AI assistant, AI agent or automated workflow?

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"AI assistant", "AI agent" and "automated workflow" describe three different ways of letting AI carry out work – not three names for the same thing. The difference lies in who starts the work, how many steps the system chooses on its own, and how much human review is needed before the result is used.

The short answer

An AI assistant is started by a person for a well-defined task and follows explicit instructions and approved source material. An AI agent works towards a goal, can choose between several permitted steps or tools, and carries the result of one step into the next – but it needs permission boundaries, review checkpoints and stopping rules. An automated workflow is triggered by a defined event or schedule and follows a flow that is specified in advance, where AI may be part of it but the steps are largely predetermined.

None of these approaches removes the need for human oversight. The more steps a system may choose on its own, the clearer its permissions, review checkpoints and stopping rules need to be.

Three definitions to work from

AI assistant. A person starts the work, provides the task and reviews the result. The assistant follows explicit instructions and approved source material. Example: you ask an assistant to summarise a meeting or review a document against fixed criteria, and you read the answer before it is used.

AI agent. The system works towards a goal, can choose between permitted steps or tools, and uses the result of one step in the next. This requires permission boundaries, clear review checkpoints and rules for when the agent must stop and wait for a person. Example: a research agent that chooses which approved sources to search, but pauses and shows its evidence before the conclusion is used.

Automated workflow. The flow is triggered by a defined event or schedule and follows a flow that is specified in advance. AI may be part of the flow, but the steps are largely predetermined rather than chosen by the system itself. Example: a new form response automatically triggers a summary that is sent out following the same template every time.

Foundation courses in the catalogue instead build understanding, assessment, architecture or governance, rather than primarily producing a finished assistant, agent or automation. That is a fourth way of engaging with the field – a basis for choosing the right solution later on.

When to choose which

Start by asking: does the work need to be started by a person, or can it be triggered by an event or schedule? If a person should always start and approve the work, an AI assistant is often enough. If the system needs to choose between several steps or tools to reach a goal, you are moving towards an AI agent. If the same flow should run the same way every time without anyone actively starting it, you are describing an automated workflow.

Then ask: how serious are the consequences of a mistake? The higher the risk, the more important clear review checkpoints become, regardless of which of the three you choose. Many organisations do well to start with a well-scoped AI assistant, test it thoroughly, and only then build towards an agent or an automated workflow.

The development ladder

The three solution types are often steps in a progression, from a simple question to a flow that runs without a human starting it each time:

  1. 1One-off prompt. You ask for a summary of one text on a single occasion.
  2. 2Saved template. The same instruction is saved and reused by you every week.
  3. 3Reusable AI assistant. A project with an instruction and approved material that a person starts and reviews.
  4. 4AI agent with tools and several steps. A goal is broken into steps where the agent chooses among permitted tools and stops at the checkpoints.
  5. 5Automated workflow. A new form response starts a defined flow that runs the same way every time.

Most organisations benefit from moving through this ladder step by step rather than jumping straight to an automated workflow. Each step reveals what actually works in your own organisation.

Human oversight at every level

More autonomy does not remove the need for human oversight. The more steps a solution may choose on its own, the clearer its permissions, review checkpoints and stopping rules must be.

This applies to all three solution types: an AI assistant can misunderstand an instruction or use the wrong source, an AI agent can choose a step that was not intended, and an automated workflow can keep running even after its input has become wrong. Build in clear boundaries for what the solution may do, points where a person reviews the result, and rules for handling uncertainty – before the solution is used in a live setting.

In summary

AI assistant, AI agent and automated workflow are three different ways of organising work with AI, with different degrees of human initiation and autonomy. Choose the simplest solution that covers the need, test it carefully, and build from there.

The course catalogue includes courses for each solution type – from foundation courses on AI assistants to more advanced courses on AI agents and automated workflows – so you can choose a course based on what you are actually going to build.

Read also

For a closer comparison of chatbot, AI assistant and AI agent, see the article AI agent vs chatbot vs AI assistant.

Sources

Published: 19 September 2026.

Content produced and fact-checked by AI‑Agenter. Last reviewed: 18 September 2026.