What Is UiAgent in UiPath? A Guide to Goal-Based Automation with AI Agents

UiPath has been a leader in the RPA space for years—especially with UiAutomation, which has been its biggest strength for building enterprise-grade, reliable automations. Over time, we have seen UiPath evolve from simple rule-based bots to a platform infused with AI. Now, with UiAgent (currently in preview—name may still change, knowing UiPath 🤷), the landscape is evolving once again

To me, UiAgent feels like UiPath’s way of redefining how we approach automation in an agentic world—similar to what OpenAI is doing with Operator, and Anthropic with Claude. But the difference is: UiAgent sits natively inside UiPath Studio and Orchestrator, which makes it enterprise-ready from day one.

How UiAgent Works

If you’ve worked with UiPath before, you’ll find the setup surprisingly simple:

• Start with the “Use Application/Browser” container activity.

• Inside it, drop the UiAgent activity.

From there, you simply tell the agent what you want it to do, choose the LLM behind it, and let it get to work.

The UiAgent Decision Cycle

UiAgent doesn’t just run a static sequence—it follows a continuous cycle until the goal is reached:

1. Understand – Interpret intent and read the application’s state.

2. Plan – Decide the best next action.

3. Execute – Carry it out.

This Understand → Plan → Execute cycle repeats until the target outcome is achieved. And importantly, every step is logged—reasoning, screen analysis, and actions taken—giving enterprises the auditability they demand.

Guardrails and Control

Naturally, no business would want an AI agent running unchecked. UiPath has said guardrails are coming, such as:

• Setting a max number of steps.

• Restricting what tools/functions can be accessed.

• Defining scope boundaries.

That governance layer is exactly what enterprises need before deploying at scale.

My Hands-On Test

I gave UiAgent a real-world test:

The result? UiAgent analyzed the page, filtered the right product, and added it to the cart—and it did this correctly five times in a row. For me, that’s proof the hallucination risk is fairly low compared to generic LLM usage.

Benefits and Value Proposition

Here’s where UiAgent delivers real value:

• Less Maintenance Pain – Bots breaking with UI changes has been one of the RPA’s challenge. UiAgent’s adaptability reduces that pain significantly.

• Cross-Portal Workflows – Need to extract data from multiple vendor apps? Traditionally, you’d code separate flows. UiAgent generalizes the task.

• Goal-Based, Not Step-Based – Instead of chaining 30–50 activities, just state the outcome.

• Faster Development – UiPath was already low-code and fast. UiAgent trims the build cycle even further.

• Resilient in Dynamic Environments – Frequent UI updates don’t derail automations as easily.

• Closer to Business Users – Outcomes can be expressed in natural language, shrinking dependency on developers.

Trade-Offs to Consider

As with any new capability, there are things to watch:

• Licensing Costs – The final licensing model isn’t yet published, but I believe it would be usage-based consumption, which could raise costs when combined with unattended robots.

• LLM Unpredictability – No matter how solid, LLMs can still drift. Enterprises will need validation steps for critical processes.

• Less Determinism – You give up some fine-grained step control in exchange for flexibility. For certain use cases, that’s a trade-off worth making; for others, maybe not.

Where UiAgent Fits Today

UiAgent isn’t a silver bullet, but here are scenarios where it shines (with relatable examples):

• Multi-Portal Workflows – Same tasks repeated across different applications. e.g., entering customer orders across three supplier systems without building three separate flows.

• Dynamic Environments – Applications frequently updated with UI changes. e.g., e-commerce portals that update UI layouts weekly.

• Ad-hoc or Exploratory Tasks – When scripting every path isn’t worth it.

• Knowledge-Heavy Repetition – e.g., cross-referencing compliance data across multiple regulator portals.

My Final Thoughts

For me, UiAgent marks the shift from task-based to goal-based automation. It’s no longer about coding, ‘How do I automate these 30 clicks?’ but instead asking, ‘What outcome do I want?

For clients, architects, and business leaders, the implications are clear:

• Lower maintenance overhead – less time fixing bots when things change.

• Faster adaptability – automation that keeps up with evolving business needs.

• Closer alignment between intent and execution – outcomes that match what the business really wants.”

UiAgent is still in preview, but with more refinement and new capabilities ahead—will UiPath continue to hold its place as the Switzerland of UiAutomation with it's competition against the big players?

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