Intelligent Automation vs. Hyperautomation
In recent years, Intelligent Automation (IA) has become increasingly popular due to its ability to combine cognitive technologies like artificial intelligence, machine learning, computer vision, and natural language processing with Robotic Process Automation (RPA) to automate various business processes.
However, businesses are now exploring Hyperautomation, a more comprehensive approach to automation, going beyond just intelligent automation. Gartner defines hyperautomation as a business-driven, disciplined approach that organizations use to rapidly identify, vet and automate as many business and IT processes as possible.
According to the research firm, hyperautomation initiatives continue to grow at a relentless pace with 80% of respondents revealing they will increase or sustain hyperautomation spending.
This blog highlights the key differences between Intelligent Automation and Hyperautomation.
Learn More: What is Automation?
Intelligent Automation is an approach that leverages cognitive technologies to automate business processes, making them more efficient and reducing the need for human intervention. It involves using RPA, machine learning, computer vision, and natural language processing to mimic human intelligence.
By doing so, Intelligent Automation enables companies to enhance operational efficiency and minimize the need for human intervention, ultimately resulting in reduced costs and increased productivity.
Learn More: What is Process Automation?
Hyperautomation is a comprehensive approach to automation that goes beyond IA. Gartner defines it as a disciplined approach used by enterprises to identify, vet, and automate as many business and IT processes as possible.
This requires the use of technologies, tools, or platforms such as AI, machine learning, RPA, business process management (BPM), and intelligent business process management suites, among other tools.
Differences Between Intelligent Automation and Hyperautomation
Intelligent Automation is a relatively limited approach to automation that typically involves using technologies such as RPA, machine learning, computer vision, and natural language processing.
These technologies are applied to specific business processes, such as data entry or invoice processing.
In contrast, Hyperautomation is a more comprehensive approach that seeks to automate as many business and IT processes as possible. It combines multiple technologies, including Intelligent Automation, artificial intelligence, and machine learning, to automate processes.
- Cognitive Abilities
Intelligent Automation has limited cognitive abilities and can only automate repetitive and rules-based tasks. It can’t handle complex decision-making, unstructured data, or natural language processing tasks.
Hyperautomation, however, has more advanced cognitive abilities, and it can automate complex tasks that involve unstructured data, decision-making, and natural language processing. It leverages technologies like AI and machine learning to understand, interpret data and discover processes for automation, making it more versatile than IA.
While IA focuses on automating single tasks or processes, hyperautomation involves integrating multiple technologies and platforms. This complexity requires expertise in AI, machine learning, data analytics, and process automation, making the implementation challenging.
Intelligent Automation is not scalable, especially when dealing with large amounts of data. Its limited cognitive abilities can also limit its scalability, making it unsuitable for organizations with complex processes.
In contrast, hyperautomation is more scalable as it leverages technologies like AI and machine learning, which can process large amounts of data. It can scale to meet the needs of different organizations, making it a flexible approach to automation.
Learn More: How to Achieve Successful Automation Outcomes?
Kickstart Your Automation Journey With Scout®
Today, over 60% of the teams’ workday is spent on unstructured interactions in documents, emails, communications, custom applications, and websites – outside of ERP, CRM, and other systems of record.
This massive unstructured and undocumented interaction dataset between people and software is untapped and contains a goldmine of insights that could give a significant competitive edge to enterprises.
Through Soroco Scout®, powered by the world’s first work graph platform, organizations can unlock this data source to discover areas where inefficiencies occur and build credible, scalable automation pipelines.
Scout® work graph can enable enterprises to understand the exact processes that should be automated — and what should not be automated, thus enabling enterprises to realize the promised value from their automation initiatives.
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