According to CIO, RPA applies technology alongside logic to automate business processes. Its rapid adoption in several industries comes from the inherent benefits the technology brings to companies. However, RPA can be cumbersome to implement, and there needs to be an overarching focus on connectivity. The technology is constantly evolving, with innovative new approaches needed to stay relevant to business needs and integrate with other technologies companies are using.
In this article, we’ll look at how RPA works in concert with emerging technology such as Big Data and Artificial Intelligence to make for a more connected and well-rounded system.
Both AI and Big Data have risen in popularity over recent years. Big Data may be defined as multiple streams of incoming data and classified as either structured or unstructured. AI is a methodology of using computer software to train a system to perform basic tasks and make simple decisions.
With time, these systems have become dependent on each other. The volume of data that Big Data streams create is impossible for a human being to analyze efficiently. Thus, companies have adopted AI to help them deal with those streams of data. The Information Commissioner’s Office of the UK (ICO) describes this as using AI to unlock the potential of Big Data.
However, most studies into Big Data only offer insight into its use in customer relationship management. Very little information has been published regarding its use in the automation of business processes. Towards Data Science calls this “Intelligent Automation” — a marrying of data science and RPA. The core elements of intelligent automation come from using a connected system to feed input into a processing center, then using the results generated to improve the system further. Machine Learning, alongside the use of Artificial Intelligence, has made it easier than ever before for businesses to utilize AI agents to train their systems in RPA.
Most companies are considering adopting RPA alongside AI, but their approach to this adoption can make a world of difference to its effectiveness. AI isn’t a “magic bullet” that can solve all of a business’s problems, and so companies need to be selective about where they implement their AI solutions to guide their RPA modules.
Ideally, companies should be looking at simple-to-automate tasks at first. By training the AI on these simple RPA systems, the processing system can learn what constitutes success and failure. It allows businesses to be more conservative with their RPA and AI rollout. They reap the benefits of the new technology but don’t have to bear a massive cost if the system doesn’t perform as expected.
RPA and AI have a broader scope for application than just manufacturing processes. Administrative processes can also benefit from the intelligent use of RPA and AI. Arista Consulting has developed ARISTAXPRESS for this particular purpose. By combining an OCR processor to read invoices, the AI can parse the results into a QAD ERP consumable format.
Some of the features that ARISTAXPRESS provides to a business include:
If you’re looking for a method of implementing automated invoice processing, then ARISTAXPRESS was developed for this express purpose. Visit Arista Consulting today to get started.