AI Governance
Risk, compliance, observability, and control patterns for enterprise AI systems.
When dozens of agents operate under those conditions, you get agent sprawl. And with it, security exposure, compliance liability, and AI spending that grows without producing board-level ROI.
Agent adoption is accelerating across the enterprise, but governance hasn't kept pace. When adoption moves faster than oversight, the result is cost overruns, security incidents, and compliance failures, especially in high-volume or high-risk enterprise workflows.
This article breaks down where AI hallucinations come from, how they surface in enterprise workflows, and a four-layer defense architecture you can use to contain them.
Learn the key differences between deterministic vs. probabilistic AI and why enterprise leaders need both to build compliant, scalable AI workflows.
AI agents fail multi-step tasks ~70% of the time without oversight. When to add human checkpoints, how to design escalation, and what the EU AI Act requires.