> tpl_air_010
AI System Inventory and Accountability Register
Enterprise-wide AI and machine learning system registry recording statutory risk tiers (Unacceptable, High, Limited, Minimal under the EU AI Act), model lineage, training data dependencies, deployment context, designated business/technical owners, and ongoing impact assessment statuses.
Enterprise AI inventory cataloging models, statutory risk tiers, data lineage, and accountable human owners for EU AI Act compliance.
Important Tech Document Template & Operational Notice
TinyCTO.tv Tech Document Template Notice: This template is a general educational and operational starting point. It is not legal, tax, accounting, investment, procurement, regulatory, security or certification advice. Requirements vary by jurisdiction, organization, contract and risk. Review and adapt it with qualified professionals before relying on it.
Problem Solved
Enterprises deploy shadow AI applications and open-source models across business units without central oversight, creating immense regulatory liabilities, IP leakages, and unmonitored algorithmic risks.
When to Use
- •Establishing a centralized inventory of all internal, third-party, and embedded AI/ML systems
- •Classifying AI systems into statutory risk tiers under the EU AI Act (Articles 5, 6, and 50) and NIST AI RMF
- •Designating explicit legal, business, and engineering accountability for algorithmic decisions and automated agents
When NOT to Use
- •For raw physical server hardware and cloud VM asset tracking (use standard ITAM / CMDB)
- •For detailed feature store metadata and schema definitions (use TPL-AIM-018)
5 Template Sections & Structural Outline
System identifier, operational state (Experimental, Staging, Production, Retired), business domain, and primary intended purpose.
Classifying systems into Unacceptable (Prohibited), High-Risk (Annex III critical infrastructure/biometrics), Limited Risk (chatbots/deepfakes), or Minimal Risk.
Base foundation model (GPT-4o, Claude 3.5, Llama 3), hosting topology (Proprietary API, Sovereign VPC, Edge), and RAG vector store dependencies.
Designating Business Owner, Technical Lead, Legal/Compliance Custodian, and designated Human-in-the-Loop (HITL) operators.
Annual recertification schedule, bias audit milestones, external regulatory filing references (EU Article 60 database), and retirement protocols.
Completion Instructions
Independent Review Checklist
- All mandatory sections completed
- No secrets or passwords included
- Executive sponsor sign-off obtained
AI System Inventory and Accountability Register - Worked Case Study
Fictional Entity: Enterprise AI Governance System & Autonomous Agent Registry
Real-world production case study demonstrating complete operational adoption for Enterprise AI Governance System & Autonomous Agent Registry.
- •Cataloged 142 AI models and autonomous agent workflows across 8 business units within 90 days
- •Identified 6 High-Risk AI systems under EU AI Act Annex III, establishing human oversight guardrails prior to regulatory deadlines
- •Consolidated foundation model vendor spend across OpenAI and AWS Bedrock, eliminating 38 redundant shadow API accounts
Frequently Asked Questions
What criteria mandate an AI system to be registered as "High-Risk" under the EU AI Act?
Under EU AI Act Article 6 and Annex III, systems used in critical infrastructure management, educational admissions/scoring, employment recruitment/evaluation, credit scoring, health/life insurance pricing, biometric identification, and law enforcement are strictly classified as High-Risk and subject to mandatory pre-deployment conformity assessments.
How does this register prevent "shadow AI" across enterprise business units?
By coupling procurement expenditure approval (TPL-COM-011) and cloud IAM service account vending (TPL-CLD-002) to mandatory registration in the AI System Inventory. API keys and cloud LLM endpoints are only provisioned after the system passes initial risk tiering.
Who must be designated as the accountable person for an autonomous AI agent?
Every deployed AI system must designate a named Business Owner (accountable for business outcomes and legal liability) and a Technical Owner (responsible for system performance, monitoring, and emergency shutdown execution).
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Authoritative Sources
- EU Artificial Intelligence Act (Regulation EU 2024/1689)European Parliament and Council • OFFICIAL REQUIREMENT
- NIST AI Risk Management Framework (AI RMF 1.0)National Institute of Standards and Technology • OFFICIAL REQUIREMENT
- ISO/IEC 42001:2023 Artificial Intelligence — Management SystemInternational Organization for Standardization • OFFICIAL REQUIREMENT