What is an AI agent, and how does it work?

What is an AI agent, in plain English?

Picture an assistant you don't give step-by-step instructions to, just an outcome: "reconcile yesterday's payments" or "answer this request according to our current policy." The agent works out what's being asked, checks the information it has, decides what to do first and keeps going until it's finished or hits something that needs a person.

Under the hood there's usually a large language model, the same kind of technology behind conversational assistants, but connected to tools and company data. That connection is what makes it an agent: without tools, a model can only write; with tools, it can act.

How do AI agents work?

An agent works in a loop: it looks at the situation, decides the next action, runs it with a tool, checks the result and decides again. To make that loop useful and safe in a business, it's built from five parts:

• Goal: what it needs to achieve and what counts as done.
• Tools: the actions it can take, such as looking up a record in the CRM, reading a PDF, creating an entry in the ERP or drafting an email.
• Memory and context: what it knows about the task in progress, plus the company knowledge it needs, like policies, catalogs or history.
• Permissions: which systems and data it can access, always least-privilege, with time and cost limits per task.
• Human approval: the checkpoints where it stops and waits for a person, for example before moving money, contacting a customer or changing important data.

What are the types of AI agents, with examples?

A practical way to classify agents is by how much autonomy they have. An assistive agent prepares the work and a person reviews all of it; a human-in-the-loop agent handles routine steps and pauses on sensitive ones; an autonomous agent completes low-risk tasks within defined rules. There are also multi-agent systems, where several specialized agents split up a process. Some examples by department:

• Finance: matches bank statements against invoices in the ERP and proposes the reconciliation for someone to approve.
• Customer service: understands requests by email, chat or WhatsApp, checks the order and replies based on current policy.
• Sales: qualifies leads, updates the CRM and drafts quotes.
• Logistics: flags delayed shipments and coordinates rescheduling with the customer.
• HR: answers employee questions by citing the handbook.
• IT: triages tickets and suggests fixes from the knowledge base.

AI agent vs. chatbot: what's the difference?

A chatbot talks: it answers questions from a script or from the information it was given. An agent works: on top of understanding the message, it checks systems, makes decisions within rules and takes action to finish the task.

That's why you measure them differently. A chatbot is measured by conversations handled; an agent, by workflows completed. In practice, many modern chatbots already include agent capabilities, like checking order status or booking an appointment.

AI agent vs. RPA: what's the difference?

RPA (robotic process automation) repeats fixed steps across screens and systems: click here, copy there, paste somewhere else. It's great when inputs always look the same, but it breaks when a document's format or an email's wording changes.

An AI agent understands the content even when it arrives in a different shape every time, and decides the next step based on the situation. They aren't mutually exclusive: a common pattern is an agent deciding what to do while an automation or RPA bot handles the repetitive steps.

How do you get started with AI agents?

Pick a workflow that's high-volume, rule-based and currently depends on copying and pasting between tools. Measure how long it takes and how many errors it produces today, decide what the agent can do on its own and what a person must approve, and test it on real data in a tightly scoped pilot before you scale.

Rival Tech designs AI agents for real operational workflows, deployed in your own cloud with human approval on sensitive actions. We're a nearshore team in Bogotá, Colombia, working US Eastern and Central hours, in English. We start with a free demo on a use case similar to yours. Email us at tech@soyrival.com.

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