AAT-27: AI & Autonomous Technologies Testing Techniques
Mechanisms exist to develop and implement fact-checking techniques to verify the accuracy and veracity of information generated by Artificial Intelligence (AI) and Autonomous Technologies (AAT).
Renumbered: Formerly AAT-26 in SCF 2025.4.
Code reused: In SCF 2025.4 and earlier, AAT-27 was AI & Autonomous Technologies Output Filtering. That control is now AAT-17.1.
Control Question: Does the organization develop and implement fact-checking techniques to verify the accuracy and veracity of information generated by Artificial Intelligence (AI) and Autonomous Technologies (AAT)?
General (1)
| Framework | Mapping Values |
|---|---|
| NIST AI 600-1 | MP-2.3-003 MS-1.1-002 MS-2.2-002 MS-2.5-003 MS-2.6-004 MS-2.9-001 MS-2.11-001 MS-4.2-001 MG-3.1-004 |
US (1)
| Framework | Mapping Values |
|---|---|
| USA Texas TRAIGA 2025 | 552.105(e) |
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 develop and implement fact-checking techniques to verify the accuracy and veracity of information generated by AAT.
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-27_A01 fact-checking techniques are developed to verify the accuracy and veracity of information generated by Artificial Intelligence (AI) and Autonomous Technologies (AAT).
- AAT-27_A02 fact-checking techniques are implemented to verify the accuracy and veracity of information generated by Artificial Intelligence (AI) and Autonomous Technologies (AAT).
Evidence Requirements
- E-AAT-07 Artificial Intelligence Test, Evaluation, Validation & Verification (AI TEVV) Practices
-
Documented evidence of Artificial Intelligence Test, Evaluation, Validation & Verification (AI TEVV) practices.
Artificial Intelligence (AI) & Autonomous Technologies Governance
Technology Recommendations
Micro/Small
- Verify AI-generated content before acting on it
Small
- Fact-checking procedures for AI-generated content
Medium
- Formal AI output verification policy
- Fact-checking techniques for AI content
Large
- AI content verification program
- Automated fact-checking tools integration
Enterprise
- Enterprise AI content verification framework
- AI fact-checking tools
- Automated hallucination detection