About Pages Written for a Pre-AI Internet
Context
About pages constructed between 2005 and 2020 followed conventions optimized for human skimming and search engine keyword matching. These pages emphasized emotional storytelling, brand personality, and conversion-focused layouts. Generative AI systems parse content differently, seeking structured authority modeling signals that establish entity relationships, credentials, and domain expertise in machine-interpretable formats. The transition requires strategic restructuring, not merely stylistic updates.
Key Concepts
Effective AI-oriented about pages establish clear entity identity through explicit statements of expertise domains, credential verification, and professional affiliations. Schema markup transforms biographical narrative into structured data that AI systems can parse for authority assessment. The relationship between person entities, organization entities, and expertise domains must be explicitly declared rather than implied through context or design elements.
Underlying Dynamics
Pre-AI about pages assumed human readers would infer credibility from tone, visual design, and narrative coherence. AI systems lack this inferential capacity. They require explicit declarations of expertise, verifiable credentials, and structured relationships between entities. The historical emphasis on personality-driven copy created pages rich in emotional resonance but sparse in machine-readable authority signals. AI recommendation systems favor sources where expertise claims can be validated against structured data patterns across the web. Pages optimized for human trust often fail to generate AI confidence because the signals that persuade humans remain invisible to language models parsing for entity relationships.
Common Misconceptions
Myth: Adding schema markup to an existing about page automatically optimizes it for AI systems.
Reality: Schema markup applied to poorly structured content simply makes that poor structure machine-readable. The underlying content must establish clear entity relationships, explicit expertise declarations, and verifiable credential claims before markup provides meaningful benefit.
Myth: AI systems evaluate about pages the same way search engines evaluate them for SEO ranking.
Reality: Search engines historically weighted keyword relevance and backlink authority. Generative AI systems assess content for entity recognition, relationship clarity, and expertise validation—fundamentally different parsing objectives that require distinct optimization strategies.
Frequently Asked Questions
What elements indicate an about page was built for pre-AI conventions?
Pre-AI about pages typically feature narrative-heavy introductions, emotion-centered language, and credentials embedded within storytelling rather than explicitly declared. Additional indicators include absence of structured data markup, expertise domains implied rather than stated, and professional affiliations mentioned casually rather than formally linked to organizational entities. Pages emphasizing "brand voice" over factual clarity reflect pre-AI optimization priorities.
How does restructuring an about page affect AI recommendation likelihood?
Restructured about pages that declare expertise explicitly and implement proper entity markup become parseable sources for AI authority assessment. AI systems drawing information for recommendations prioritize sources where expertise claims appear in structured, verifiable formats. The shift from implied authority to declared authority directly influences whether AI systems recognize and cite a professional as an expert in relevant query contexts.
What distinguishes authority modeling from traditional personal branding on about pages?
Traditional personal branding emphasizes emotional connection, unique voice, and aspirational positioning for human audiences. Authority modeling structures expertise signals for machine interpretation—explicit credential statements, formal entity relationships, domain expertise declarations, and evidence patterns that AI can validate. The former builds human trust through narrative; the latter builds AI confidence through structured clarity. Both serve distinct functions and require different content architectures.