+Άρθρο 26 Υποχρεώσεις των φορέων εφαρμογής συστημάτων ΤΝ υψηλού κινδύνου
---+Άρθρο 26 1.
---+Άρθρο 26 2.
---+Άρθρο 26 3.
---+Άρθρο 26 4.
---+Άρθρο 26 5.
---+Άρθρο 26 6.
---+Άρθρο 26 7.
---+Άρθρο 26 8.
---+Άρθρο 26 9.
---+Άρθρο 26 10.
---+Άρθρο 26 11.
---+Άρθρο 26 12.

Άρθρο 26 Υποχρεώσεις των φορέων εφαρμογής συστημάτων ΤΝ υψηλού κινδύνου

1. Επισκόπηση

,
Άρθρο 26 1.
Οι φορείς εφαρμογής συστημάτων ΤΝ υψηλού κινδύνου λαμβάνουν κατάλληλα τεχνικά και οργανωτικά μέτρα για να διασφαλίσουν ότι χρησιμοποιούν τα συστήματα αυτά σύμφωνα με τις οδηγίες χρήσης που τα συνοδεύουν, βάσει των παραγράφων 3 και 6.
Άρθρο 26 2.
Οι φορείς εφαρμογής αναθέτουν την ανθρώπινη εποπτεία σε φυσικά πρόσωπα που διαθέτουν την αναγκαία ικανότητα, κατάρτιση και εξουσία, καθώς και την αναγκαία υποστήριξη.
Άρθρο 26 3.
Οι υποχρεώσεις που καθορίζονται στις παραγράφους 1 και 2 ισχύουν με την επιφύλαξη άλλων υποχρεώσεων των φορέων εφαρμογής βάσει του ενωσιακού ή του εθνικού δικαίου και της ελευθερίας του φορέα εφαρμογής να οργανώσει τους πόρους και τις δραστηριότητές του για τον σκοπό της εφαρμογής των μέτρων ανθρώπινης εποπτείας που υποδεικνύει ο πάροχος.
Άρθρο 26 4.
Με την επιφύλαξη των παραγράφων 1 και 2, στον βαθμό που ο φορέας εφαρμογής ασκεί έλεγχο επί των δεδομένων εισόδου, ο εν λόγω φορέας εφαρμογής διασφαλίζει ότι τα δεδομένα εισόδου είναι συναφή και επαρκώς αντιπροσωπευτικά σε σχέση με τον επιδιωκόμενο σκοπό του συστήματος ΤΝ υψηλού κινδύνου.
Άρθρο 26 5.
Οι φορείς εφαρμογής παρακολουθούν τη λειτουργία του συστήματος ΤΝ υψηλού κινδύνου με βάση τις οδηγίες χρήσης και, κατά περίπτωση, ενημερώνουν τους παρόχους σύμφωνα με το άρθρο 72. Όταν οι φορείς εφαρμογής έχουν λόγο να θεωρούν ότι η χρήση του συστήματος ΤΝ υψηλού κινδύνου σύμφωνα με τις οδηγίες μπορεί να έχει ως αποτέλεσμα το εν λόγω σύστημα ΤΝ να συνιστά κίνδυνο κατά την έννοια του άρθρου 79 παράγραφος 1, τότε, χωρίς αδικαιολόγητη καθυστέρηση, ενημερώνουν τον πάροχο ή τον διανομέα και τη σχετική αρχή εποπτείας της αγοράς και αναστέλλουν τη χρήση του συστήματος. Όταν οι φορείς εφαρμογής έχουν εντοπίσει σοβαρό περιστατικό, ενημερώνουν επίσης αμέσως πρώτα τον πάροχο και, στη συνέχεια, τον εισαγωγέα ή τον διανομέα και τις αρμόδιες αρχές εποπτείας της αγοράς για το εν λόγω περιστατικό. Σε περίπτωση που ο φορέας εφαρμογής δεν είναι σε θέση να επικοινωνήσει με τον πάροχο, εφαρμόζεται το άρθρο 73, τηρουμένων των αναλογιών. Η υποχρέωση αυτή δεν καλύπτει ευαίσθητα επιχειρησιακά δεδομένα φορέων εφαρμογής συστημάτων ΤΝ που είναι αρχές επιβολής του νόμου.

