You have a task you would like AI to help with. Should it follow the same steps every time, or work out what to do as it goes? That is a useful way to think about workflows and agents.
A workflow follows a path someone has set out. An agent can choose some of its next steps while working towards a goal.
What is an AI workflow?
An AI workflow is a sequence that people have already designed. A form arrives, information is extracted, a model classifies it, a template is filled in and a person approves the result. The system may use an AI model at one or more steps, but the route is predictable.
That is often a strength. A fixed process is easier to test, explain, measure and secure. It works well when the task is repetitive and the acceptable path is known in advance.
What makes something an AI agent?
An AI agent is given a goal and a defined set of tools or information. It can inspect what it finds, decide which permitted action is useful next and repeat that process until it reaches a result or needs help. It does not need to receive every intermediate instruction from a person.
That flexibility is useful for open-ended work, but it is not magic. The agent is still constrained by its instructions, available tools, permissions and checks.
The same task, two designs
Workflow: prepare a weekly sales summary
Every Friday, the system pulls the same reports, calculates the same figures, fills a fixed template and sends it to a manager for review. The steps are known, so a workflow is usually the clearest option.
Agent: investigate an unexpected sales decline
The instruction is to identify likely causes and prepare evidence. The agent may need to inspect different reports, compare time periods, look for product or region changes, check notes and decide which lead deserves follow-up. The path cannot be fully specified beforehand, so controlled agent behaviour can be useful.
How to choose
| If your task is mainly… | Start with… |
|---|---|
| Repeated, predictable and easy to describe step by step | A workflow |
| Open-ended, investigative or dependent on changing information | A constrained agent |
| High-risk, irreversible or regulated | A workflow with human approval; add autonomy only where it is justified |
| A mixture of routine and judgment | A workflow that gives an agent a limited subtask |
Autonomy is not all or nothing
A useful system does not have to be either fully scripted or fully autonomous. You can give an agent a narrow job, such as collecting evidence and drafting a recommendation, while keeping approval, payment, publication or customer contact with a person.
Good design asks four practical questions: What outcome is needed? Which tools are necessary? Which actions require approval? What evidence must the system show before it can claim completion?
Why simpler is often better
An agent can take more possible routes through a task. That flexibility can be useful, but it also means more to check if something goes wrong. A workflow is often the better starting point when a fixed process solves the real problem.
Use an agent when the uncertainty in the task matters more than the predictability of the route. Then make its boundaries visible: limited tools, clear stop conditions, logs, checks and an escalation path to a person.
Agent, chatbot and workflow
These terms describe different roles, not competing technologies. A chatbot usually answers in conversation. A workflow coordinates predefined steps. An agent can pursue a goal across several steps and tools. One product can contain all three: a chatbot interface, a workflow for routine requests and an agent for the ambiguous cases.
Copy-and-use prompts
Use these prompts as a starting point in the AI tool of your choice. Replace the text in square brackets with your own situation. Do not paste confidential customer, financial or personal data unless you are certain the tool and your organisation’s rules allow it.
1. Should this be a workflow or an agent?
2. Design a reliable fixed workflow
3. Write a safe agent brief
These prompts improve structure and oversight; they do not guarantee a correct outcome. Check important results and adjust the permissions to the task.
Frequently asked questions
Does every workflow with an LLM count as an agent?
No. Using a language model inside a predetermined sequence does not by itself make the system an agent. The key question is whether the model can dynamically direct some of the process or tool use.
Are agents always better than workflows?
No. For stable, repetitive work, a workflow is usually easier to validate and maintain. Agent behaviour becomes useful when the task requires investigation, adaptation or judgment between several possible next steps.
Can a workflow include human approval?
Yes. Human review is often the right control for decisions with financial, legal, reputational or customer impact.
Sources and further reading
Anthropic: Building Effective AI Agents explains the distinction between predefined workflow paths and systems that dynamically direct their process and tool use.
OpenAI: A practical guide to building agents discusses agent design, orchestration, tools and guardrails.
An everyday way to choose
If you need the same three spreadsheet figures every Monday, fixed steps may be enough. If the question changes each week and you need to investigate different information, an agent may help. Either way, you can review the result before anything is sent.
Our AI task chooser walks through that decision in a few clicks.
Continue reading
What Is an AI Agent? A Plain-English Explanation
AI Agent vs Chatbot: What Is the Real Difference?
Can AI Act on Its Own?
Can AI Agents Work Together?