Interoperability
The ability of diverse AI systems and components to exchange, understand, and use information seamlessly, often via open standards or APIs.
Definition
Critical in complex ecosystems where models, data services, and workflows span multiple platforms. Governance promotes use of open standards (ONNX for model exchange, REST/GraphQL for APIs), well-defined data schemas, and semantic ontologies. It also enforces versioning policies and backward compatibility to prevent integration failures as components evolve.
Real-World Example
A healthcare consortium ensures interoperability by requiring all partners to export predictive-model artifacts in ONNX format and to use FHIR standards for patient data exchange. This lets hospitals plug each other’s AI modules into their systems with minimal custom integration work.
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