Real risks live at runtime: Why CISOs must care about deep telemetry in 2026

Cloud environments are becoming increasingly dynamic and are heavily influenced by AI, creating a gap between what security tools detect and what security teams can address, thus challenging Chief Information Security Officers (CISOs) with new operational risks. The widespread deployment of agentic AI and large language models (LLMs) generates additional noise and distractions, making deep runtime telemetry a critical priority to detect relevant threats. Existing security tools often miss new risk factors associated with AI, such as agent entitlements, decision-making, and communication, as well as model risks and protocol-related vulnerabilities. To effectively manage these risks, CISOs must focus on runtime insights that provide visibility into what is being executed and running in production, which is essential for ensuring observability, traceability, and explainability of AI systems. As enterprises generate value during runtime, prioritizing runtime telemetry helps filter the noise, sharpen priorities, and facilitate actionable security measures, making it indispensable for modern security architecture in AI and cloud-powered enterprises.

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