Vetting AI tools
Master the AI Tool Vetting Lifecycle. Learn to define enterprise workflows, map threats (MITRE ATLAS/OWASP LLM), and evaluate vendor evidence consistently. Develop skills to measure model quality/cost and negotiate contracts for strong data protection. Finally, plan deployment, monitoring, and lifecycle controls for sustained safety and compliance.

Course Content
Master the AI Tool Vetting Lifecycle. Learn to define enterprise workflows, map threats (MITRE ATLAS/OWASP LLM), and evaluate vendor evidence consistently. Develop skills to measure model quality/cost and negotiate contracts for strong data protection. Finally, plan deployment, monitoring, and lifecycle controls for sustained safety and compliance.
Course Objectives
By the end of this course, you will be able to:
- Define an AI tool vetting workflow that fits your enterprise process. Why it matters: a clear path shortens MTTA for risk decisions and reduces rework across security, legal, and engineering.
- Map threats and failure modes using MITRE ATLAS and the OWASP Top 10 for LLMs. Why it matters: you will prevent common prompt, data, and supply chain failures and cut MTTR when incidents occur.\
- Evaluate vendor security, privacy, and compliance evidence with a consistent rubric. Why it matters: you will enforce policy and audit requirements and avoid gaps in DPAs and data handling.
- Measure model quality, latency, safety, and cost with repeatable tests. Why it matters: you will make data driven buy or build decisions and keep accuracy and spend within budget.
- Negotiate contracts, DPAs, and acceptable use terms for AI tools. Why it matters: strong terms protect sensitive data and limit downstream liabilities from model misuse or drift.
- Plan deployment, monitoring, and lifecycle controls for sustained safety and compliance. Why it matters: continuous controls keep AI tools accurate, abuse resistant, and auditable over time.














