Examples of Business Process Automation, by Type

Most lists of automation examples are organized by department — finance, HR, operations. That's useful, but it hides a more practical distinction: the underlying type of automation a process needs, which determines how it gets built and roughly how hard it is.

This page groups examples by pattern instead of department, because the pattern is what actually shapes a project's scope and cost, regardless of which team owns the process.

Pattern 1: Rule-Based Automation

This is "if this happens, do that" logic applied to structured, predictable inputs. It's the most established and usually the fastest to build.

• Moving a new CRM record into the accounting system once a deal closes
• Sending a reminder email three days before an appointment
• Flagging an inventory count that drops below a threshold
• Routing a support ticket to a queue based on its category field

Rule-based automation works well precisely because the input is already structured — a form field, a database value, a fixed status. There's no interpretation required, just consistent execution.

Pattern 2: AI-Assisted Automation

This pattern handles input that doesn't arrive in a fixed format — the kind of work that used to require a person to read, understand, and decide.

• Extracting line items and totals from a scanned invoice that varies by vendor
• Classifying an open-text customer message into the right category before routing it
• Summarizing a long email thread into a short update for a manager
• Answering a routine question from approved company information during a call or chat

The distinguishing feature here isn't complexity for its own sake — it's that the input varies in a way fixed rules can't fully anticipate, so some form of interpretation is required before rule-based logic can take over.

Pattern 3: Approval and Escalation Workflows

Technically a form of rule-based automation, but worth treating separately because the goal is accountability and visibility, not just data movement.

• Routing an expense claim to the right approver based on amount, with automatic reminders if it stalls
• Escalating a support ticket that hasn't been answered within a set time
• Requiring a second sign-off on any transaction above a defined threshold, with a full audit trail

Pattern 4: Exception Handling

The pattern that determines whether an automation is trustworthy or a liability: what happens when the input doesn't match any expected case. A well-built automation flags the exception to a person rather than guessing, silently failing, or producing a wrong result with no record of it.

A Worked Example Combining All Four Patterns

A vendor invoice arrives as a scanned PDF. AI-assisted extraction reads the vendor name, line items, and total (Pattern 2), because the layout varies by vendor and can't be handled by fixed rules alone. Rule-based logic then matches it against the original purchase order and receipt (Pattern 1). If the invoice total is above a set threshold, it's routed to a manager for sign-off with a reminder if it stalls (Pattern 3). If the extraction confidence is low, or the invoice doesn't match any open purchase order, it's flagged for a person to review rather than processed automatically (Pattern 4). This is a realistic shape for most real automations — a blend of patterns rather than a single one applied in isolation.

Choosing the Right Pattern for Your Process

Most real projects combine more than one pattern — AI to read a messy input, rules to route and match it, an approval step for anything above a threshold, and exception handling underneath all of it. Recognizing which parts of your process fall into which pattern is usually the fastest way to get an accurate scope and cost from any vendor.

For examples organized by department instead, see our business process automation examples page, or read the business process automation overview for how these patterns map to the categories of work we build.