The Standard

The AICAP Standard

The AICAP Standard defines the technical and governance requirements for responsible AI systems. It is continuously updated as global AI regulations evolve, ensuring organizations following AICAP are always aligned with current regulatory expectations.

The standard integrates guidance from major regulatory and governance frameworks worldwide.

Integrated Frameworks

EU AI Act

The European Union's comprehensive risk-based framework for AI regulation.

NIST AI RMF

The US National Institute of Standards and Technology AI Risk Management Framework.

ISO/IEC 42001

International standard for AI management systems and governance.

OECD AI Principles

Intergovernmental standards for trustworthy AI development and deployment.

Compliance Requirements

Each pillar defines specific requirements that AI systems must meet for AICAP compliance.

01

AI Governance

AI governance policies and procedures
Executive accountability structure
Risk management oversight board
Internal AI compliance controls
Governance review cadence (quarterly minimum)
Incident escalation procedures
02

Transparency & Explainability

Model decision explainability documentation
Consumer-facing AI disclosure notices
Algorithmic transparency reports
High-risk system explainability controls
Training data provenance disclosure
Automated decision notification system
03

Safety & Risk Management

AI risk assessment methodology
Adversarial and red-team testing
Safety monitoring and alerting
Incident reporting mechanisms
Model validation and testing protocols
Bias detection and mitigation procedures
04

Data Governance

Data provenance documentation
Bias monitoring and reporting
Privacy impact assessments
Dataset governance policies
Data retention and deletion policies
Cross-border data transfer controls
05

Continuous Monitoring

Automated regulatory change monitoring
Compliance drift detection
Model lifecycle tracking
Ongoing audit documentation
Real-time compliance score tracking
Periodic reassessment schedule

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