Agentic AI vs RPA: Which is Right for Your MSP?

RPA follows predefined scripts and rules—it can only do exactly what it's programmed to do. Agentic AI uses reasoning and learning to make autonomous decisions, adapt to new situations, and handle ambiguous requests without explicit programming.

Yes. Many organizations use RPA for highly structured, repetitive tasks (data entry, form filling) while deploying agentic AI for complex decision-making tasks. However, agentic AI can often replace RPA entirely by handling both simple and complex scenarios.

Agentic AI is significantly better for service desks because tickets are inherently variable—users describe problems in different ways, issues have varying contexts, and resolutions require judgment. RPA struggles with this variability while agentic AI excels at it.

While initial costs may be similar, agentic AI typically delivers better ROI because it handles more scenarios without custom scripting, requires less maintenance, and improves over time through learning. RPA often incurs ongoing costs for script updates and exception handling.

RPA requires extensive process mapping and script development for each workflow. Agentic AI can be deployed faster because it learns and adapts rather than requiring explicit programming for every scenario.