Securing AI extends beyond immediate code patches - it demands structured governance, continuous auditability, and clear career specializations. In Part 2 of this masterclass series, InfosecTrain breaks down AI compliance frameworks, regulatory readiness, evidence collection, and tailored learning paths.

The "course titled" Practical AI Security Engineering Program helps architects build resilient AI controls.

Listen Part - 1 here: ⁠Securing AI Systems Attack Surfaces & Defenses | Part - 1⁠

📘 What You’ll Learn:

AI Security Governance: Implementing structured compliance frameworks to ensure continuous auditability across enterprise AI implementations.
Evidence Collection & Audit Readiness: Gathering verifiable technical artifacts to satisfy evolving AI regulations and internal risk thresholds.
Accountability & Responsible Use: Establishing clear ownership metrics for AI outcomes across developers, security teams, and executive stakeholders.
Role-Based Learning Pathways: Navigating specialized roadmaps designed for security engineers, system architects, auditors, and GRC leads.
Career Transition Strategies: Skills and credentials needed to transition into high-demand AI security engineering and oversight roles.

🎧 Essential listening for security engineers, auditors, GRC leads, AppSec teams, and tech leaders building structured AI defense programs.

Watch Part - 1 here: https://www.youtube.com/watch?v=iwaTgPD9h1A

Watch Part -2 here: https://www.youtube.com/watch?v=gNmBaDq1teQ