Plain definitions of the terms behind AI clones, AI employees and the governance that keeps them accountable.
An AI employee is a software worker hired into a defined business role, with its own responsibilities, tools, permissions and goals. Unlike a chatbot that answers questions, an AI employee carries out ongoing work across company apps and channels, and reports on what it did and the value it produced.
Read moreAn AI clone is an AI worker built to carry the knowledge, voice and working style of a role, a team or a specific person. It acts on their behalf across apps and channels, using layered knowledge and memory so its work matches how that person or organization operates.
Read moreAI agent vs. AI employee describes two levels of AI work. An AI agent is software that plans and takes actions toward a single goal. An AI employee is hired into a whole role, owning several ongoing responsibilities, with permissions, memory and reported results.
Read moreAn AI teammate is an AI worker that joins a human team as a working member. It takes requests in the team's normal channels, such as chat, email and meetings, shares the team's context, and hands off work to people at clear points.
Read moreAgentic AI is artificial intelligence that pursues goals by planning steps, choosing tools and taking actions with limited human direction. Instead of only generating text in reply to a prompt, an agentic system reads results, adjusts its plan and keeps working until the task is complete or blocked.
Read moreA personal AI clone is an AI assistant modeled on one individual. It learns that person's priorities, contacts, tone and routines, then handles tasks on their behalf, such as email, scheduling, research and household planning, under permissions the person controls.
Read moreAn area of responsibility (AOR) is a defined part of a job that one person or AI worker owns, with a clear scope, expected outcomes and a way to measure them. Roles are usually made of three to five AORs, such as pipeline hygiene or inbox triage.
Read moreAI agent governance is the set of policies, permissions and oversight practices that control what AI agents can access and do inside an organization. It covers who approves an agent's scope, which data and actions it may use, how its work is logged and how issues are handled.
Read moreDefault-deny permissions is a security model in which a user, system or AI agent starts with no access at all. Every app, record type and action must be explicitly granted, so anything not on the allow list is blocked automatically.
Read moreAn AI audit trail is a time-stamped record of every action an AI system takes, including what it was asked, which tools and data it used, what it changed and who it contacted. It lets people review, explain and verify AI work after the fact.
Read moreHuman-in-the-loop is an approach to AI in which a person reviews, approves or corrects the system's work at defined points before it takes effect. It keeps people responsible for important decisions while the AI handles preparation, drafting and routine steps.
Read moreAI agent skills are packaged capabilities that let an AI agent perform a specific kind of work, such as updating CRM records, drafting a research report or scheduling meetings. Each skill bundles instructions, tool connections and rules so the agent can do that job consistently.
Read moreAn AI knowledge base is a structured collection of documents, policies, facts and examples that an AI system draws on to answer questions and do work accurately. It grounds the AI in an organization's own information instead of relying only on what the underlying model learned in training.
Read moreUpdated October 2026