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Licensed under CC BY 4.0.", "creators": [ { "affiliations": [ { "name": "SEO specialista a copywriter Daniel Ber\u00e1nek" } ], "person_or_org": { "family_name": "Ber\u00e1nek", "given_name": "Daniel", "identifiers": [ { "identifier": "0009-0004-0050-0264", "scheme": "orcid" } ], "name": "Ber\u00e1nek, Daniel", "type": "personal" } } ], "dates": [ { "date": "2026-08-07", "type": { "id": "issued", "title": { "de": "Ver\u00f6ffentlicht", "en": "Issued" } } } ], "description": "

The emergence of AI-driven search and answer engines has fundamentally disrupted the logic of digital visibility. Traditional Search Engine Optimization (SEO), built on keyword-document matching, and AI Optimization (AIO), focused on answer-engine citation, provide increasingly insufficient responses to a landscape in which artificial intelligence recommends entities rather than ranks pages.

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This paper theorizes Digital Identity Optimization (DIO) as a third-generation framework for digital visibility. Building on Beránek’s (2026) foundational manifest, it defines DIO as the systematic optimization of an entity’s digital identity—its distributed digital representation across human and machine interpretive systems—so that AI systems, search engines, and human audiences can consistently, correctly, and confidently identify, understand, and recommend that entity.

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The paper develops the framework along three analytical axes: (1) comparative complexity of SEO, AIO, and DIO; (2) differential value across stakeholder profiles; and (3) multilateral digital identity structures. For large multi-product corporations, the latter is developed as a brand–category/segment–product model; other entity types may exhibit analogous but different structures.

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Conceptually, DIO is presented as a bottom-up discovery rather than a top-down fabrication. It crystallizes a latent intersection of psychology, semiotics and post-structuralist thought, branding, SEO, structured data, knowledge graphs, and AI retrieval. Practically, it requires alignment across three domains: human-facing interpretation, pre-AI technical representation, and AI-mediated reconstruction.

This record contains the identical preprint first published on ResearchGate: Beránek, D. (2026). Digital Identity Optimization (DIO): A Conceptual Framework for Entity-Based Visibility in the Age of AI-Mediated Search. ResearchGate. https://doi.org/10.13140/RG.2.2.17127.41120

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