What is Hyperautomation?

Hyperautomation is a combination of approaches, processes, and techniques that uses advanced technologies such as artificial intelligence (AI), machine learning (ML), and robotic process automation (RPA) to identify and automate manual work to increase efficiency and improve operational agility.

How does Hyperautomation Work?

Hyperautomation involves an ecosystem of technologies that enables end-to-end process automation to significantly reduce human intervention, all while creating a better way of working across an entire organization. 

The technologies are used to coordinate and streamline tasks and processes, reduce costs and human error, and create efficiencies. The types of technologies used will depend on what your organization is trying to achieve.

Why is Hyperautomation Important?

According to Gartner, “Many organizations are supported by a ‘patchwork’ of technologies that are not lean, optimized, connected, clean or explicit”. 

Post-COVID-19, increased competition, resource shortages, development skills gaps, and the demand for low-code tools will force more organizations worldwide to adopt hyperautomation to accelerate digital transformation. 

Hyperautomation gives organizations the ability to achieve these and other outcomes including:

  • Simplify complex work
  • Remove or reduce deficiencies
  • Gain greater visibility into company-wide performance in real-time
  • Improve engagement with customers and employees
  • Integrate applications and bypass disconnected legacy systems
  • The ability to make faster and more informed decisions
  • Redeploy resources to higher-value work
  • Close skills gaps
  • Increase innovative thinking

What is the Difference Between Automation and Hyperautomation?

While many organizations use automation to some degree, it only simplifies and streamlines specific isolated tasks and isn’t a unified approach. This makes it challenging and costly to meet the needs of an entire organization. 

Hyperautomation, on the other hand, is a unified approach that reduces siloed tool development and utilization to better support company-wide processes or initiatives.

Hyperautomation Tools

There are many hyperautomation solutions that can greatly improve and alleviate tedious business processes across virtually all industries, including:

  • Robotic Process Automation (RPA) handles task automation and streamlines work based on a series of actions that people might ordinarily complete. Rule-based human activity can be minimized, removed, or replaced using RPAs. RPAs offer many benefits, such as automating labor-intensive or non-value-added administrative tasks while increasing productivity.
  • Intelligent Business Process Management Suites (iBPMS) is a technology that handles process automation. It combines business process management (BPM) software with the capabilities of other tools like artificial intelligence (AI) to speed up and automate workflows. iBPMS can play a significant role in process optimization.
  • Artificial Intelligence (AI) technology learns and simulates human processes and behaviors to solve problems or complete tasks. It can be considered “human intelligence technology”.
  • Machine Learning (ML) is a type of AI that analyzes data and automatically learns and identifies patterns to make decisions.
  • Natural Language Processing (NLP) is a subset of AI that can understand and translate text and speech similarly to people.
  • Optical Character Recognition (OCR) enables computers to recognize the text that appears on physical documents to be deciphered and converted to electronic data. This has many applications, including making documents searchable or editable.

Other types of hyperautomation technologies can be used to automate processes, convert data, or simulate human interactions. 

Hyperautomation Companies

Gartner, known for its “Magic Quadrant” of service providers in various categories, lists these as top hyperautomation companies in 2020—with most fitting into the competitive RPA space.


  • AutomationAnywhere
  • Blue Prism
  • Work Fusion


  • NICE
  • EdgeVerve Systems
  • Kofax

Key players in ML include SAS, IBM, TIBCO, Microsoft, and SAP. Some of these may overlap in the RPA, NLP, or other aligned spaces.

RPA vs Hyperautomation

When it comes to RPA vs hyperautomation, there is a difference. RPA is just one type of technology under the hyperautomation umbrella. Hyperautomation involves other technologies to enhance intelligent automation. RPA can be either assisted or unassisted and does the work of people to complete a task. This is especially useful when tasks are repetitive. 

  • Assisted RPA is desktop-based and executed by humans to handle a specific task but uses bots to perform more repetitive elements.
  • Unassisted RPA refers to centralized server bots that are scheduled to automate a task.

When it comes to transcending RPA to deliver hyperautomation, three key steps should be involved:

  • Defining an automation journey
  • Developing a strategy to combine digital tools
  • Bolstering business processes with AI

What is the Future of Hyperautomation?

It’s estimated that technologies like AI will become one of the top trends in 2021, dominating the business world. This demand will push the global hyperautomation technology market to $596.6 billion in 2022, up from the estimated $532.40 billion in 2021. By 2024, a continued drive towards hyperautomation will lead organizations to adopt at least three out of the 20 types of process-agonistic software that enables hyperautomation. 

As we advance, Gartner explains, the acceleration of digital business will become reliant on three key pillars:

  • Efficiency 
  • Speed
  • Democratization

Further, a recent report, Top Strategic Technology Trends for 2021, discusses the idea that “Organizations that don’t focus on efficiency, efficacy, and business agility will be left behind.” 

Hyperautomation as part of your overall automation strategy will need to be a vital part of keeping up with the competition. 

Updated: March 21, 2022

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