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AAT-11: AI & Autonomous Technologies Risk Management Decisions

AAT 10 — Critical Identify

Mechanisms exist to leverage decision makers from a diversity of demographics, disciplines, experience, expertise and backgrounds for mapping, measuring and managing Artificial Intelligence (AI) and Autonomous Technologies (AAT)-related risks.

Renumbered: Formerly AAT-07 in SCF 2025.4.

Code reused: In SCF 2025.4 and earlier, AAT-11 was Robust Stakeholder Engagement for AI & Autonomous Technologies. That control is now AAT-33.

Control Question: Does the organization leverage decision makers from a diversity of demographics, disciplines, experience, expertise and backgrounds for mapping, measuring and managing Artificial Intelligence (AI) and Autonomous Technologies (AAT)-related risks?

General (3)
Framework Mapping Values
ISO 42001 2023 6.1.1 6.1.2 6.1.2(a) 6.1.2(b) 6.1.2(c) 6.1.2(d) 6.1.2(d)(1) 6.1.2(d)(2) 6.1.2(d)(3) 6.1.2(e) 6.1.2(e)(1) 6.1.2(e)(2) 6.1.3 6.1.3(a) 6.1.3(b) 6.1.3(c) 6.1.3(d) 6.1.3(e) 6.1.3(f) 6.1.3(g) 6.1.4 8.2
NIST AI 100-1 (AI RMF) 1.0 GOVERN 3.1
NIST AI 600-1 GOVERN 1.4 MP-1.1-003 MAP 1.2 MP-1.2-001 MP-5.1-002 MEASURE 1.1 MS-2.8-001 MS-2.11-003 MEASURE 3.2 MS-3.2-001 MANAGE 1.3
EMEA (1)
Framework Mapping Values
EMEA EU AI Act Article 9.2(a)

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. ▪ AAT is regarded as a technology and governed by the entity's existing IT governance practices. ▪ No formal Governance, Risk & Compliance (GRC) team exists to provide oversight of AAT-related activities. GRC functions are assigned 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 leverage decision makers from a diversity of demographics, disciplines, experience, expertise and backgrounds for mapping, measuring and managing AAT-related risks.

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

  1. AAT-11_A01 the organization leverages decision makers from a diversity of backgrounds for mapping, measuring and managing Artificial Intelligence (AI) and Autonomous Technologies (AAT)-related risks (e.g., demographics, disciplines, experience and expertise).

Evidence Requirements

E-AAT-05 Risk Management Decision Makers for Artificial Intelligence and Autonomous Technologies (AAT)

Documented evidence of diversity of demographics, disciplines, experience, expertise and backgrounds for mapping, measuring and managing Artificial Intelligence (AI) and Autonomous Technologies (AAT)-related risks.

Artificial Intelligence (AI) & Autonomous Technologies Governance

Technology Recommendations

Micro/Small

  • AI risk management decisions documented (accept, mitigate, avoid, transfer)
  • AI governance program
  • NIST AI RMF Manage function

Small

  • Formal AI risk management decision process
  • AI governance program
  • NIST AI RMF Manage function

Medium

  • Structured AI risk management decisions aligned to NIST AI RMF Manage function
  • AI risk register with decision audit trail
  • AI governance program

Large

  • Enterprise AI risk management decision framework
  • NIST AI RMF Manage function
  • Executive AI risk acceptance and treatment decisions documented
  • AI risk decisions integrated with GRC platform

Enterprise

  • Enterprise AI risk management governance (NIST AI RMF, ISO 42001)
  • Board-level AI risk acceptance and treatment decisions
  • AI risk decisions integrated with ERM and GRC platforms
  • NIST AI RMF Manage function at enterprise scale

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