risks correlating fragility across organizations, echoing concerns from financial stability research. To counteract these tendencies, the paper proposes three deliberate structural interventions: actively rehearsed manual-override capacity, systematic monitoring for distributional drift, and institutionalized diversity of oversight, positioning resilience-preserving redundancy as a necessary long-run investment rather than a short-run inefficiency. The paper is conceptual, synthesizing resilience theory with organizational and information systems literature on algorithmic management, and outlines directions for future empirical testing of the proposed mechanisms and interventions. 2026-01-01T00:00:00Z