AI applied where traditional RPA stops
A bot that follows a script handles the expected well and fails at the rest. AI automation exists for the rest: the divergence that was not in the flow, the layout that changed, the scenario nobody wrote. The difference shows up at the first exception, not in the demo.
The limit of the bot that follows a script
Deterministic automation solves the happy path and hands the rest back to a person.
Every exception goes back to a human
The declared gain disappears when a relevant share of executions falls into manual handling because it was not anticipated.
The test scenario is written by someone who already knows the system
Coverage reflects what the team imagines can fail, not what the system actually allows.
Adapting requires reprogramming
Every layout or rule change becomes a development ticket before the bot runs again.
How it works
The agent works in a cycle, and every step is recorded.
Perceive
Reading the current state of the system, including computer vision where the interface is the only source available.
Plan
Defining the sequence of actions from the stated goal, not from a fixed path written in advance.
Act
Execution in SAP, the web application or the legacy system, with the same access control and logging as deterministic automations.
Learn
Feeding the result into the next behavior, so a divergence handled once does not need intervention again.
Where AI changes the result
Cases where the decision made during execution is worth more than raw speed.
| Application | What it does | Typical module |
|---|---|---|
| Fiscal close | Reconciliation, adjustment and submission for approval, handling divergences | SAP FI |
| Procurement cycle | Replenishment, purchase order creation and approval follow-up | SAP MM and SD |
| Regression before go-live | System exploration, test case generation and execution | Cross-module |
| Computer vision | Reading interfaces without an API and legacy systems | Legacy |
| Exception handling | Decision during execution without sending it back to the human queue | Cross-module |
Numbers
Results from real operating cases.
- 78%Reduction in monthly fiscal close timeSAP FI case. Measured in the operation of a large customer.
- 3×Faster procurement cycleSAP MM and SD case. Measured in the operation of a large customer.
- 100×More scenarios tested compared with manual QARegression before go-live case. Measured in the operation of a large customer.
Frequently asked questions
Does this replace the RPA I already have?
Not necessarily. Stable, high-volume flows are still well served by deterministic automation. AI comes in where there is variation, frequent exceptions or a need to explore the system.
How do I audit an agent’s decision?
Every decision is recorded with the state that motivated it and the action chosen. Without that trail, the agent should not operate on a critical process.
Where can I see this in depth?
On the Agentic automation page, with the pillars, the journey and the full cases.
See also
Which exception sends the most work back to your team?
Bring the process where your current automation fails the most. That is where the difference shows up first.