To be responsible-AI-ready an organisation implements a high-level AI governance policy that states what the organisation wants from AI and the principles it follows, who holds which role (a Chief AI Officer, a governance board for AI, leads for risk and for compliance), how AI systems are classified and approved, and the risk thresholds that trigger escalation; an AI risk management procedure under which each AI system has its risks identified, assessed, mitigated and monitored in a structured way, with a risk assessment before deployment, impact assessments on privacy, ethics and human rights, a risk score with a mitigation plan, and monitoring that continues after deployment; and data governance and protection policies that cover the quality of data, where it came from and how it is managed over its life, how bias in datasets is found and reduced, compliance with the Personal Data Protection Law and data minimisation, and secure storage, access control and retention.
The graph holds this control, the 0 it maps to, and the evidence behind each claim, over MCP and REST.