AI Agents Inventory and Attributes - Classification attributes for the AI Agents Inventory
AI Agents Inventory and Attributes
Chapter 11. Classification attributes for the AI Agents Inventory
Executive Summary: Chapter Overview
IF4ITThe Bottom Line
Core Concepts
| Concept | Definition & Strategic Role |
|---|---|
| Agent Type | The primary purpose/function class of the agent — the cut most people mean by “type.” |
| Autonomy Level | How much independent action the agent may take, from advisory to fully autonomous — an enforced attribute, not just a label. |
| Orthogonal dimensions | Interaction mode, served audience, and build source cut across type and each shift the governance profile. |
Quick Q&A
Question: Why classify agents on several axes instead of one type?
Read More Below
Classification attributes categorize each agent along the orthogonal dimensions that determine its governance profile.
| Attribute Name | Maturity | Description and Notes |
|---|---|---|
| Agent Type | Crawl | Description — The primary purpose/function class of the agent. Benefit(s) — Drives baseline expectations for risk, oversight, and the controls a class of agent typically needs. Source — Manual. Examples — Personal Productivity; Work/Process Automation; Stakeholder Interaction; System/Operations; Data/Analytics; Developer/Engineering; Decision Support/Advisory; Orchestration/Supervisory Notes — A suggested baseline set; extend as the enterprise’s agent estate grows. |
| Autonomy Level | Crawl | Description — The degree of independent action the agent is permitted, on a graded scale from advisory through human-approved and supervised to fully autonomous. Benefit(s) — Sets the level of control an agent requires and is enforced through release workflows and runtime boundaries, not left implicit. Source — Manual. Examples — Advisory; Human-Approved Actions; Supervised Autonomy; Full Autonomy Notes — See the Autonomy and Behavioral Controls category for enforcement attributes. |
| Interaction Mode | Crawl | Description — How the agent interacts: with people, with systems, or in the background on events. Benefit(s) — Distinguishes human-facing agents (higher communication-liability surface) from machine-facing and event-driven ones. Source — Manual. Examples — Human-Facing; System-Facing; Background / Event-Driven |
Served Audience [Multi-Value] | Crawl | Description — Whom the agent serves — internal stakeholders (employees, consultants) and/or external ones (prospects, customers, partners, vendors). Benefit(s) — External-facing agents carry the highest liability and regulatory exposure; this flag routes them to stricter controls. Source — Manual. Examples — Internal — Employees; External — Customers Notes — Orthogonal to Agent Type; a Stakeholder Interaction agent may serve either audience. |
| Build / Source | Crawl | Description — Whether the agent was built internally, provided by a vendor, or assembled from both. Benefit(s) — Encodes where accountability sits — a fully internal build places liability with the enterprise; a vendor-provided one may share or shift it. Source — Manual. Examples — Internally Built; Vendor-Provided; Hybrid Notes — The builder relationship resolves to “Self” for internally built agents (see Vendor and Supplier). |
How to cite this page
When referencing this page in academic work, internal standards, or external publications, include the page title, IF4IT as author and publisher (The International Foundation for Information Technology (IF4IT), LLC), the URL, and your access date.
Example (informal web citation):
The International Foundation for Information Technology (IF4IT), LLC. Classification attributes for the AI Agents Inventory | AI Agents Inventory and Attributes. https://if4it.org/best-practices/ai-agents-inventory-and-attributes/classification-attributes-for-the-ai-agents-inventory/ (accessed 2026-07-23).
See About Us for content governance and site-wide citation guidance.
Copyright for The International Foundation for Information Technology (IF4IT), LLC: 2008 - Present
Legal Disclaimers