As the adoption rate of automation increases in enterprises, different types of process automation terminologies such as RPA, intelligent automation, cognitive automation, or hyperautomation are used frequently without a clear explanation of their meaning. This can cause confusion among technologists, business users or executives.
While RPA is a user-interface centric automation technology, other terms mentioned above do not have specific, generally accepted meanings. You can assume all of them to refer to automation.
However, different vendors and industry analysts are trying to use some of these terminology to explain recent trends. Therefore, to be on the same page with them, it makes sense to know how different vendors or industry analysts use these terms and we provide such explanations below to help users overcome confusion and miscommunication issues.
What is intelligent automation?
Intelligent automation, also called cognitive automation, is a technology that combines robotic process automation (RPA) with technologies such as:
- Artificial intelligence (AI)
- Machine learning (ML)
- Natural language processing (NLP)
- Optical character recognition (OCR)
- Intelligent document processing (IDP)
This allows end-to-end process automation through intelligent bots with decision making capabilities. Intelligent bots can handle complex and unstructured inputs and learn and improve their own processes.
Watch how IBM’s AI-driven Robotic Process Automation (RPA) solution can help you build smarter bots that decrease repetitive, error-prone manual tasks — and time-wasting swivel-chair interactions.
AI + bots: Making processes smarter with intelligent bots from IBM RPA
What is hyper-automation?
Hyper-automation is a business approach that involves automating as many business and IT processes as possible. It aims to streamline processes across an organization through the combined use of intelligent automation and its constituent technologies with tools and technologies such as:
- Process mining
- Low-code/no-code tools
- Digital twins
- Internet of Things (IoT)
- Integration platform as a service (iPaaS)
Feel free to check our article on examples of hyper-automation in different industries.
Intelligent automation vs Hyperautomation
As we discussed in our article on hyperautomation, different industry analysts and vendors use different terminology to imply the same thing. Intelligent automation and hyper-automation can sometimes be used interchangeably, along with cognitive automation and intelligent process automation, to refer to the technology that combines RPA and AI to automate complex processes.
Hyper-automation is a term coined by Gartner and defined as “a disciplined, business-driven approach to rapidly identify, vet and automate as many business and IT processes as possible. Hyper-automation enables scalability, remote operation and business model disruption.” Gartner ranks hyper-automation among the top trending technologies for 2022.
Using intelligent automation and hyper-automation interchangeably makes sense since both involve combining automation technologies such as RPA with AI and other tools and technologies to achieve higher levels of automation in an organization.
On the other hand, as seen in the definitions above, the two terms can be differentiated as follows: hyper-automation is a business approach whereas intelligent automation is a specific technology that is used within hyper-automation initiatives.
IBM differentiates two terms in a similar vein: “Intelligent automation is comprised of robotic process automation (RPA), artificial intelligence (AI) and machine learning (ML). Hyper-automation is a business-driven, disciplined approach that organizations use to rapidly identify, vet and automate as many business and IT processes as possible. Therefore, intelligent automation is often used within hyper-automation efforts.”
You can also check our article on the difference between intelligent automation and RPA.
Why is it important now?
Because it has significant potential for impact and companies are frustrated with the current level of progress in their automation efforts.
Gartner, without citing any quantitative backup, claims that organizations will lower operational costs by 30% by combining hyper-automation technologies with redesigned operational processes by 2024. The number is probably wrong but it is beyond doubt that automating operational decision making will be impactful and will be a focus area for companies.
Due to several issues, traditional, product based automation approaches with limited reliance on machine learning have failed to deliver significant benefits:
- Process complexity has slowed down automation efforts even in rules based processes
- Employees have yet to adopt a culture of looking for automation opportunities and rapidly experimenting with new technologies
- Most efforts did not rely on building custom machine learning models which limited application areas
What are the benefits of intelligent automation?
There are multifarious advantages offered by intelligent automation. It empowers humans with upgraded technologies that will help in making faster and smarter decisions.
- With IA, one can expect an all-around improvement in process efficiency. It can replicate decisions made by humans, perform changes, and can be programmed to solve various issues. The superior IA is capable of doing tasks that regular IT automation cannot.
- It will help in improving the overall experience gained by your customers. According to a study, the chatbots powered by AI have given resolution to 90% of complaints in a reduced time-frame.
- IA also helps with optimizing the operations carried out at the back office. The machines can do tedious and repetitive tasks in a short time, with fewer errors.
- When you start using IA for your business, it will reduce your overall long-term costs and the risks associated with your business. The self-learning feature of IA can significantly reduce costs, and it will also allow procurement functions to be more agile. It also helps to give quick responses to business opportunities.
- It assists in optimizing the overall productivity of your workforce.
- When you use IA for business, you can expect round-the-clock and effective monitoring. In most cases, it was seen that IA efficiently helps in better fraud detection.
- Also, with IA, you can be more innovative with your products and services. By performing different tasks efficiently, it will not only help you with existing tasks but also will encourage you to take up innovative workings.
What are the benefits of hyper-automation?
Automation initiatives mainly focus on cost reduction and increase in compliance. In addition to those, top benefits of hyperautomation for businesses include:
- Agility: The business doesn’t need to rely on a single technology for automation purpose. Reliance on a suite of tools along with cultural change, enable organizations to achieve scale and flexibility in operations.
- Enabling employees and improving their productivity: Automation frees the time of employees so that they can focus on more value-added tasks.
- Improved collaboration: Hyper-automation enables businesses integrate digital technologies across their processes and legacy systems. With the integration of technologies, stakeholders have better access to data and can communicate seamlessly throughout the organization.
If you are looking for vendors that can provide necessary technologies to achieve hyper automation, check out in www.ibm.com.