Robotic Process Automation vs. Intelligent Automation for Businesses

Staff is relieved of the burden of boring and repetitive duties thanks to process automation and intelligent process automation, which frees them up to focus on more inventive and creative tasks. However, what do these processes refer to? Let’s begin by clarifying each term first.

Intelligent Automation for Business

Incorporating technologies like machine learning (ML), intelligent document understanding robotic process automation (RPA), natural language processing (NLP), and, artificial intelligence (AI) allows for the creation of a digital solution for operational business processes known as intelligent automation (IA), also known as intelligent process automation (IPA). While robotic process automation (RPA) is a technique used to automate repetitive and routine customer care jobs, IA uses artificial intelligence technology to replicate human intelligence and offers the tools and methods needed to finish high-functioning activities that call for deliberation, analysis, and decision-making. This IA technological solution is essential because it gives employees like customer service agents more time to focus on having conversations and building connections with clients.

Intelligent Automation Examples

Intelligent automation enables businesses to concentrate their attention on more crucial business processes. In the end, IA saves time, and we are all aware that time is money. Let’s look at a few instances where IA is being used effectively in various industries.


A treatment or diagnostic can be suggested by intelligent automation software after searching through enormous volumes of structured data and taking into account details like a patient’s medical history or symptoms. A computer can complete tasks that would take a doctor hours to complete. As a result, medical personnel can devote more time to patients rather than laboriously searching through databases of medical research.

Market for Intelligent Virtual Assistants

Companies are increasingly choosing intelligent virtual assistants (IVAs) over chatbot alternatives. IVAs use IA to start human-like conversations, as opposed to standard chatbots that use scripts to simulate human conversations and interactions. IVAs can correctly respond to questions for which they haven’t had specialized training or programming thanks to natural language processing. They utilise machine learning algorithms and deep learning technologies to expand their vocabulary, comprehend slang terms, and respond accurately to customer questions. IVAs provide customers with a great experience through educational and casual chats.

Onboarding and Offboarding Employees

Processes like onboarding and offboarding can involve countless hours of labor from employees. Although acquiring resignation letters, processing payments, completing paperwork, and receiving training are all very straightforward chores, they can be tiresome and time-consuming. However, these procedures can be shortened and successfully accomplished in a timely manner with IA. Employees are free to focus their attention on other areas while computers handle the busy labor.

Inventory Management

Traditional inventory control frequently involves substantial manual processing that takes a long time. Businesses can no longer rely on inventory personnel to execute technological duties like producing invoices and work orders thanks to clever automation. IA is instead used to manage back-office tasks including supply chains, fulfillment and shipping, inventory tracking, and more using automated inventory control systems.

RPA for Business

Robotic process automation (RPA) refers to programs, software or scripts, that automate simple, routine, rule-based processes that take a lot of time to complete manually. RPA lowers labor expenses while simultaneously minimising human mistakes.

These “robots” have been designed to carry out predetermined duties precisely and on their own. They are capable of information retrieval, unstructured data analysis, transaction processing, and even interfacing with other digital systems.

RPA was one of the first technologies to be used in the financial sector, but now businesses from many sectors, like retail, manufacturing, supply chain management, healthcare, and HR services, employ it.

RPA Examples

There are numerous RPA application cases in various businesses that can rely on automation to release some workers’ time for creative work. Several of the most typical ways that robotic process automation is used are illustrated in the examples below.

Payroll Management

Year-round human labor is needed for numerous steps in the payroll processing process. Fortunately, operations like producing pay stubs, figuring out expenses and deductions, collecting and storing crucial data, and producing annual reports may all be automated using RPA technologies. Payroll processing automation lowers costs, improves accuracy and efficiency, and removes the stress of understanding complex tax law.

Web Analytics

Understanding their audience better depends on the ability to analyze vast amounts of online behavioral data, which is used by all businesses. Automated web analytics tools can precisely forecast consumer behavior, enabling businesses to promote goods and services in light of this new knowledge. This not only increases sales but also improves consumer satisfaction.

Credit Card Requests

RPA technology is used to process the majority of credit card applications in financial organizations. The software is set up to gather data, examine paperwork, perform background and credit checks, and then determine whether or not to grant credit to a potential applicant.

The Primary Distinction Between RPA and Intelligent Automation for Business

Intelligent automation (IA) is frequently confused with robotic process automation (RPA), although the two are distinct from one another. IA systems can have RPA capabilities, but RPA does not require IA capabilities to work. RPA refers to technical tools and procedures that do time-consuming operations autonomously and significantly faster than people. These jobs are frequently rule-based, repetitious, and straightforward.

RPA can be challenging at times since the systems are configured to closely adhere to a set of rules. For example, if a consumer enters wrong information, the system will fail to perform the task. Here is when intelligent automation enters the picture. IA is incorporated when RPA is no longer effective, enabling the system to execute complicated operations utilizing AI logic and decision-making methods.

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