+AI TEVV Reporting
---+AI & Autonomous Technologies Residual Risks
---+AI & Autonomous Technologies Viability Decisions

AI TEVV Reporting

Description

Mechanisms exist to report the status and results of Artificial Intelligence Test, Evaluation, Validation & Verification (AI TEVV) to relevant stakeholders, including governing bodies, as required.

Possible Solutions & Considerations

Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2

∙ Report AI testing results to management

Small Business (10-49 staff) / BLS Firm Size Classes 3-4

∙ Document and communicate AI test results to stakeholders

Medium Business (50-249 staff) / BLS Firm Size Classes 5-6

∙ Formal AI TEVV reporting process
∙ Standardized reporting templates

Large Business (250-999 staff) / BLS Firm Size Classes 7-8

∙ AI TEVV reporting program
∙ Regular stakeholder briefings
∙ Findings tracking

Enterprise (> 1,000 staff) / BLS Firm Size Class 9

∙ Enterprise AI TEVV reporting framework
∙ Automated test result dashboards
∙ Board-level AI risk reporting

SCR-CMM

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

SCR-CMM Level 1 criteria definitions are not available for this control:
▪ A reasonable person would conclude this control requires a structured process.
▪ At this level of maturity, the "ad hoc" nature of performing a capability informally would indicate the intent of the control is not met due to a lack of consistency and formality.

Level 2 Planned Tracked

SCR-CMM Level 2 criteria definitions are not available for this control:
▪ A reasonable person would conclude a well-defined and standardized process is required.
▪ At this level of maturity, the “requirements-driven” nature of performing the control is focused on a localized and/or regionalized implementation, not uniform and consistent across the organization.
▪ Requirements are narrowly scoped for applicability and are primarily derived from compliance obligations (e.g., laws, regulations and contracts).

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 report the status and results of Artificial Intelligence Test, Evaluation, Validation & Verification (AI TEVV) to relevant stakeholders, including governing bodies, as required.

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.

1. Oversigt

Titel Standard
AI & Autonomous Technologies Residual Risks

Description

Mechanisms exist to identify and document residual risks (defined as the sum of all unmitigated risks) to both downstream acquirers and end users of Artificial Intelligence (AI) and Autonomous Technologies (AAT).

Possible Solutions & Considerations

Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2

∙ Project team review
∙ Artificial Intelligence (AI) / autonomous technologies governance program

Small Business (10-49 staff) / BLS Firm Size Classes 3-4

∙ Project team review
∙ Artificial Intelligence (AI) / autonomous technologies governance program

Medium Business (50-249 staff) / BLS Firm Size Classes 5-6

∙ Project team review
∙ Legal review
∙ Steering committee
∙ Artificial Intelligence (AI) / autonomous technologies governance program

Large Business (250-999 staff) / BLS Firm Size Classes 7-8

∙ Legal review
∙ Steering committee
∙ Board of Directors (BoD)
∙ Artificial Intelligence (AI) / autonomous technologies governance program

Enterprise (> 1,000 staff) / BLS Firm Size Class 9

∙ Legal review
∙ Steering committee
∙ Board of Directors (BoD)
∙ Artificial Intelligence (AI) / autonomous technologies governance program

SCR-CMM

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 identify and document negative, residual risks (defined as the sum of all unmitigated risks) to both downstream acquirers and end users of 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.
AI & Autonomous Technologies Viability Decisions

Description

Mechanisms exist to define the criteria as to whether Artificial Intelligence (AI) and Autonomous Technologies (AAT) achieved intended purposes and stated objectives to determine whether its development or deployment should proceed.

Possible Solutions & Considerations

Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2

∙ Project team review
∙ Artificial Intelligence (AI) / autonomous technologies governance program

Small Business (10-49 staff) / BLS Firm Size Classes 3-4

∙ Project team review
∙ Artificial Intelligence (AI) / autonomous technologies governance program

Medium Business (50-249 staff) / BLS Firm Size Classes 5-6

∙ Project team review
∙ Legal review
∙ Steering committee
∙ Artificial Intelligence (AI) / autonomous technologies governance program

Large Business (250-999 staff) / BLS Firm Size Classes 7-8

∙ Legal review
∙ Steering committee
∙ Board of Directors (BoD)
∙ Artificial Intelligence (AI) / autonomous technologies governance program

Enterprise (> 1,000 staff) / BLS Firm Size Class 9

∙ Legal review
∙ Steering committee
∙ Board of Directors (BoD)
∙ Artificial Intelligence (AI) / autonomous technologies governance program

SCR-CMM

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 define the criteria as to whether AAT achieved intended purposes and stated objectives to determine whether its development or deployment should proceed.

