As an executive there’s no doubt that you’ve been hearing about and considering automation software to help carry out business processes. There’s been a lot of talk about robotic process automation, intelligent process automation, and hyperautomation. Here, we will take a deep look at intelligent process automation vs robotic process automation to clarify similarities and differences.
Robotic process automation (RPA) is technology that enables bots to carry out tasks that a human would otherwise have to do. RPA bots can fulfill rule-based and structured tasks that are repeatable and frequently occurring. They do so by first being trained or programmed by a human. Then, they can be left alone (unassisted) or work alongside a human (assisted) to transform inputs to outputs.
Robotic process automation uses structured data. As such, it is commonly deployed to complete tasks like data entry, opening accounts, onboarding clients, and processing data. RPA is best applied in work processes that are performed on a routine basis and according to guidelines (rules).
RPA’s benefits include:
It is easy to confuse robotic process automation (RPA) with intelligent process automation (IPA). However when looking at IPA vs. RPA, the major differentiator is that intelligent process automation involves artificial intelligence (AI).
Intelligent process automation takes advantage of natural language processing, intelligent document processing, machine learning, and the like to be able to perform in line with human intelligence.
For processes that require high-function tasks like analysis, creativity, problem-solving, and judgement, intelligent process automation can play the part. Unlike RPA which mimics human action through training and rules, intelligent process automation can learn to perform the actions better with more data and time. IPA is able to learn over time because of machine learning and natural language processing (NLP).
Intelligent process automation is also more specifically used and deployed in comparison with robotic process automation. In most instances, it’s very quick and easy to get a RPA solution up and running.
On the other hand, IPA is used for defined purposes and complex scenarios which may require additional configuration. That being said, intelligent process automation can be used in a wide array of scenarios, including answering clients’ questions in real-time, improving regulatory compliance, and analysing portfolio data to communicate with customers about their finances.
To put it simply, hyperautomation is the overarching use of technology to automate and execute tasks and provide analysis in an effort to optimise decision-making and functions.
You can think of hyperautomation as the category in which robotic process automation, intelligent process automation, and machine learning sit alongside decision management systems and integrated tools that allow people to better manage a business’ operations.
Hyperautomation does not replace the need for humans, Instead, it contributes to the transformation that is underway across industries in which data and insights are able to direct the optimal path forward and also reduce the need for humans to perform repetitive, data-heavy tasks.
We’ve worked towards understanding the meaning of these technologies and terms, but to clarify the differences, here’s a quick summary of intelligent process automation vs robotic process automation vs hyperautomation.
Robotic process automation is a way to automate low-level, repetitive, and structured tasks. RPA bots are trained to mirror what a human would otherwise do. It can work in place of a person or with a person to perform the technical elements of a process. RPA’s uses are wide-ranging, but they are constrained to handle rule-based tasks.
Intelligent process automation does have some elements of robotic process automation, but they work in tandem with machine learning, analytics, workflows, natural language processing, and artificial intelligence.
These factors allow for IPA to manage higher-level tasks that can work as if it was human intelligence. Thus, IPA involves creativity, judgement, analytics, and decisions in its execution. For this reason, IPA tasks don’t have to be strictly rule-based as the technology uses machine learning to improve itself over time.
Hyperautomation refers to the overall infrastructure of the aforementioned technologies and business systems. By combining AI tools, RPA, and IPA, hypermautomation enables businesses to get work done faster and smarter.
From just knowing what RPA and IPA can do, it’s clear that using them can only make your business better. Even though most business leaders know that automation is a. Inevitable and b. Powerful, some stil are hesitant about incorporating such tools in their business.
In an effort to calculate how many companies are using IA and RPA, Everest Group performed market research of what they call “Pinnacle Enterprises.” These are companies that are strategically-focused for the long haul and, as such, are using IA.
In conducting their research, they found that all types of organisations of all different sizes are adopting RPA. Within Pinnacle Enterprises, the organisations have realised a 50% improvement in operations.
Intelligent process automation provides a long list of benefits to organisations of all sizes. The combination of robotic process automation with machine learning and artificial intelligence means that IPA can:
To make automation a reality within your business, you can take one of two paths. Either you pick solutions that integrate RPA and artificial intelligence through the use of APIs/web services, or you select an integrated solution that delivers all of these technologies innately. This allows you to automate a process from start to finish smoothly without having to compare intelligent process automation vs robotic process automation.
Opting for an integrated platform will make it easy to scale and deploy your software solution. Rather than having to manage integrations and pay separate vendors, you just have to get accustomed to using one system that does it all.
A single platform will likely result in less costs overall and decrease the need of an expert IT team to piece together disparate systems. One system means that all your data is neatly stored, organised, and always readily accessible for advanced analytics and reporting.
Intelligent process automation is made up of five main technologies, which we’ve mentioned briefly, but will expand upon now:
Examples of intelligent process automation can be found in any industry. Let’s consider this example from finance services.
Banks and service-based financial providers can utilise IPA to pull data from customers’ phone calls, emails, and chats. They can then sort their customers at different stages of their journeys to provide customised offerings and pre-empt issues before they arise.
IPA tools can also update customer profiles automatically as new data enters the system through these various channels. Then, IPA can be deployed to update customers on the status of their finances or portfolios.
The different types of automation available are changing how businesses run. Whether you are considering intelligent process automation vs robotic process automation or the use of multiple technologies to operate more efficiently, an integrated platform such as a data automation platform can be the answer to all your needs.
With hyperautomation, you are able to transform your organisation to better serve customers, employees, and stakeholders.
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