Over the last few months, UiPath has been introducing concepts around Agentic Automation; where software robots are not just executors of predefined steps, but dynamic entities capable of perceiving context, reasoning, and taking adaptive actions based on goals.
For years, RPA has followed a predictable flow: structured inputs, rule-based logic, and human escalation for exceptions. Agentic systems challenge that model. They bring together LLMs, context awareness, orchestration intelligence, and decision-making layers that could enable a robot to plan its actions, not just perform them.
From an architectural point of view, this shift could redefine how we design automations. Instead of linear workflows, we might see multi-agent ecosystems, each handling sub-goals and coordinating through shared context (documents, conversations, or APIs). Governance and traceability become even more critical; not because we’re losing control, but because we’re giving automations the ability to act independently within guardrails.
As someone who’s worked with automation at different maturity stages, I find this transition fascinating. It could bridge the current gap between AI orchestration and enterprise-grade reliability, if we can ensure transparency and accountability in every decision taken by these agents.
I’m curious to hear from others in the UiPath community:
- How do you envision Agentic Automation fitting into existing UiPath ecosystems; an evolution of Orchestrator and Apps, or a parallel layer for adaptive logic?
- What areas of improvement do you see before such systems can be trusted in production environments?
- Have you experimented with any of UiPath’s agentic features or similar autonomous frameworks? What impressed you most so far?
- What kind of governance model or monitoring do you think will be required to ensure responsible autonomy?
Let’s open this as a space to exchange real insights and expectations; not just about what’s new, but about how it should evolve.