![Muhammad A.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Muhammad A.")
MA

Muhammad A.

Lead Automation Consultant

Mid-Market (51-1000 emp.)

6/30/2026

"Extending RPA Capabilities with Agentic AI"

4.5/5

What do you like best about UiPath Agentic Automation?

Having worked extensively with the UiPath ecosystem, what I appreciate most about UiPath Agentic Automation is its ability to automate processes that go beyond rule-based tasks. We have used it in scenarios involving document processing and decision-making workflows, where AI agents can understand context and take actions with minimal human intervention. Since it is tightly integrated with existing UiPath products, the learning curve was relatively smooth for our team. From an ROI perspective, we started seeing value fairly quickly as it reduced manual effort, improved processing speed, and allowed teams to focus on higher-value activities. While the pricing may appear premium initially, especially for organizations just starting their automation journey, the overall return justifies the investment when deployed for enterprise-scale and complex business processes. It has helped us design more intelligent and scalable automation solutions while significantly reducing manual effort across critical workflows. Review collected by and hosted on G2.com.

What do you dislike about UiPath Agentic Automation?

While UiPath Agentic Automation is powerful, there is still a learning curve when moving from traditional RPA to agent-based automation. Designing and troubleshooting agent workflows requires a different mindset, and debugging can sometimes be challenging due to the dynamic nature of AI responses. The licensing cost may also be on the higher side for smaller teams. That said, most of these challenges are manageable with proper training and experience. Review collected by and hosted on G2.com.

What problems is UiPath Agentic Automation solving and how is that benefiting you?

UiPath Agentic Automation is helping us address business processes that require contextual understanding and dynamic decision-making, which were challenging to automate using traditional RPA. We are using it in document processing and workflow orchestration scenarios, where AI agents analyze information, make decisions, and trigger the appropriate actions. As a result, we have reduced manual intervention, improved processing speed, and achieved better operational efficiency while expanding automation coverage across complex business processes. Review collected by and hosted on G2.com.

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