AI Explained Simply
What Is an AI Agent and How Is It Different From a Chatbot?
Chatbots can answer questions. AI agents can go further — they can reason, plan and take actions to help achieve a goal.
In simple terms:
A chatbot mainly talks with you, while an AI agent can potentially do things for you.
First, what is a chatbot?
A chatbot is software designed to have a conversation with a person.
Traditional chatbots often follow predefined rules or scripts. They might answer common questions such as:
- What are your opening hours?
- How can I reset my password?
- Where is my order?
- How do I contact support?
Modern AI-powered chatbots can be much more flexible. They can understand natural language, explain information and respond to more complex questions.
So what is an AI agent?
An AI agent is a system designed to work towards a goal and take a series of actions to help achieve that goal.
Instead of simply answering one question, an agent may be able to:
- Understand what you are trying to achieve
- Break the goal into smaller tasks
- Decide what to do next
- Use tools and information
- Perform actions
- Review the result
- Continue until the task is complete
Chatbot:
“Here are some hotels you could consider.”
AI Agent:
“I found suitable hotels based on your requirements, compared the options and prepared a shortlist for you.”
“Here are some hotels you could consider.”
AI Agent:
“I found suitable hotels based on your requirements, compared the options and prepared a shortlist for you.”
Chatbot vs AI Agent
| Chatbot | AI Agent |
|---|---|
| Primarily responds to questions | Works towards a goal |
| Usually waits for the next instruction | Can determine the next step |
| Mainly conversational | Conversational and action-oriented |
| Often provides information | Can potentially use tools and perform tasks |
| Typically handles one interaction at a time | Can potentially complete multi-step workflows |
A simple workplace example
Imagine you need to organise a meeting with several colleagues.
You might ask a chatbot:
“Write an email inviting the project team to a meeting next week.”
The chatbot produces the email, but you still need to organise everything yourself.
An AI agent connected to the right systems could potentially:
1. Check calendars
Find suitable availability.
2. Find a time
Identify a suitable meeting slot.
3. Create the meeting
Prepare the calendar invitation.
4. Prepare an agenda
Draft relevant discussion points.
The important difference is that the agent is not simply generating text. It is helping complete a workflow.
How can an AI agent take actions?
An agent becomes particularly useful when it is securely connected to tools, applications or data.
Depending on the permissions it has been given, an agent might interact with:
- Calendars
- Documents
- CRM systems
- Databases
- Business applications
- Customer support systems
- Workflow automation tools
This means AI can potentially move from simply providing an answer to helping complete the work.
Where could businesses use AI agents?
🎧 Customer Service
Research customer issues, find information and help resolve requests.
📈 Sales
Research leads, prepare information and support follow-up activities.
👥 HR
Answer employee questions and help with repetitive HR processes.
⚙️ Operations
Monitor workflows, identify issues and coordinate routine activities.
📊 Project Delivery
Collect updates, identify risks and prepare progress summaries.
💡 Knowledge Management
Search organisational information and help employees find answers.
Does an AI agent work completely by itself?
Not necessarily — and in many business situations, it should not.
Organisations can design agents so that important actions require human approval.
For example, an agent could:
Research → Analyse → Recommend → Ask for approval → Take action
This approach is often called human-in-the-loop.
It allows organisations to gain the productivity benefits of AI while maintaining appropriate human oversight.
More autonomy also means more responsibility
If an AI system can take actions, organisations need appropriate permissions, security, monitoring, governance and human oversight. The more important the decision or action, the more important these controls become.
What is an agentic workflow?
You may also hear the term agentic AI or agentic workflow.
This generally refers to AI systems that can work through multiple steps rather than simply responding once to a prompt.
Goal → Understand → Plan → Act → Check → Adjust → Complete
The exact capabilities vary significantly between different AI products, but the underlying idea is that AI becomes more capable of helping complete an outcome rather than simply generating content.
Will AI agents replace people?
A more useful way to think about AI agents is that they can take on parts of a workflow — particularly repetitive, information-heavy or administrative tasks.
People remain particularly important for:
- Judgement
- Leadership
- Empathy
- Accountability
- Complex decision-making
- Creativity and context
- Managing exceptions
The opportunity is therefore often not simply replacing work, but redesigning how people and AI work together.
From answering questions to getting work done
Chatbots introduced many people to conversational AI. AI agents represent the next step: systems that can potentially reason across tasks, use tools and help complete real business workflows.
The best place to start is not by asking, “Where can we build an AI agent?” but rather, “Which repetitive business problems could AI help us solve?”
Great article, thanks for sharing