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The article addresses the critical shift in AI governance from static policy design to dynamic runtime monitoring as autonomous agents operate continuously across heterogeneous enterprise environments. It highlights the technical challenge of reconciling high-speed agent adoption with necessary data controls, specifically focusing on visibility into hidden actions like external internet calls or private email transmissions within agentic workflows. This discussion is central to the practical deployment and safety management of AI systems in production settings.
AI governance shifts to runtime as always-on agents spread
As enterprises move from debating artificial intelligence adoption to deploying it, AI governance has become the harder question. Autonomous agents now run around the clock across a sprawl of platforms, and controls built for deterministic software were never designed for them. At Dell Technologies Inc.’s “AI Leadership Symposium,” cost and control were recurring themes in enterprise […] The post AI governance shifts to runtime as always-on agents spread appeared first on SiliconANGLE.
As enterprises move from debating artificial intelligence adoption to deploying it, AI governance has become the harder question. Autonomous agents now run around the clock across a sprawl of platforms, and controls built for deterministic software were never designed for them. At Dell Technologies Inc.’s “AI Leadership Symposium,” cost and control were recurring themes in enterprise AI discussions. The…
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