AI Governance & Compliance Checklist
Benchmark internal AI controls, data privacy protections, and regulatory readiness across 12 practical checkpoints.
12 Governance Verification Checks
1. Policy & Guidelines
2. Data Privacy & IP Safeguards
3. Human Oversight & Incident Readiness
4. Operational Accountability & Training
Governance Assessment Results
- No incident management response procedure for hallucinations or data leaks
- Lack of prompt/output audit logging for traceability
AI Governance Maturity: 43/100 (Early Stage)
AI Governance maturity evaluated at 43/100 (Early Stage). 5/12 governance controls are currently operational. Found 2 critical gaps.
Değerlendirme Boyutları
Önemli teknik ve operasyonel faktörler genelinde ağırlıklı analiz
1/3 core workplace policies established.
2/3 data protection and copyright guardrails implemented.
1/3 operational safeguards and incident protocols active.
1/3 vendor security assessments and training programs completed.
Teşhis Bulguları
Otomatik mimari, ekonomik ve teknik gözlemler
Establish AI Incident Triage Procedure
Define protocol for isolating compromised credentials, revoking API keys, and handling suspected customer data ingestion.
Öncelikli Uygulama Adımları
- Formulate an emergency key revocation checklist.
- Define legal counsel and compliance notification SLAs (< 72 hours).
- Run a tabletop exercise simulating a model output hallucination in billing.
Tamamlayıcı Sonraki Adımlar
Conduct Responsible AI Training Workshop
Train team members on prompt engineering best practices, hallucination verification, and privacy hygiene.
Need an enterprise AI governance framework or compliance baseline?
Robonom assists organizations in drafting AI policies, establishing audit gateways, and ensuring EU AI Act / ISO 42001 readiness.
Sıkça Sorulan Sorular
What is shadow AI and why is it a significant corporate liability?
Shadow AI refers to employees using unapproved, personal freemium AI tools and browser extensions for work tasks. Without commercial enterprise agreements, free-tier models may store user prompts for training, exposing proprietary intellectual property and customer PII to unauthorized third parties.
What regulations govern enterprise AI usage?
Key frameworks include the EU AI Act (enforcing transparency and risk categorization), GDPR / CCPA (governing personal data processing in model training and inference), and standard ISO 42001 (Artificial Intelligence Management System).
Why is audit logging essential for enterprise AI?
Centralized audit logging records prompt timestamps, user IDs, model hashes, and outputs. If intellectual property infringement, hallucinated commitments, or security leaks occur, audit logs provide the necessary digital evidence for investigation and defense.
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