Όσον αφορά φορείς εφαρμογής που είναι χρηματοοικονομικά ιδρύματα τα οποία, βάσει του ενωσιακού δικαίου για τις χρηματοοικονομικές υπηρεσίες, υπόκεινται σε απαιτήσεις όσον αφορά την εσωτερική διακυβέρνηση, τις εσωτερικές ρυθμίσεις ή τις εσωτερικές διαδικασίες τους, η υποχρέωση παρακολούθησης που προβλέπεται στο πρώτο εδάφιο θεωρείται ότι εκπληρώνεται με τη συμμόρφωση με τους κανόνες σχετικά με τις ρυθμίσεις, τις διαδικασίες και τους μηχανισμούς εσωτερικής διακυβέρνησης δυνάμει του σχετικού δικαίου για τις χρηματοοικονομικές υπηρεσίες.
Άρθρο 26 6.
Οι φορείς εφαρμογής συστημάτων ΤΝ υψηλού κινδύνου τηρούν τα αρχεία καταγραφής που δημιουργούνται αυτόματα από το εν λόγω σύστημα ΤΝ υψηλού κινδύνου στον βαθμό που τα εν λόγω αρχεία καταγραφής βρίσκονται υπό τον έλεγχό τους για χρονικό διάστημα κατάλληλο για τον επιδιωκόμενο σκοπό του συστήματος ΤΝ υψηλού κινδύνου, τουλάχιστον έξι μηνών, εκτός εάν προβλέπεται διαφορετικά στο εφαρμοστέο ενωσιακό ή εθνικό δίκαιο, ιδίως στο ενωσιακό δίκαιο για την προστασία των δεδομένων προσωπικού χαρακτήρα.

Οι φορείς εφαρμογής που είναι χρηματοοικονομικά ιδρύματα τα οποία, βάσει του ενωσιακού δικαίου για τις χρηματοοικονομικές υπηρεσίες, υπόκεινται σε απαιτήσεις όσον αφορά την εσωτερική διακυβέρνηση, τις εσωτερικές ρυθμίσεις ή τις εσωτερικές διαδικασίες τους, διατηρούν τα αρχεία καταγραφής στο πλαίσιο της τεκμηρίωσης που τηρείται δυνάμει του σχετικού ενωσιακού δικαίου για τις χρηματοοικονομικές υπηρεσίες.
Άρθρο 26 7.
Πριν από τη θέση σε λειτουργία ή τη χρήση συστήματος ΤΝ υψηλού κινδύνου στον χώρο εργασίας, οι φορείς εφαρμογής που είναι εργοδότες ενημερώνουν τους εκπροσώπους των εργαζομένων και τους επηρεαζόμενους εργαζομένους ότι θα υπόκεινται στη χρήση του συστήματος ΤΝ υψηλού κινδύνου. Οι πληροφορίες αυτές παρέχονται, κατά περίπτωση, σύμφωνα με τους κανόνες και τις διαδικασίες που ορίζονται στο ενωσιακό και το εθνικό δίκαιο και την ενωσιακή και εθνική πρακτική σχετικά με την ενημέρωση των εργαζομένων και των εκπροσώπων τους.
Άρθρο 26 8.
Οι φορείς εφαρμογής συστημάτων ΤΝ υψηλού κινδύνου που είναι δημόσιες αρχές ή θεσμικά και λοιπά όργανα ή οργανισμοί της Ένωσης συμμορφώνονται με τις υποχρεώσεις καταχώρισης που αναφέρονται στο άρθρο 49. Σε περίπτωση που οι εν λόγω φορείς εφαρμογής διαπιστώνουν ότι το σύστημα ΤΝ υψηλού κινδύνου το οποίο προτίθενται να χρησιμοποιήσουν δεν έχει καταχωριστεί στη βάση δεδομένων της ΕΕ που αναφέρεται στο άρθρο 71, δεν χρησιμοποιούν το εν λόγω σύστημα και ενημερώνουν τον πάροχο ή τον διανομέα.
Άρθρο 26 9.
Κατά περίπτωση, οι φορείς εφαρμογής συστημάτων ΤΝ υψηλού κινδύνου χρησιμοποιούν τις πληροφορίες που παρέχονται βάσει του άρθρου 13 του παρόντος κανονισμού για να συμμορφωθούν με την υποχρέωσή τους να διενεργούν εκτίμηση αντικτύπου σχετικά με την προστασία των δεδομένων βάσει του άρθρου 35 του κανονισμού (ΕΕ) 2016/679 ή του άρθρου 27 της οδηγίας (ΕΕ) 2016/680.
Άρθρο 26 10.
Με την επιφύλαξη της οδηγίας (ΕΕ) 2016/680, στο πλαίσιο έρευνας για τη στοχευμένη αναζήτηση προσώπου που είναι ύποπτο ή έχει καταδικαστεί για διάπραξη αξιόποινης πράξης, ο φορέας εφαρμογής συστήματος ΤΝ υψηλού κινδύνου για εξ αποστάσεως βιομετρική ταυτοποίηση σε ύστερο χρόνο ζητεί άδεια, εκ των προτέρων, ή χωρίς αδικαιολόγητη καθυστέρηση και το αργότερο εντός 48 ωρών, από δικαστική αρχή ή διοικητική αρχή της οποίας η απόφαση είναι δεσμευτική και υπόκειται σε δικαστικό έλεγχο, για τη χρήση του εν λόγω συστήματος, εκτός εάν αυτό χρησιμοποιείται για την αρχική ταυτοποίηση δυνητικού υπόπτου βάσει αντικειμενικών και επαληθεύσιμων γεγονότων που συνδέονται άμεσα με την αξιόποινη πράξη. Κάθε χρήση περιορίζεται σε ό,τι είναι απολύτως αναγκαίο για τη διερεύνηση συγκεκριμένων αξιόποινων πράξεων.

