RPA and AI: Automation on a Whole New Level

Robotic process automation and artificial intelligence are currently under the spotlight. In their quest to maximally increase efficiency, the world of contemporary business has turned to business process automation. However, the fast development of artificial intelligence made this technology available.

When joined together, AI and RPA can bring automation to an entirely new level.

The Definition and Use of RPA

In order to understand how to use the full potential of these two potent technologies, it’s important to first learn how to differentiate them. Before you equip your office with new tools, it’s only natural to go through their properties.

Therefore, let’s explain how RPA and AI work.

Considering the fact RPA is a simpler piece of technology, we’ll start with this one.

Robotic Process Automation is a piece of software designed to take care of all manual activities that take place in an office. Any task that falls into the category of manual labor – which is actually mechanical, redundant work that no one looks forward to – can be placed on the RPA’s to-do list.

This is possible because RPA can copy human actions. This software can accomplish logins, data entry, approve an action, simultaneously work with different platforms, etc.

Other than its properties, there’s another item that makes RPA technology quite popular and desirable – its price. RPA costs significantly less than maintaining an employee. Unlike an employee, RPA isn’t prone to making mistakes, it doesn’t have strictly defined work hours, and it won’t ask for any sick days.

In addition, RPA doesn’t come with a predefined area of expertise. This software can be applied to many different aspects of your business – depending on what you are training it for.

How AI Complements RPA

RPA can only get you so far. Although this is a reliable technology that you can depend on – RPA will always act in accordance with the instructions you gave – that’s not what you’ll always want.

To further explain – RPA is a hard-working, dependable software, but it’s not an intelligent one. When faced with something that’s not a datasheet, RPA will get confused. For example, customer emails all contain a similar amount of information. Unlike with datasheets, customer service comes with variables, considering that the same question can be asked in many different forms.

Free-form language is one of the biggest problems for RPA technology.

This is where AI comes in. Artificial Intelligence is capable of recognizing information even if it doesn’t always arrive in the same patterns.

For instance, if AI would be challenged with a message from a dissatisfied customer, this technology would be able to understand different segments. AI would be able to notice that the type of the email is actually a complaint, it would know which item seems to be problematic, and what’s exactly wrong with the order.

Furthermore, AI would be able to recognize and define the order number, even though it’s not included in the mail, track down the employee responsible for the mistake, and notify them about the problem.

Another situation where AI needs to take over is cognitive reasoning.

RPA can work with a number of criteria. If you teach it how, this software will be able to delegate loans instead of you by determining if a candidate fulfills certain standard – like being of age, having a job, etc. The problem appears when the criteria become complex, and when a decision needs to be made based on a larger amount of information.

So, when not all pieces of information are equally relative and important, RPA isn’t capable of making a proper decision.

Companies like WorkFusion, that offer intelligent solutions for automation, have already blended RPA technologies with AI. With their services, you can start using cheap and reliable RPA with the cognitive abilities of AI.

 

The combination of RPA and AI is a cost-effective, time-efficient blend that, if trained properly, can take care of an important part of your overall workload. When joined together, these two technologies become a highly productive, self-learning system.