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.

1.1 Referencer

1.2 Identificerede krav

1.3 Relaterede reguleringer

2. Identificerede krav

Krav
Kilde Krav

3. Relaterede reguleringer

Linkede sager

Sagslinks
Linktype Sag
is related to Annual
is related to relative Control Weighting = 05
is related to Technology
is related to Protect
is related to SCRM Focus Tier 2 OPERATIONAL
is related to SCRM Focus Tier 3 TACTICAL
blocks Loss of Accountability / Attribution
blocks Excessive or Unauthorized Privilege
blocks Unauthorized Privilege Elevation
blocks Unauthorized Access
blocks Loss, Theft or Damage of Assets
blocks Unauthorized Modification / Loss of System Integrity
blocks Business / Service Interruption
blocks Data Loss / Integrity Compromise
blocks Reduced Operational Productivity
blocks System / Data Compromise (Technical Vector)
blocks System / Data Compromise (Non-Technical Vector)
blocks Revenue Loss
blocks Contractual Default / Termination
blocks Loss of Competitive Advantage
blocks Reputational Harm / Loss of Stakeholder Trust
blocks Regulatory / Legal / Contractual Financial Liability
blocks Exposure from Unaddressed Vulnerabilities
blocks System / Service Compromise
blocks Failure to Support Business / Mission Objectives
blocks Unaddressed Security / Compliance Exposure
blocks Unperformed / Unowned Control Responsibilities
blocks Uncontrolled Internal Security / Privacy Exposure
blocks Uncontrolled Third-Party Security / Privacy Exposure
blocks Lack of oversight of internal controls
blocks Lack of oversight of third-party controls
blocks Harm from Illegal, Abusive or Unsafe Content / Conduct
blocks Loss of Investigative / Evidentiary Capability
blocks Delayed Containment / Increased Incident Impact
blocks Incident Persistence / Recurrence
blocks Incident Response / Recovery Cost
blocks Undetected / Delayed Detection of Adverse Activity
blocks Third-Party Cybersecurity Compromise / Exposure
blocks Third-Party Physical Security Disruption / Exposure
blocks Sub-Tier / Fourth-Party Supply Chain Exposure
blocks Third-Party Legal / Compliance Exposure
blocks Harm from Unauthorized / Unintended Product or Service Use
blocks Third-Party Dependency Failure
is related to Process
blocks Loss of Authorization / Certification / License
blocks Inability to Demonstrate Due Diligence / Due Care
blocks Unreliable Assurance / Decision Information
blocks AI Output / Decision Integrity Failure
blocks Unintended or Unsafe Technology Behavior
blocks AI Bias / Discriminatory Outcome
blocks Drought & Water Shortage
blocks Earthquakes
blocks Fire & Wildfires
blocks Floods
blocks Hurricanes & Tropical Storms
blocks Landslides & Debris Flow
blocks Pandemic (Disease) Outbreaks
blocks Severe Weather
blocks Space Weather
blocks Thunderstorms & Lightning
blocks Tornadoes
blocks Tsunamis
blocks Volcanoes
blocks Winter Storms & Extreme Cold
blocks Malicious Cyber Activity
blocks Dysfunctional Management Practices
blocks Human Error
blocks Technical / Mechanical Failure
blocks Statutory / Regulatory / Contractual Change
blocks Data Quality Degradation / Data Poisoning
blocks Artificial Intelligence & Autonomous Technologies (AAT) System Failure or Unintended Behavior
blocks Fraud, Corruption and/or Intentional Criminal Conduct
blocks Conflict of Interest (COI) / Undue Influence / Insider Misconduct
blocks Workforce Shortage / Loss of Critical Skills / Labor Disruption
blocks Adversarial Artificial Intelligence (AI) Attack
is blocked by AAT-30 AI TEVV Reporting – Assessment Procedure
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