+Artikel 26 Skyldigheter för tillhandahållare av AI-system med hög risk
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Artikel 26 Skyldigheter för tillhandahållare av AI-system med hög risk

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1. Översikt

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Artikel 26 1.
Tillhandahållare av AI-system med hög risk ska vidta lämpliga tekniska och organisatoriska åtgärder för att säkerställa att de använder sådana system i enlighet med de bruksanvisningar som åtföljer systemen, enligt punkterna 3 och 6.
Artikel 26 2.
Tillhandahållare ska tilldela fysiska personer som har nödvändig kompetens, utbildning och auktoritet samt nödvändigt stöd uppgiften att utöva mänsklig kontroll.
Artikel 26 3.
De skyldigheter som fastställs i punkterna 1 och 2 påverkar inte andra skyldigheter för tillhandahållare enligt unionsrätten eller nationell rätt eller tillhandahållarens frihet att organisera sina egna resurser och sin egen verksamhet i syfte att genomföra de åtgärder för mänsklig kontroll som leverantören anger.
Artikel 26 4.
Utan att det påverkar tillämpningen av punkterna 1 och 2 ska tillhandahållaren, i den mån tillhandahållaren utövar kontroll över indata, säkerställa att indata är relevanta och tillräckligt representativa med tanke på det avsedda ändamålet med AI-systemet med hög risk.
Artikel 26 5.
Tillhandahållare ska övervaka driften av AI-systemet med hög risk på grundval av bruksanvisningen och, i förekommande fall, informera leverantörerna i enlighet med artikel 72. Om tillhandahållare har skäl att tro att användningen av AI-systemet med hög risk i enlighet med instruktionerna kan leda till att AI-systemet utgöra en risk i den mening som avses i artikel 79.1 ska de, utan oskäligt dröjsmål, informera leverantören eller distributören och den berörda marknadskontrollmyndigheten och tillfälligt avbryta användningen av det systemet. Om tillhandahållare har fastställt en allvarlig incident ska de också omedelbart informera först leverantören och sedan importören eller distributören och de berörda marknadskontrollsmyndigheterna om den incidenten. Om tillhandahållaren inte kan nå leverantören ska artikel 73 gälla i tillämpliga delar. Denna skyldighet omfattar inte känsliga operativa uppgifter om tillhandahållare av AI-system som är brottsbekämpande myndigheter.

För tillhandahållare som är finansinstitut som omfattas av krav avseende sina interna styrelseformer, arrangemang eller processer enligt unionsrätten om finansiella tjänster ska övervakningsskyldigheten i första stycket anses vara uppfylld genom att reglerna om interna styrelseformer, arrangemang, processer och mekanismer enligt relevant unionsrätt om finansiella tjänster följs.
Artikel 26 6.
Tillhandahållare av AI-system med hög risk ska spara de loggar som genereras automatiskt av det AI-systemet med hög risk, i den mån sådana loggar står under deras kontroll, under en period som är lämplig för det avsedda ändamålet med AI-systemet med hög risk, dock i minst sex månader, om inte annat föreskrivs i tillämplig unionsrätt eller nationell rätt, i synnerhet unionsrätten om skydd av personuppgifter.

