AI Agentic Assessments: Eliminate Manual Work & Reduce Risk
summary
Claims that Privado AI agents can auto-populate templates by ingesting PDFs, Jira/Confluence text, contracts or pasted transcripts and extracting data elements (it maps “inet” to IP), legal bases, and vendors; demo uses Claude/OpenAI to create a PRD and shows agents filling ROPA, legitimate‑interest and CNIL PIA templates, flagging missing retention, generating issues, and producing risk modeling with impact/likelihood scores and remediation guidance; integrations (Ironclad, Slack), approver workflows and versioning are shown and the live demo completes successfully.
AI-written summary · about
chapters (14)
- 0:00AI agentic assessments intro
- 1:29Motivation for Prevado’s agentic assessments
- 3:59Agentic assessments with docs
- 6:25Skills of the assessment agent
- 8:53Demo setup
- 11:01ROPA assessment walkthrough
- 14:53Q&A on data categories
- 17:01Legitimate interest assessment
- 21:39Customizing assessments
- 24:49Privacy principles maintenance
- 25:52CNIL PIA assessment walkthrough
- 30:24Agent capabilities and risk modeling
- 31:07Q&A on risk models
- 33:56Final Q&A
related talks
43mAI Procurement Agents | The Future of Intelligent Procurement
29mLeveraging AI to Enhance DevEx & Operational Efficiency
44mPannel Discussion | Agentic Automation: Are AI Agents The Future of Digital Work
42mAI for security - friend or foe?
31mGenAI after the Hype: Transforming Organizations with GenAI-based Agents
28mAI for Everything After Code
36mBuilding Agentic AI Assistants: Lessons from productionising agents in Preclinical R&D
50mWhy use AI in insurance underwriting and claims? (PRT271)