Next in Privacy Innovation: AI Agents that Make Governance Scalable
summary
Claims a privacy stack that moves teams from manual checks to continuous, agent-driven governance: weekly evidence-based scans of websites and apps via web auditor and app auditor (able to crawl 100k–300k pages and install from stores), automated data maps that merge code scanners, Datadog/New Relic APM and CLM contract scans, and agentic automation (the REN agent) that converts Jira/Confluence changes into reviews, triages risks, creates issues and runs workflows. Notable numbers: 600% jump in SEIPAs, 75% of US sites previously missing CCPA opt-outs, assessments cut from 4–6 hours to ~10–20 minutes with the cookie agent and copilot assessments.
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chapters (15)
- 0:00Privacy innovation intro
- 1:49Privacy regulation changes
- 5:03Enforcement and litigation risks
- 8:36AI adoption challenges
- 10:21Website and app compliance risks
- 12:25Data mapping weaknesses
- 14:54Future of privacy controls
- 15:57Automating data maps
- 17:22Agentic privacy governance
- 19:17Key trends and roadmap
- 21:06Privacy assessment tool
- 25:03Live data map automation
- 29:23Web and app auditing
- 37:05REN AI privacy agent
- 41:00Q&A and closing
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