Insights on AI behavioral assurance, drift detection, and compliance monitoring for regulated enterprises.
The best frontier models now hallucinate between 1% and 58% depending on the task. Billions are flowing into improving accuracy. For regulated enterprises, that investment is raising the monitoring bar, not lowering it.
The market is full of AI drift detection tools: Evidently AI, Arize, Fiddler. Nearly all track data distribution shifts. For regulated enterprises, that is the wrong measurement, and the gap has real compliance consequences.
Over half of all US states have adopted the NAIC Model Bulletin on AI - and the AI Systems Evaluation Tool is coming next. A practical breakdown of what insurers must do now, what's changing, and the monitoring gap most carriers haven't addressed.
Your AI passed every test before deployment. Six months later, the same API, the same model name - but completely different behavior. Here's everything enterprises need to know about the silent risk regulators now require you to detect.
Enterprises invest heavily in AI development and deployment - then stop. RAND Corporation and Forrester research reveals why the operate phase is the longest, most critical, and least monitored stage of the AI lifecycle.
Your observability tools show you what your AI did. Behavioral assurance tells you whether it's still doing what you approved it to do. For regulated enterprises, the difference is existential.
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