+AI & Autonomous Technologies Business Case
---+AI & Autonomous Technologies Potential Benefits Analysis
---+AI & Autonomous Technologies Potential Costs Analysis
---+AI & Autonomous Technologies Targeted Application Scope
---+AI & Autonomous Technologies Cost / Benefit Mapping

AI & Autonomous Technologies Business Case

Description

Mechanisms exist to benchmark capabilities, targeted usage, goals and expected benefits and costs of Artificial Intelligence (AI) and Autonomous Technologies (AAT).

Possible Solutions & Considerations

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

∙ AI business case documentation (costs, benefits, risks)
∙ AI governance program

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

∙ Formal AI business case process
∙ AI governance program
∙ NIST AI RMF Map function

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

∙ Formal AI business case with risk-benefit analysis
∙ AI governance program
∙ NIST AI RMF Map function
∙ AI procurement review process

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

∙ AI business case framework with risk, cost, and benefit analysis
∙ Executive review and approval of AI business cases
∙ NIST AI RMF Map function

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

∙ Enterprise AI business case and portfolio management
∙ Board-level AI investment review and approval
∙ NIST AI RMF Map function at enterprise scale
∙ AI ROI tracking and 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

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 benchmark capabilities, targeted usage, goals and expected benefits and costs 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.

1. Przegląd

Tytuł Norma
AI & Autonomous Technologies Potential Benefits Analysis

Description

Mechanisms exist to assess the potential benefits of proposed Artificial Intelligence (AI) and Autonomous Technologies (AAT).

Possible Solutions & Considerations

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

∙ AI benefits documentation (accuracy improvements, efficiency gains, cost savings)
∙ AI governance program

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

∙ Formal AI benefits analysis for each deployed system
∙ AI governance program
∙ NIST AI RMF Map function

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

∙ Quantified AI benefits analysis (ROI, efficiency, accuracy)
∙ AI governance program
∙ NIST AI RMF Map function

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

∙ Structured AI benefits analysis integrated with business case process
∙ AI KPI tracking for benefits realization
∙ NIST AI RMF Map function

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

∙ Enterprise AI benefits realization framework
∙ AI ROI and value tracking integrated with GRC
∙ Board-level AI value reporting
∙ NIST AI RMF Map function at scale

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 assess the potential benefits of proposed 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 Potential Costs Analysis

Description

Mechanisms exist to assess potential costs, including non-monetary costs, resulting from expected or realized Artificial Intelligence (AI) and Autonomous Technologies (AAT)-related errors or system functionality and trustworthiness.

Possible Solutions & Considerations

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

∙ AI cost analysis (licensing, compute, maintenance, training data)
∙ AI governance program

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

∙ Formal AI cost analysis for each system
∙ AI governance program
∙ Total cost of ownership (TCO) assessment

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

∙ Quantified AI cost analysis including operational and hidden costs
∙ AI governance program
∙ NIST AI RMF Map function

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

∙ Structured AI cost analysis integrated with financial planning
∙ AI FinOps practices for cloud-based AI workloads
∙ NIST AI RMF Map function

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

∙ Enterprise AI cost management program
∙ AI FinOps and cloud cost optimization (e.g., AWS Cost Explorer, Azure Cost Management)
∙ Board-level AI investment and cost reporting
∙ NIST AI RMF Map function at scale

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 assess potential costs, including non-monetary costs, resulting from expected or realized AAT-related errors or system functionality and trustworthiness.

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 Targeted Application Scope

Description

Mechanisms exist to specify and document the targeted application scope of the proposed use and operation of Artificial Intelligence (AI) and Autonomous Technologies (AAT).

