Robotic Process Automation (RPA), Intelligent Automation, and Hyperautomaton often cause confusion, when it comes to choosing the best automaton software solution before starting your digital transformation journey. Some companies end up with complex challenges as they start in a hurry to experience scaled results without any prior knowledge about the software automation process. Some companies end up with a much larger portfolio of standard operating systems as they adopt new digital technologies without understanding the need to re-engineer their existing business processes first. In this article, we have shared a complete guide to –
How they differ from each other – how to choose the best automation application for your business.
Robotic Process Automation (RPA)
RPA is the lowest-level automation of any business process. According to Gartner, RPA can be defined as a noninvasive integration technology applied to automate routine, repetitive, and predictable tasks through orchestrated UI interactions that emulate human actions. Largely powered by pre-programmed scripts, APIs, and other RPA tools can perform the most basic tasks that can save teams a tremendous amount of time and effort. For instance, the operations like extracting data from forms, copying files, validating inputs, sending schedule messages, etc. there are two main types of RPA –
1. Assisted: RPA bots are deployed on an individual desktop, where the human worker carries out certain aspects of the tasks, relying on the bot to perform the rest of the process operation.
2. Unassisted: RPA bots are deployed on centralized servers, allowing manual control to perform end-to-end tasks.
RPA technology acts as a foundation layer upon which intelligent automation and hyperautomation are built. Without RPA, automating communication between AI systems and various corporate systems is impossible. The application could be based on windows applications, web applications, mainframe applications, java apps, or mobile apps.
Intelligent Automation (IA)
Intelligent automation is the incorporation of advanced technologies like machine learning, natural language processing, structured data programming, and intelligent data processing to step up from what RPA offers. Intelligent Automation can handle a wide range of tasks from performing analytics to conditioning logic. It can help businesses with processing higher-function tasks that require knowledge for reasoning, judgment, decision-making, and analysis. For example, reviewing the provided context to suggest the best reply based on the user’s replies.
What is the difference between RPA and Intelligent automation?
In comparison to RPA, IA tools are capable of handling more complex cognitive tasks and can be applied to automate end-to-end workflow execution. Respectively businesses using intelligent automation software can gain higher productivity. For instance, any financial service business engaged with processing invoices may experience difficulties as every client has their own standardized way of sending invoices. And business needs to employ individuals to read the documents and enter the information into the accounting system. With an increasing number of invoices, the business might require a large number of resources to keep up with the volume of data. By building an IA model to read and understand the documents using IDP and then processing the results using the RPA, businesses can reduce time, effort, and costs.
According to Gartner, Hyperautomation is one of the top technological trends to watch. Hyperautomation is one of the go-to automation tools for most businesses seeking full-level digital transformation. It is a combination of RPA and intelligent automation powered with a wide range of AI capabilities like OCR, NLP, and IDP, to deliver adjacent solutions like low-code/no-code platforms, event-driven software architecture, intelligent business process management systems, intelligent decision support systems among others.
As the name suggests, hyperautomation allows higher-level functioning from task automation to orchestration to intelligence, enabling businesses to generate predictive insights, guided recommendations, process mining, and adaptive decision-making. These automation tools can be deployed either semi-or-fully autonomous for end-to-end process execution across multiple systems.
Robotic Process Automation vs Intelligent Automation vs Hyperautomation
When they first think of automation, executives may get excited about the several options available, some may be tempted to implement the most advanced technology – hyperautomation – as means to build business architecture for future needs. However, it is best to know about the system requirements and level of digital infrastructure required to do so. And it is suggested that without any knowledge of how these technologies work, the team might end up with challenges.
Gartner also warns that by 2024, over 70% of larger enterprises will have to manage over 70 concurrent hyperautomation initiatives which may require strategic governance, or else they will face significant instability due to a lack of oversight. It is recommended that enterprises should follow automation starting from the bottom. For instance, start with employing simpler RPA solutions for error-prone, redundant, and repetitive processes. To understand each automation process well we provided a detailed overview
|Use Case||Scripted automation of repetitive, rule-based, tasks requires data and/or UI manipulations||Intelligent-based multi-step task automation and automation of standard operational workflows||Intelligent-based multi-step task automation and automation of standard operational workflows|
|Core Technology applications||
Rule-based task automation for back-office processes
Improved staff efficiency and productivity
Reduced error rates
|Implementation||Most RPA tools are non-invasive and conducive to a wide array of business applications. Fast time-to-market, proven ROI.||IA tools require unconstrained access to data, as well as a suitable target environment for deployment. May not be applicable to legacy systems. Slower time to market, but higher ROI.||Requires a certain degree of digital infrastructure maturity, as well as a meticulous cross-system orchestration to deliver outcomes. Longest time-to-market, but highest ROI in the long-term.|
Which Automation Technology To Choose?
The pathway for adoption of any business automation technology differs from business to business, depending on the knowledge, complexity, and standardization of existing business processes. And the following steps can help in identifying the need for adopting RPA, IA, and hyperautomation for your business.
- Conduct in-depth business analysis to identify the current gaps in workflows, particularly which systems require switching from one to another for obtaining data or input.
- Strategize which processes require automatic execution or are performed semi-manually.
- Identify automation options available in the market that best suit your business needs and meet your existing technology portfolio.
- Develop and execute an RPA implementation roadmap.
SoulPage digital automation services can help with all the questions about RPA, intelligent automation, and hyperautomation implementation. SoulPage delivers specialized services along with RPA consultation on organizational transition, value-added tools focused on RPA implementation, assisted and managed RPA implementation service, building personalized RPA centers of excellence, and more.
SoulPage RPA+AI-driven automation services can be implemented with ease by anyone, anywhere. To know more about our RPA service or more about other soulpage services, connect with us.
Q. What is an Intelligent and cognitive automation process?
Intelligent automation with a combination of robotic process automation and artificial intelligence technologies to empower rapid end-to-end operations, processes, and IT automation to accelerate digital transformation for enhanced customer/employee/partner experiences.
Q. what value does intelligent automation provide?
- Increasing productivity
- Exceptional customer service
- Optimized process and operations costs and risks
- Product and service innovation
- Effective process management and control
Q. What is the future of hyperautomation?
According to Gartner, Hyperautomation will be practiced by most large-scale organizations to automate at least 25% of their digital workforce tasks in the next five years. And it is expected that hyperautomation will help these organizations to cut 30% of their operational costs in the next two years of implementation.