---
title: "Automating Tasks with AI Agents: What Is Realistic Today"
description: "Which tasks AI agents can automate today: recurring processes, deadline detection, summaries – and where humans decide."
type: "wissen"
product: "agent"
slug: "ki-agent-aufgaben-automatisieren"
source_language: "de"
target_languages: ["de", "en", "es", "pl", "tr"]
published: "2026-06-10"
status: "publish"
faq_json: [{"q":"Which tasks can AI agents automate?","a":"Above all, recurring tasks with leeway: evaluating documents, detecting deadlines, creating summaries, reminders and routines on a schedule, preparing drafts."}, {"q":"What distinguishes agent automation from classic automation?","a":"Classic automation follows rigid if-then rules. An AI agent can understand and classify content – it also automates tasks that can't be forced into fixed rules."}, {"q":"Which tasks should an agent not handle alone?","a":"Anything with external impact: sending emails, making calls, changing master data. The proven approach is the approval principle – the agent prepares, a human approves."}, {"q":"How do I set up automated tasks?","a":"In webRichtung agent via Automations: you activate functions individually, and you set up schedules directly in the chat – for example a weekly reminder or evaluation."}, {"q":"What's the best way to start?","a":"With a task that occurs regularly, has clear criteria, and no external impact: for example, checking processed documents for clearly documented deadlines."}]
language: "en"
source_id: "wissen/ki-agent-aufgaben-automatisieren"
source_hash: "1d306aed5b4d143f8620362d024951eefdd13767f2c1837ff667e302201bee15"
---

AI agents today primarily automate tasks that are recurring but require understanding: reading and classifying documents, detecting deadlines, creating summaries, completing routines on a schedule, preparing drafts. In doing so, they close the gap between classic automation, which only follows rigid rules, and work that until now necessarily depended on humans.

## The difference from classic automation

Classic automation works according to "if X, then Y" – reliably, as long as the world looks exactly as it did during setup. An AI agent, by contrast, can understand content: it recognizes that "payable by 07/15" and "payment term: 14 days from invoice date" mean the same thing, even though no rule anticipated this. This makes tasks with leeway automatable – exactly the ones at which if-then systems fail.

## What agents automate well today

- **Evaluating documents:** Reading, classifying incoming mail, invoices, and contracts, and detecting clearly documented deadlines – a letter becomes a prepared deadline instead of a forgotten one.
- **Routines on a schedule:** Reminders, regular evaluations, recurring tasks – once set up, they run without a chat.
- **Condensing and summarizing:** Getting long threads, conversation notes, or documents to the point, for example to prepare for an appointment.
- **Preparing tasks:** Deriving what needs to be done from processes and documents, and creating tasks with a description and sources – for your review.
- **Creating drafts:** Preparing replies, texts, and evaluations that a human only reviews instead of writing.

You can find a broader collection with practical cases under [AI agents: 7 examples](/en/wissen/ki-agent-beispiele.html).

## Where humans decide

Not everything an agent could do should it do alone. A proven principle: **external impact goes through approvals.** Sending emails, making calls, changing master data – the agent prepares this, you get a query and decide. There are two reasons for this: mistakes with external impact are expensive, and responsibility cannot be delegated to software. Good systems make this boundary technically visible rather than leaving it to chance.

## What this looks like in practice

In [webRichtung agent](https://www.webrichtung.de/module/agent/), the automation toolkit is called **Automations** – in two forms: **Functions** are capabilities that your assistant is allowed to carry out independently; you activate them individually and adjust settings such as the minimum confidence – if the agent isn't confident enough, it doesn't create anything but gets in touch. **Schedules** are fixed, recurring tasks that you set up directly in the chat. Whatever awaits your decision is collected in the Queries area.

## The right way to start

Start with a task that meets three criteria: it occurs regularly, good results are clearly recognizable, and it has no external impact. Checking deadlines on processed documents is a typical first candidate – the benefit shows quickly, and errors remain internally correctable. When the results hold up over a few weeks, you expand step by step – with the same ground rules: clear specifications, graduated autonomy, approvals for anything that goes out.