Knowledge-Centric Information Systems
For decades, data engineering has developed mature architectural principles for integrating, governing, validating, cataloging, and serving organizational data. The rise of large language models does not eliminate these concerns; it exposes a broader version of them. Organizational knowledge is becoming executable infrastructure: systems increasingly retrieve it, assemble it, reason over it, and act on it. This paper argues that enterprise artificial intelligence (AI) systems suggest a transition toward an architectural discipline for representing, maintaining, governing, and operationally delivering organizational knowledge. We refer to this discipline as \emph{knowledge architecture}. W...
| Authors | Mariano Garralda-Barrio |
|---|---|
| Primary category | cs.SE |
| Published | 1 July 2026 |
| Last updated at source | 1 July 2026 |
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