Tillhandahållare som är finansinstitut som omfattas av krav avseende sina interna styrelseformer, arrangemang eller processer enligt unionsrätten om finansiella tjänster ska bevara loggar som en del av den dokumentation som ska bevaras enligt relevant unionsrätt om finansiella tjänster.
Artikel 26 7.
Innan ett AI-system med hög risk tas i bruk eller används på en arbetsplats ska tillhandahållare som är arbetsgivare informera arbetstagarrepresentanterna och de berörda arbetstagarna om att de kommer att vara föremål för användning av AI-systemet med hög risk. Denna information ska, i tillämpliga fall, tillhandahållas i enlighet med de regler och förfaranden som fastställs i unionsrätten och nationell rätt samt praxis i fråga om information till arbetstagare och deras representanter.
Artikel 26 8.
Tillhandahållare av AI-system med hög risk som är offentliga myndigheter eller unionens institutioner, organ eller byråer ska fullgöra de registreringsskyldigheter som avses i artikel 49. Om dessa tillhandahållare finner att det AI-system med hög risk som de avser att använda inte har registrerats i den EU-databas som avses i artikel 71 får de inte använda det systemet och ska informera leverantören eller distributören.
Artikel 26 9.
I tillämpliga fall ska tillhandahållare av AI-system med hög risk använda den information som tillhandahålls enligt artikel 13 i denna förordning för att fullgöra sin skyldighet att genomföra en konsekvensbedömning avseende dataskydd enligt artikel 35 i förordning (EU) 2016/679 eller artikel 27 i direktiv (EU) 2016/680.
Artikel 26 10.
Inom ramen för en utredning för målinriktad sökning av en person som misstänks ha begått ett brott eller som har dömts för att ha begått ett brott ska tillhandahållaren av ett AI-system med hög risk för biometrisk fjärridentifiering i efterhand, utan att det påverkar tillämpningen av direktiv (EU) 2016/680, på förhand eller utan oskäligt dröjsmål och senast inom 48 timmar, av en rättslig myndighet eller en administrativ myndighet vars beslut är bindande och föremål för rättslig prövning begära tillstånd för användning av det systemet, utom när det används för den inledande identifieringen av en potentiell misstänkt på grundval av objektiva och verifierbara fakta med direkt anknytning till brottet. Varje användning ska begränsas till vad som är absolut nödvändigt för att utreda ett specifikt brott.

Om det tillstånd som begärts enligt första stycket nekas ska användningen av det system för biometrisk fjärridentifiering i efterhand som är kopplat till det begärda tillståndet upphöra med omedelbar verkan, och de personuppgifter som är kopplade till användningen av det AI-system med hög risk för vilket tillståndet begärdes ska raderas.

Under inga omständigheter får ett sådant AI-system med hög risk för biometrisk fjärridentifiering i efterhand användas för brottsbekämpande ändamål på ett icke målinriktat sätt, utan koppling till ett brott, ett straffrättsligt förfarande, ett verkligt och aktuellt eller verkligt och förutsebart hot om ett brott eller sökning efter en specifik försvunnen person. Det ska säkerställas att inget beslut som har negativa rättsliga följder för en person får fattas av de brottsbekämpande myndigheterna enbart på grundval av utdata från sådana system för biometrisk fjärridentifiering i efterhand.

Denna punkt påverkar inte tillämpningen av artikel 9 i förordning (EU) 2016/679 och artikel 10 i direktiv (EU) 2016/680 avseende behandling av biometriska uppgifter.

Oavsett ändamål eller tillhandahållare ska varje användning av sådana AI-system med hög risk dokumenteras i den relevanta polisakten och på begäran göras tillgänglig för den berörda marknadskontrollmyndigheten och den nationella dataskyddsmyndigheten, med undantag för utlämnande av känsliga operativa uppgifter som rör brottsbekämpning. Detta stycke påverkar inte de befogenheter som tilldelas tillsynsmyndigheterna genom direktiv (EU) 2016/680.

Tillhandahållare ska lämna in årliga rapporter till de berörda marknadskontrollmyndigheterna och nationella dataskyddsmyndigheterna om sin användning av system för biometrisk fjärridentifiering i efterhand, med undantag för utlämnande av känsliga operativa uppgifter som rör brottsbekämpning. Rapporterna får aggregeras för att täcka mer än en användning.

