Discussion

Correspondence Assessment explains how organizations can make warranted judgments about the condition of the representation networks through which they reason and act. The contribution is not that organizations need more assessment in general. The contribution is that AI-native organizations need assessment of a specific object: correspondence state across bounded representation networks.

The theory contributes to organization and management theory by identifying a condition that is neither organizational performance nor strategic fit. Correspondence state concerns whether representations preserve meaningful, traceable, and governable relationships. This matters because managers often act on representations as if their relationships were intact. Assessment provides a disciplined way to qualify that assumption before action.

The theory contributes to information systems by extending traceability from artifact management to organizational judgment. A traceable assessment is not merely better documented; it is more reviewable, contestable, and governable. The theory contributes to organizational learning by explaining how assessment history supports future reinterpretation, criteria refinement, boundary revision, and capability improvement.

The theory also clarifies the role of AI. AI systems may assist assessment, but they do not replace assessment authority. The warrant for assessment comes from criteria, evidence, confidence, traceability, and accountable governance. This boundary protects organizations from treating fluent machine-generated explanations as organizational judgment.