EPISODE · Apr 1, 2026 · 52 MIN
AI Risk Management for Leaders | Governance, Trust & Accountability in 2026
from InfosecTrain · host InfosecTrain
AI doesn’t fail silently when it fails; it impacts trust, compliance, and your entire business reputation. As AI adoption reaches a fever pitch in 2026, the risk landscape has shifted from technical "bugs" to systemic organizational liabilities. In this episode, InfosecTrain provides a high-level briefing for executives, CISOs, and decision-makers on how to move from reactive troubleshooting to proactive, AI-first risk management.📘 What You’ll Learn:Why Traditional Risk Methods Fail: Understanding the unique, non-linear nature of AI risks compared to legacy IT systems.The AI Risk Lifecycle: How to structure a governance approach that tracks risks from data ingestion to post-deployment model drift.Proven Frameworks: A leadership guide to implementing the NIST AI RMF and ISO 42001 for consistent, measurable results.The Accountability Gap: How to connect AI risk directly to business accountability, legal compliance, and stakeholder trust.Operational vs. Ethical Risk: Balancing the drive for efficiency with the necessity of ethical, unbiased AI output.🎧 Essential listening for GRC leaders and AI program owners looking to secure their organization’s digital future.Watch the full episode on YouTube: https://www.youtube.com/watch?v=TrJMzDq5_yQ
What this episode covers
AI doesn’t fail silently when it fails; it impacts trust, compliance, and your entire business reputation. As AI adoption reaches a fever pitch in 2026, the risk landscape has shifted from technical "bugs" to systemic organizational liabilities. In this episode, InfosecTrain provides a high-level briefing for executives, CISOs, and decision-makers on how to move from reactive troubleshooting to proactive, AI-first risk management.📘 What You’ll Learn:Why Traditional Risk Methods Fail: Understanding the unique, non-linear nature of AI risks compared to legacy IT systems.The AI Risk Lifecycle: How to structure a governance approach that tracks risks from data ingestion to post-deployment model drift.Proven Frameworks: A leadership guide to implementing the NIST AI RMF and ISO 42001 for consistent, measurable results.The Accountability Gap: How to connect AI risk directly to business accountability, legal compliance, and stakeholder trust.Operational vs. Ethical Risk: Balancing the drive for efficiency with the necessity of ethical, unbiased AI output.🎧 Essential listening for GRC leaders and AI program owners looking to secure their organization’s digital future.Watch the full episode on YouTube: https://www.youtube.com/watch?v=TrJMzDq5_yQ
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AI Risk Management for Leaders | Governance, Trust & Accountability in 2026
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