In the modern era, automation has become a norm in business enterprises. It has eased different simple and complex processes, enabling leaders to focus on key business aspects while saving on costs in labor-intensive tasks. Intelligent automation (IA), Robotic Process Automation (RPA), and hyperautomation are three often confused automation techniques. These automation solutions can fall into the business jargon category.
This article will succinctly discuss IA, RPA, and hyperautomation to better understand the three automation concepts. Also, it will provide critical insights into which automation technique best suits your business needs and how to go about your automation journey.
Brief Overview: Intelligent Automation, RPA, Hyperautomation
It is best to perceive automation as a continuous initiative from thinking to doing, focusing on the process, and concentrating on data. As manual laborers move away from high-volume, repetitive tasks to roles requiring high-caliber cognitive insight, more complex automation technologies will be necessary. Having said that, let’s introduce these three automation techniques, shall we?
Intelligent Automation explained
Intelligent automation (IA), also known as cognitive automation, is a step-up technology of rules-based robotic process automation. It is powered by RPA combined with other technologies, including:
- Natural Language Processing (NLP)
- Machine Learning (ML)
- Artificial Intelligence (AI)
- Intelligent document processing, and
- Optical character recognition.
IA enables enterprise-wide process automation via smart bots with high-level decision-making capabilities. Therefore, these bots can manage unstructured and sophisticated inputs while learning and improving their processes.
Automating processes with IA can result in higher productivity and efficiency than Robotic Process Automation (RPA). For example, a bank implemented intelligent automation to smoothen its corporate credit evaluations. This solution resulted in an 80% increase in employee productivity.
Robotic Process Automation explained
RPA is a subset of intelligent automation and the lowest-level business process automation solution. It is a non-invasive integration technological solution that automates predictable, repetitive, and routine activities through orchestrated user interface interactions that mimic human actions.
Basically, there are two types of RPA – Unassisted and assisted.
- This robotic process automation involves deploying bots on a clustered server, enabling manual control. It can automate edge-to-edge programs and facilitate workflow scheduling from a focal control point.
- This RPA type involves deploying bots in a specific PC, letting the manual laborer work on particular areas of the task. The user relies on the bot to handle other, more complex, cumbersome aspects of the process.
The most typical RPA technological solutions can save an organization enormous effort and time. For example, a bank automated three basic business processes using RPA solutions. The result was a 63% cutback in working hours.
One can perceive hyperautomation as the pinnacle of IA, which leaders are currently targeting to achieve. In fact, Gartner listed hyperautomation among the top 12 technologies to look out for in the modern era.
In simple words, hyperautomation combines various automation tools and techniques with several ML apps and packaged software to conduct different levels of work. Therefore, it drives high-level functions, from simple activity automation to intelligence and orchestration. As a result, it enables predictive insights, process mining, adaptive decision-making, and guided recommendations.
Hyperautomation is powered by intelligent automation plus other fundamental technologies, such as:
- Low-code and no-code tools
- Internet of Things (IoT)
- Digital twins
- Integration Platform as a Service (iPaaS)
- Process mining
- Application Programming Interfaces (APIs)
- Intelligent business process management suites (iBPMS)
Intelligent Automation, RPA & Hyperautomation (Differences)
Still, lacking a clear difference between the three automation solutions? Well, gain more insights from the visual presentation below.
|Intelligent Automation (IA)||Robotic Process Automation or RPA||Hyperautomation|
|Primary Use Case||Automation of standard operational workflows and multi-step processes||Scripted automation of easy, repetitive activities that need data and/or user interface manipulations||Automation of common operational workflows and multi-step processes|
|Implementation Difficulty||Moderate. Intelligent automation tools need unrestricted access to information and a favorable target deployment setting.
It has a relatively slower time-to-market but has high returns on investment (ROI).
It may not be appropriate for legacy systems
|Low. Many RPA tools are conducive and non-invasive to a broad range of business apps.
It has a fast time-to-market with proven ROI.
|High. Hyperautomation requires a specific level of IT infrastructure maturity and diligent cross-system orchestration to provide the highest gains.
It has the longest time-to-market but the most significant ROI from a long-term perspective.
|Core Technologies||RPA along with:
Natural Language Processing (NLP),
Machine Learning (ML),
Artificial Intelligence (AI).
Intelligent document processing, and
Optical character recognition.
|RPA uses rule-based activity automation for office processes to:
Reduce error rates
Improve employee productivity and efficiency
|AI/ML, including OCR and NLP
Low-code and no-code tools
Event-driven software architecture.
Which automation technology best suits your current needs?
Based on the descriptions of these automation technologies, it is clear that hyperautomation is by far the most advanced. It is the basis of building a future-proof business. However, we must warn business leaders that hyperautomation requires high-level IT infrastructure maturity, including:
- Robust data fabric or data pipelines
- A well-established cloud-based data lake, and
- Automated digital infrastructure configuration, orchestration, and provisioning.
Similarly, hyperautomation (like RPA and IA) delivers high ROI for well-regulated business processes. If a business lacks a solid digital strategy, it is limited to how much it can automate.
Gartner warned that by 2024, 70 plus percent of large organizations will have to handle over 70 simultaneous hyperautomation programs. To manage these initiatives effectively, enterprises need strategic governance. Otherwise, they will face high instability because of inadequate oversight.
With the increase in automation solutions, IA, RPA, and hyperautomation will only improve. Hyperautomation is the next big thing that leaders should be thinking of. However, they should be careful and ensure they have adequate capacity to avoid instability, which may put them at a competitive disadvantage.
Therefore, we recommend using the bottom-up technique in implementing enterprise automation. Begin deploying simple RPA solutions for repetitive, error-prone, and redundant processes. Depending on the response, prioritize other areas for improvement – more sophisticated workflows, where advanced intelligence is necessary for efficient execution. Once you’re done with that, focus on combining workflows that require switching between multiple applications.
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