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What is the difference between AI agents and RPA?
Agents vs scripted bots
AI agents make decisions. RPA bots follow scripts. AI agents read unstructured inputs like email and PDF. RPA bots require stable, structured screens. AI agents resolve exceptions. RPA bots escalate. In B2B order processing, AI agents reach 80 to 95 percent autonomy where RPA peaks at 30 to 50 percent.
AI agents vs RPA in depth
Key terms
- AI agent
- Software that perceives, decides, and acts toward a goal.
- RPA bot
- Scripted UI replay against fixed screens.
- Unstructured input
- Email, PDF, and Excel data that RPA cannot natively read.
- Reasoning
- The decision capability that lets an agent handle exceptions.
- Maintenance
- Ongoing cost of keeping the automation running.
Proof points
- 99 percent first-time-right rate on autonomous orders.
- 43 percent capacity released across order processing teams.
- 30B+ B2B transactions executed across the Go Autonomous customer base.
- 18 percent quote-to-order win rate uplift after deployment.
Frequently asked questions
When is AI agents the right fit?
Choose this side for narrow, well-defined work where inputs are structured and the rules are stable. It scales linearly with volume and breaks when inputs drift outside the script.
When is RPA the right fit?
Choose this side for work with unstructured input, exceptions, and decisions. It scales with data and feedback rather than with people, which is why it outperforms once volume and variance rise.
Can both approaches coexist?
Yes. Many manufacturers run both during the transition. The structured path keeps running on the older approach while the long tail moves to AI agents. Plan a 12-month convergence.
AI agents vs RPA in action.
Book a 30-minute demo and see how Autonomous Commerce executes B2B transactions in your stack.
AI agents vs RPA in action.
Book a 30-minute demo and see how Autonomous Commerce executes B2B transactions in your stack.
