Managing AI Agents in AI Governance

Overview

An AI Agent in AI Governance is an inventory object used to represent a runtime orchestration component that performs tasks using models, data, tools, or workflow logic.

AI Agents are commonly found in agentic and compound AI architectures, including:

  • Conversational assistants that retrieve information or call tools

  • Automation agents that execute multi‑step workflows

  • Orchestration layers coordinating multiple models or agents

  • Analytical or monitoring agents operating semi‑autonomously

The AI Agent inventory object helps organizations understand, document, and govern agent behavior as it operates in production environments, while keeping clear separation between business intent, operational systems, and technical components.

Technical Enablement Video

When should I use the AI Agent object?

Use the AI Agent object when you need to represent:

  • A runtime component that orchestrates tasks, rather than producing a single static output

  • An AI capability with instructions, autonomy, memory, or tool access

  • Agentic workflows involving planning, reasoning, or coordination

  • AI artifacts discovered automatically through supported cloud or platform integrations

You may not need an AI Agent if:

  • The AI capability consists of a single predictive or generative model with no orchestration layer

  • The system behaves like a traditional ML service without task execution or tool calling

AI Agents in AI Governance Inventories

AI Governance distinguishes between business context, operational capability, and technical components. In the recommended baseline model:

Project

business initiative or use case

AI System

deployed AI‑enabled application or capability

AI Agent, Model, Dataset

technical runtime components

AI Agents are generally treated as technical components, even though some customer architectures may be agent‑first.

Important:

The platform does not enforce a strict hierarchy. AI Agents can exist independently, but are often easier to govern when linked to an AI System or Project.

Creating AI Agents

Automation-first inventory creation (recommend)

The recommended method for creating AI Agent inventory records is through AI Automations. AI Automations automatically scan supported cloud environments, APIs, pipelines, and applications to detect deployed AI agents, models, and datasets. When an agent is discovered, OneTrust automatically creates or updates the corresponding AI Agent inventory record.

Automation‑discovered agent records may include:

  • Agent identifiers and aliases

  • Hosting provider and deployment region

  • Model bindings and data sources

  • Operational status and lifecycle metadata

  • Source system and automation provenance

This approach helps organizations:

  • Maintain a continuously up‑to‑date AI Agent inventory

  • Reduce reliance on manual self‑reporting

  • Improve auditability and traceability

  • Support scalable governance across environments

Note:

AI Automations are deployed using a lightweight worker node, designed for simplified setup and minimal operational overhead. For setup instructions, see AI Automation Feature Guide

Manual creation (optional)

Manual creation is supported, but should be considered secondary to automation‑based discovery. You may choose to create an AI Agent manually when:

  • Documenting an agent before deployment

  • Modeling a planned or conceptual architecture

  • Adding context not available from automated discovery

  1. On the AI Governance menu, select Inventory > AI agents. The AI agents screen appears.

  2. Click the Add agent button. The Create new modal appears.

  3. Provide a unique name and choose the appropriate organization level. The Organization field will default to the current level.

  4. Click Show More Details to enter additional details and context for the agent using the provided system attribute, including:

    • Agent type and autonomy level

    • Instructions, tools, and resources

    • Intended audience or operational status

    Note:

    To learn how to add custom attributes so they appear in this modal as available fields, see Managing Attributes for AI Governance.

  5. (Optional) Link the agent to related inventory records (AI Systems, Models, Datasets, Assets).

  6. Click the Save button. The Inventory details screen appears. The new project will also be added to the Agents list screen.

  7. The inventory will be created using the assigned default workflow. To change the default option, see Creating & Managing AI Governance Workflows.

Automation vs Manual creation

Aspect

AI Automations (Recommended)

Manual Creation

Primary use

Discover deployed agents in real environments

Model planned or conceptual agents

Data freshness

Continuous, sync-based updates

Sync unless manually updated

Scale

Designed for multi-environment enterprise use

Best for limited or early-stage use

Provenance

Includes source system and automation metadata

User-entered

Effort

Low, ongoing effort after setup

Higher manual effort over time

Governance role

System of record for technical artifacts

Supplementary

To manage AI Agent inventory details & workflows

  1. On the AI Governance menu, select Inventory > AI agents.

    The AI agents screen appears.

  2. Click on the name of an agent.

    The Inventory Details screen appears with the Details tab open by default.

  3. In the Details tab, update the agent's details or actions as necessary. This may include:

    • Add or modify relationships to Models, Datasets, Assets, or AI Systems

    • Advance or revert workflow stages

    • Track updates over time for audit and oversight purposes

    Tip:

    AI Agent records are often updated more frequently than business‑context records, reflecting the iterative nature of agent development and deployment.

  4. Click the Save button to retain your changes.

To delete an AI Agent inventory

  1. On the AI Governance menu, select Inventory > AI agents.

    The Agents screen appears.

  2. Hover over the row of an agent record to reveal and click the Context Menu icon.
  3. Select Delete.

    The Delete Record modal appears.

  4. Click the Confirm button. The agent will be removed.
    Important:

    Deleting an inventory record does not affect the underlying agent or platform.

FAQ

What is the difference between an AI Agent and an AI System?

An AI System represents the operational AI capability or application delivered to users or downstream systems. An AI Agent represents a runtime component that performs tasks within that system.

In simple terms:

  • AI System = what the business deploys

  • AI Agent = how work gets done at runtime

Can an AI Agent exist without an AI System?

Yes. The current product supports AI Agents as standalone records. However, for most customer implementations, it is clearer to treat agents as components of an AI System, unless the architecture is explicitly agent‑first.

Should every AI System have an AI Agent?

No. Many AI Systems, especially traditional predictive or rules‑based systems, do not require an agent layer. Only create AI Agent records when there is meaningful orchestration, autonomy, or tool‑enabled behavior to govern.

Where should assessments attach for agentic AI?

Assessments can attach to multiple inventory types.

Projects

assess the use case or initiative

AI Systems

assess the deployed capability

Models or AI Agents

assess technical or behavioral risk

What policies evaluate for AI Agents?

Today, policies can evaluate attributes and metadata on AI Agent records, including seeded and custom fields populated manually or through automation. Policy support for richer runtime or evaluation‑driven signals is expected to expand over time.