Short answer
An AI agent is a system that uses a language model to decide which actions to take, then takes them through connected tools: reading a database, sending an email, updating a booking record. It runs multi-step, checks the result of each step, and retries or stops. Taking actions, not just producing replies, is the defining feature.
Also called: Agentic AI, Autonomous agent
The loop is what separates an agent from a single model call. The model receives a goal and a description of the tools available to it, chooses one, and the surrounding software executes that choice and feeds the result back. The model then decides what to do next with the new information. Nothing in that loop is magic: an agent can only do what its tools allow, so a booking agent without write access to the calendar can describe an appointment but cannot make one.
That constraint is also the main design lever. Most useful agents in a small business are narrow: one job, three or four tools, a clear stopping condition. Narrow scope makes behaviour predictable and failures cheap to catch. Where the task is fully deterministic, such as filing an attachment when a form is submitted, an agent is the wrong tool, and ordinary workflow automation costs less and breaks less often.
Common questions
What can an AI agent actually do in a small business?
Whatever its connected tools allow. Common builds read incoming enquiries and draft replies, pull order status from a database, file documents into the right folder, or check a calendar and propose a booking slot. The limits are set by tool access and permissions rather than by the model’s general ability.
Do AI agents replace staff?
In practice they absorb the repetitive middle of a job rather than the job. An agent that drafts every reply still needs someone to approve the ones involving money, exceptions or a complaint. Teams that plan for that review step get more usable automation than teams that plan for full replacement.
Where this comes up in our work
Related terms
Chatbot vs AI Agent
A chatbot responds within a conversation: a message arrives, an answer goes back, and the exchange ends there.
Large Language Model (LLM)
A large language model is a neural network trained on large volumes of text to predict likely continuations, which lets it write, summarise, classify and translate without being programmed for each task.
Workflow Automation
Workflow automation is software that runs a defined sequence of business steps without a person moving data between systems: a submitted form creates a record, notifies the right team, files the attachment and schedules a follow-up.
Human-in-the-Loop
Human-in-the-loop is a design pattern where an AI system prepares work and a person approves, edits or rejects it before it takes effect: drafted replies queued for a one-click send, extracted invoice fields shown for confirmation.
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