Automatic bank statement reconciliation | Invoice processing and data extraction from non-standard documents
Automatic order allocation to suppliers | Contract verification and order status checking via intelligent agents
Inventory monitoring and replenishment management | Intelligent order management: delays, out-of-stock items, alternative options
Intelligent CV processing | Automation of the new employee onboarding process

Complex process involving context-based decisions, not just predefined rules
Input data is variable, semi-structured, or unstructured (e.g. emails, documents)
Requires interactions between AI, RPA robots, and human users throughout execution

The goal is clear, but the steps to achieve it may differ depending on the situation
High case volume, but with many exceptions and variations from the standard
The process can be integrated with existing systems such as ERP, CRM, or other RPA robots

A UiPath RPA robot executes exact steps based on fixed rules.
An agent implemented with UiPath Agentic AI understands a goal, plans its own actions, and makes decisions based on the context in which it operates, without following a preset flow.
No. UiPath Agentic AI and UiPath RPA complement each other.
The agent is the “brain” that thinks and decides, while the RPA robots are the “hands” that execute the technical tasks => together they form an autonomous and efficient system.
Not all processes justify Agentic AI. It is ideal for dynamic processes with many exceptions, decisions, and human collaboration.
For repetitive and well-defined tasks, RPA remains the best option.
Use classic UiPath RPA when processes are clear, repetitive, rule-based, and without major exceptions — such as automatically filling out forms or reconciling data.
Use UiPath Agentic AI when the process involves decisions, frequent variations, unstructured data, communication with people, or real-time adaptation.
The two technologies are not in competition — they can work together, with the agent “thinking” while the robot “executes”.