Three AI governance questions every executive needs to answer

As AI agents become more autonomous, widely adopted, and connected to sensitive corporate data and credentials, executives must balance their potential business value against growing security and governance risks. The article argues that leaders should be able to answer three evidence-based questions: whether AI agents are behaving within policy, what AI systems are in use and who is accountable for them, and what verifiable record exists of their actions and approvals. It presents runtime observability as the basis for answering these questions, combining kernel-level data on processes, files, and network connections with agent-level semantic context such as prompts, tool calls, and session activity. According to the author, this correlation can provide a more complete view of agent behavior and support rapid responses to anomalous or malicious activity across endpoints, cloud environments, and third-party platforms.

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