The simple explanation
An agent is not a digital person. It is an arrangement of a model, instructions, information, tools and controls. Its useful question is not ‘Is it autonomous?’ but ‘What may it do, how do we observe it, and when must a person decide?’
Picture it this way
Imagine a new assistant with a clear brief, a limited set of approved tools and a supervisor. The assistant can inspect a situation and choose a next step—but important actions still require permission.
An agent’s decision loop
A company receives an invoice, extracts its fields, sends exceptions to a person and posts approved data to finance.
- 01Receive a goal
- 02Understand available context
- 03Choose an approved tool
- 04Take one action
- 05Observe the result
- 06Continue, ask or stop
What it can do
- Choose among approved tools
- Adapt a sequence to the situation
- Summarize and transform information
- Ask for missing context
- Escalate to a person
What it cannot do
- Guarantee truth
- Know hidden business context
- Accept responsibility
- Safely use unlimited access
- Decide that oversight is unnecessary
Agent, chatbot or traditional automation?
A chatbot mainly responds in conversation. An agent may also use tools and change external state. Traditional automation follows a predefined path; an agent can choose among allowed paths using a model.
An agent is not automatically better than a workflow. If the steps and rules are stable, traditional automation is often cheaper, clearer and safer.
Control is a design choice.
People define permissions, review risky actions, resolve uncertainty, monitor outcomes and remain accountable for the system’s use.
From understanding to a useful system
Estimate the opportunity before investing, then compare deterministic automation with AI where interpretation is genuinely useful.
Now you understand the basic idea behind AI agents.
Continue when you are curious—or return to a completely different part of Aurora.
Sources and further reading
Updated 29 July 2026