Medlemsstaterna får införa mer restriktiva lagar om användningen av system för biometrisk fjärridentifiering i efterhand i enlighet med unionsrätten.
Artikel 26 11.
Utan att det påverkar tillämpningen av artikel 50 i denna förordning ska tillhandahållare av AI-system med hög risk som avses i bilaga III och som fattar beslut eller hjälper till att fatta beslut som rör fysiska personer informera de fysiska personerna om att de är föremål för användning av AI-systemet med hög risk. När det gäller AI-system med hög risk som används för brottsbekämpande ändamål ska artikel 13 i direktiv (EU) 2016/680 tillämpas.
Artikel 26 12.
Tillhandahållare ska samarbeta med de berörda behöriga myndigheterna i alla åtgärder som dessa myndigheter vidtar med avseende på AI-systemet med hög risk i syfte att genomföra denna förordning.

1.1 Referenser

1.2 Identifierade krav

1.3 Relaterade standarder

2. Identifierade krav

Krav

3. Relaterade standarder

Standarder
SCF AI & Autonomous Technologies Deployment

Description

Mechanisms exist to ensure the deployment of Artificial Intelligence (AI) and Autonomous Technologies (AAT) includes appropriate technical and organizational measures so that AAT are used in accordance with the AAT developer-provided instructions.

Possible Solutions & Considerations

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

∙ Deploy AI tools only for documented, approved purposes

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

∙ AI deployment approval process
∙ Document intended use and technical measures

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

∙ Formal AI deployment policy
∙ Technical and organizational measures for AI deployment

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

∙ AI deployment governance program
∙ Formal approval workflows
∙ Post-deployment monitoring

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

∙ Enterprise AI deployment governance framework
∙ Automated deployment controls
∙ Continuous monitoring
∙ Regulatory compliance

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 ensure the deployment of AAT includes appropriate technical and organizational measures so that AAT are used in accordance with the AAT developer-provided instructions for use.

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.
SCF AI & Autonomous Technologies Oversight Functions Competency

Description

Mechanisms exist to ensure the deployment of Artificial Intelligence (AI) and Autonomous Technologies (AAT) assigns human oversight to individuals who have the necessary:
(1) Competence;
(2) Training;
(3) Authority; and
(4) Resources.

Possible Solutions & Considerations

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

∙ Train AI system operators on oversight responsibilities

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

∙ Training program for personnel overseeing AI systems

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

∙ Formal AI oversight training program
∙ Competency requirements for AI oversight roles

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

∙ AI training and certification program for oversight personnel

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

∙ Enterprise AI training and certification program
∙ Role-based AI competency framework
∙ Continuous learning 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 ensure the deployment of AAT assigns human oversight to individuals who have the necessary:
(1) Competence;
(2) Training;
(3) Authority; and
(4) Resources.

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.
SCF AI & Autonomous Technologies Data Relevance

Description

Mechanisms exist to ensure the input to Artificial Intelligence (AI) and Autonomous Technologies (AAT) is relevant to the intended purpose of the AAT.

Possible Solutions & Considerations

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

∙ Validate that inputs to AI tools are relevant before submitting

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

∙ Policy requiring relevance checking of AI inputs

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

∙ Formal AI input validation policy
∙ Input relevance criteria documentation

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

∙ Input validation controls for AI systems
∙ Automated input filtering

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

∙ Enterprise AI input governance framework
∙ Automated input validation and filtering
∙ Data quality controls for AI pipelines

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 ensure the input to AAT is relevant to the intended purpose of the 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.
SCF AI & Autonomous Technologies Irregularity Reporting

Description

Mechanisms exist to ensure serious incidents and/or irregularities associated with the deployment of Artificial Intelligence (AI) and Autonomous Technologies (AAT) are reported without delay to the:
(1) AAT provider;
(2) AAT importer or distributor, if applicable; and/or
(3) Local law authorities and/or governmental agency, as required.

