AI Governance & EU AI Act: Clear Roles, Real Accountability | Module 3.1

Описание: When an AI system fails, who is truly accountable in your organization—the vendor, the data team, legal, or you as an executive? This training module helps you turn that blurred picture into a clear, practical AI ownership and governance model you can actually lead, especially under the EU AI Act.

You’ll see how boards, C‑suites, legal, data, and engineering teams each share responsibility—and where the accountability line really sits when things go wrong.

In this video, you will learn how to:
Map AI ownership across board, C‑suite, legal, risk, and product teams
Align governance, accountability, and operating models for the EU AI Act
Define who sets AI risk appetite and who answers to regulators
Clarify roles for product owners, data scientists, and MLOps engineers
Separate technical responsibility from business accountability for outcomes
Use an AI governance committee as a “central nervous system” for decisions
Reduce shadow AI and inconsistent controls across tools and processes

This module fits early in a broader corporate AI and security training path from Kryptomindz, where you progress from AI risk fundamentals to hands‑on practices in data security, DevSecOps, secure SDLC, zero‑trust architecture, and responsible AI.

For corporate training on AI Governance, Cybersecurity, DevSecOps, Cloud & Blockchain Security:
🌐 https://kryptomindz.com | ✉️ [email protected] | ☎️ +91-9873062228

If you’re an executive, risk leader, or product owner working with AI, watch through to the end to benchmark your current governance model and identify gaps.

Subscribe for more practical modules on AI security, EU AI Act readiness, and secure software development.

#AIgovernance #EUAIAct #ResponsibleAI #Cybersecurity #DevSecOps #CloudSecurity #AICompliance #RiskManagement