Agentic AI in Action: From Framework to Deployment
summary
Panel lays out concrete governance steps: adopt the Model Governance Framework for Agentic AI, classify deployments as internal/external and assist/autonomous, and apply threshold-based human oversight (example: human checks above $1,000 or periodic audits every 100 records). Contracts use disclaimers and damage caps; vendors claim ownership of vectors when they convert customer data so unpack de-identification vs anonymization. Examples include super‑RPA, supply‑chain agents, and tiered car chatbots where high‑risk queries bypass LLMs.
AI-written summary · about
chapters (6)
- 0:00Introduction and panel setup
- 1:54Defining AI governance
- 8:28Legal risks in AI deployment
- 13:06Service delivery models and risks
- 20:50Governance for agentic systems
- 26:22Q&A on privacy and oversight
related talks
30mAgentic AI in Practice – Between Potential, Governance and Digital Sovereignty
33mUnlocking Agentic AI: [...]
08mWhy AI Governance Matters More Than Ever
24mAI Governance for developers: A practical framework for deploying autonomous coding agents safely…
29mBuilding Trust in AI Agents
44mPannel Discussion | Agentic Automation: Are AI Agents The Future of Digital Work
20mImplementing Agentic AI Systems That Redefine Industries
39mBuilding a Responsible AI Governance Program