How Intelligent Process Automation Can Make Your Job Easier

How Intelligent Process Automation Can Make Your Job Easier

Automation is nothing new for businesses. Steam-powered machines date back to the First Industrial Revolution, and we’re now in the midst of the Fourth Industrial Revolution, often called Industry 4.0. While the Third Industrial Revolution introduced businesses to the digital age, the element that separates Industry 4.0 is how many intelligent automated processes can be completed with no human intervention.

Intelligent process automation (IPA) refers to the use of a wide range of technologies to improve business processes. This includes making tasks more efficient, safer, and freeing up human workers from some of the most tedious and repetitive tasks. Even if you aren’t familiar with the technical details behind intelligent automation, you’ve certainly encountered it before.

If you’ve ever gone online to order a T-shirt and customized the size, color, or any other elements, you’ve seen IPA in action. The display of the shirt (and its price tag) updates every time you change one of the details. This is made possible thanks to configure/price/quote (CPQ) software, and it’s just one great example of process automation at work. Here’s a breakdown of the different types of IPA and how each one can make jobs easier in your enterprise.

Digital Process Automation

Any large business that wants to stay relevant has either completed or is going through a digital transformation. This is, essentially, the process of replacing legacy systems with up-to-date digital software solutions. The rise of big data means that traditional methodology no longer works for efficient business processes, so automation technologies need to take over digital processes.

DPA implementation has drastically improved data management for enterprises, which can now collect data from previously disparate data silos in one convenient source of truth, thanks to API-led integrations. This allows businesses to continuously collect structured and unstructured data from a variety of sources and analyze it in near real-time. This is, naturally, great for business intelligence, and the analysis of historical data combined with current data can even help make predictions about future business needs.

A good example of DPA is when a customer reaches out to a customer support contact center and is greeted by an interactive voice response (IVR) system or chatbot. This automated process gathers customer information and connects them to the right support agent for their needs as quickly as possible.

Robotic Process Automation

RPA is the form of intelligent process automation that most people are likely familiar with. Robotic process automation has been used to improve workflows and save humans from performing difficult manual tasks for centuries now. Robots are frequently used in assembly lines and on manufacturing floors to perform routine tasks with little supervision. Bots are also frequently used in warehouses to operate forklifts, thanks to the use of AI and sensors. RPA tools make it easier to eliminate bottlenecks in the supply chain and free human workers up for more core business tasks.

Artificial Intelligence


AI is the newest form of IPA, and modern advancements in the field are generally made possible by machine learning (ML). Computer algorithms can be trained using structured data, unstructured data, or some combination of the two in order to achieve desired results. These algorithms are able to build and improve on themselves without human intervention. It might sound like the stuff of science fiction, but examples of machine learning can be seen every day.

A common example is the use of natural language processing by digital assistants to understand and carry out verbal commands. Anyone who uses smart home technology should be quite familiar with this. Such cognitive technology is often used in large enterprises for advanced data analytics. Computer algorithms can analyze complex big data sets far faster than a human mind ever could, and this gives business leaders a holistic view of the company. AI is also frequently used to speed up processes that take too long via traditional methods.