Agentic AI + RPA

What is agentic RPA?

Agentic RPA combines robotic process automation (RPA) with AI to bring a new level of intelligence to your processes. With AI, building a robotic task in Appian RPA is easier than ever. Instead of manually defining each step, agentic RPA adapts in real time and determines the best next action, saving you development time and effort.

How agentic RPA makes automation adaptive

Agentic RPA makes automation smarter and more intuitive. By combining AI with robotic process automation, agentic RPA overcomes technical barriers and simplifies automation across different software systems. Robotic tasks can recognize and interact with on-screen elements, making it possible to process visual data just like a human would.

Many automation processes are designed to handle routine or predictable tasks, with workflows that align to specific business needs. When those needs evolve, workflows must be updated, requiring additional development time. Agentic RPA reduces this development effort by making dynamic adjustments to workflows on its own.

How Appian agentic RPA differs from other AI automation

Agentic RPA is designed for enterprises that need more than just basic automation. While many AI solutions focus on boosting individual productivity, Appian delivers a platform built for large-scale deployments across your organization.

Unlike tools that are limited to browser-based tasks, agentic RPA extends automation to legacy systems and Windows applications, giving you the flexibility to streamline complex processes across diverse environments.

Agentic RPA also keeps you in control. You manage your virtual machines and define how and when AI-powered automation runs, ensuring automation aligns with your governance policies and operational needs.

Key benefits of agentic RPA

Agentic RPA provides the following key benefits:

• Faster automation setup: Reduces reliance on lengthy robotic tasks and rule-based configurations.
• Adaptive decision-making: Adjusts workflows in real time based on changing data.
• Automate any software system: Works with legacy systems like SAP and Citrix.
• Lower development effort: Automates complex processes without requiring deep technical expertise, so you can spend less time on setup and more time on other important tasks.

Example use cases for agentic RPA

Agentic RPA supports three common use cases:

• Stay resilient to unexpected UI changes: Agentic RPA automatically detects and adapts to interface changes, so robotic tasks keep running without frequent manual updates.
• Automate any Windows software, even legacy systems: Agentic RPA uses smart screen vision and AI-driven decision-making to automate systems like SAP, MS Office, and Citrix, even when field IDs are missing or unpredictable.
• Handle business exceptions dynamically: Agentic RPA recognizes issues like missing or changed fields and keeps the robotic task running instead of stopping.

Stay resilient to unexpected UI changes

Agentic RPA keeps robotic tasks resilient when a user interface changes. Robotic tasks are designed to follow expected patterns, but when a user interface changes, robotic tasks may no longer function correctly. Traditionally, developers manually update the robotic task to account for these changes—like a redesigned login page or a button moving to a new location. Agentic RPA eliminates this overhead by automatically detecting and adapting to interface changes, allowing robotic tasks to continue running smoothly without requiring frequent updates.

Automatic adaptation to UI changes means fewer manual fixes, lower maintenance costs, and uninterrupted automation, even when business-critical systems change.

Automate any Windows software

Agentic RPA automates Windows software systems like SAP, MS Office, and Citrix-based apps that are otherwise challenging to automate. Agentic RPA solves this challenge by combining smart screen vision with AI-driven decision-making, allowing you to automate tasks—even when field IDs are missing or unpredictable.

For example, automating an SAP transaction used to require complex workarounds like keyboard shortcuts. Agentic RPA can navigate the interface, fill in fields, and complete transactions reliably, reducing manual intervention, streamlining development, and improving automation resilience.

Handle business exceptions dynamically without complex workarounds

Agentic RPA handles business exceptions dynamically, without the complex workarounds that traditional automation requires. Managing business exceptions in automation can be tricky, and traditional approaches rely on workarounds that make development more complex, maintenance harder, and automation less resilient. Agentic RPA simplifies exception handling with intelligent, dynamic responses.

For example, if a robotic task tries to access something that is not available or has changed, agentic RPA can recognize the issue and keep the robotic task running instead of stopping.

Dynamic exception handling reduces the need for manual error handling, making automation more robust, easier to maintain, and adaptable to real-world conditions.

