How AI App Learning Process Can Gain from RPA

AI (Artificial Intelligence) app learning can be best described as the process through which the applications that power AI systems acquire the knowledge they need to perform various tasks well.

It is important to remember that AI revolves around the development of computer systems that are capable of fully mimicking human cognitive processes. And one of the key human cognitive processes is, of course, the learning process – through which we acquire the knowledge necessary for us to perform various day to day tasks. 

In a similar manner, AI applications need to acquire knowledge to perform the various cognitive tasks they are given on a day to day basis. And that is what AI app learning is all about. In this article, we venture to explore how the said AI app learning process can benefit from RPA (Robotic Process Automation).

Find out how AI applied learning can be achieved from RPA

In RPA, software bots get to perform both low-level and high-level tasks using preprogrammed logic. Now there are at least three ways in which an AI app learning process can gain from RPA.

Firstly, by monitoring how the RPA bots are able to perform various tasks, AI systems can come up with even better ways of performing the same tasks. Because they are designed to mimic human cognitive processes, the AI systems are perfectly capable of ‘monitoring’ the operations of RPA systems. 

The difference between the AI and RPA systems, by the way, is in the fact that the AI systems have greater cognitive capability. For instance, AI systems are able to operate on their own logic, while RPA systems depend on pre-programmed logic to operate.

 Leveraging on that, they can just monitor the steps by which the RPA bots are performing tasks, then find ways of tweaking those steps to enhance efficiency.

Secondly, by monitoring how the RPA bots are able to perform tasks, AI systems can figure out how to perform different but related tasks. So this is about learning the logic by which task A is performed, then applying that logic to the performance of task B.

Thirdly, RPA bots can be linked with AI systems, giving them the data that they need to hasten the learning process. One area where RPA bots excel in is that of data extraction.

So what you can do is interlink the RPA bots with the AI systems, to funnel the data that the RPA bots extract into the AI systems. The AI systems then analyze the data and use it to sharpen their ability to perform various tasks.

AI application service with RPA

The fact that AI app learning can benefit from RPA opens up a huge array of possibilities. It means that AI and RPA don’t have to be viewed as separate parallel entities. On the contrary, we can leverage the power of RPA to enhance AI capabilities. 

And this is where the AI application service with RPA comes into the picture. Using AI application service with RPA, it becomes possible to achieve results that would be totally unachievable using RPA or AI separately.

Conclusion

Contact SmartOSC DX at email [email protected]  for AI application service with RPA, through which you can achieve the best possible automation solutions for your enterprise needs.