AI Readiness
Organizational preparation for machine-readable identity, provenance, continuity, public authority, and trustworthy resolution.
Definition
The condition in which an organization can present consistent, current, attributable, and machine-readable public information across systems and over time.
Why It Matters
AI systems synthesize answers from fragmented public information. Readiness reduces ambiguity.
Readiness Domains
Identity clarity, canonical sources, structured data, provenance, public authority, continuity, correction procedures, governance, access controls, and recognition testing.
Minimum Record
Canonical name, aliases, entity type, domains, responsible authority, contact, evidence, review date, status, and revision history.
Institutional Use
Public bodies should distinguish official records from commentary and preserve leadership, department, and correction continuity.
Testing
Use neutral prompts, dated captures, reproducible conditions, source review, and separation of independent and seeded results.
Limitations
Readiness does not guarantee ranking, answers, citations, recommendations, or model behavior.
Lifecycle
Assess, normalize, verify, publish, resolve, observe, correct, and maintain.