+Articolo 26 Obblighi dei deployer dei sistemi di IA ad alto rischio
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Articolo 26 Obblighi dei deployer dei sistemi di IA ad alto rischio

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1. Panoramica

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Articolo 26 1.
I deployer di sistemi di IA ad alto rischio adottano idonee misure tecniche e organizzative per garantire di utilizzare tali sistemi conformemente alle istruzioni per l'uso che accompagnano i sistemi, a norma dei paragrafi 3 e 6.
Articolo 26 2.
I deployer affidano la sorveglianza umana a persone fisiche che dispongono della competenza, della formazione e dell'autorità necessarie nonché del sostegno necessario.
Articolo 26 3.
Gli obblighi di cui ai paragrafi 1 e 2 lasciano impregiudicati gli altri obblighi dei deployer previsti dal diritto dell'Unione o nazionale e la libertà del deployer di organizzare le proprie risorse e attività al fine di attuare le misure di sorveglianza umana indicate dal fornitore.
Articolo 26 4.
Fatti salvi i paragrafi 1 e 2, nella misura in cui esercita il controllo sui dati di input, il deployer garantisce che tali dati di input siano pertinenti e sufficientemente rappresentativi alla luce della finalità prevista del sistema di IA ad alto rischio.
Articolo 26 5.
I deployer monitorano il funzionamento del sistema di IA ad alto rischio sulla base delle istruzioni per l'uso e, se del caso, informano i fornitori a tale riguardo conformemente all'articolo 72. Qualora abbiano motivo di ritenere che l'uso del sistema di IA ad alto rischio in conformità delle istruzioni possa comportare che il sistema di IA presenti un rischio ai sensi dell'articolo 79, paragrafo 1, i deployer ne informano, senza indebito ritardo, il fornitore o il distributore e la pertinente autorità di vigilanza del mercato e sospendono l'uso di tale sistema. Qualora abbiano individuato un incidente grave, i deployer ne informano immediatamente anche il fornitore, in primo luogo, e successivamente l'importatore o il distributore e le pertinenti autorità di vigilanza del mercato. Nel caso in cui il deployer non sia in grado di raggiungere il fornitore, si applica mutatis mutandis l'articolo 73. Tale obbligo non riguarda i dati operativi sensibili dei deployer dei sistemi di IA che sono autorità di contrasto.

Per i deployer che sono istituti finanziari soggetti a requisiti in materia di governance, di dispositivi o di processi interni stabiliti a norma del diritto dell'Unione in materia di servizi finanziari, l'obbligo di monitoraggio di cui al primo comma si considera soddisfatto se sono soddisfatte le regole sui dispositivi, sui processi e sui meccanismi di governance interna a norma del pertinente diritto in materia di servizi finanziari.
Articolo 26 6.
I deployer di sistemi di IA ad alto rischio conservano i log generati automaticamente da tale sistema di IA ad alto rischio, nella misura in cui tali log sono sotto il loro controllo, per un periodo adeguato alla prevista finalità del sistema di IA ad alto rischio, di almeno sei mesi, salvo diversamente disposto dal diritto dell'Unione o nazionale applicabile, in particolare dal diritto dell'Unione in materia di protezione dei dati personali.

