Ready to Automate Get Your Free AI Checklist (1).pdf

This AI Regulatory Compliance Checklist is a practical, copy-ready framework designed to help businesses align their AI systems with global compliance standards such as the EU AI Act, GDPR, and ISO/IEC 42001. Covering every critical area—from legal readiness and data governance to model transparency, security, human oversight, vendor management, and continuous monitoring—it provides step-by-step guidance to ensure your AI adoption is defensible, auditable, and trusted. With actionable checkpoints and regulator-ready documentation practices, this checklist empowers organizations to minimize legal risks, strengthen accountability, and build AI systems that are both ethical and compliant at scale.

1. AI Regulatory Compliance Checklist
Copy-Ready and Practical
Practical steps to ensure your AI systems meet global compliance
standards before risk escalates.

2. WHY AI REGULATORY
COMPLIANCE MATTERS?
REGULATORS WORLDWIDE ARE DRAFTING BINDING AI LAWS; NON-
COMPLIANCE LEADS TO FINES, BANS, OR LOSS OF TRUST.
AI COMPLIANCE IS NO LONGER OPTIONAL; IT IS A BUSINESS CONTINUITY
REQUIREMENT.
THIS CHECKLIST ENSURES YOUR AI ADOPTION IS LEGALLY DEFENSIBLE,
AUDITABLE, AND TRUSTED.

3. STEP 1: LEGAL & REGULATORY
READINESS MAP APPLICABLE AI REGULATORY COMPLIANCE LAWS (EU AI ACT,
GDPR, US STATE AI BILLS, ISO/IEC 42001).
DOCUMENT RISK CATEGORIES: PROHIBITED, HIGH-RISK, AND
LIMITED-RISK AI SYSTEMS.
ESTABLISH COMPLIANCE OWNERSHIP AT THE EXECUTIVE LEVEL.
REQUIRE WRITTEN ACCOUNTABILITY CHAINS FOR AI DECISION-
MAKING.
MAINTAIN A COMPLIANCE IMPACT LOG FOR EACH AI PROJECT.

4. STEP 2: DATA GOVERNANCE COMPLIANCESTEP 2: DATA GOVERNANCE COMPLIANCE VERIFY ALL TRAINING AND OPERATIONAL DATA SOURCES FOR LEGAL PROVENANCE.
MAINTAIN DATA LINEAGE RECORDS (WHO COLLECTED, WHEN, UNDER WHAT LEGAL
BASIS).
ENCRYPT SENSITIVE DATASETS END-TO-END (SEE AI SECURITY).
APPLY JURISDICTION-SPECIFIC DATA RESIDENCY RULES (EU VS. US VS. APAC).
DOCUMENT BIAS DETECTION PROCEDURES AND RESULTS FOR REGULATORS

5. STEP 3: MODEL TRANSPARENCY & DOCUMENTATION MAINTAIN MODEL CARDS: PURPOSE, LIMITATIONS, RISKS,
TRAINING DATA SUMMARY.
PROVIDE EXPLAINABILITY REPORTS FOR REGULATORS AND
CUSTOMERS.
TRACK ALL THIRD-PARTY AI COMPONENTS AND OPEN-SOURCE
MODELS USED.
ARCHIVE EVERY MODEL VERSION WITH VALIDATION EVIDENCE.
DISCLOSE TO USERS WHENEVER AI INFLUENCES SIGNIFICANT
DECISIONS.

6. STEP 4: SECURITY & RISK CONTROLS
PERFORM THREAT MODELING FOR AI-SPECIFIC ATTACKS (PROMPT INJECTION,
DATA POISONING).
REQUIRE ADVERSARIAL TESTING BEFORE DEPLOYMENT.
ESTABLISH ROLLBACK PROCEDURES IF AI OUTPUTS BREACH COMPLIANCE.
DEPLOY CONTINUOUS MONITORING FOR UNAUTHORIZED MODEL DRIFT.
ALIGN AI SYSTEM LOGS WITH ENTERPRISE SIEM (SECURITY INCIDENT
MONITORING).

7. STEP 5: HUMAN OVERSIGHT & ETHICS
COMPLIANCE
STEP 5: HUMAN OVERSIGHT & ETHICS
COMPLIANCE
ASSIGN HUMAN-IN-THE-LOOP CHECKPOINTS FOR ALL HIGH-RISK AI
OUTPUTS.
DOCUMENT HOW HUMAN REVIEW OVERRIDES AI-DRIVEN DECISIONS.
TRAIN REVIEWERS ON REGULATORY OBLIGATIONS, NOT JUST WORKFLOWS.
ESTABLISH ETHICS BOARD REVIEWS FOR AI MODELS IMPACTING
EMPLOYMENT, HEALTH, OR FINANCE.

8. STEP 6: VENDOR & THIRD-PARTY COMPLIANCESTEP 6: VENDOR & THIRD-PARTY COMPLIANCE
REQUIRE VENDORS TO PROVIDE COMPLIANCE CERTIFICATIONS BEFORE INTEGRATION.
AUDIT AI DEVELOPMENT COMPANY VENDORS FOR ADHERENCE TO GLOBAL
STANDARDS.
DEMAND SOURCE OF TRAINING DATA DISCLOSURE FROM THIRD-PARTY PROVIDERS.
ENSURE CONTRACTS INCLUDE AI LIABILITY CLAUSES.
BAN SHADOW AI TOOLS NOT CLEARED THROUGH COMPLIANCE REVIEW.

9. STEP 7: MONITORING, REPORTING & SCALING
COMPLIANCE
SCHEDULE QUARTERLY COMPLIANCE AUDITS FOR ALL AI SYSTEMS.
INTEGRATE COMPLIANCE CHECKS INTO CI/CD PIPELINES.
ESTABLISH REGULATOR-READY REPORTING TEMPLATES.
RUN POST-IMPLEMENTATION IMPACT ASSESSMENTS FOR EVERY NEW AI
ROLLOUT (AI IMPLEMENTATION).
SCALE COMPLIANCE FRAMEWORKS AS SYSTEMS EXPAND ACROSS
DEPARTMENTS.

10. YOUR COMPLIANCE GAPS WON’T FIX THEMSELVES.YOUR COMPLIANCE GAPS WON’T FIX THEMSELVES.
EVERY DELAY INCREASES LEGAL RISK AND COSTS.
?????? BOOK A FREE COMPLIANCE READINESS CALL