RPA or Hyperautomation or Intelligent Automation or AI, Which is it?

The language around automation technology is changing faster than ever. As new technologies emerge, the language we use to describe them does too. But with the changing definitions and alphabet soup, it can be hard to keep up and even harder to know what you need for your business use case. We will look at both the definitions of RPA, Hyperautomation, Intelligent Automation and AI, and how to know which you need.

What is RPA?

RPA stands for Robotic Process Automation and it was the first of these technologies to be developed.

Repetitive computer-based tasks that are executed according to a clear set of business rules are good candidates for RPA. The tasks usually have limited complexity of 10-20 steps.

Benefits of RPA infrastructure check up

An automation is the list of each step in the task and how it is completed. It is the workflow and the rules that direct the task.

The automaton is carried out by a software robot – we like to think of them as digital workers. Digital Workers are your computerized colleagues that handle the tedious, repetitive tasks that breed errors and burn out in human office workers.

Examples of great RPA Use cases could be:

  • Migrating data is needed for Changing ERPs, migrating to the cloud, or changing automation platforms. The task of copying and pasting the data, double checking that all of the fields align is perfect for RPA robots.
  • Financial Reconciliation double checks that information matches across multiple systems, updating errors, and preparing data for reporting. This can be handled in a fraction of the time by digital workers.
  • Generating Reports includes pulling data from multiple systems, formatting it and distributing these reports to stakeholders on a daily/weekly/monthly cadence. RPA Robots extract and format exact accurate information according to their instructions (think Excell pivot table wizards and ERP pulls). AI can be added to reporting if you want that data summarized or extrapolated on.

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Hyperautomation vs Intelligent Automation

Hyperautomation is a term coined by Gartner, in Hype Cycle for Artificial Intelligence 2020. RPA becomes hyperautomation when you add additional technologies like:

Automation solutions for finance and accounting leaders
  • OCR- Optical Character recognition gives the robots eyes, allowing them to read documents and screens.
  • IDP – Intelligent Document Processing allows the robots to understand the content of the document.
  • Machine Learning allows them to remember the feedback and get better over time.
  • AI decision-making allows them to interpret the data and generate a confidence score for how well they understood.

These technologies allow the software robots to do more, handling more complex tasks, Hyper-charging RPA.

Intelligent Automation is the term that has come into use in 2022-2023 with the emergence of Generative AI. The inclusion of these technologies makes robots more intelligent. IA smart robots can have eyes, ears, mouths and creative thoughts.

RPA +AI = IA (Intelligent Automation) 

So Hyperautomation or Intelligent Automation? – They are the same. As software robots evolve and get smarter, the descriptions we use evolve to reflect their expanded capability.

Examples of Hyperautomation or Intelligent Automation use cases:

  • Processing forms – The ability to read the information in the form is provided by OCR tools. Intelligent Document Processing enables the digital workers to understand the document as a whole and determine if the forms are complete and accurate.
  • Invoice Processing – In this 3-way matching example the digital worker needs to read a scanned receipt and check it against the matching invoice and the entry in the ERP.
  • Working in legacy systems – Annual reports could only be exported to auditors in PDF format. OCR tools are used to read the finance data, and IDP was applied to extract and compile that data into reports for auditors.

Intelligent Automation or AI

AI (Artificial intelligence) is a field that is exploding with potential. The ability of computers to understand the way that humans think, work and communicate is changing the game.

A guide to intelligent automation

Generative AI has created a whole new field where software robots can generate words, code, summarize and sort data, and other new skills every week.

AI is fulfilling the promises that RPA made back in 2015, making the processing of background computer tasks more intuitive and relieving human office workers of tedious tasks.

Intelligent Automation is RPA + AI. The ability to see, read and think comes from AI, but the hands that move the data, click the mouse, and send the email belong to RPA digital workers.

Is it AI or Intelligent Automation?  The answer is both. This is where the foundations of RPA still have value. The Generative AI thoughts and AI decisions that these new software’s make still need the RPA robots to carry out the tasks.

Uses cases for Intelligent Automation with Generative AI

  • Document Indexing – The smart robot needed to read thousands of legal contracts, understand the clauses, and index each. This enabled the company to batch update contracts as local laws change and update customers.
  • Chat with your Data – Generative AI can read thousands of documents in your organizations’ data cloud. It can summarize and make them searchable via chat by your employees.
  • Reseach and Compliance Monitoring – The AI reads hundreds of government news board posts a year and notifies compliance officers of regulatory changes that would impact a global manufacturer.

So Do I need RPA or Hyperautomation or Intelligent Automation or AI?

The answer is all of them.

The term Hyperautomation has morphed into Intelligent Automation to encompass all of the new AI capabilities that can enhance automation.

Hyperautomation or Intelligent Automation allows humans to interact with their robot colleagues

Some processes need AI Powered enhanced robots, and some processes only the less expensive RPA worker bee robots.

AI thinking still needs the action layer of traditional automation to take the actions that create business outcomes. Choosing the right blend of technologies to solve your unique business problems is where WonderBotz expertise shines. We can help you find the right tool for the task and integrate it into your Intelligent Automation tech stack.

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