Building Resilient AI: A Framework for Enterprise Security
summary
Claims a concrete framework with four core pillars (governance, technical safeguards, compliance alignment, continuous monitoring), describes implemented components: real-time anomaly detection with seamless data ingestion, pattern analysis, automated high-priority alerts, and coordinated remediation, plus automated compliance reports and regulatory mapping to GDPR/CCPA. Describes identity controls (MFA, granular RBAC), drift detection and explainability hooks, and says these pieces are engineered to speed deployment, reduce incidents, and produce audit trails used for stakeholder confidence.
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chapters (12)
- 0:00Introduction and Speaker Background
- 0:48AI Transformation Challenge
- 1:15AI Security Risks
- 2:54Framework Foundation for AI Governance
- 5:05Fortifying AI Excellence
- 6:08Real-Time Anomaly Detection
- 7:11Automated Compliance Workflows
- 7:57Monitoring and Explainability Tools
- 8:33Building Stakeholder Trust
- 9:31Benefits of AI Governance Framework
- 11:32Future-Proofing AI Innovation
- 12:08Conclusion
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