Possible Solutions & Considerations

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

∙ Report serious AI incidents and irregularities to management

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

∙ Incident reporting procedure for AI irregularities

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

∙ Formal AI incident and irregularity reporting policy
∙ Regulatory reporting contacts

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

∙ AI incident response program with regulatory reporting integration

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

∙ Enterprise AI incident management platform
∙ Automated regulatory notification
∙ Legal and compliance integration

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 ensure serious incidents and/or irregularities associated with the deployment of AAT are reported without delay to the:
(1) AAT provider;
(2) AAT importer or distributor, if applicable; and/or
(3) Local law authorities and/or governmental agency, 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.
SCF AI & Autonomous Technologies Use Notification To Employees

Description

Mechanisms exist to ensure employees, including workers' representatives, are informed about Artificial Intelligence (AI) and Autonomous Technologies (AAT) deployments, prior to the use of the AAT in a production environment.

Possible Solutions & Considerations

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

∙ Inform employees of AI tools being used in their work

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

∙ Policy requiring employee notification of AI tools affecting their work

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

∙ Formal employee notification policy for AI deployments
∙ Communication procedures

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

∙ AI transparency program for employees
∙ Works council/union notification as required

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

∙ Enterprise AI employee transparency framework
∙ Formal notification procedures
∙ Labor law compliance tracking

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 ensure employees, including workers' representatives, are informed about AAT deployments, prior to the use of the AAT in a production environment.

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.
SCF AI & Autonomous Technologies Use Notification To Users

Description

Mechanisms exist to ensure Artificial Intelligence (AI) and Autonomous Technologies (AAT) that make decisions, or assist in making decisions, inform the people in a clear manner that they are:
(1) Utilizing an AAT solution; and
(2) Expected to validate the output for relevance and accuracy.

Possible Solutions & Considerations

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

∙ Inform users when AI is making or assisting decisions affecting them

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

∙ User notification policy for AI-assisted decisions

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

∙ Formal user notification policy and procedures for AI decision support

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

∙ AI user transparency program
∙ Automated user notifications for AI decisions

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

∙ Enterprise AI user transparency framework
∙ Automated disclosure mechanisms
∙ Regulatory compliance (EU AI Act, GDPR)

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 ensure AAT that make decisions, or assist in making decisions, inform the people in a clear manner that they are:
(1) Utilizing an AAT solution; and
(2) Expected to validate the output for relevance and accuracy.

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.
SCF AI & Autonomous Technologies Event Logging

Description

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.

Possible Solutions & Considerations

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

∙ Enable basic logging on AI/ML systems

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

∙ Configure event logging on AI systems
∙ Define log retention periods

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

∙ Formal AI event logging policy
∙ Centralized log collection

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

∙ SIEM integration for AI system logs
∙ Defined logging standards for AI platforms

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

∙ Enterprise SIEM platform
∙ Standardized AI event logging schema
∙ Automated alerting for anomalous AI events

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 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.
SCF AI & Autonomous Technologies Registration

Description

Mechanisms exist to maintain a current registration for Artificial Intelligence (AI) and Autonomous Technologies (AAT) with the appropriate governing body, as required by statutory or regulatory requirements.

Possible Solutions & Considerations

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

∙ Determine whether any AI use requires registration (e.g., EU AI Act high-risk systems)

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

∙ Track AI registration obligations by jurisdiction in compliance checklist

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

∙ Register high-risk AI systems with relevant authorities as required

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

∙ AI registration compliance program
∙ Track registration requirements by jurisdiction

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

∙ Enterprise AI regulatory compliance platform
∙ Automated registration tracking
∙ EU AI Act database registration compliance

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

Compliance (CPL) 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 CPL 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 CPL domain capabilities are well-documented and kept current by process owners.
▪ A Governance, Risk & Compliance (GRC) team, or similar function, is appropriately staffed and supported to implement and maintain CPL domain capabilities.
▪ Technology is leveraged to enhance the efficiency and accuracy of governance, risk management and compliance operations (e.g., GRC 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 CPL 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 maintain a current registration for AAT with the appropriate governing body, as required by statutory or regulatory requirements.

