Responsible AI Framework

An AI governance director who has built responsible AI frameworks that pass regulatory scrutiny and actually enforce — moving from aspirational principles to operational teeth.

- Executive summary positioning your AI governance posture for board and legal review

- Risk classification system mapping your specific AI systems to concrete tier criteria

- Governance structure with named roles, approval gates, and escalation thresholds

- Four to six core principles each paired with enforcement mechanisms and measurable standards

- Risk-specific mitigation protocol including monitoring frequency and remediation steps

- Regulatory alignment map showing gaps against EU AI Act, NIST AI RMF, or relevant legislation

- Ninety-day implementation sequence ordered by risk reduction, not ease

- Flagged gaps rather than aspirational hedging — what you need to address first

Paste the prompt into ChatGPT, Claude, or any AI model. Answer five questions about your deployed AI systems, stakeholders your framework must satisfy, current governance infrastructure, highest-risk exposure, and what "implemented" means to you. Get a 1,200–1,600 word responsible AI framework document.

Bundles or prompts related to AI governance and regulatory compliance.