AI agents

Productivity agents

Agents embedded in productivity tools, email, and apps, acting for individual users. Approving the tool decided that it may be used. It did not decide what any given action it takes is allowed to do.

In short

Productivity agents run with an individual's identity and an individual's permissions, inside tools the organization already approved. The gap is not discovery and it is not access: it is that nothing evaluates the specific action before it happens. Certiv sits in the execution path on the endpoint and does exactly that.

Why approved tools still leave a gap

They act as the person, not as a service

A productivity agent runs with an individual's identity and an individual's permissions. Whatever that person can reach, it can reach, and it does so without a service account anyone reviewed.

Nobody filed a ticket

The analyst pasting customer data into a chatbot to summarize a deal, the PM wiring a copilot into systems nobody mapped. Well-intentioned people doing their jobs, creating a threat surface as a side effect.

The apps became action-takers

Enterprise applications are moving from display-only to action-taking: querying data, invoking APIs, deciding autonomously. The permission model underneath them was written for a human clicking.

Banning them costs more than it saves

These agents are attached to how work now gets done. Blanket bans push usage somewhere unobservable rather than removing it.

Govern the action, keep the productivity

The reason blanket bans fail here is that these agents are attached to how the work gets done. Removing them removes the work, so usage moves somewhere nobody can see rather than stopping.

Certiv discovers every agent, copilot, and automation running across endpoints, sanctioned or not, then evaluates each action against enterprise policy with full session context and allows, blocks, redirects, or escalates it to a human before it executes. IT governs access without blanket bans.

Straight Answers

What Teams Ask About Productivity Agents

Expand to view common questions.

What counts as a productivity agent?
Agents embedded in productivity tools, email, and apps, acting for individual users: internal copilots, assistants wired into documents and tickets, and automations built on top of enterprise applications. Certiv treats them as agents like any other: Scout observes AI agent activity regardless of which platform or framework the agent runs on, and monitors IDE copilots, browser agents, custom applications, MCP servers and multi-agent frameworks.
These are approved tools. What is the exposure?
Sanctioning the tool is not the same as governing the action. A productivity agent inherits a person's identity and permissions, then decides on its own what to read, send, or change. The approval covers whether the tool may be used; it says nothing about whether a particular action it is about to take is within policy. Certiv evaluates each action, with session context, before it executes.
Do we have to ban them to control them?
No, and that is the point. Certiv discovers every agent, copilot, and automation running across endpoints, sanctioned or not, and inventories what is in use, by whom, and what it does, so IT can govern access without blanket bans. Routine, policy-compliant work keeps running; the actions that fall outside policy are the ones that get blocked, steered, or escalated.
Is Certiv monitoring employees?
No. Scout observes AI agents and agentic activity, not everything a person does on their workstation. It does not monitor browser history, record keystrokes, or indiscriminately inspect documents. If an AI agent is not involved, Certiv is not looking. Privacy Mode goes further: routine, policy-compliant agent work stays private by default.

See Certiv on Your Own Endpoints

Deploy in minutes. See every agent, then control what happens next.

Book a Demo

Keep reading

Shadow agents

The agents nobody filed a ticket for, and why discovery alone changes nothing.

For IT teams

Rolling agents out across the fleet without losing control of it.

Pre-execution policy enforcement

The mechanism: intercept, evaluate, and enforce policy on every agent action before it runs.