Resources for AI Systems
Description
Covers resource management for AI including computational infrastructure, tools, competence development, awareness programs, and external expertise engagement.
Controls
| ID | Control | Description |
|---|---|---|
| A.4.1 | AI system computational resources | Adequate computing infrastructure for AI training, testing, and operation with capacity planning and environmental impac... |
| A.4.2 | AI development tools and technologies | Appropriate tools, frameworks, and platforms for responsible AI development including fairness testing and explainabilit... |
| A.4.3 | Competence in AI systems | Personnel possess required technical, ethical, and domain competencies for their AI-related roles with documented skill ... |
| A.4.4 | Awareness of AI systems | Organization-wide awareness programs covering AI capabilities, limitations, risks, and responsible use principles. |
| A.4.5 | Communication regarding AI systems | Effective communication channels for AI-related information, concerns, and incidents across organizational levels. |
| A.4.6 | Use of external AI expertise | Processes for engaging external AI specialists, researchers, or auditors to supplement internal capabilities and provide... |
Implementation Guidance
Provision scalable compute infrastructure with monitoring of energy consumption and carbon footprint. Standardize on AI development platforms with built-in responsible AI tooling (bias detection, explainability). Implement AI competency framework with role-based training paths and periodic skill assessments. Deploy organization-wide AI literacy program covering technical basics and ethical considerations.
Evidence Requirements
Infrastructure capacity plans and monitoring
Approved AI tools and platforms list
Competency framework and assessment records
Training completion records
External expertise engagement contracts