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RPA vs. Hyperautomation: What's the Difference?

Catherine Canary, Appian
April 7, 2023

Have you seen the efficiency gains you’d hoped for from your investments in task automation tools like robotic process automation (RPA)? Despite prioritizing automation efforts, many IT leaders still lack the tools for broader, end-to-end process automation—or as Gartner calls it, hyperautomation. If you’ve found yourself grappling with numerous disconnected islands of automation, where do you go from here? According to Gartner, "Enterprise architecture and technology innovation leaders . . . must deliver end-to-end automation beyond RPA by combining complementary technologies to augment business processes.” But what’s the difference between hyperautomation and robotic process automation (RPA), and what exactly does it mean to go beyond bots?

[ Learn how to successfully implement end-to-end intelligent process automation strategies. Get the Process Automation Guide. ]

Robotic process automation vs. hyperautomation.

RPA is nothing new. Bots automating simple, repetitive tasks—you’ve been hearing about this stuff for years now. And chances are good your organization has at least dipped its toes into the RPA waters. So, what have you found? Maybe you’ve noticed how RPA is effective at automating routine, monotonous activities like data entry. Maybe you’ve also noticed how it falls short of allowing you to automate more complex tasks and processes.

But leading organizations today automate everything—from simple tasks to large-scale, intricate, end-to-end business processes. If bots alone aren’t getting them there, then how are they doing it?

They’re using hyperautomation.

Simply put, the difference between hyperautomation and RPA is that RPA is a single technology that can automate simple tasks, and hyperautomation is a combination of technologies that can automate complex, end-to-end business processes. But that’s not the whole story. There’s more you need to know to attain the competitive edge hyperautomation offers.

Benefits and limits of robotic process automation (RPA).

RPA is used for automating high-volume, repetitive, manual tasks. RPA bots are digital workers that can run 24x7x365 on enterprise servers with little to no human intervention. Today, most organizations have incorporated bots into their business processes in one form or another. In a 2022 survey, Deloitte found that 74% of organizations were currently implementing RPA. While RPA bots are not capable of human-like cognitive decision making, they can mimic some manual human actions, such as entering data into forms, clicking buttons, and copying and pasting information.

RPA is a popular automation approach across industries and can be used almost any time you’re dealing with simple but repetitive tasks that are time-consuming and prone to error. For example, an RPA bot can be used to fill out a form on a website, route an invoice, or update customer information in a database.

But it has its limitations.

For example, RPA bots can hit a wall when faced with the need to make a cognitive decision. For that, you’d need a technology with artificial intelligence capabilities. RPA may also not be the best option in situations where an application programming interface (API) is present. While RPA can integrate basic information between applications, such as by copying and pasting on-screen information between systems, it can’t integrate the kind of complex application data that an API can access. This is where hyperautomation comes in.


Hyperautomation, defined.

Hyperautomation is a more advanced, complete approach to intelligent automation that aims to enhance the capabilities of RPA by combining it with technologies capable of human-like cognition, such as artificial intelligence and machine learning. This Gartner®-coined term also often encompasses a host of other technologies, such as intelligent business process management (iBPM), intelligent document processing (IDP), natural language processing (NLP), optical character recognition (OCR), chatbots, virtual assistants, and low-code. You can use a hyperautomation strategy to automate any business process end to end, from simple tasks to complex workflows that involve decision making.

Gartner’s path to hyperautomation

Because hyperautomation tools are capable of making decisions, they can adapt to changing circumstances. Additionally, with a hyperautomation approach, you can automate processes across multiple systems, applications, and data sources. And when paired with a data fabric, hyperautomation tools can directly access data in any number of separate systems and applications.

[ Want insight into the future of automation technologies and capabilities your competitors will be using? Read the Gartner report: Beyond RPA: Build Your Hyperautomation Technology Portfolio. ]


3 differences between RPA and hyperautomation.

Here are the main differences between RPA and hyperautomation.

  1. Scope of automation. RPA is limited to automating simple, repetitive tasks. Hyperautomation aims to use intelligent automation to streamline end-to-end business processes, from simple tasks to complex workflows that involve human and machine-based decision making.
  2. Flexibility and adaptability. RPA relies on rules-based programming, meaning bots can only follow pre-defined rules and cannot make decisions based on data. In contrast, hyperautomation uses artificial intelligence, machine learning, business process management, workflow orchestration, and other automation tools to make decisions based on data, allowing it to handle more complex tasks and adapt to changing circumstances.
  3. End-to-end automation potential. Each RPA bot is limited to automating an individual task within a single application or system. Hyperautomation can automate processes across multiple systems, applications, and data sources, letting you achieve true end-to-end intelligent automation across your organization.

Hyperautomation can handle more complex tasks and make human-like judgments to adapt to changing circumstances. Hyperautomation combines RPA with other technologies, such as artificial intelligence and machine learning, to create a more intelligent and flexible automation solution that scales to meet any organization’s needs.


What’s next? A process automation platform for hyperautomation.

RPA and hyperautomation both improve efficiency and productivity in the workplace. Maybe you're just getting started on your automation journey and only have a few simple tasks you want to automate with an RPA bot. And that’s fine. But keep in mind that if you want to set your organization up to grow and scale, you’ll likely need a more comprehensive automation approach like hyperautomation to keep up with the competition.

If a hyperautomation strategy sounds like something that could benefit your organization, consider using a process automation platform. The best process automation platforms on the market offer a complete suite of built-in automation tools, plus data fabric, process mining, and total experience capabilities to support enterprise-wide digital transformation.

Want more expert insight into hyperautomation? Get the Gartner report: Emerging Technologies and Trends Impact Radar: Hyperautomation Report.