A responsible AI policy is your organization's public and internal position on how you use AI and why. This template covers principles, prohibited uses, governance structure, and the CEO statement

Boards are asking for AI risk reports. This 2-page quarterly template: RAG status, key metrics, incidents, vendor risk, regulatory changes, and what you're asking the board to decide.

An AI governance committee without a charter is just a meeting. A charter defines who has authority over what, how fast decisions are made, and what the board sees. This

When the board asks 'what's our AI risk posture?' - this is the answer. Governance structure, AI system categorization, key risk metrics, and the control hierarchy. Aligned to NIST AI

35% of AI security incidents involve simple prompt manipulation. Four attack types, a 5-factor risk scoring framework, specific mitigations per risk level, and test cases to run before shipping.

Every AI-powered feature needs a security review before it ships. 20 controls across credential security, prompt injection defenses, output validation, agent privilege boundaries, data protection, and monitoring.

What can engineers send to OpenAI, Anthropic, and Azure AI APIs? What's absolutely prohibited? What are the mandatory controls? Approved providers, data rules, and a before/during/after build checklist.

Building with AI introduces attack surfaces traditional secure development practices don't cover. API key management, prompt injection defenses, agent privilege boundaries, and production logging requirements.

Regulators, auditors, and enterprise customers ask to see AI incident logs. This template covers both the initial incident log and the post-incident review - with the regulatory assessment section most

The data travels to OpenAI's servers. It may be stored and used for training. You cannot get it back. And depending on the data, you may have 72 hours to