What is an AI agent?
An AI agent is software that can receive information, determine what should happen next, and use approved tools or systems to perform actions toward a defined goal. For a business, that means AI can move beyond answering questions and take part in real workflows.
The word "agent" is used loosely, so it helps to look at the parts. An agent needs an input, such as an email, a document or a request. It needs rules and permissions that say what it may and may not do. And it needs tools it is allowed to use, such as your CRM, your document store or your calendar. Remove the tools and you have a chatbot. Remove the rules and you have something nobody should switch on.
What does an AI agent look like in a simple example?
Imagine a potential customer emails your company requesting a quote. An AI agent could:
- Read the email and identify the request
- Extract the project details
- Create a CRM opportunity
- Search approved information
- Draft a response
- Assign the opportunity to the right person
- Schedule a follow-up
A human can still approve the final response. The agent does the reading, copying and preparing; the person decides what goes out.
How does an AI agent work?
Most agents repeat a short loop: read the input, decide the next step, use a tool, check the result, then continue or stop. The language model supplies the understanding and the proposed step. The tools are ordinary software interfaces, and the surrounding code decides what is allowed to happen.
That split matters for control. The limits belong in permissions and code, not in the model's good behavior. A well-built agent therefore has:
- A defined input, such as one mailbox or one queue
- A short list of tools, each with the narrowest access that works
- A record of each step it took
- A stopping point where a person approves or takes over
How is an AI agent different from traditional automation?
Traditional automation, including robotic process automation, follows fixed steps and works well when inputs are tidy. It breaks when the input varies, such as an email written in someone's own words. An agent can read unstructured input and decide what it means, but it is less predictable than a fixed script. Many good designs combine the two: fixed steps for the parts that must behave the same every time, and a model for reading and drafting. For a side-by-side comparison, see AI automation vs RPA.
How is an AI agent different from a chatbot?
A chatbot is mainly designed to converse. An AI agent may communicate, analyze information, interact with software and complete multiple steps. The difference matters when a business wants AI to help perform work rather than simply answer questions.
In practice the two overlap. A well-designed agent may include a chat window. What separates them is whether the system can take controlled actions, such as creating a record or queueing a draft for approval, not whether it can hold a conversation.
What can an AI agent automate?
Common uses include:
- Email processing
- CRM updates
- Lead qualification
- Customer support
- Document processing
- Recurring reporting
- Scheduling
- Data entry
- Internal research
- Knowledge retrieval
If you want a longer list to react to, see 25 business processes you can automate with AI. Our custom AI agents page shows the kinds of agents we build and how the work is scoped.
Do AI agents replace employees?
They do not have to. A practical design is often: AI prepares, a human reviews, the system executes. This removes repetitive work while keeping employees responsible for important decisions.
It also gives you a natural place to keep control. Sending a message to a customer, changing a customer record or issuing a quote can each sit behind an approval step, so the agent speeds up the preparation without taking over the decision.
What can go wrong with an AI agent?
Agents inherit the weaknesses of language models, and add some of their own because they can act. The common failure modes are worth knowing before you start:
- Confident wrong answers. Models can state things that are false in a fluent way, so checks and review matter.
- Too much access. An agent that can reach every system can also damage every system.
- Hostile text. An email or document can contain instructions meant to steer the model. This is called prompt injection, and the safe assumption is that anything the agent reads may be adversarial.
- Silent drift. A change in the connected software or the model can alter behavior without anyone noticing, which is why logs and periodic checks help.
A structured way to think about these risks is the NIST AI Risk Management Framework, a voluntary framework for managing the risks of AI. As a small example of designing against some of them, we describe our own email assistant that only drafts replies, an internal project.
What makes an agent work well in practice?
An agent is only as useful as the scope it is given. A few design choices matter more than the choice of model:
- A narrow, clearly described job, such as "read incoming quote requests and prepare a draft", rather than "handle sales"
- Access limited to the systems and documents the job needs, and nothing more
- A defined route for exceptions, so anything the agent is unsure about goes to a person
- A record of what the agent did, so mistakes can be traced and fixed
These choices are what turn a clever demonstration into something a team can rely on day to day.
Where should a business start with AI agents?
Do not start by asking where AI can be installed. Start by asking which repetitive process consumes the most unnecessary employee time. Choose one frequent, measurable workflow, automate it carefully, measure the result, and expand from there.
Some questions help you choose the first workflow:
- How often does the task happen, and how long does it take each time?
- Are the inputs and the expected output reasonably clear?
- Can you measure the time it takes today?
- If the agent gets one wrong, who catches it, and how costly is the mistake?
Once you have a candidate, how much AI automation costs explains how to weigh the time saved against the cost of building and running it.
If your employees repeatedly copy information, process documents, respond to similar emails, update systems, prepare reports or search company information, request an AI Automation Assessment to identify the best opportunities.