Side-by-side comparison
Each pattern has a sweet spot — the failure mode is using the wrong one for the workflow.
- AI agent — high autonomy, dynamic plan, LLM reasoning + tools, best for variable knowledge work.
- AI copilot — human-in-the-loop, single-app suggestion, best for productivity inside an existing UI.
- RPA — zero autonomy, brittle to UI change, best for legacy systems with no APIs.
- Workflow automation — deterministic DAGs, no reasoning, best for stable cross-system pipelines.
When to combine them
Modern enterprise stacks use all four. An agent reasons about what should happen, calls a workflow automation step to fan out to systems, and falls back to RPA only when an API does not exist. The copilot surfaces the agent's actions to the user for approval.