I deployer che sono istituti finanziari soggetti a requisiti in materia di governance, di dispositivi o di processi interni stabiliti a norma del diritto dell'Unione in materia di servizi finanziari conservano i log come parte della documentazione conservata a norma del pertinente diritto dell'Unione in materia di servizi finanziari.
Articolo 26 7.
Prima di mettere in servizio o utilizzare un sistema di IA ad alto rischio sul luogo di lavoro, i deployer che sono datori di lavoro informano i rappresentanti dei lavoratori e i lavoratori interessati che saranno soggetti all'uso del sistema di IA ad alto rischio. Tali informazioni sono fornite, se del caso, conformemente alle norme e alle procedure stabilite dal diritto e dalle prassi dell'Unione e nazionali in materia di informazione dei lavoratori e dei loro rappresentanti.
Articolo 26 8.
I deployer di sistemi di IA ad alto rischio che sono autorità pubbliche o istituzioni, organi e organismi dell'Unione rispettano gli obblighi di registrazione di cui all'articolo 49. Ove accertino che il sistema di IA ad alto rischio che intendono utilizzare non è stato registrato nella banca dati dell'UE di cui all'articolo 71, tali deployer non utilizzano tale sistema e ne informano il fornitore o il distributore.
Articolo 26 9.
Se del caso, i deployer di sistemi di IA ad alto rischio usano le informazioni fornite a norma dell'articolo 13 del presente regolamento per adempiere al loro obbligo di effettuare una valutazione d'impatto sulla protezione dei dati a norma dell'articolo 35 del regolamento (UE) 2016/679 o dell'articolo 27 della direttiva (UE) 2016/680.
Articolo 26 10.
Fatta salva la direttiva (UE) 2016/680, nel quadro di un'indagine per la ricerca mirata di una persona sospettata o condannata per aver commesso un reato, il deployer di un sistema di IA ad alto rischio per l'identificazione biometrica remota a posteriori chiede un'autorizzazione, ex ante o senza indebito ritardo ed entro 48 ore, da parte di un'autorità giudiziaria o amministrativa la cui decisione è vincolante e soggetta a controllo giurisdizionale, per l'uso di tale sistema, tranne quando è utilizzato per l'identificazione iniziale di un potenziale sospetto sulla base di fatti oggettivi e verificabili direttamente connessi al reato. Ogni uso è limitato a quanto strettamente necessario per le indagini su uno specifico reato.

Se l'autorizzazione richiesta a norma del primo comma è respinta, l'uso del sistema di identificazione biometrica remota a posteriori collegato a tale autorizzazione richiesta è interrotto con effetto immediato e i dati personali connessi all'uso del sistema di IA ad alto rischio per il quale è stata richiesta l'autorizzazione sono cancellati.

In nessun caso tale sistema di IA ad alto rischio per l'identificazione biometrica remota a posteriori è utilizzato a fini di contrasto in modo non mirato, senza alcun collegamento con un reato, un procedimento penale, una minaccia reale e attuale o reale e prevedibile di un reato o la ricerca di una determinata persona scomparsa. Occorre garantire che nessuna decisione che produca effetti giuridici negativi su una persona possa essere presa dalle autorità di contrasto unicamente sulla base dell'output di tali sistemi di identificazione biometrica remota a posteriori.

Il presente paragrafo lascia impregiudicati l'articolo 9 del regolamento (UE) 2016/679 e l'articolo 10 della direttiva (UE) 2016/680 riguardo al trattamento dei dati biometrici.

Indipendentemente dalla finalità o dal deployer, ciascun uso di tali sistemi di IA ad alto rischio è documentato nel pertinente fascicolo di polizia e messo a disposizione della pertinente autorità di vigilanza del mercato e dell'autorità nazionale per la protezione dei dati, su richiesta, escludendo la divulgazione di dati operativi sensibili relativi alle attività di contrasto. Il presente comma lascia impregiudicati i poteri conferiti alle autorità di controllo dalla direttiva (UE) 2016/680.

I deployer presentano alle pertinenti autorità di vigilanza del mercato e alle autorità nazionali per la protezione dei dati relazioni annuali sul loro uso di sistemi di identificazione biometrica remota a posteriori, escludendo la divulgazione di dati operativi sensibili relativi alle attività di contrasto. Le relazioni possono essere aggregate per coprire più di un utilizzo.

Gli Stati membri possono introdurre, in conformità del diritto dell'Unione, disposizioni più restrittive sull'uso dei sistemi di identificazione biometrica remota a posteriori.
Articolo 26 11.
Fatto salvo l'articolo 50, del presente regolamento i deployer dei sistemi di IA ad alto rischio di cui all'allegato III che adottano decisioni o assistono nell'adozione di decisioni che riguardano persone fisiche informano queste ultime che sono soggette all'uso del sistema di IA ad alto rischio. Per i sistemi di IA ad alto rischio utilizzati a fini di contrasto si applica l'articolo 13 della direttiva (UE) 2016/680.
Articolo 26 12.
I deployer cooperano con le pertinenti autorità competenti in merito a qualsiasi azione intrapresa da dette autorità in relazione al sistema di IA ad alto rischio ai fini dell'attuazione del presente regolamento.

1.1 Riferimenti

1.2 Requisiti identificati

1.3 Standard correlati

2. Requisiti identificati

Requisiti

3. Standard correlati

Standard
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.