AICM AtlasCSA AI Controls Matrix
BCR · Business Continuity Management and Operational Resilience
BCR-10Cloud & AI Related

Response Plan Exercise

Specification

Exercise the disaster response plan annually or upon significant changes, including, if possible, participation of local emergency authorities.

Threat coverage

Model manipulation
Data poisoning
Sensitive data disclosure
Model theft
Model/Service Failure
Insecure supply chain
Insecure apps/plugins
Denial of Service
Loss of governance

Architectural relevance

Physical infrastructure
Network
Compute
Storage
Application
Data

Lifecycle

Preparation

Data storage, Resource provisioning, Team and expertise

Development

Not applicable

Evaluation

Not applicable

Deployment

AI applications, Orchestration

Delivery

Operations, Maintenance, Continuous monitoring

Retirement

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

[All Actors]
1. Designing Effective Scenarios:
a. Develop progressive difficulty levels building team capabilities over time, include both technical complications and communication challenges.
b. Design scenarios that test decision-making under uncertainty and time pressure.

2. Building a Comprehensive Program:
a. Begin with tabletop sessions exploring response strategies without system impact.
b. Introduce unexpected complications challenging assumptions and standard approaches.

3. Hands-On Validation:
a. Conduct controlled technical testing in isolated environments which validate processes and with actual tools and systems.
b. Execute partial recovery activities focused on critical functions.

4. Full-Scale Exercises:
a. Organize comprehensive simulations involving all response team members, and incorporate surprise elements to test readiness and adaptability.
b. Conduct immediate debriefs while experiences remain fresh.
c. Focus evaluation on specific improvement opportunities rather than general observations.
d. Translate lessons into concrete procedure updates before the next incident.
e. Share non-sensitive insights that could benefit other ecosystem participants.

5. Cross-Entity Readiness
a. Participate in joint exercises exploring scenarios that cross organizational boundaries, may include local authorities to facilitate and test such exercise response.

Auditing guidelines

1. Examine the policy for planning and scheduling a disaster response exercise and involving local emergency authorities.

2. Evaluate if plans are tested upon significant changes or at least annually.

3. Verify that the exercises tested the recovery of all critical infrastructure components, including data centers, network connectivity, compute resources, and storage systems supporting AI operations.

4. Review exercise scenarios to confirm they included various disaster types relevant to infrastructure (e.g., power outages, network failures, facility damage, regional disasters) and assessed the organization's response capabilities.

5. Assess whether infrastructure failover mechanisms and redundancy capabilities were actively tested during exercises rather than just theoretically reviewed.

6. Verify that recovery time achievements were measured against defined recovery time objectives (RTOs) during exercises and documented in after-action reports.

7. Confirm that exercises included coordination with relevant external parties such as utility providers, facility management, or local emergency authorities, where appropriate and feasible.

8. Review documentation of lessons learned from exercises and verify that identified weaknesses in infrastructure recovery capabilities resulted in documented improvement plans with clear ownership and timelines.

9. Verify that additional exercises were conducted following significant infrastructure changes that could impact disaster recovery capabilities.

Standards mappings

ISO 42001No Gap
ISO 42001: A.10.2 (Allocating responsibilities)
ISO 27001: A.5.30 (ICT readiness for business continuity)
ISO 27001: A.5.5 (Contact with authorities)
Addendum

N/A

EU AI ActPartial Gap
Article 9 (2)
Article 9 (6)
Article 15 (1)
Article 17 (1) (d)
Article 93
Addendum

Exercise the disaster response plan annually or upon significant changes, including, if possible, local emergency authorities.

NIST AI 600-1Full Gap
No Mapping
Addendum

Insert a new suggested action to require that the disaster response plan be exercised at least annually (or upon significant changes) and that such exercises include coordination with local emergency services and other critical stakeholders.

BSI AIC4No Gap
C4 RE-06
C5 BCM-04
Addendum

N/A

AI-CAIQ questions (1)

BCR-10.1

Is a structured approach to evaluate the effectiveness of the disaster response plan followed at planned intervals or upon significant changes, including, if possible, participation of local emergency authorities?