The Machine-Readable Web: A historical, economic, and methodological publication on AI search, large language models, and digital trust

This publication examines the transformation of the web in the age of AI-mediated search, large language models, answer engines, and digital trust. It explains why websites are no longer only visual interfaces for human visitors, but also evidence-bearing information layers processed by search engines, AI systems, retrieval systems, and emerging AI agents. The central argument is that digital visibility increasingly depends on machine readability, entity consistency, verifiable context, and trust signals. The publication discusses the relevance of semantic HTML, structured data, Schema.org, JSON-LD, Knowledge Graph thinking, AEO, GEO, LLMO, and LLM-first architecture from a conceptual and methodological perspective. The document is intentionally not a technical implementation manual. It does not disclose copyable file-level procedures, client-specific methods, or guaranteed visibility techniques. Its purpose is to provide a citable English-language professional foundation document for ORCID and Zenodo DOI deposit.