Imagine that, instead of asking an AI for a text, you task it with preparing a complete draft based on approved information, reviewing requirements, and pointing out what is missing. This change helps to understand agentization: organizing certain tasks through artificial intelligence agents that use tools to advance towards a goal, within defined limits.
What does it mean to agentize a process?
The term is used with different scopes; Here we talk about incorporating agents into a work process. It is not enough to add a chat to a website. You must define what result is expected, what information the agent can use and what actions it is allowed to perform.
A difference that should be understood
In a fixed flow, the path is planned: something happens and some steps are executed. An agent can decide which tool to use or what step is needed next, based on what they find. The Anthropic guide to effective agents precisely distinguishes between predefined flows and systems where the model dynamically directs the process and the use of tools.
An example applied to the content of a company
Let's think about a hypothetical example: a small company wants to prepare publications about its services. An agent could consult an authorized catalog, identify frequently asked questions and propose a draft. Then I would check that the necessary data appears and request a review when I do not find a reliable answer.
The target must have a closing condition
The assignment would not be "improve our networks", but rather "prepare three drafts based on this catalog and leave them pending approval." This precision allows us to evaluate the result. Publishing them would be another action, with its own permissions. Separating preparation and approval makes it easier to start with an understandable scope.
What you need before putting agents to work
Technology is a part of the project. If the process is disordered, the agent can move that disorder to more tasks. Before connecting tools, it is a good idea to answer these questions:
- Goal: What specific deliverable demonstrates that the task is completed?
- Sources: What information Is it up to date and usable?
- Permissions: What can the agent view, modify, or send?
- Review: What decisions require approval? human?
- Evaluation: How will you detect errors, excessive costs or incomplete results?
Start where you can check the result
A task limited, repetitive and with clear criteria is usually a better pilot than an open process with many exceptions. Preparing information for review can be easier to evaluate than delegating a negotiation or automatically responding to any complaint.
What it can contribute and what you should not take for granted
Agentization can help coordinate steps and reduce manual work when you need to interpret information during the journey. However, it adds integration, monitoring and evaluation costs. If a simple rule solves the problem, you may not need an agent.
Nor should you confuse autonomy with reliability. An agent may misinterpret an instruction, choose an inappropriate tool, or fail to detect an error. That's why you need logs of its actions, execution limits, and a way to stop the process. Supervision must be part of the design.
A first test with business criteria
Compare the pilot with the current process: total time, necessary corrections, quality and cost. Define what improvement would justify continuing. If the team takes longer to repair results than to complete the task, review the approach before extending permissions.
Choose indicators that you can observe from day one and record incidents. This way you will have a basis to decide what to adjust in each revision.
Also discover when to automate content tasks. At LabIA we can help you identify a useful and viable first process. Tell us what task is holding you back and let's assess whether it needs rules, an agent or a simpler organization.
