Agentic AI is AI that works towards a goal with limited supervision. You give it an outcome. It plans the steps, uses tools such as email, files or a browser, and checks the results. It adjusts until the job is done or it needs a person. A chatbot answers one message at a time.
What is agentic AI in practice, and how do you tell it apart from similar tools? This guide is for operations, marketing, sales and support leads, and for the IT person who approves new tools. It explains the term and gives you a plain test for any tool a vendor calls agentic. For the narrower question of assistants versus agents, read agents vs assistants.
What is agentic AI?
Agentic AI is an AI system that pursues a goal and takes the actions needed to reach it. IBM, as of November 2026, defines it as a system that can accomplish a specific goal “with limited supervision”. IBM adds that it “consists of AI agents”, which it describes as models that mimic human decision-making to solve problems in real time.
Stanford HAI gives a fuller description, as of November 2026. It says these systems can set or interpret goals, plan and sequence actions, and use tools such as web browsers, code or APIs. They also make decisions based on feedback and adapt over time to complete tasks.
The two descriptions add up to a loop.
- You state a goal, such as “book the meeting and confirm it by email”.
- The system plans the steps.
- It acts through tools, for example a calendar or a mailbox.
- It checks what happened.
- It adjusts, or stops and asks a person.
The word “agentic” describes this behaviour. A tool is agentic when it keeps working towards the goal across several steps after the first reply.
Agentic AI vs generative AI: what is the difference?
Generative AI creates content, and agentic AI completes tasks. IBM says generative AI “creates new content such as text, images, video, audio and software code”, as of November 2026. It also says generative AI helps create, summarise and transform information, while agentic AI helps plan, coordinate and complete multi-step tasks.
The two are not rivals. A generative model can write the email. An agentic system decides that an email is the next step, sends it through your mailbox and checks for a reply. The Australian Cyber Security Centre (ACSC) notes that “the core of agentic AI is an LLM”. In practice, that means a generative model does the writing and reasoning inside the loop.
AI agents vs agentic AI: are they the same thing?
They are closely related but not identical. In our view, an AI agent is a component, and agentic AI is the larger system and the way it works. IBM’s definition says agentic AI “consists of AI agents”, so the agents are the parts and the system is the whole.
In our experience, vendors and writers often use the two terms loosely. A vendor may call a single bot an agent and call the product agentic AI. Do not rely on the label. Use the test later in this post.
For a closer look at systems with several agents, read what is a multi-agent system.
How is agentic AI different from a chatbot or an AI assistant?
A chatbot waits for each message, while agentic AI keeps working on the goal. Stanford HAI contrasts agentic AI with a “purely reactive chatbot that only responds turn-by-turn”, as of November 2026. It says agentic AI is “oriented around ongoing task execution”.
An assistant sits in between. It often helps with one task at a time and hands the next step back to you. We cover that boundary in more detail in agents vs assistants.
This table is our own summary, not a standard from any vendor or standards body.
| Chatbot or assistant | Generative AI tool | Agentic AI | |
|---|---|---|---|
| What you give it | A question or a request | A prompt | A goal |
| What you get back | An answer | New content, such as a draft or an image | A finished task, or a request for help |
| Who decides the next step | You | You | The system, within limits you set |
| Uses your tools | Rarely | Sometimes | Yes |
| Typical example | Answering a question about opening hours | Drafting a product description | Booking a meeting and confirming it by email |
Two questions sort most tools we see. First, who decides the next step, you or the system? Second, can it act inside your tools, or does it only produce text for you to copy? If you decide each step and it only writes text, it is a chatbot, an assistant or a generative tool. It is not agentic.
Is ChatGPT agentic AI?
ChatGPT started as a generative chat tool. OpenAI has since retired ChatGPT agent. Its help centre, as of November 2026, says ChatGPT agent “is no longer available”. It points users to ChatGPT Work for longer, multi-step tasks and finished deliverables.
Articles written while it was available still describe it as current. Check the vendor’s own help page before you buy on the strength of a review. The same page advises against vague prompts, and gives “Check my email and handle everything” as an example.
Apply the two questions from the table to the version you are testing.
What should a business check before using agentic AI?
Start with small, well-defined tasks and give the system the least access it needs. The ACSC and its partner agencies published guidance for large organisations and government on 1 May 2026. Its advice is to “limit initial use to low-risk, well-defined tasks”. It also says privilege risks are a key concern and that “strict adherence to the principle of least privilege is critical”. In our view, the same basics apply to smaller teams.
In practice, that gives you a short checklist.
- Pick one repetitive internal task with a clear finish, such as turning last week’s sales spreadsheet into a summary for the team.
- Give the system only the permissions that task needs.
- Decide who reviews the work and how often.
- Keep tasks that commit money, prices or legal terms with a person.
Email needs particular care. The ACSC warns that attackers can hide instructions in phishing emails to trick an email-reading agent into downloading malware. A message from outside your business can carry text written to steer the agent. That is why an inbox task is a poor first choice, and why narrow permissions matter.
The ACSC also suggests asking whether a low-value process should exist at all. Removing it may carry less risk than handing it to an agent.
Where TobyBot fits
TobyBot is an agentic bot by Xinference. You set a goal. TobyBot plans the steps, shown as one card for each, then runs them with your tools. Every tool call and result is visible while it runs, and you can pause it.
To follow what happens between a request and a result, read what happens after you type a request. To see TobyBot on a real task, visit TobyBot or talk to us.
Questions
What is agentic AI in simple terms?
It is AI that you give a goal to, not a single question. It plans the steps, uses your tools to carry them out and checks its own results. It stops when the job is done or when it needs a person.
What is an example of agentic AI?
A simple example is a system that books a meeting. It checks the calendar, sends the invitation by email and confirms the time once the other person replies. A chatbot would only tell you how to do it.
Is agentic AI the same as AGI?
No. Agentic AI describes how a system works, which is towards a goal across several steps with limited supervision. AGI refers to a much broader idea of general human-level intelligence. An agentic system can be narrow and still be agentic.
Does agentic AI work without people?
It works with limited supervision, which still involves people. They set the goal, choose the tools it can use and review the results. The ACSC advises limiting initial use to low-risk, well-defined tasks.
Is agentic AI safe for business use?
It depends on the task and the access you grant. The ACSC calls privilege risks a key concern and says giving an agent only the access it needs is critical. Begin with a small task and narrow permissions, and keep a person on high-impact decisions.
Try TobyBot. See what teams set it to do, or book a demo and bring a goal.
