AI agents in business process automation

An AI agent can carry out a multi-step task using data and tools. The company still needs to define the goal, permitted actions, sources, limits and points at which a person makes the decision.

Choose a process with a known path

We describe the input, decision points, outcome and owner. A useful starting point is a repeatable task whose failure cases the team can recognise. Adding a model alone does not repair organisational disorder.

Separate planning from execution

The agent may prepare a proposal, while an execution layer rechecks the target, permissions and current state. Each tool has a narrow contract. Data in a message or document is treated as content, not as an automatic system command.

Set autonomy boundaries

Read operations may allow more autonomy. Irreversible or high-impact actions require a preview and approval. OWASP recommends explicit approval for high-risk actions, plus interruption and rollback where available.

Documentation: OWASP AI Agent Security Cheat Sheet.

Test the complete scenario

Beyond the correct path, we test missing data, conflicting sources, denial, timeout, tool failure and duplication. The agent should stop in a defined state and pass a person the information needed to decide.

Measure process outcomes

We assess accuracy, time, cost, corrections, escalations and the impact of errors. Results are compared with the previous process over the same scope. A model, prompt, tool or data-source change triggers another review.