Alzheimer’s disease (AD) is biologically heterogeneous, motivating a shift from symptom-based diagnosis toward biomarker-defined disease. The NIA-AA AT(N) framework formalizes this transition by defining AD through amyloid-β deposition, pathologic tau, and neurodegeneration, independent of clinical presentation. This narrative review synthesizes literature from 2018–2025—identified through structured searches in PubMed and Alzheimer’s & Dementia using terms such as p-tau217, GFAP, and plasma-first. Studies were included if they were large-scale, prospective, or autopsy-validated; screening prioritized cohorts with standardized plasma assays and reported diagnostic performance. This timeframe was selected to capture the emergence of high-accuracy plasma biomarkers and the first clinically validated assays. Empirical evidence demonstrates that blood-based biomarkers now enable scalable detection across the AD continuum. Plasma p-tau231 increases early with emerging amyloid-β pathology, while glial fibrillary acidic protein reflects astroglial activation in cognitively normal individuals. For established pathology, plasma p-tau217 shows superior diagnostic accuracy and is increasingly supported as a clinically actionable marker. Building on these findings, we conceptually outline a three-stage diagnostic architecture integrating primary care plasma screening, digital cognitive assessment, and specialist interpretation. Modeled projections, informed by the Taiwan-ADNI triage framework, suggest that such a system could reduce reliance on confirmatory PET imaging by up to 80%. Implementation must address biological confounders, cross-assay variability, and bias inherent in high-resource research cohorts. As multimarker panels expand, artificial intelligence offers a theoretical mechanism for integrating high-dimensional signatures, adjusting for demographic variables, and supporting longitudinal monitoring at scale. Ultimately, a plasma-first, AI-enabled diagnostic framework provides a blueprint for scalable, population-level precision screening.