Possible Solutions & Considerations

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

∙ AI scope definition (systems, use cases, data in scope)
∙ AI governance program

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

∙ Documented AI application scope for each system
∙ AI governance program
∙ NIST AI RMF Map function

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

∙ Formal AI application scope definition process
∙ AI governance program
∙ NIST AI RMF Map function
∙ Scoping aligned to regulatory requirements

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

∙ Enterprise AI application scope management
∙ NIST AI RMF Map function
∙ AI scope reviews for regulatory compliance (EU AI Act, CCPA)

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

∙ Enterprise AI application scope and portfolio management
∙ NIST AI RMF Map function at enterprise scale
∙ Regulatory scope mapping (EU AI Act risk tiers, sector-specific requirements)
∙ Board-approved AI scope definitions

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 specify and document the targeted application scope of the proposed use and operation 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 Cost / Benefit Mapping

Description

Mechanisms exist to map risks and benefits for all components of Artificial Intelligence (AI) and Autonomous Technologies (AAT), including third-party software and data.

Possible Solutions & Considerations

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

∙ AI cost/benefit mapping (simple comparison document)
∙ AI governance program

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

∙ Formal AI cost/benefit mapping for each system
∙ AI governance program
∙ NIST AI RMF Map function

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

∙ Structured AI cost/benefit mapping with risk overlay
∙ AI governance program
∙ NIST AI RMF Map function

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

∙ Enterprise AI cost/benefit mapping integrated with risk and business case
∙ NIST AI RMF Map function
∙ AI portfolio cost/benefit reporting

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

∙ Enterprise AI cost/benefit framework integrated with GRC and ERM
∙ NIST AI RMF Map function at enterprise scale
∙ Board-level AI portfolio cost/benefit analysis
∙ Quantitative AI risk-adjusted ROI analysis

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 map risks and benefits for all components of AAT, including third-party software and data.

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 Odwołania

1.2 Zidentyfikowane wymagania

1.3 Powiązane regulacje

2. Zidentyfikowane wymagania

Wymagania
Źródło Wymaganie

3. Powiązane regulacje

Regulacje
Źródło Regulacja

Powiązane zgłoszenia

Powiązania
Typ powiązania Zgłoszenie
is related to Annual
is related to relative Control Weighting = 08
is related to Process
is related to Govern
is related to SCRM Focus Tier 1 STRATEGIC
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 Semi-Annual
is related to Identify
blocks Failure to Achieve Strategic / Mission Objectives
blocks Inability to Demonstrate Due Diligence / Due Care
blocks Unreliable Assurance / Decision Information
blocks Sensitive Data / Compliance Exposure from Unsanctioned AI Use
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 Economic Shock / Market Disruption
blocks Workforce Shortage / Loss of Critical Skills / Labor Disruption
is blocked by AAT-14 AI & Autonomous Technologies Business Case – Assessment Procedure
  • Secure Controls Framework -

    The Secure Controls Framework® (SCF)

    "The SCF is the Common Controls Framework™ (CCF), the world's most comprehensive cybersecurity and data privacy metaframework - it is also free to use. The entire concept is building secure, compliant and resilient capabilities in the most efficient and cost-effective manner possible.

    The SCF is more than just a unified control catalog, since its included content creates a playbook for Governance, Risk & Compliance (GRC) capabilities. Used globally by organizations of every size, the SCF is a robust and scalable solution for security, compliance and resilience controls. As a comprehensive security framework, the SCF maps 1,400+ controls across 200+ laws, regulations, and industry frameworks so you can implement once and comply everywhere.

    Like it or not, cybersecurity is a protracted war on an asymmetric battlefield, where the threats are everywhere and as defenders we have to make the effort to work together to help improve cybersecurity and data privacy practices, since we all suffer when massive data breaches occur or when cyber attacks have physical impacts. Hackers share information on attack methods with other hackers, so why shouldn’t the good guys share information on how to best protect an organization? We decided to take action and make a difference, since we feel it is too important to wait for someone else to fix the problems that exist.

    The SCF is made up of volunteers, mainly specialists within the cybersecurity profession, who focus on GRC and the cybersecurity side of data privacy. These are auditors, engineers, architects, incident responders, consultants and other specialists who live and breathe these topics on a daily basis. The end product is "expert-derived content" that makes up the SCF." https://securecontrolsframework.com/ 

    Terms & Conditions

    The SCF End User License Agreement (EULA) governs the use of the Secure Controls Framework® (SCF) under the Creative Commons Attribution-No Derivatives 4.0 International Public License.