Equipment Redundancy
Specification
Supplement business-critical equipment with both locally redundant and geographically dispersed equipment located at a reasonable minimum distance in accordance with applicable industry standards.
Threat coverage
Architectural relevance
Lifecycle
Resource provisioning
Not applicable
Not applicable
AI applications, Orchestration
Operations, Maintenance, Continuous monitoring
Archiving
Ownership / SSRM
PI
Owned by the Cloud Service Provider (CSP)
The Cloud Service Provider (CSP) is responsible for the design, development, implementation, and enforcement of the control to mitigate security, privacy, or compliance risks associated with cloud computing (processing, storage, and networking) technologies in the context of the services or products they develop and offer. The CSP is responsible and accountable for implementing the control within its own infrastructure/environment. The CSP is responsible for enabling the customer and/or upstream partner to implement/configure the control within their risk management approach. The CSP is accountable for ensuring that its providers upstream implement the control related to the service/product developed and offered by the CSP.
Model
Owned by the Model Provider (MP)
The model provider (MP) designs, develops, and implements the control as part of their services or products to mitigate security, privacy, or compliance risks associated with the Large Language Model (LLM). Model Providers are entities that develop, train, and distribute foundational and fine-tuned AI models for various applications. They create the underlying AI capabilities that other actors build upon. Model Providers are responsible for model architecture, training methodologies, performance characteristics, and documentation of capabilities and limitations. They operate at the foundation layer of the AI stack and may provide direct API access to their models. Examples: OpenAI (GPT, DALL-E, Whisper), Anthropic(Claude), Google(Gemini), Meta(Llama), as well as any customized model.
Orchestrated
Shared Model Provider-Orchestrated Service Provider (Shared MP-OSP)
The MP and OSP are jointly responsible and accountable for the design, development, implementation, and enforcement of the control to mitigate security, privacy, or compliance risks associated with Large Language Model (LLM)/GenAI technologies in the context of the services or products they develop and offer.
Application
Owned by the Application Provider (AP)
The Application Provider (AP) is responsible for the design, development, implementation, and enforcement of the control to mitigate security, privacy, or compliance risks associated with Large Language Model (LLM)/GenAI technologies in the context of the services or products they develop and offer. The AP is responsible and accountable for the implementation of the control within its own infrastructure/environment. If the control has downstream implications on the users/customers, the AP is responsible for enabling the customer and/or upstream partner in the implementation/configuration of the control within their risk management approach. The AP is accountable for carrying out the due diligence on its upstream providers (e.g MPs, Orchestrated Services) to verify that they implement the control as it relates to the service/product develop and offered by the AP. These providers build and offer end-user applications that leverage generative AI models for specific tasks such as content creation, chatbots, code generation, and enterprise automation. These applications are often delivered as software-as-a-service (SaaS) solutions. These providers focus on user interfaces, application logic, domain-specific functionality, and overall user experience rather than underlying model development. Example: OpenAI (GPTs,Assistants), Zapier, CustomGPT, Microsoft Copilot (integrated into Office products), Jasper (AI-driven content generation), Notion AI (AI-enhanced productivity tools), Adobe Firefly (AI-generated media), and AI-powered customer service solutions like Amazon Rufus, as well as any organization that develops its AI-based application internally.
Implementation guidelines
Auditing guidelines
1. Examine the process to identify business-critical equipment and any redundant equipment. 2. Examine the process to identify the applicable industry standards. 3. Evaluate if the redundant business-critical equipment is independently located at a reasonable distance. 4. Verify that data centers housing redundant equipment are located at a minimum distance from each other according to relevant industry standards (e.g., Uptime Institute, ISO 22301, NIST), confirming that this distance is sufficient to isolate them from common threats. 5. Review the implementation of redundant power systems, including uninterruptible power supplies, backup generators, and redundant power distribution units, and confirm that they support critical AI processing equipment. 6. Assess the redundancy of the networking infrastructure, verifying redundant routers, switches, load balancers, and internet connections from different providers to avoid single points of failure. 7. Verify implementation of redundant compute resources for AI workloads, including server clusters, virtualization hosts, and container platforms, confirming automated failover capabilities. 8. Examine redundant system implementation, including RAID configurations, distributed storage systems, and data replication mechanisms across geographically separated locations. 9. Review monitoring systems that detect failures in redundant components and automated alerting mechanisms that notify appropriate personnel. 10. Verify documentation of regular testing procedures for redundant systems and examine records of recent failover tests confirming redundancy functions as designed.
Standards mappings
No ISO 42001 mapping. 27001: A.8.14 (Redundancy of information processing facilities)
Addendum
There is no control in ISO 42001 that covers AICM BCR-11 topic of business-critical equipment to be reasonably at a minimum distance for redundancy. However, it is fully covered by ISO 27001: A.8.14 Redundancy of information processing facilities, where processing facility shall implement that which makes them redundant to include minimum distance of critical systems.
Article 15 (4) (accuracy, robustness, and cybersecurity)
Addendum
Independently located at a reasonable minimum distance in accordance with applicable industry standards.
No Mapping
Addendum
The entire requirement BCR-11: Establish requirements for the redundancy of business-critical equipment by ensuring that redundant assets are independently located in accordance with industry standards or cross reference related NIST publications (such as SP 800-53) that cover physical resiliency.
PS-02 PS-06 OPS-09
Addendum
N/A
AI-CAIQ questions (1)
Are business-critical equipment supplemented with both locally redundant and geographically dispersed equipment located at a reasonable minimum distance in accordance with applicable industry standards?