Growing up in the second half of the 20th century, many of us imagined a future where robots did everything for us. From cooking, to cleaning, to driving us to work. The most optimistic among us took it even further, like American chemist and Nobel Laureate Glen Seaborg. In 1967, Seaborg predicted that by the year 2020, that there would not only be robots to perform household chores but also an intelligent species of animals capable of performing manual labor.
So, while we do not quite live in the world that Seaborg envisioned, robots do play important roles in our daily lives. Technologies like robotic process automation and intelligent process automation are changing the ways that organizations produce and provide goods and services, while also making work for enjoyable for employees. In this article, we will explore robotic process automation and intelligent process automation in more detail and conclude by looking at the key differences between the two.
What is Robotic Process Automation?
Robotic process automation (RPA) uses technology to emulate human tasks to complete a business process. The types of human actions that RPA bots mimic are repetitive computer-based tasks that are rule-based, have defined inputs and outputs, are repeatable, and occur frequently.
Robotic process automation utilizes structured data to complete tasks. Examples of tasks where RPA technology works well are data entry, data processing and mapping, and client onboarding and new account openings.
RPA is often confused with artificial intelligence. While some argue that RPA qualifies as a form of AI technology and RPA is often combined with AI, the two technologies are distinct. Unlike AI, RPA bots generally do not have the ability to learn. With RPA, if something changes in an automated task, the bot will not be able to adjust and figure it out on its own. RPA is designed to mimic human actions while AI is intended to simulate the ways that humans think.
What is Intelligent Process Automation?
Intelligent process automation (IPA) builds upon and encompasses RPA with artificial intelligence. IPA not only mimics human actions but can learn to do them better over time. IPA typically consists of four core technologies:
- Machine learning
- Natural-language processing (NLP)
- Intelligent workflows
We already discussed RPA above, let’s briefly look at the other three.
Machine learning (ML) is an application of artificial intelligence. It gives systems the ability to access data and learn from it without being programmed. ML uses algorithms that are either supervised or unsupervised to identify patterns in structured data. Supervised algorithms create inputs and outputs prior to making predictions of their own. Unsupervised algorithms observe structured data and develop insights from pattern recognition.
When combined with RPA, bots can evaluate their efficiency and make adjustments to improve processes. Through deep learning, systems can utilize data gathered in one context to improve upon others.
Natural-language processing (NLP)
NLP is a software tool that parses human language to give machines the ability to read, understand, and derive meaning. The technology works through a combination of techniques like statistical and machine learning to algorithms.
NLP is commonly used to create chatbots. Chatbots use Robotic Process Automation to communicate with human users and to complete tasks. Among other things, NLP helps chatbots to determine the meaning of interactions and to provide users with relevant responses.
Introducing bots into workflows can lead to confusion and inefficiencies. Human stakeholders need to understand their roles and responsibilities. For instance, when does a robot handoff a task to a human, and vice versa? Process management software helps stakeholders to understand and track processes to avoid bottlenecks.
IPA plays an important role in improving both employee satisfaction and customer experiences. For employees, they better understand their roles and appreciate the opportunity to work on tasks that are less repetitive and offer more value to their organization. Value is passed onto customers since more resources can be devoted to providing excellent customer service.
Customers also benefit from user-friendly IPA technology. For example, new customer onboarding has traditionally been a drawn-out process, especially in industries like banking where organizations must collect large amounts of information and documentation. With IPA, however, organizations can easily capture and extract data from onboarding documents, reducing wait times, and significantly improving customer experiences.
What are the key differences between RPA and IPA?
Intelligent Process Automation is basically an upgraded form of robotic process automation. Unlike RPA, intelligent process automation can understand context, learn, and iterate. IPA can also handle both unstructured and structured data and supports some level of informed decision-making. Informed decision making can further be divided into task level or process level automation. IPA helps organizations to access and analyze unstructured data like images or text that is inaccessible by other means to gain important insights.
IPA can take unstructured data and turn it into structured data for use with RPA technologies. For reasons like these, the technologies are not mutually exclusive but can work together to optimize business processes.
So, while we may be a long way off from robot servants that do our laundry and mow our lawns, robots are already and will continue to play increasingly important roles in our daily lives. Robotic process automation makes work less tedious and allows organizations to scale their operations to provide more value to customers. Intelligent process automation builds upon RPA, giving systems the ability to automate tasks and to learn from them.
For organizations that are new to automation, getting started with RPA technologies is the way to go. They are easy to use and can be implemented with low-code business process management software. Once automation has been introduced into one or more processes, organizations can consider introducing intelligent process automation (IPA) for complex business processes.