What is the difference between RPA and Intelligent Automation (IA)?

All answers to this question.

You're spot on—RPA is the "muscle" and AI is the "brain." When you combine them, you get Intelligent Automation (IA), often called "Hyperautomation." A classic use case is Document Understanding. Standard RPA struggles with invoices that don't follow a fixed template. By integrating a "Machine Learning Extractor," the bot can "read" the invoice, identify the "Total Amount" regardless of where it's placed, and even handle messy handwriting. The key is to use the RPA bot to fetch the document, send it to an AI model for "classification and extraction," and then use the bot again to enter the structured results into your ERP.

   Answered 2025-01-17 by Elizabeth Martinez

If we integrate AI, how do we handle the "Confidence Scores"? Should the bot automatically reject a transaction if the AI is only 70% sure?

   Answered 2025-01-19 by Steven Clark

• That is a critical design decision, Steven. We typically set a "Confidence Threshold." For example, if the score is >90%, the bot proceeds. If it's between 70-90%, it sends a task to a human for "Validation." If it's <70%, the bot flags it as an exception. This "Action Center" approach ensures that the AI learns from human corrections over time, improving its accuracy. It’s essential for maintaining data integrity while still benefiting from the speed of automation for the majority of clear-cut cases.

     Commented 2025-01-21 by Anthony Lewis

"Process Mining" is another part of IA. It helps you find out what to automate before you even build a bot, preventing you from automating a broken process.

   Answered 2025-01-23 by Barbara Robinson

• Spot on, Barbara. Automating a bad process just makes it fail faster. Mark, make sure your roadmap includes that "thinking" phase Elizabeth described!

     Commented 2025-01-25 by Elizabeth Martinez