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AI & Automation

Technical

# Agentic workflows: frequently asked questions

What an agentic workflow is, how it differs from regular automation, when to use an AI agent and how to keep it safe and auditable.

Dutchify September 10, 2026 4 min read  Delen

### Table of Contents

[What is an agentic workflow?](#what-is-an-agentic-workflow)[What is the difference between an agentic workflow and regular automation?](#what-is-the-difference-between-an-agentic-workflow-and-regular-automation)[When do you choose an AI agent instead of a fixed workflow?](#when-do-you-choose-an-ai-agent-instead-of-a-fixed-workflow)[How do you keep an agentic workflow safe and auditable?](#how-do-you-keep-an-agentic-workflow-safe-and-auditable)

## What is an agentic workflow?

An agentic workflow is an automated process in which an AI agent reasons about the next step itself, calls tools or systems, and only stops once the goal is reached. In a classic workflow every step is fixed in advance; in an agentic workflow the goal is fixed and the agent decides the route.

Our page on [agentic workflows](/en/services/agentic-workflows) covers this in more depth.

## What is the difference between an agentic workflow and regular automation?

Regular automation follows a fixed script: if A, then B. An agentic workflow is given a goal and chooses which steps and tools are needed, also when the situation differs from the standard case.

That makes an agentic approach stronger with variation and exceptions, and a fixed script better for fully predictable work.

## When do you choose an AI agent instead of a fixed workflow?

Choose an AI agent when input differs each time, judgement is required and there are too many exceptions to write out. If the process is stable and can be fully described in rules, a fixed workflow is simpler, cheaper to maintain and more predictable.

## How do you keep an agentic workflow safe and auditable?

You bound what the agent may do: which tools it can call, which data it can see and which actions need human confirmation. On top of that you log every step and every tool call, so you can reconstruct afterwards why something happened.

With those boundaries and logging the agent stays an executor inside limits you set.

agentic workflows

AI agent

automation

FAQ

### Related services

Need help with this topic? See how we approach it.

-   [Complete websites ](/en/services/complete-websites)
-   [AI & automation ](/en/services/ai-automation)

## Related articles

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### AI for Ecommerce: A Technical Implementation Guide for Scale

Deep dive into AI-driven e-commerce: from vector search and RAG-based assistants to computer vision in logistics. A technical guide for scaling platforms.

](/en/knowledge-base/ai-voor-ecommerce-technical-guide)[

### AI automation for SMBs: 2 real-world examples

Two real-world examples of AI automation for SMBs: an AI agent that handles customer email, and 43% lower customer service costs with more revenue.

](/en/knowledge-base/ai-automation-smb-real-world-examples)[

### RAG Architecture: The Future of Intelligent AI Systems

Learn how Retrieval-Augmented Generation (RAG) overcomes the limitations of LLMs like GPT-4 by connecting them to your own data for accurate, real-time AI responses.

](/en/knowledge-base/retrieval-augmented-generation-rag-architecture)

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