Deploying AI agents is the start of the governance problem

Deployment Gap

Model deployment controls do not govern every action

MLOps, model hosting, evaluation, monitoring, and access controls are necessary for deploying AI. Agentic systems add another layer: deployed agents can call tools, modify systems, submit data, create tickets, send messages, change infrastructure, and trigger workflows.

SMERC focuses on that action layer. It evaluates whether a proposed action is recoverable enough to execute before the agent creates side effects.

Production Questions

Questions teams need after deploying AI agents

• Which tools can the deployed agent use without approval?
• Which actions need throttling, freezing, denial, or human escalation?
• How quickly can the organization recover if the action is wrong?
• What evidence proves why the action was allowed or blocked?
• Which executor is qualified for this task, data, and authority level?

First Proof Path

Start with deployment workflow shadow mode

The current SMERC pilot path starts with GitHub Actions shadow-mode scoring for AI-assisted code, deployment, and infrastructure workflows. The goal is reviewer evidence before enforcement.