This study develops a conceptual and operational framework for rethinking authenticity in architecture mediated by artificial intelligence. Although classical accounts have established the importance of origin, authorship, agency, lived experience, meaning, value, and responsibility, their human-centered and author-centered assumptions do not fully explain design processes shaped by data, algorithms, generative models, prompts, platforms, software, and repeated human selection. To address this gap, the research adopts a qualitative, theoretical, and interpretive design based on a selected interdisciplinary corpus of theoretical sources from architecture, philosophy, and technology studies. The material was examined through qualitative content analysis, conceptual analysis, comparative analysis, and theoretical inference, moving iteratively from initial codes to axial categories, comparative typologies, and relational synthesis. The findings identify five interrelated dimensions of authenticity: origin and provenance; authorship and attribution; agency and actor networks; experience, meaning, and value; and responsibility, human judgment, and process traceability. These dimensions support the formulation of networked authenticity as a relational, processual, interpretive, and traceable condition whereby human and technological contributions are differentiated but assessed within the same production network. The proposed model is further operationalized through an interpretive matrix that enables multidimensional evaluation without reducing authenticity to a single score. A constructed worked example demonstrates the application of the matrix and its capacity to distinguish among different levels of evidential adequacy across the five dimensions, although empirical validation across documented architectural cases remains for future research. The framework provides a basis for analyzing artificial intelligence-mediated architectural production while retaining human judgment, contextual interpretation, and professional responsibility.