Artificial intelligence (AI) and Robotic Process Automation (RPA) are two technologies to automatize activities in organizations and achieve more efficient goals and results, while reducing operational costs and saving time. 

Although the bigger concept of artificial intelligence involves RPA, they are not the same thing. Basically, RPA is a software that can mimic human actions and AI is the simulation of the human thinking. 

But that definition doesn’t help a lot on understanding the differences between the two of them, let’s go deeper! 

Robotic Process Automation (RPA)  

As established, RPA is the use of software called “robots” that are specialized in standardize and automate cyclic tasks. So, the thing about RPA is that it doesn’t learn from repetition. 

They will always perform the same way and not seek a way to optimize the process. Then, the major use of RPA is to offload repetitive tasks and free up human time. 

Using RPA, even though it doesn’t try to find better ways to achieve results, can lead to: 

  • Accuracy: because it minimizes human action and costs. 
  • Compliance: it follows rules precisely. 
  • Speed: complete tasks faster than humans. 
  • Reliability: they are always available to complete tasks, minimizing delay. 

RPA have huge impact on business that deal with a lot of data. Because they can process a considerable size of information while maintain accuracy and without manual input. 

Artificial Intelligence (AI) 

On the other hand, AI is based on thinking and learning, and do way more than creating rule-based engines to automate repetitive tasks. It doesn’t only automate the process, but the decision making. 

While RPA can reduce impact on employees, AI seeks to replace human labor. That can happen because the process of AI is based in learning, reasoning and self-correcting.  So, RPA uses structured inputs and logic, AI seeks to develop its own logic.  

AI can capture data from material world and then make decisions based on the best result. It doesn’t require data to be structured to take information out of it. That allows AI perform tasks that aren’t rule-based 

AI and RPA together 

Even though AI and RPA aren’t the same thing, they can be used together to optimize results. When they work together, we get what is called a Intelligent Process Automation (IPA) or Smart Process Automation (SPA)

While the RPA deals with the repetitive tasks, the inclusion of machine learning models can allow the software to learn during the cycles, add data and recognize patterns. 

Of course, that’s the best solution for organizations that deal with both structured and unstructured data. But is also possible to use only one of them and still make process more efficient. 

For instance, RPA works when there are multiple sources of data, the process is repetitive, there is a solid way to define start and finish and high volume of structured data.

On the other hand, you can use AI for actions that require a more complex system. So, when you don’t have certain tasks, or the process are not rule-based and use unstructured data. 

AI in Procurement 

As said before, AI focus on solving problems with large amounts of data. By that, they learn the successful patterns and apply it to the operation. AI can make procurement more efficient and trustworthy.  

With AI, your procurement will have better decisions, because it can provide timely analytics and data-driven insights on sourcing and other aspects of order. 

It will help identify new opportunities inside operations, such as new suppliers, better routes and inventory optimization. Also, it will help align the whole operation across all units or different locations. 

As established, RPA and AI can automate manual tasks, freeing time for employees act in a more strategic way.  Finally, it can identify new markets to enter and optimize the relation between suppliers, with a data-driven management. 

In sum 

AI and RPA are technologies to automate process and workflows. They can perform actions as humans and have better results while reducing operational costs and saving employee time. 

Although they are very similar, we can synthesize the difference as Thinking vs Doing and Process Centric vs Data Centric.  

That means, the AI process try to emulate the human thinking, so the process of decision and judgement on the information available. RPA only complete tasks based on rules. 

On the other hand, RPA focus is the process. The AI is data-centric, it can extract results from unstructured data and learn from it, adapting its decisions to scenarios. 

With Supply Brain the purchasing process is automated following intelligent rules and it can be done 100% autonomously, i.e. without human intervention for simplified purchases.

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