<img height="1" width="1" style="display:none" src="https://www.facebook.com/tr?id=1582589251849414&amp;ev=PageView&amp;noscript=1">

RPA & AI: Same Difference?

Healthcare automation takes many different forms. While it is sometimes beneficial to think of business automation as a monolith, it is –– in reality –– made up of many different technological applications. Two of the most commonly used healthcare automation features are Robotic Process Automation (RPA) and Artificial Intelligence (AI). RPA and AI can both improve how a healthcare organization operates –– from enhancing patient care, to increasing internal productivity. However, RPA and AI are also both very distinct technologies and they function in very different ways. Here, we’ll take a closer look at RPA and AI and explain what healthcare professionals need to know about them. 

The Basics of RPA

In simple terms, RPA bots are designed to perform repetitive tasks based on pre-programmed logic. RPA software cannot “learn,” “think,” or replicate human subjective judgment. It is, first and foremost, a tool. 

Part of the reason that RPA and AI are so often confused for each other has something to do with the increased global interest in RPA. Even though the underlying technologies have been around for decades, in the last several years global spending on RPA software has been doubling annually. This phenomenon has effectively served to lower the bar for implementation; reducing costs, creating new efficiencies, improving ease of use, and the proliferation of vendors with expertise in the technology right along with it. 

The shift to RPA also coincides with a worldwide eagerness across industries to take full advantage of the promise of AI and Machine Learning (ML). For many, RPA serves as a necessary/less intimidating first step toward “true” automation –– AI. Once smaller, more routine parts of a process or workflow are running autonomously, the addition of AI technology can be integrated to deliver more complex, cognitive automation.


While RPA and AI often work in concert, they are fundamentally different technologies. RPA, actions are taken to perform tasks in a process, in a set number of ways, and within set intervals. Conversely, AI actions are not necessarily process-based at all. AI and ML algorithms are data-driven and trained on sample datasets to perform the work they are designed to do. They are then set up to function inside operational workflows to make decisions.

Another key difference is the way in which RPA and AI differ on requirements. RPA requires little-to-no subjective decision-making. AI, on the other hand, requires active decision-making with some degree of “thinking” and “learning” relative to natural language, reasoning, judgment, context, and providing insights.

RPA and AI Examples

Our own work in this area serves as an example. We worked to automate the claims management and billing processes for a client that provides in-office infusion services. The project used RPA to automate the work involved in claim status checks, claims settlement, and EOB retrieval, which had previously been completed manually. Tasks like logging in to 10-15 different payor websites, searching for and retrieving documents, and then downloading or saving to PDF and storing in an organized folder structure are now handled by a bot.

Were we to take things a few steps further and build a predictive model that could identify and flag claims likely to be delayed or denied based on the information in the stored documents, AI would be required to “read” the documents and extract the pertinent information needed to make a determination. Based on the data, AI would then “decide” if the claim in question should be flagged as likely to be delayed or denied. This would make it possible to proactively work the claim to improve revenue flow and “learn” how to improve accuracy over time based on the accuracy of those decisions.


As noted above, even though they are distinct technologies, AI can play a role in advancing the capabilities of RPA. Added to a high-performing RPA process, AI and ML can augment the human workforce (not replace it!) with digital labor by performing complete business functions from start to finish.

Contact Us

If you’d like to learn more about the other top myths surrounding RPA, download the full eBook or contact us here to get started with us today.

Have any questions or want to know more? We have answers.

Contact Us Today

Subscribe to Our Blog


Did you know if hospitals do not achieve productivity growth by 2025, up to 60% could face negative margins? Amitech helped Mercy save $3M in the first year!


Ring in the new year by learning about the top 4 benefits of data analytics in healthcare in 2023!


Technology is changing the game for businesses. Here are the top 5 intelligent automation trends in 2023!