{"id":26770,"date":"2026-09-21T13:26:56","date_gmt":"2026-09-21T11:26:56","guid":{"rendered":"https:\/\/scheer-pas.com\/en\/?post_type=post_type_article&p=26770"},"modified":"2026-09-24T13:16:17","modified_gmt":"2026-09-24T11:16:17","slug":"the-four-approaches-to-process-automation-and-when-to-use-each","status":"publish","type":"post_type_article","link":"https:\/\/scheer-pas.com\/en\/blog\/article\/the-four-approaches-to-process-automation-and-when-to-use-each\/","title":{"rendered":"The Four Approaches to Process Automation (and When to Use Each One)"},"content":{"rendered":"
<\/div>
\n
\n \"Four <\/div>\n\n<\/div><\/div>
\n\t

BLOG<\/p>\n<\/div><\/div><\/div><\/div>

\n\n\t
\n\t\t

The Four Approaches to Process Automation (and When to Use Each One)<\/h1>\t<\/div>\n\n<\/div><\/div>
\n\t

September 16 | Sharam Dadashnia<\/p>\n<\/div><\/div><\/div><\/div><\/div>

<\/div><\/div>
<\/div>
\n\t
\n\t\t
<\/div>\n\t\t\t\t
<\/div>\n\t<\/div>\n<\/div><\/div><\/div><\/div>
<\/div><\/div>
<\/div>
\n\t
\n

Not all automation is created equal. Nevertheless, in many discussions, four very different approaches are grouped under the same term: a rule-based workflow, a single AI agent, an agent acting as an orchestrator, and a business process in which a process engine specifically controls agents.<\/p>\n<\/div>\n<\/div><\/div><\/div><\/div>

<\/div><\/div>
<\/div>
\n\t
\n\t\t
<\/div>\n\t\t\t\t
<\/div>\n\t<\/div>\n<\/div><\/div><\/div><\/div>
<\/div><\/div>
<\/div>
\n\t
\n

This leads to poor decisions. One team expects an AI agent to provide the traceability of a BPMN process. Another spends months building a process architecture, even though a single fixed rule would have sufficed. Yet another automates individual tasks, even though the bottleneck lies between departments, systems, and wait times.<\/p>\n

 <\/p>\n

The right question, therefore, is not: Where can we use AI?<\/i> But rather: What kind of decision needs to be made at which point in a process\u2014and what form of automation is appropriate for that?<\/i><\/p>\n

 <\/p>\n

The current state of affairs confirms this distinction. The BPM Pulse Survey 2026 by BearingPoint<\/a> describes AI in process management as a relevant topic, while the productive use of agent-based systems simultaneously raises questions about control, transparency, and accountability. Agents expand process automation. They do not automatically make it better.<\/p>\n

 <\/p>\n

Below, four approaches are presented side by side\u2014along with their appropriate areas of application and their limitations.<\/p>\n<\/div>\n<\/div><\/div><\/div><\/div>

<\/div><\/div>
<\/div>
\n
\n \"Rule-based <\/div>\n\n<\/div><\/div><\/div>
<\/div><\/div>
<\/div>
\n\n\t
\n\t\t

Approach 1: Rule-based automation<\/h2>\t<\/div>\n\n<\/div><\/div>
\n\t
\n

Rule-based automation is the right approach when the workflow is known, the inputs are structured, and the decision is unambiguous.<\/p>\n

 <\/p>\n

An example: An invoice is approved if the order number, amount, and cost center match the stored data. A purchase order is forwarded if it exceeds a specified value. A data record is created as soon as all required fields are filled in.<\/p>\n

 <\/p>\n

No agent is needed here. There are no open-ended questions to interpret. The rule can be reviewed, tested, and modified as needed.<\/p>\n

 <\/p>\n

This is not a step backward compared to AI. On the contrary: deterministic steps are often faster, more cost-effective, and easier to trace. They should remain where they fit.<\/p>\n

 <\/p>\n

Rule-based automation works particularly well when:<\/p>\n