Free Lesson

How To Balance AI Governance With Operational Realities

45 min

Apr 3, 2026 3:00 PM

Virtual (Zoom)

In this video

What you'll learn

Governance that fits real-world delivery

How to align governance with product timelines, team capacity, technical constraints, and operational pressure.

How to design scenario-based tests for AI systems

Move beyond generic benchmarks and test for real-world failure modes, edge cases, and high-impact production systems.

Setting and calibrating evaluation thresholds for production

How to define minimum launch thresholds, operating thresholds, and escalation thresholds based on risk, business impact,

Monitoring and control after launch

How to think about post-deployment oversight, incident response, and continuous improvement.

Why this topic matters

AI governance often fails in practice because it is either too heavy or too vague. Teams need governance that works in the real world with clear testing, clear ownership, and clear standards for production. That includes how to design scenario-based tests for AI systems and setting and calibrating evaluation thresholds for production AI. The goal is simple: reduce risk, move faster, build trust.