AI-powered automation has become more available than ever before, and many organizations, including SMEs, are starting to utilize it to its right capacity to gain a competitive edge.
The age of automation has arrived quicker than expected. According to a study by the World Economic Forum, over 80% of business leaders are planning to speed up the integration of process automation tech and expanding their use of remote work in the post-pandemic business environment.
One of the biggest contributors to the proliferation and versatility of business process automation (BPA) solutions is the integration of smart AI. Not only is AI the most prominent technology on the radar for businesses today, but it is also the most accessible as AI can be deployed on the cloud to allow multiple applications cross-talk and share data to make repetitive processes more streamlined, efficient, and accurate.
In this blog, we’ll look at how AI works in automation and its various business benefits.
How does AI benefit business process automation?
The deployment of AI on the cloud is one of the most common entry points to automation for modern businesses, specifically small and medium businesses. It has become almost mandatory for businesses to have at least one cloud platform to store business data virtually and enable the use of collaboration tools that are compatible with remote working and multi-geography operations. The next big step for enterprises, then, is to streamline and automate business functions and infrastructure management using AI.
AI for enterprise process automation is designed to solve complex business problems where human-like intelligence is replicated to imitate human workflows. Thanks to the advancements in the field, its scope, functionality, and accessibility have grown exponentially. As AI becomes more prominent and available across the world, we have significantly reduced human dependency for low-value tasks, while employees can focus on more crucial elements of their job roles and provide more creative inputs.
From the automation perspective, artificial intelligence is perhaps the most crucial technology for enterprises to integrate, most importantly for its ability to reduce errors and operational costs by self-learning and upgrading itself. Machine Learning (ML) allows systems to learn from numerous data sets and the machine’s own past actions and interactions and improve itself without continuous programming. As organizations go through an enormous amount of data every day, ML can draw meaningful insights from various data points and work on minute details that even an expert human eye can miss.
Many fast-growing companies have realized the potential of AI automation early on and are now using it to make their business environment more agile, responsive, and adaptable to external uncertainties. And the rate of adoption is growing drastically. As per a Gartner study, 69% of all managerial work will be automated by 2024.
But how does AI work in various categories of automation? Let’s find out.
Types of automation and role of AI
We often classify automation within businesses into Robotic Process Automation (RPA) and Business Process Automation (BPA) solutions or platforms. It’s important to understand the key differences among these variants before understanding the role of AI in it.
Robotic process automation, also referred to sometimes as robotic process automation, is a software system that makes it easier to build, deploy, and maintain robots that emulate human intelligence to conduct repetitive business tasks quickly and accurately. As RPA replicates repetitive human actions like extracting data, downloading, and copy-pasting data from one resource to another, it requires little to no AI support as the RPA system can work on its own and doesn’t require specialized learning to do its task effectively.
Business process automation (BPA), on the other hand, is used to automate and orchestrate business functions in their entirety, from start to finish. Some common use cases of BPA with AI include automating supply chain processes, sales forecasting, providing after-sales services, and more. For example, a banking company can automate its entire loan distribution process from day 1 using BPA. Here, AI plays the most important role, as it needs to learn about an entire system of calculations and derivations, emulate it, and adapt it to a variety of data.
Now that we know the role of AI in RPA and BPA, it also provides the following capabilities that further expand your automation capabilities:
Interactive AI: The biggest strength of AI is its ability to mimic human intelligence, not only with its functionality but also with the way it interacts with people. Using AI, you can create a smart chatbot as a customer service front that provides predictive queries to customers and provides the most relevant answer in real-time. Interactive AI also learns from the variety of questions to upgrade itself without the need for constant programming, which makes it capable enough to automate even on voice commands.
Natural Language Processing (NLP): Although programming has its own language, it doesn’t always work when a machine has to interact with actual humans. NLP empowers man-machine communication with an AI that understands, reads, and derives meaning out of the language we use in our everyday lives. Nowadays, NLP has advanced to such a point that it also understands the mood of the user with their tone of voice to give a better customer experience at all times.
Add AI-driven capabilities to your BPA and cloud deployments
As your company grows, your processes change accordingly. Needless to say, the software supporting your process automation would therefore need to change too. That’s where our team comes in to maintain and upgrade any existing BPA deployment.
VBeyond Digital provides ROI-driven BPA and AI solutions to large enterprises and small and medium businesses, customized to their unique needs. We serve as end-to-end automation and cloud implementation and support partners for your organization, helping you build the right strategies and then with implementing enterprise-wide change.