# What is agentic AI?

Agentic AI is AI that acts rather than only answers: given a goal, it plans the steps, uses tools and other software to carry them out, checks the results and adjusts. It runs on the same language models as generative AI, but it does things in your systems, so how much it may do alone is the central question.

Updated 7 November 2026

## How is agentic AI different from generative AI?

Agentic AI differs from generative AI in what happens to the output. Generative AI produces something, such as a paragraph, an image or a block of code, and a person decides what to do with it. Agentic AI goes on to use it: it calls tools, changes records, sends requests and decides the next step from the result.

Google Cloud's definition puts it in one line: agentic AI "can set goals, plan, and execute tasks with minimal human intervention". It describes the cycle as perception, reasoning, planning, action and reflection. The model at the centre is the same kind of large language model; what's new is that it's connected to systems it can change.

|  | Generative AI | Agentic AI |
| --- | --- | --- |
| Input | A prompt | A goal |
| Output | Content | Completed steps, plus content along the way |
| Uses tools | Rarely | Always: search, email, calendar, databases, other software |
| Who decides the next step | The person | The model, within limits |
| Main risk | A wrong answer | A wrong action |

## How is agentic AI different from an AI agent?

An AI agent is one system; agentic AI is the wider approach. Google Cloud compares agents to "individual tools in a toolbox", with agentic AI as "the coordinated use of those tools to build an entire house". Anthropic uses "agentic systems" as the umbrella for both fixed workflows that call a model at certain steps and agents that direct their own steps. The [AI agent explainer](https://mojobase.ai/learn/what-is-an-ai-agent) covers how a single agent works.

## What are the levels of autonomy in agentic AI?

Agentic AI ranges from AI that only suggests to AI that acts entirely on its own, and the right level depends on what a mistake would cost. A useful way to think about it is five levels:

| Level | What the AI does | Who approves | Fits |
| --- | --- | --- | --- |
| 1. Answers | Replies to questions; changes nothing | Nobody needed | Research, summaries |
| 2. Drafts | Prepares the change: an email, a task, an edit | A person, every time | Customer replies, anything public |
| 3. Suggests in bulk | Prepares many changes for one review | A person, in one go | Filing, tagging, task lists |
| 4. Acts, with a log | Makes chosen kinds of change itself, each recorded and reversible | A person can undo after | Routine, reversible work |
| 5. Acts freely | Does whatever its tools allow | Nobody | Rarely sensible in a business |

The useful setting isn't one level for everything. It's a level per kind of change: a business might let AI file email on its own (level 4), suggest new tasks in bulk (level 3) and always draft, never send, customer replies (level 2).

## What patterns does agentic AI use?

Agentic systems are built from a few repeating patterns, which Anthropic describes from its work with customers:

- **Prompt chaining:** a task split into fixed steps, each feeding the next, such as an outline, then a check, then the document.
- **Routing:** sorting an input and sending it to the right handler, such as refund requests to one process and technical questions to another.
- **Parallelisation:** several model calls at once, either on separate parts of a job or on the same job for a second opinion.
- **Orchestrator and workers:** a central model that "dynamically breaks down tasks, delegates them to worker LLMs, and synthesizes their results".
- **Evaluator and optimiser:** one model writes, another checks and gives feedback, in a loop.
- **Autonomous agent:** a model using tools in a loop until it's done.

Anthropic's advice is to start with the simplest pattern that works and add autonomy only where it pays off, because agentic systems "often trade latency and cost for better task performance".

## How do you keep agentic AI safe?

You keep agentic AI safe by limiting what it can do, not by trusting what it will choose. OWASP calls the core failure "excessive agency", triggered by three things: excessive functionality, excessive permissions and excessive autonomy. Each has a matching control:

1. **Functionality:** give the AI only the tools its job needs. A system that drafts email doesn't need a delete tool.
2. **Permissions:** let it act as a specific person, seeing and changing only what that person could.
3. **Autonomy:** require approval for changes that can't be undone, such as sending, paying or deleting.
4. **Records:** log every action with who, what and why, and make it reversible where possible.
5. **Untrusted input:** treat what it reads, such as incoming email or web pages, as data, never as instructions.

## What does agentic AI mean for a small business?

For a small business, agentic AI means the routine follow-through can happen without the owner. The value isn't one clever answer; it's the dozen small jobs a day that each need reading something, deciding and acting: reply to this, chase that, file this, move that meeting. Agentic AI is most useful where it can see all of those sources at once, and least risky where the rules about what it may do are set once and enforced by the software.

## How does Mojobase handle agentic AI?

Mojobase's AI works across email, calendar, documents, tasks, customers, Numbers and the Handbook, and the limits are built in rather than left to the model. Each kind of change is set to Suggest or Auto, so filing an email might happen at once while a new task waits for you. Scheduled runs, such as the morning sweep, only ever write drafts and suggestions, which Mojobase enforces itself by offering them only those tools.

Every agent, Mojobase's own or yours through the one MCP server, acts as a person and sees only what they can. Everything any of them does is in Activity, with Undo. More on [how the AI works](https://mojobase.ai/ai).

## Further reading

1. [What is agentic AI?, Google Cloud](https://cloud.google.com/discover/what-is-agentic-ai)
2. [Building effective agents, Anthropic](https://www.anthropic.com/engineering/building-effective-agents)
3. [LLM06:2025 Excessive Agency, OWASP Gen AI Security Project](https://genai.owasp.org/llmrisk/llm062025-excessive-agency/)
4. [Agentic AI: Threats and Mitigations, OWASP Gen AI Security Project](https://genai.owasp.org/resource/agentic-ai-threats-and-mitigations/)

## Questions people ask

### What is the difference between agentic AI and generative AI?

Generative AI creates content, such as text, images or code, in answer to a prompt. Agentic AI uses that ability to take actions towards a goal: it might write the email and also find the recipient, attach the invoice and schedule the follow-up. Google Cloud calls agentic AI a subset of generative AI.

### What is the difference between agentic AI and an AI agent?

An AI agent is one system that uses a model and tools in a loop to finish a task. Agentic AI is the broader idea: software designed to act with some autonomy, which may be one agent, several working together, or a fixed workflow with AI steps.

### Is agentic AI safe?

It's as safe as the limits around it. OWASP warns of "excessive agency": an AI given more functions, permissions or autonomy than its job needs. Limit its tools, let it draft where mistakes can't be undone, and keep a log with undo.

### What are examples of agentic AI?

An assistant that goes through the morning's mail and drafts every reply; a support agent that answers order questions and hands refunds to a person; a coding assistant that edits files, runs tests and fixes failures; a research tool that searches, reads and writes a report.

### Is agentic AI just a buzzword?

Partly. Vendors use it for anything with AI in it. The useful meaning is narrow: software where a model decides which steps to take and takes them, rather than a person or fixed code deciding. Ask what a product's AI can actually do without you.

## Related

- [How the AI works](https://mojobase.ai/ai)
- [Agents](https://mojobase.ai/agents)
- [What is an AI agent?](https://mojobase.ai/learn/what-is-an-ai-agent)
- [What is an MCP server?](https://mojobase.ai/learn/what-is-an-mcp-server)
- [MCP server](https://mojobase.ai/mcp)
- [Security](https://mojobase.ai/security)
- [What is workflow automation?](https://mojobase.ai/learn/what-is-workflow-automation)

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Source: https://mojobase.ai/learn/what-is-agentic-ai · Updated 7 November 2026