CIO wants to replace our entire RPA infrastructure with agentic AI systems by end of 2027, claiming agents will handle everything RPA does plus complex decision-making. I'm skeptical because our high-volume transaction processing needs deterministic, repeatable execution - exactly what RPA excels at. Agents are expensive at $0.15-0.40 per task versus $0.02 for RPA bots, and they're still immature for governed production environments in banking. The orchestration argument makes sense where RPA handles structured work and AI agents manage exceptions and unstructured data, but fully replacing RPA seems premature. Anyone actually running production workloads with AI agents instead of traditional bots? What's the cost and reliability comparison looking like?

Reply 1:
Your CIO is falling for the hype cycle. AI agents aren't replacing RPA - they're complementary technologies working together through orchestration platforms. We run 340 RPA bots for rules-based processing like data entry, report generation, and system reconciliation, plus 28 AI agents handling customer queries, document classification, and fraud detection. The bots process 2.4 million transactions monthly with 99.97% reliability. The agents handle 15,000 exceptions monthly with 87% resolution rate. Cost per transaction: $0.018 for RPA, $0.28 for agents. The agents are fantastic for cognitive tasks, but suggesting they replace RPA for high-volume repetitive work is financially ridiculous and technically unnecessary.

Reply 2:
Insurance industry here, and we're seeing the same orchestration pattern as the best practice. Agentic AI shines on claims assessment where you need to read unstructured medical records, evaluate policy coverage nuances, and make judgment calls on approvals. Traditional RPA crushes the post-decision work - updating policy systems, generating letters, triggering payments, maintaining compliance logs. We measured this extensively: agents provide 40% better accuracy on complex claims decisions, but RPA completes downstream tasks 8x faster and 12x cheaper. The real transformation happens when Maestro or similar orchestration tools coordinate both - agent makes the decision, RPA executes the workflow, human reviews edge cases. That hybrid architecture is where we're seeing 5-10x ROI instead of the 2-3x from pure RPA deployments.