Robotic process automation (RPA) andintelligent automation (IA)remove the burden of repetitive and tedious tasks that draw out organizational productivity.These technologies free up resources so they can focus on high-value tasks. However,RPA and IA are different from each other. In this blog post, we define each concept and outline itsunique benefits.
What is intelligent automation?
Intelligent automation (sometimes called intelligent process automation) is a digital solution that combines AI, machine learning, intelligent document processing, natural language processing, and robotic process automation (RPA). In simplest terms, using IA means deploying a machine or technology to perform mundane tasks intelligently. IA can process higher-functioning tasks requiring some analysis, reasoning, decision, and .
Businesses need to implement a self-evolving IA strategy toconstantly improve process efficiencies, cope with digital disruptions, and keep up with competitors.
Find out how IA can increase enterprise agility.
What is robotic process automation?
Gartner defines RPA as a noninvasive integration technology that automates repetitive, routine, and predictable tasks via an orchestrated user interface interactions that emulate human actions. It refers to scripts, software, or applications that automate rule-based, repetitive, and straightforward tasks that are typically time-consuming when manually performed. Thus, it helps reduce labor costs while preventing human error.
RPA can either be unassisted or assisted. Unassisted RPA deploys bots on a centralized server for manual control, making it ideal for automating workflow scheduling and end-to-end tasks from a central aspect of control. Assisted RPA deploys bots on individual desktops, so a human resource can efficiently perform some tasks while relying on the bot to perform more technically complex or cumbersome tasks.
How do RPA and IA work together?
Intelligent automation is often mistaken for RPA. They’re related, but they’re not exactly similar to each other. IA platforms may have RPA capabilities, but RPA does not require IA capabilities to work.RPA systems are programmed to follow a strict set of rules, which can be problematic in some cases. Following are some use cases where IA is :
- Financial services – IA helps banks and other financial institutions speed up customer response times while complying with stringent regulations.For example, an IA platform can replace legacysolutions to ensure that loans are closed faster while improving the overall client experience.
- Government – IA can introduce efficiencies for processes that involve manual form-filling, such as applications for passports, birth,and marriage certificates, driving licenses, etc. This eliminates mundane tasks to allow employees to focus on serving constituents.
- Manufacturing – Using IA in supplychain management allows all paperwork to be done in a centralized digital location.This saves time by reducing manual input while reducing human errors. For example, automation can connect existing ERP with other systems to create a central point of reference for all orders and thus reduce lead time.
Intelligent automation uses RPA to automate repetitive and routine tasks. It simulates human intelligence using artificial intelligence technologies and provides the techniques and tools to perform high-value tasks that require decision-making. IA can increase process efficiency, optimize back-office operations, improve the customer experience, reduce costs and risks, optimize workforce productivity, and ensure effective monitoring and fraud detection.
Get in touch with InfoCepts to learn how data-driven IA and RPA can improve your business.
Additional sources: https://www.nitcoinc.com/blog/intelligent-process-automation-vs-robotic-process-automation/
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