This paper introduces Ontological Knowledge Blocks (OKBs), a governance infrastructure designed to automate compliance and validation for AI systems deployed in critical infrastructure. OKBs compile regulatory obligations into machine-checkable constraints, enabling profile-based
AI-enabled services operating in critical infrastructure face complex governance obligations regarding transparency, accountability, and fairness. Current documentation-centric compliance methods are insufficient for scalable, automated AI systems. The authors propose Ontological Knowledge Blocks (OKBs), a programmable governance framework that formalizes regulatory obligations by structuring them as a 5-tuple binding normative requirements to RDF/OWL schemas, executable SHACL validation rules, and PROV-O provenance links.
The OKB system features a deterministic regulatory compiler that translates structured Intermediate Representation (IR) records into composable Knowledge Base (KB) modules. This allows for profile-based governance reconfiguration, enabling system operators to adapt compliance profiles dynamically. Prototypes were evaluated in an AI-assisted HPC resource allocation scenario, demonstrating profile-sensitive validation and performance metrics (SHACL latency between 12.6 ms and 100.3 ms), confirming the efficacy of profile-based validation.