An agentic workflow is a piece of work where an AI tool acts as an agent. It works out the next step, uses your systems to take it, checks the result and carries on until the task is done. It follows agent skills that set out how your business does the work, and a person checks the parts that matter.
The AI tools your team already uses, such as Claude, ChatGPT and Microsoft Copilot, can work this way once they have the right instructions and connections. What makes them useful in your business isn't a new AI model. It's the agent skills, the company knowledge and the connections to your systems around them.
The Short Answer
- An agentic workflow lets the AI decide how to complete the steps. It works within limits you set, using the tools and systems you've connected.
- An AI workflow follows fixed steps. The AI does a defined job at each step, in the same order every time.
- Automation follows rules. No AI judgement is involved, which is often exactly what you want.
- Agents run your agent skills. The skills hold your method, and your company brain holds what your business knows.
- Start simple. Use a fixed workflow where the task is predictable, and let the AI decide the steps only where the work varies.
- People stay in charge. Every workflow has an owner, and a person checks the results that matter.
Workflows, Agents and Agentic Workflows
The terms get used loosely, so it helps to start with a clear line. In Building Effective Agents (19th December 2024), Anthropic separates the two: "Workflows are systems where LLMs and tools are orchestrated through predefined code paths." Agents, by contrast, decide their own process and which tools to use as they go.
An agentic workflow sits between the two in practice. The overall job and its limits are set, and the AI uses its judgement within them.
| Automation | AI Workflow | Agentic Workflow | |
|---|---|---|---|
| Who decides the next step | Fixed rules | Fixed steps, with AI doing the work at each one | The AI, within limits you set |
| Good for | Predictable, rule-based tasks | Repeatable tasks that need reading, writing or checking | Tasks that vary each time and need several steps |
| Example | Copying a new order into the accounts system | Reading an inspection form and checking each field | Turning meeting notes into updated client records and a follow-up draft |
Our work with Quantem is a good example of an AI workflow. AI reads each inspection form and checks the data, then a coordinator reviews it before it goes into the maintenance system. The steps are the same every time, and that's the right design for that job.
Where Agent Skills and Your Company Brain Fit
An agent is only as good as what it's working from. Three things make the difference:
- Agent skills are reusable instructions that tell the AI how to do a task your way: the steps, the format and the checks to run before it finishes.
- Your company brain gives it what your business knows: pricing, past work, procedures and the judgement of your experienced people.
- Connections to your systems let it read and update the tools where the work lives, such as your CRM, finance or job system.
That's why we say agents run your agent skills. The AI tools act as the agents. The method, the knowledge and the connections are what we build with your team.
Agentic Workflow Examples
These are the kinds of workflows growing businesses start with. Each keeps a person in the loop.
- Meeting notes to client records. After a client meeting, the AI turns the notes into the format your team uses, updates the record in your CRM or recruitment system and drafts the follow-up email for the consultant to check and send.
- Briefs to estimates. The AI reads a new brief, finds similar past jobs, applies your pricing rules and drafts an estimate for the account lead to review.
- Job sheets to the job system. The AI reads a job sheet from the field, updates the job record, flags missing details and asks a coordinator to approve anything unusual.
- Month-end commentary. The AI pulls the figures from your accounting system, follows your reporting rules and drafts the commentary for the finance lead to sign off.
When You Don't Need an Agent
Anthropic's advice is to find the simplest solution that works and only add complexity when it clearly improves the result. We agree. If a task follows the same steps every time, a fixed AI workflow is easier to test, cheaper to run and simpler to trust. Let the AI decide the steps only where the work genuinely varies, such as handling different kinds of requests or pulling information from several places.
Keeping People in Charge
An agentic workflow should make your team's work easier to check, not harder. Build in:
- An owner for every workflow. Someone on your team decides how it works and when it changes.
- Review points. A person approves anything that reaches a client, moves money or changes an important record.
- Limited access. The AI gets only the systems and permissions the task needs. Start read-only where you can.
- A record of what happened. Keep a log of the steps the AI took, so results can be checked and improved.
How to Start
- Pick one recurring task. Choose work that takes real time and follows a recognisable pattern.
- Map how it's done today. Fix the process first, so the AI isn't learning a workaround.
- Write the agent skill. Capture the steps, the format and the checks, with the people who do the work.
- Connect the systems it needs. Give the AI access to the right information, and no more.
- Run it with a person checking every result. Widen the AI's room to decide only as trust builds.
How ELab AI Helps
ELab AI is an AI advisory and implementation business. Every engagement works through the same four parts: your people, your processes, your company brain, then your tools and systems. We don't build AI agents. The AI tools your team uses act as the agents, and we build the agent skills, the company brain and the connected workflows they run, then test them with your team on real work. See how we work.
Frequently Asked Questions
What Are Agentic Workflows?
Agentic workflows are pieces of work where an AI tool acts as an agent. It works out the next step, uses your systems, checks the result and carries on until the task is done, following your agent skills, with a person checking the results that matter.
What's the Difference Between an AI Workflow and an Agentic Workflow?
An AI workflow follows fixed steps, with AI doing a defined job at each one. In an agentic workflow, the AI decides how to complete the steps within limits you set. Fixed workflows suit predictable tasks, and agentic workflows suit work that varies.
Is an Agentic Workflow the Same as Automation?
No. Automation follows fixed rules with no AI judgement. An agentic workflow uses AI to read, decide and act. Many businesses use both: automation for predictable steps and agents where judgement is needed.
Do We Need to Build Our Own AI Agents?
Usually not. Claude, ChatGPT and Microsoft Copilot can act as agents once they have good agent skills, your company knowledge and connections to your systems. The value is in those, not in a custom-built agent.
Are Agentic Workflows Safe?
They can be, with the right controls. Give the AI only the access the task needs, keep a person reviewing anything that reaches a client or changes an important record, and keep a log of what the AI did.
Where Should We Start With Agentic Workflows?
Start with one recurring task that takes real time, fix the process, write the agent skill and run it with a person checking every result. Widen it as the team builds confidence.
Getting Started
If you're working out where agentic workflows would make the biggest difference, take our AI Readiness Assessment. It looks at your people, processes, company brain, then tools and systems.
If you'd like help building agent skills and connected workflows, tell us about your business or book a conversation.