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Intelligent Automation vs Hyperautomation Comparison for 2024

Written by
Cem Dilmegani
Cem Dilmegani
Cem Dilmegani

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

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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:

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.

What is hyperautomation?

Hyperautomation 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:

Feel free to check our article on examples of hyperautomation 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 hyperautomation 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.

Hyperautomation 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. Hyperautomation enables scalability, remote operation and business model disruption.” Gartner ranks hyperautomation among the top trending technologies for 2022.

Using intelligent automation and hyperautomation 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: hyperautomation is a business approach whereas intelligent automation is a specific technology that is used within hyperautomation 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). Hyperautomation 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 hyperautomation efforts.”

You can also check our article on the difference between intelligent automation and RPA.

If you have other questions, we can help:

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Cem Dilmegani
Principal Analyst

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Cem's hands-on enterprise software experience contributes to the insights that he generates. He oversees AIMultiple benchmarks in dynamic application security testing (DAST), data loss prevention (DLP), email marketing and web data collection. Other AIMultiple industry analysts and tech team support Cem in designing, running and evaluating benchmarks.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

Sources:

AIMultiple.com Traffic Analytics, Ranking & Audience, Similarweb.
Why Microsoft, IBM, and Google Are Ramping up Efforts on AI Ethics, Business Insider.
Microsoft invests $1 billion in OpenAI to pursue artificial intelligence that’s smarter than we are, Washington Post.
Data management barriers to AI success, Deloitte.
Empowering AI Leadership: AI C-Suite Toolkit, World Economic Forum.
Science, Research and Innovation Performance of the EU, European Commission.
Public-sector digitization: The trillion-dollar challenge, McKinsey & Company.
Hypatos gets $11.8M for a deep learning approach to document processing, TechCrunch.
We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million, Business Insider.

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