Εάν απορριφθεί το αίτημα άδειας που προβλέπεται στο πρώτο εδάφιο, η χρήση του συστήματος εξ αποστάσεως βιομετρικής ταυτοποίησης σε ύστερο χρόνο που συνδέεται με το εν λόγω αίτημα άδειας διακόπτεται με άμεση ισχύ και τα δεδομένα προσωπικού χαρακτήρα που συνδέονται με τη χρήση του συστήματος ΤΝ υψηλού κινδύνου για το οποίο ζητήθηκε η άδεια διαγράφονται.

Σε καμία περίπτωση το εν λόγω σύστημα ΤΝ υψηλού κινδύνου για εξ αποστάσεως βιομετρική ταυτοποίηση σε ύστερο χρόνο δεν χρησιμοποιείται για σκοπούς επιβολής του νόμου με μη στοχευμένο τρόπο, χωρίς οποιαδήποτε σύνδεση με αξιόποινη πράξη, με ποινική διαδικασία, με πραγματική και υπαρκτή ή πραγματική και προβλέψιμη απειλή αξιόποινης πράξης ή με την αναζήτηση συγκεκριμένου εξαφανισθέντος προσώπου. Διασφαλίζεται ότι καμία απόφαση που έχει δυσμενείς νομικές συνέπειες για ένα πρόσωπο δεν μπορεί να ληφθεί από τις αρχές επιβολής του νόμου αποκλειστικά με βάση τα στοιχεία εξόδου τέτοιου είδους συστημάτων εξ αποστάσεως βιομετρικής ταυτοποίησης σε ύστερο χρόνο.

Η παρούσα παράγραφος δεν θίγει το άρθρο 9 του κανονισμού (ΕΕ) 2016/679 και το άρθρο 10 της οδηγίας (ΕΕ) 2016/680 για την επεξεργασία βιομετρικών δεδομένων.

Ανεξάρτητα από τον σκοπό ή τον φορέα εφαρμογής, κάθε χρήση τέτοιου είδους συστημάτων ΤΝ υψηλού κινδύνου τεκμηριώνεται στον σχετικό αστυνομικό φάκελο και τίθεται στη διάθεση της σχετικής αρχής εποπτείας της αγοράς και της εθνικής αρχής προστασίας δεδομένων κατόπιν αιτήματος, εξαιρουμένης της αποκάλυψης ευαίσθητων επιχειρησιακών δεδομένων που σχετίζονται με την επιβολή του νόμου. Το παρόν εδάφιο δεν θίγει τις εξουσίες που ανατίθενται με την οδηγία (ΕΕ) 2016/680 στις εποπτικές αρχές.

Οι φορείς εφαρμογής υποβάλλουν ετήσιες εκθέσεις στις σχετικές αρχές εποπτείας της αγοράς και στις εθνικές αρχές προστασίας δεδομένων σχετικά με την εκ μέρους τους χρήση των συστημάτων εξ αποστάσεως βιομετρικής ταυτοποίησης σε ύστερο χρόνο, εξαιρουμένης της αποκάλυψης ευαίσθητων επιχειρησιακών δεδομένων που σχετίζονται με την επιβολή του νόμου. Οι εκθέσεις μπορούν να έχουν συγκεντρωτική μορφή, ώστε να καλύπτουν πάνω από μία περίπτωση εφαρμογής.

Τα κράτη μέλη μπορούν να θεσπίζουν, σύμφωνα με το ενωσιακό δίκαιο, πιο περιοριστικούς νόμους σχετικά με τη χρήση συστημάτων εξ αποστάσεως βιομετρικής ταυτοποίησης σε ύστερο χρόνο.
Άρθρο 26 11.
Με την επιφύλαξη του άρθρου 50 του παρόντος κανονισμού, οι φορείς εφαρμογής των συστημάτων ΤΝ υψηλού κινδύνου που αναφέρονται στο παράρτημα III και λαμβάνουν αποφάσεις ή βοηθούν στη λήψη αποφάσεων που αφορούν φυσικά πρόσωπα ενημερώνουν τα φυσικά πρόσωπα ότι υπόκεινται στη χρήση του συστήματος ΤΝ υψηλού κινδύνου. Για συστήματα ΤΝ υψηλού κινδύνου που χρησιμοποιούνται για σκοπούς επιβολής του νόμου εφαρμόζεται το άρθρο 13 της οδηγίας (ΕΕ) 2016/680.
Άρθρο 26 12.
Οι φορείς εφαρμογής συνεργάζονται με τις σχετικές αρμόδιες αρχές σε κάθε ενέργεια στην οποία προβαίνουν οι εν λόγω αρχές σε σχέση με το σύστημα ΤΝ υψηλού κινδύνου για την εφαρμογή του παρόντος κανονισμού.

1.1 Παραπομπές

1.2 Εντοπισμένες απαιτήσεις

1.3 Σχετικά πρότυπα

2. Εντοπισμένες απαιτήσεις

Απαιτήσεις

3. Σχετικά πρότυπα

Πρότυπα
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.