Behavioral Telemetry

Behavioral telemetry refers to the collection and analysis of user interaction data, including how people use AI systems, what features they engage with, and patterns in their decision-making within applications. For AI governance, this data is critical for detecting model drift, identifying bias in real-world usage, and understanding whether AI systems are being deployed as intended. Organizations use behavioral telemetry to audit algorithmic fairness, track unintended consequences of AI decisions, and ensure compliance with regulations requiring transparent documentation of system performance across different user populations.

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ResearchGlobal2026-09-19

Mandiant: AI Agents Create Attack Surface That Identity and Telemetry Controls Cannot Yet See

Mandiant issued a warning that AI agents expand enterprise attack surfaces in ways that conventional identity and monitoring controls are not equipped to detect. The firm called for adaptive identity governance, continuous behavioral telemetry, and faster automated response pipelines. Compliance teams are advised to connect agent prompt streams, endpoint signals, and API activity into existing SIEM and EDR workflows.

Mandiant agentic AI identity management SIEM behavioral telemetry incident response attack surface