Connecting agentic RPA with other actions

Agentic RPA works with existing actions to enhance automation. Agentic RPA supports the following combinations:

• Login automation: Log in to a system, then continue the workflow with other actions to navigate or extract data.
• Data extraction: Capture details from a desktop app and store them in a variable for use in an Appian process model.
• Error handling: If an action encounters an issue, such as a missing field, the process can continue by dynamically adjusting to the interface changes.

Get started with agentic RPA

Ready to get started? Add the RUN AGENTIC RPA action to your robotic task definition.

Best practices for agentic RPA prompts

When creating a prompt for an Agentic RPA action, structure your instructions into five distinct sections to ensure reliable, predictable, and safe execution.

1. Objective & Global Rules Define the ultimate goal of the automation and the global rules of engagement.

• State the core task ("Create a user in the CRM" or "Log in to the SAP application").
• Set the autonomy level / Anti-looping ("Complete the process autonomously" or "Do not retry any action under any circumstance").
• Define the global failure state ("If any validation fails, stop processing immediately").

2. Inputs & Context Tell the agent exactly what data it has access to and where it comes from.

• List the specific variables or data maps provided (username, password, InvoiceData).
• Specify credentials or authentication requirements.

3. Step-by-Step Execution & Guardrails Break the process down into chronological steps. For every action, provide:

• The Anchor: For web, use URLs and menus. For desktop/legacy apps, use visual anchors like window titles ("Wait for a window titled 'SAP'") and visual descriptions ("green tick button").
• The Action: What to click, navigate to, or type.
• Fuzzy Logic / Tolerance: Explicitly state how strictly to compare data. If minor typos, capitalization, or currency symbols can be ignored, say so (treat "1250" and "$1,250.00" as matches).
• Alternative Paths: If the primary action fails, define what the agent should try next ("If the default address doesn't match, click the edit icon and check the list").
• Negative Constraints: Tell the agent what not to touch ("Do not modify the secondary contact").
• Verification & Failure: End every step by asking the agent to verify the action succeeded, and instruct it to fail immediately if it didn't.

4. The "Definition of Done" (Checklist) Provide a summary checklist of every milestone that must be achieved for the whole process to be considered successful. This forces the LLM to review its own work before finishing.

• Example: "Return success only if: Login completed, Data was entered, Save was confirmed, and no errors were displayed."
• Example: “Consider the login successful only if 'SAP Easy Access' is visible on the screen."

5. Strict Output Formatting Eliminate the AI's conversational tendencies so your RPA platform can parse the result.

• Specify the exact expected output (true/false, a specific JSON schema, or a specific ID number).
• Add a strict prohibition on extra text: "Do not return explanations, status messages, or any other text."

Example prompt

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Objective & Global Rules:

Create a new employee profile in the HR system using the provided input map. Complete autonomously. If any required element is missing, validation fails, or an error occurs, stop processing immediately and return false.

Inputs & Context:

Use the `EmployeeData` map, containing: First Name, Last Name, Personal Email, Department, and Start Date. Use the provided standard system credentials for login.

Step-by-Step Execution & Guardrails:

- Navigate to `https://hr.example.com/login` and enter credentials. If login fails, return false.  
- Navigate to "Directory" > "Add New Employee".  
- Enter First Name, Last Name, and Personal Email exactly as provided.  
- Select the Department. Treat minor formatting variations ("IT", "I.T.", "Information Technology") as matches.  
- Enter the Start Date in the `MM/DD/YYYY` format expected by the system.  
- Do not assign any user roles or system permissions; skip the "Access Configuration" tab entirely.  
- Click "Save Profile" and wait for the confirmation banner to load. If the confirmation does not appear, return false.

Definition of Done:

Return Success only if all of the following occurred successfully:

1. Login completed.  
2. Navigation to the "Add New Employee" screen succeeded.  
3. Name, Email, Department, and Start Date were entered correctly.  
4. Access and permission configurations were bypassed.  
5. The profile was saved and the visual confirmation banner was verified.

Strict Output Formatting:

Return only `Success` or `Failure`. Do not return explanations, status messages, error descriptions, or any other text.

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