--- title: "What does an AI agent do in a business process?" description: "The boundary between proposing and executing, made concrete: what an agent does and what you leave for a person to decide." source_name: "Gen8" source_url: "https://gen8.app/en/kennis/wat-doet-een-ai-agent/" site_home: "https://gen8.app/" source_description: "Managed AI service for SMEs. We set up, connect and manage; you stay in control." locale: "en" authors: - name: "Olivier Hokke" url: "https://gen8.app/en/kennis/author/olivier-hokke/" copyright: "© 2026 Gen8 VOF · Dutch Chamber of Commerce 92978789 · Delft" published_at: "2026-09-20T16:36:44.562Z" modified_at: "2026-10-21T16:27:52.995Z" --- # What does an AI agent do in a business process? An AI agent in a business process is not a chatbot with extra permissions. It is a workflow that assesses a signal and makes a proposal, while a person decides where consequences are significant. By Olivier Hokke · September 20, 2026 · Decisions and control ## Three things an agent does An agent in a business process essentially does three things. It **assesses** a signal: an incoming email, a meeting transcript, a document in a folder. It **retrieves context** from systems you have allowed it to read: the CRM, knowledge base, project board. And it **proposes an action**: a draft reply, a task with an owner and date, a CRM update with a visible difference. What it does not do, unless you explicitly configure it: write without anyone watching. ## Proposing or executing: the boundary The question is not whether AI can do something, but what happens when it goes wrong. That is why we draw the boundary according to the consequences of an error. - **Read-only**: the agent reads and reports but changes nothing. Suitable for knowledge bases, reporting and progress monitoring. - **Proposals with approval**: the agent prepares a change and a person approves it. Suitable for CRM updates, client replies and tasks affecting others. - **Automatic with a log**: the agent executes without intervention, and every step is logged with a way back. Only where the consequences of an error are small and reversible. A process almost always starts in the first or second category. Only when a second implementation shows that proposals are consistently good does a step move to the third. ## What you leave for a person to decide Some decisions you do not leave to a model, however well it performs: - Anything creating an obligation: sending a proposal, accepting a contract, releasing a payment. - Anything with a human element the model cannot see: a client who has already called three times, a colleague under pressure. - Anything about which the agent itself is uncertain. A good workflow has an explicit way out: *I do not know*, back to a person. ## How to set this up concretely Start with one process and describe, for each step, who currently decides and what happens when it goes wrong. Choose the control level for each step. Make approval visible in the system where work happens, not a separate dashboard nobody opens. And log everything, including rejections: that is the source you can later use to change the control level based on evidence. ## What to do with this Take one process and write down for each step: who decides now, what happens if it goes wrong, and which control level fits. That overview is the starting point of every process discussion. ## Frequently asked questions Is an agent with human approval not simply a slower workflow? Approval takes seconds; the preparatory work previously took minutes or hours. And approval is precisely what lets you automate a step later based on evidence. Can an agent learn from rejected proposals? The log of rejected proposals is the source for refining rules and context. That happens in a controlled way, not through the model quietly learning on its own. ## Want to apply this to your own process? Bring one process to a conversation. We assess suitability, risk and the cost of the first step. [Book an introduction]() - Reply within one business day - No obligation