Know where your AI governance stands before AI becomes unmanaged risk.
Complete a short executive assessment and receive an AI governance maturity level, domain-level scores, and practical next-step recommendations based on the Orentika AI Governance Framework.
Five executive domains. Nine governance functions. One maturity path.
Orentika helps organizations move from informal AI adoption to governed, measured, and decision-ready AI governance.
Strategy & Governance
Direction, accountability, policy, oversight, and executive reporting.
AI Inventory & Classification
Visibility into AI systems, use cases, agents, vendors, data, and risk tiers.
Risk & Compliance
AI risk, privacy, legal, regulatory, bias, accuracy, and business impact review.
Controls & Assurance
Safeguards, approval workflows, evidence, assurance, and governance controls.
Monitoring & Decision Intelligence
Ongoing oversight, incident response, trends, dashboards, and decision support.
The Orentika AI Governance Maturity Model
Level 1 — Ad Hoc
AI use is informal, inconsistent, and largely dependent on individual effort.
Level 2 — Aware
Foundational governance has started, but coverage is incomplete and inconsistent.
Level 3 — Governed
Governance processes are documented, assigned, repeatable, and operational.
Level 4 — Orchestrated
Governance is integrated, measured, monitored, and evidenced.
Level 5 — Predictive
Governance is intelligence-driven, automated, risk-informed, and executive-ready.
Discover your AI governance maturity in five minutes.
Answer the questions below. Your results stay in your browser unless you choose to contact Orentika for a review.
Level 1 — Ad Hoc
Recommended next steps
Want a deeper review of your results?
Book a complimentary 30-minute AI Governance Readiness Review with Orentika.
Turn assessment results into an actionable roadmap.
AI Governance Readiness Assessment
A deeper review of governance maturity, evidence gaps, risks, and executive priorities.
AI Policy & Acceptable Use
Practical policy, roles, approval thresholds, and responsible use guidance.
AI Inventory & Classification
Visibility into AI systems, vendors, use cases, data, agents, and risk tiers.
AI Controls & Assurance
Control design, evidence model, monitoring practices, and executive reporting.