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For most of the last decade, running a powerful AI model meant sending your data to someone else's infrastructure and hoping that infrastructure would perform. But that arrangement is breaking down as a trust dilemma grows between model owners, data owners and infrastructure providers. Organizations across finance, healthcare, government, and defense increasingly want to run the model inside their own walls, under their own controls, without losing access to whatever made the model strong in…
<p>Across 108 enterprises, trust in automated agent evaluation rose sharply in July — and the failure rate it is supposed to predict did not move at all. The share of organizations that fully [...]
<p>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 thei [...]