What is an ‘AI agent,’ anyway?

“AI agent” has quickly become one of the AI buzz terms of 2025.

OpenAI released its first AI agent, known as Operator, on Jan. 23, 2025. Operator is an AI “assistant” that can go off and open its own internet browser to solve a task. For example: “Book a table for two at a romantic French bistro in San Francisco for next Saturday night.” OpenAI has a video explainer here.

What is an AI agent? How does it work? We’re here for you.

Think of an AI agent as a digital assistant. It’s kind of a supercharged chatbot. Here’s an overview of how an AI agent works.

A traditional chatbot does this…

A traditional chatbot is a computer program that uses pre-defined rules, decision trees, and scripted responses to interact with users. They’re primarily used for information retrieval, to handle basic interactions, and to answer common customer support questions.

Essentially: A traditional chatbot is like a call center staffer forced to stick to a pre-written script, never allowed to deviate or freelance.

…but An AI agent does that

An AI agent may perform similar tasks, but the agent understands language in ways that a traditional chatbot does not.

A traditional chatbot can’t handle queries outside its predefined and scripted conversational flow. They struggle with open-ended conversations.

An AI agent can understand and generate natural language, process and analyze large amounts of information, and assist with complex activities such as writing, coding, problem-solving, and creative tasks.

An AI agent isn’t merely customer-facing, as we commonly think of a customer service chatbot. AI agents may be grounded in a company’s internal business data, including structured data like spreadsheets, but also unstructured data like emails, PDFs, and text documents. An AI agent may be able to synthesize large batches of internal data and generate previously unseen patterns or offer new insights.

Because AI agents are built on large language models (LLMs) and trained on enormous datasets, they can engage in more nuanced conversations with their users and do a better job of matching the user’s intent with the task it sets about to perform.

the ai agent is learning, and remembering, as it works

Like other AI systems, AI agents are trained on massive amounts of data upon their initial release. Unlike traditional chatbots, however, AI agents continue to ingest data from each and every interaction. They refine their algorithm to improve accuracy and effectiveness, using feedback to enhance future responses.

This also means that whatever data is fed into the AI agent—in the form of a question, or an assignment, or a dataset—is retained by the AI agent. It’s not like a Google search history that can be wiped from your laptop browser. The AI agent retains all.

concerns with AI agents, ‘automated decision tools’

The increasing use of AI agents raises a number of legal, ethical, and societal concerns.

In some circumstances, deep learning models may produce unfair, biased, or inaccurate results. Applying safeguards, such as human reviews, ensures customers receive helpful and fair responses from the agents deployed. But as more and more companies replace human staff members with AI agents, decisions become further removed from actual human contact.

This can lead to critical life-or-death decisions—as in the medical or insurance fields—being made by machine.

Lawmakers in many states are now considering legislation around “automated decision tools” like AI agents, to ensure a degree of caution and fairness when these tools are used in making a “consequential life decision.”

Examples of those decisions include choices around employment, education, housing, utilities, financial services, health care, legal services, access to services, and voting.

The market-defining power of ai agents

Another concern with AI agents is their potential ability to control the flow of customers to non-tech businesses.

Luiza Jarovsky, co-founder of the AI, Tech & Privacy Academy, explains it like this:

If a large number of people start using AI agents instead of visiting the company's websites themselves, many service providers that haven't closed deals with OpenAI (and other agentic AI companies) will go bankrupt. To be a strong player in any given market, service providers will have to close deals with agentic AI companies such as OpenAI.

This will give OpenAI and others the power to set the rules, including algorithmic rules, design rules, and economic rules. It could become more expensive for consumers, as end products may get more expensive due to service providers having to pay the AI agent's fees.

For further reading on automated decision tools (ADTs) and legislation: