The agent evaluation gap: Enterprise AI organizations have a reality-alignment problem, not a coverage problem — and most are shipping to production anyway
AI Summary
Many enterprises are increasingly allowing AI agents greater autonomy, despite a lack of trust in the evaluation processes meant to ensure their reliability. A significant number of organizations have deployed agents that passed internal evaluations but failed in real-world applications, highlighting a disconnect between evaluation metrics and actual performance.
From the source
Across 157 enterprises, organizations are granting AI agents more autonomy while trusting the evaluations meant to gate that autonomy less. Half have already shipped an agent that passed their internal evaluations and then failed a customer in production; only one in twenty fully trusts automated evaluation today; and the most-cited weakness is that evaluations do not align with real-world outcomes. Yet two-thirds already allow, or are actively engineering toward, deploying agent changes to prod
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