Interoperability and Portability Policy and Procedures
Specification
Establish, document, approve, communicate, apply, evaluate and maintain policies and procedures for interoperability and portability including requirements for: a. Communications between application interfaces b. Information processing interoperability c. Application development portability d. Information/Data exchange, usage, portability, integrity, and persistence Review and update the policies and procedures at least annually or upon significant changes.
Threat coverage
Architectural relevance
Lifecycle
Data collection, Data curation, Data storage
Design, Training
Validation/Red Teaming
Orchestration, AI Services supply chain, AI applications
Maintenance, Continuous monitoring, Continuous improvement
Not applicable
Ownership / SSRM
PI
Shared Cloud Service Provider-Model Provider (Shared CSP-MP)
The CSP and MP 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.
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 Orchestrated Service Provider-Application Provider (Shared OSP-AP)
The OSP and AP 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. Verify the existence of documented policies and procedures addressing interoperability and portability ensuring it contains communications between application interfaces, information processing interoperability, application development portability. 2. Confirm that the policies and procedures have received appropriate approval from relevant authority within the CSP's organization. 3. Examine evidence of a regular review and update cycle, ensuring the policies and procedures are evaluated and updated. 4. Verify the Application Provider’s due diligence process for ensuring that upstream providers implement controls related to interoperability and portability. 5. Verify that the policies are effectively communicated to relevant stakeholders, including internal personnel and any external partners or customers impacted by these controls. 6. Verify that the review and update of the interoperability and portability policies and procedures occur at least annually, and that evidence of review (e.g., change logs, approvals) is retained.
Standards mappings
42001: B.8.2
Addendum
N/A
Article 11 (1) Annex IV (1) (b) Article 50 (2) Article 53 (1) (b) Annex XI (2) (3)
Addendum
Create policies or procedures for interoperability and portability.
No Mapping
Addendum
The NIST AI 600-1 framework does not establish requirements in the domain of interoperability and portability.
C4 PC-02 C5 PI-01
Addendum
N/A
AI-CAIQ questions (2)
Are interoperability and portability policies and procedures established, documented, approved, communicated, evaluated, and maintained, including requirements for: a. Communications between application interfaces b. Information processing interoperability c. Application development portability d. Information/Data exchange, usage, portability, integrity, and persistence?
Are interoperability and portability policies and procedures reviewed and updated at least annually or upon significant changes?