RPA uses software robots to perform rule-based steps in applications. Intelligent automation adds AI, document understanding and workflow orchestration so whole processes can be automated. Agentic AI uses language-model agents that plan and take actions toward a goal using tools, within guardrails and human oversight. Most enterprises combine all three.
What is robotic process automation (RPA)?
RPA software robots mimic human actions in user interfaces, clicking, typing and copying data between applications, following fixed rules. RPA is fast to deploy and works well for stable, structured, high-volume tasks, but it is brittle when inputs or screens change.
What is intelligent automation?
Intelligent automation combines RPA with AI capabilities such as intelligent document processing, machine learning and natural language processing, plus workflow orchestration and human-in-the-loop review. It can handle unstructured inputs and exceptions, so complete processes can be automated rather than isolated tasks.
What is agentic AI?
Agentic AI uses large language models as agents that interpret a goal, plan steps and call tools such as search, APIs, RPA bots or workflows to achieve it. Agents handle variability and judgment that rules cannot express, but need clear permissions, guardrails, monitoring and human approval for consequential actions.
When should you use each?
Use RPA for deterministic steps in systems without APIs. Use intelligent automation when documents, decisions or exceptions are involved. Use agentic AI for variable, language-heavy work such as triaging requests, researching information or drafting responses, with deterministic automation executing the final actions.
How do they work together?
A practical architecture uses process orchestration as the backbone, agents for interpretation and judgment, IDP for documents, and bots or APIs for system actions, all governed by one automation center of excellence with shared monitoring and audit.
