AAT-36.8: AI & Autonomous Technologies Event Logging
Mechanisms exist to ensure Artificial Intelligence (AI) and Autonomous Technologies (AAT) system event logging capabilities at a minimum provide: (1) Start date, start time, end date and end time for each use; (2) Database(s) against which input data has been checked by the system; (3) Input data for which the search has led to a match; and (4) Identification of individual(s) involved in the verification of the results.
Renumbered: Formerly AAT-16.8 in SCF 2025.4.
Control Question: Does the organization ensure Artificial Intelligence (AI) and Autonomous Technologies (AAT) system event logging capabilities at a minimum provide: (1) Start date, start time, end date and end time for each use; (2) Database(s) against which input data has been checked by the system; (3) Input data for which the search has led to a match; and (4) Identification of individual(s) involved in the verification of the results?
General (1)
| Framework | Mapping Values |
|---|---|
| NIST AI 600-1 | GV-4.3-002 MANAGE 4.1 |
EMEA (1)
| Framework | Mapping Values |
|---|---|
| EMEA EU AI Act | Article 12.1 Article 12.2 Article 12.3(a) Article 12.3(b) Article 12.3(c) Article 12.3(d) Article 16(e) Article 26.6 |
Capability Maturity Model
Level 0 — Not Performed
Practices are non-existent, based on the inability to demonstrate an implemented and operational capability. A reasonable person would conclude the control is not being performed.
Level 1 — Performed Informally
Artificial Intelligence and Autonomous Technology (AAT) domain capabilities are ad hoc and inconsistent. Capability criteria associated with this control may include: ▪ Policies, standards & procedures associated with AAT domain capabilities provide limited coverage due to the depth and breadth of the existing documentation. ▪ AAT-related processes are expected to follow the organization's existing processes (e.g., incident response, asset management, change control and risk assessments). ▪ No formal Governance, Risk & Compliance (GRC) team exists to provide AAT oversight, where the Chief Information Officer (CIO), or similar function, governs technology decisions what is acceptable for AAT within the organization.
Level 2 — Planned & Tracked
Artificial Intelligence and Autonomous Technology (AAT) capabilities are requirements-driven, but are not standardized across the entity (e.g., local/regional level consistency). Capability criteria associated with this control reasonably expect the following criteria to exist: ▪ Policies and standards associated with AAT domain capabilities are formally documented and centrally-managed by the entity. ▪ Standardized Operating Procedures (SOP) associated with AAT domain capabilities are documented and maintained by process owners. ▪ IT and/or cybersecurity personnel work with business stakeholders and process owners to appropriately scope and reasonably implement cybersecurity and data protection controls associated with AAT domain capabilities to address applicable statutory, regulatory and/or contractual requirements for Technology Assets, Applications, Services and/or Data (TAASD). ▪ Artificial Intelligence (AI)-related controls are primarily administrative and preventative in nature (e.g., policies, standards and procedures & guidelines). ▪ Asset management may be a defined function (e.g., team or department) or assigned as an additional duty to existing IT and/or cybersecurity personnel.
Level 3 — Well Defined
Artificial Intelligence and Autonomous Technology (AAT) capabilities are standardized across the entity for applicability to People, Processes, Technologies, Data and/or Facilities (PPTDF) to ensure consistency for Technology Assets, Applications, Services and/or Data (TAASD). Capability criteria associated with this control reasonably expect the following criteria to exist: ▪ Policies and standards associated with AAT domain capabilities are formally documented and centrally-managed by the entity's Governance, Risk & Compliance (GRC) team, or similar function. ▪ Standardized Operating Procedures (SOP) associated with AAT domain capabilities are well-documented and kept current by process owners. ▪ An Artificial Intelligence Governance (AIG) team, or similar function, is appropriately staffed and supported to implement and maintain AAT domain capabilities. ▪ Technology is leveraged to enhance the efficiency and accuracy of AI governance, risk management and compliance operations (e.g., dedicated AI governance platform). ▪ The entity's Governance, Risk & Compliance (GRC) team, or similar function, works with business stakeholders and process owners to appropriately scope and reasonably implement cybersecurity and data protection controls associated with AAT domain capabilities to address Minimum Compliance Requirements (MCR) (e.g., applicable statutory, regulatory and/or contractual requirements) and Discretionary Security Requirements (DSR) (e.g., entity-required controls). ▪ An implemented and operational capability exists to ensure AAT system event logging capabilities at a minimum provide: (1) Start date, start time, end date and end time for each use; (2) Database(s) against which input data has been checked by the system; (3) Input data for which the search has led to a match; and (4) Identification of individual(s) involved in the verification of the results.
Level 4 — Quantitatively Controlled
Utilize SCR-CMM Level 3 criteria definitions: ▪ There are no defined Level 4 criteria, since it is reasonable to assume a quantitatively-controlled process is not necessary to operationalize this control. ▪ While it may be possible to develop “metrics-driven” capabilities for this control, the criteria would be organization-specific to define.
Level 5 — Continuously Improving
Utilize SCR-CMM Level 3 or Level 4 (if available) criteria definitions: ▪ There are no defined Level 5 criteria, since it is reasonable to assume a continuously-improving process is not necessary to operationalize this control. ▪ Level 5 capabilities should be considered “world-class” where the control builds on Level 4 capabilities, but are continuously improving through Artificial Intelligence (AI) and/or Machine Learning (ML) technologies. ▪ While it may be possible to develop responsive capabilities for this control through the use of AI and/or ML technologies, the criteria would be organization-specific to define.
Assessment Objectives
- AAT-36.8_A01 Artificial Intelligence (AI) and Autonomous Technologies (AAT) system event logging capabilities are configured to provide start date, start time, end date and end time for each use.
- AAT-36.8_A02 Artificial Intelligence (AI) and Autonomous Technologies (AAT) system event logging capabilities are configured to provide database(s) against which input data has been checked by the system.
- AAT-36.8_A03 Artificial Intelligence (AI) and Autonomous Technologies (AAT) system event logging capabilities are configured to provide input data for which the search has led to a match.
- AAT-36.8_A04 Artificial Intelligence (AI) and Autonomous Technologies (AAT) system event logging capabilities are configured to provide identification of individual(s) involved in the verification of the results.
Evidence Requirements
- E-AAT-14 AI Production Monitoring & Serious Incident Reporting
-
Documented evidence of production monitoring of Artificial Intelligence and Autonomous Technologies (AAT), including event logging and serious incident reporting / root cause analysis.
Artificial Intelligence (AI) & Autonomous Technologies Governance
Technology Recommendations
Micro/Small
- Enable basic logging on AI/ML systems
Small
- Configure event logging on AI systems
- Define log retention periods
Medium
- Formal AI event logging policy
- Centralized log collection
Large
- SIEM integration for AI system logs
- Defined logging standards for AI platforms
Enterprise
- Enterprise SIEM platform
- Standardized AI event logging schema
- Automated alerting for anomalous AI events