We Urgently Need Real-Time Monitoring of AI Agents' Actions
Opinion | By Madhulika Srikumar and Claire Leibowicz | October 29, 2026
Right now, we're effectively flying blind when deploying these tools. Here's what we need to do instead.
The Oversight Gap
As AI agents move from experimental demos to production systems that take real actions—booking, transacting, negotiating, and executing multi-step tasks on our behalf—the gap between what these systems do and what we can observe has become a critical risk. We are, in effect, flying blind.
In 2026, agentic AI has become entrenched across enterprise workflows: coding agents ship code, procurement agents place orders, and customer-facing agents resolve disputes with minimal human intervention. Yet most organizations still rely on post-hoc logs and periodic audits rather than continuous, real-time oversight. When an agent goes off-script—misusing a tool, pursuing a misaligned sub-goal, or being manipulated by an adversarial input—the damage is often done before anyone notices.
Three Pillars of Real-Time Monitoring
Closing this gap requires a deliberate monitoring architecture built around three pillars:
1. Visibility Into Agent Actions
We need instrumentation that captures every tool call, API request, and decision point as it happens—not reconstructed after the fact. Action-level telemetry, permission tracing, and the ability to replay an agent's trajectory are baseline requirements for accountability.
2. Detection of Anomalous Behavior
Visibility alone is not enough. Real-time monitoring must include behavioral baselines and anomaly detection that flag deviations—unusual tool use, escalation patterns, or attempts to bypass guardrails—while there is still time to intervene.
3. Timely Human Intervention
Monitoring without a response mechanism is surveillance theater. Organizations need clear escalation paths, kill switches, and human-in-the-loop checkpoints calibrated to the stakes of each task.
Why This Can't Wait
AI agents operate at machine speed and scale. Errors compound across steps, and a single compromised agent can propagate harm through connected systems within seconds. Traditional audit cycles measured in weeks or quarters are fundamentally mismatched to systems that make thousands of decisions per hour.
Real-time monitoring is also a governance imperative. Regulators and standards bodies increasingly expect demonstrable oversight of autonomous systems. Building observability into agent deployments now is both a safety measure and a path to compliance.
What Needs to Happen Next
- Standardize agent telemetry. Common logging formats for agent actions would let platforms, auditors, and security teams reason about behavior consistently.
- Make monitoring a first-class product feature. Developers should treat observability as core infrastructure, not an afterthought bolted on post-deployment.
- Establish intervention protocols. Define who can halt an agent, under what conditions, and with what safeguards against abuse.
- Invest in independent oversight. Third-party monitoring and red-teaming can catch what internal teams miss.
We have the technical means to watch what our agents do. What we lack is the will to deploy them with the same rigor we apply to any other high-stakes system. Until real-time monitoring becomes standard practice, every agent we deploy is a bet we cannot fully see.