Key takeaways:
- An AI agent can take steps to finish a task. A basic chatbot usually answers a question and waits for the next one.
- You just give it a goal, and it uses the tools it can access to decide what to do next.
- Agents are becoming more accessible in everyday business tools, including customer support, scheduling, and research tools.
An AI agent is a software system that uses artificial intelligence to plan and decide what steps to take to get a task done.
Imagine a customer messaging a gift shop. They describe what they want, how much they can spend, and where the gift needs to go. A chatbot might answer questions about the shop’s products. An AI agent connected to the shop’s systems could check what’s in stock, help the customer choose, prepare the order, guide them through secure payment, and confirm the purchase. A staff member wouldn’t need to handle every step manually.
That’s one answer to what is an AI agent. Let’s look at how it differs from other AI tools and what it can do for a small business.
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AI agent vs. chatbot vs. assistant
These tools may all chat with human users, but they don’t always do the same job.
A chatbot answers messages. Ask a gift shop’s chatbot, “Do you deliver on weekends?” and it might give you the delivery policy. Some chatbots follow a script. Others use AI to understand natural language, or the words people use in everyday conversation. You may also hear them called conversational agents.
An AI assistant helps you do something. It could suggest gifts within your budget or write a note for the card. You usually guide the task and decide what happens next.
An AI agent works toward a result. With the right access, it could check stock, prepare an order, and guide the customer to checkout. It chooses its next step based on what it finds.
The names can occasionally overlap. Some chatbots and AI assistants can also act as agents when they’re connected to tools that let them take action. The clearest way to tell is to ask: Does it just give me an answer, or can it help complete the task?
How an AI agent works
An AI agent needs a goal and access to the available tools it will use. Here’s how the gift order example in action:
- Getting the goal: The customer wants a gift under $50 delivered by Friday.
- Working out the steps: The agent needs to find a suitable gift, check stock, and confirm delivery times.
- Using its tools: It checks the shop’s product and order systems, then helps prepare the purchase.
- Checking the result: If the gift is sold out, it finds another option or asks the customer what they’d like to do.
Many modern agents use large language models (LLMs) to understand user requests and decide to perform tasks. These are the AI models that can read and write language. The agent also needs tool use access to other apps or systems where it can find information or take action. Without those external tools, it may only be able to suggest the next step.
Note: At the end of the day, these are still tools and can make mistakes. Human discretion is still needed. You’ll want to set up your AI agents to escalate problems to human managers when needed.
If you want to see agentic AI working up close, read our article on how to manage your online presence faster and smarter with Network Solutions Agentic AI.
Types of AI agents
There are several ways to describe the types of AI agents. One common set of agent types focuses on how an agent chooses an action. These technical names can sound complicated, but the ideas are straightforward:
- Rule followers (simple reflex agents): These agents act on what is happening right now, using a set rule to choose their response. For example, an agent might flag an appointment request because the customer left the date field empty.
- Context keepers (model-based reflex agents): These agents keep track of information from earlier steps instead of looking only at the latest message. If a customer has already given their order number, an agent can use it when checking a delivery problem.
- Goal seekers (goal-based agents): These agents choose actions based on the result they’re trying to reach. If a customer wants an appointment next Tuesday, an agent might check the calendar and offer times that meet that request.
- Option weighers (utility-based agents): These agents compare choices to find the one that best fits a set of priorities. A delivery agent, for example, might consider both price and arrival time before suggesting an option.
- Learners (learning agents): These agents use feedback or experience to improve how they make decisions over time. For example, a support agent could be updated based on which suggested replies staff accept or correct.
These types describe how an agent decides what to do, not separate products you have to choose from. Some autonomous agents can carry out several permitted steps with little direction, while others pause often for a person’s input.
Real-world examples and use cases of AI agents
AI agents are easier to understand when you see the full task they handle, from a customer’s request to the next step.
Task automation means letting software handle steps a person would otherwise do. In everyday business processes, AI agents can take on repetitive tasks, such as checking order updates, and routine tasks, such as booking appointments.
These examples show what that looks like:
- Customer service: A customer asks where their order is. An agent checks the order details, finds the latest delivery status, and prepares an update. If the customer disputes a charge, it passes the issue to a person.
- Scheduling: A customer asks for a haircut next Tuesday afternoon. An agent checks the calendar, offers open times, and books the one the customer chooses.
- Research: A shop owner wants to know which questions customers asked most often this month. An agent reviews approved support records and prepares a short summary.
- Account help: A business owner asks when a domain renews. A connected agent looks up the account details and helps them find the next step.
What an agent can do depends on the systems it’s connected to, what it’s allowed to access, and whether it needs customer data for the task.
Our AI All-Access Pack includes a Research Agent that can prepare reports with sources. Its AI tools also help with account-related requests.
To learn more about using AI in your business, read our article on What is agentic commerce, and why should business owners care?
Benefits of AI agents
AI agents can help small businesses accomplish tasks that take time away from customers and other work:
- Save time on repetitive work: An agent can check an order and draft an update. That helps staff complete tasks without looking up the same details for every customer.
- Respond outside business hours: A support agent can answer common delivery questions overnight, as long as the systems it needs are available.
- Handle several requests at once: During a busy sale, an agent can check delivery options for multiple customers without making each one wait for a staff member.
- Give staff more time to solve problems: An agent can handle complex tasks, such as checking order details and support history before preparing a reply. Businesses can automate complex tasks in steps and have staff review the result when needed.
- Improve with feedback: Some AI agents can learn and adapt over time using feedback or past interactions to improve future responses. For example, a support agent might learn which return questions come up most often and offer the right steps sooner. This depends on how the agent is set up.
Challenges and limitations of AI agents
AI agents can be useful, but it helps to know where they need support:
- They can make mistakes: An agent might misunderstand a customer or use an old price. Check its information before it promises a delivery date or confirms an order.
- Some conversations need a person: An upset customer may need care and judgment that an agent can’t provide. Make human intervention easy when a situation is sensitive or unusual.
- They need clear setup: Agents work best on specific tasks with reliable information. Regular human oversight helps you catch problems and keep the information they use up to date.
- Their access needs limits: Security concerns matter when an agent can view customer details or change settings. Give it only the access it needs and require approval for important actions. That helps with maintaining control.
Remember that there are still plenty of factors to consider when using AI agents. If you want to prepare your online store toward AI use, read our guide on agentic commerce readiness.
Frequently asked questions
Agentic AI describes generative AI systems that can plan steps and take action toward a goal. An AI agent is one example.
An autonomous agent can choose and take allowed steps without a person directing every move. It should still have clear limits.
ChatGPT is an AI assistant. With certain tools and features, it can also work through some tasks like an agent.
No. A chatbot mainly answers messages, while an AI agent can use connected tools to work through a task. Some chatbots also have agent features, so the difference depends on what the tool can do.
No. Some AI tools include pre-built AI agents you can use without coding. A custom agent with special connections may need technical help.
Using AI agents calls for basic checks: review their work, limit what they can access, and approve important actions before they happen.
What’s next for AI agents?
AI agents are becoming part of tools small businesses already use. For instance, our AI tools can help your business grow faster and be more productive.
In the future, an agent might connect more of a business’s everyday work—spotting a customer question, finding the right information, and helping resolve it in one go. For now, start with one clear task, check the results, and scale from there.