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.
SCF Data Protection Impact Assessment (DPIA)

Description

Mechanisms exist to conduct a Data Protection Impact Assessment (DPIA) on Technology Assets, Applications and/or Services (TAAS) that store, process and/or transmit Personal Data (PD) to identify and remediate reasonably-expected risks.

Possible Solutions & Considerations

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

∙ Risk Management Program (RMP)
∙ Data Protection Impact Assessment (DPIA)
∙ Privacy Impact Assessment (PIA)

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

∙ Risk Management Program (RMP)
∙ Data Protection Impact Assessment (DPIA)
∙ Privacy Impact Assessment (PIA)

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

∙ Risk Management Program (RMP)
∙ Data Protection Impact Assessment (DPIA)
∙ Privacy Impact Assessment (PIA)

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

∙ Risk Management Program (RMP)
∙ Data Protection Impact Assessment (DPIA)
∙ Privacy Impact Assessment (PIA)

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

∙ Risk Management Program (RMP)
∙ Data Protection Impact Assessment (DPIA)
∙ Privacy Impact Assessment (PIA)

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

Risk Management (RSK) 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 RSK domain capabilities are formally documented and centrally-managed by the entity.
▪ Standardized Operating Procedures (SOP) associated with RSK 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 RSK domain capabilities to address applicable statutory, regulatory and/or contractual requirements for Technology Assets, Applications, Services and/or Data (TAASD).
▪ Risk management-related controls are primarily administrative and preventative in nature (e.g., policies, standards and procedures & guidelines).
▪ Risk management may be a defined function (e.g., team or department) or assigned as an additional duty to existing IT and/or cybersecurity personnel.
▪ Risk management processes (e.g., risk assessments) and technologies focus on protecting High Value Assets (HVAs), including environments where sensitive/regulated data is stored, transmitted and processed.
▪ IT and/or cybersecurity personnel implement and maintain a form of Risk Management Program (RMP) that provides operational guidance on how risk is identified, assessed, remediated and reported.
▪ Data/process owners are expected to self-manage risks associated with their systems, applications, services and data, based on the organization's published policies and standards, including the identification, remediation and reporting of risks.
▪ Business process owners (BPOs) are made aware of cybersecurity and data protection risk(s).

Level 3 Well Defined

Risk Management (RSK) 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 RSK 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 RSK domain capabilities are well-documented and kept current by process owners.
▪ A risk management team, or similar function, is appropriately staffed and supported to implement and maintain RSK domain capabilities.
▪ Technology is leveraged to enhance the efficiency and accuracy of risk management operations (e.g., risk management solution, GRC platform and TPRM tool).
▪ 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 RSK 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 conduct a Data Protection Impact Assessment (DPIA) on Technology Assets, Applications and/or Services (TAAS) that store, process and/or transmit Personal Data (PD) to identify and remediate reasonably-expected risks.

Level 4 Quantitatively Controlled

Risk Management (RSK) capabilities, in addition to being standardized across the entity and centrally managed to ensure consistency across Technology Assets, Applications, Services and/or Data (TAASD), efforts are metrics driven to provide sufficient insight for decision makers to predict optimal performance, ensure continued operations and/or identify areas for improvement. Capability criteria associated with this control reasonably expect the following criteria to exist:
▪ Applicable SCR-CMM Level 3 (Well Defined) capabilities are implemented and operational.
▪ Metrics reporting includes quantitative analysis of Key Performance Indicators (KPIs).
▪ Metrics reporting includes quantitative analysis of Key Risk Indicators (KRIs).
▪ Scope of metrics, KPIs and KRIs covers organization-wide cybersecurity and data protection controls, including functions performed by third-parties.
▪ Organizational leadership maintains a formal process to objectively review and respond to metrics, KPIs and KRIs (e.g., monthly or quarterly review).
▪ Based on metrics analysis, process improvement recommendations are submitted for review and are handled in accordance with change control processes.
▪ Business and technical stakeholders are involved in reviewing and approving proposed changes to evolve capabilities.

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.