A framework for explaining the power of IA

IA, also called Hyperautomation, is a concept leveraging a new generation of software-based automation.

It combines methods and technologies to execute business processes automatically on behalf of knowledge workers.

This automation is achieved by mimicking the capabilities that knowledge workers use in performing their work activities (eg. language vision, execution, and thinking & learning).

The goal of using IA is to achieve a business outcome through a redesigned automated process, with no or minimal human intervention.

As a result, IA increases process speed, reduces cost, enhances compliance and quality, increases process resilience, and optimizes decision outcomes.

Ultimately, it improves customer and employee satisfaction and boosts revenues.

This definition has been written by the authors, inspired by IEEE Std. 2755-2017.
*IEEE Guide for Terms and Concepts in Intelligent Process Automation*

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According to the Institute for Robotic Process Automation (IRPA), 75% of the AUTOMATION Project do not have an ROI!

A recent MIT Sloan survey found that only 10% of companies achieve ROI with AI.

And they are not alone. Gartner has found that 85% of ML projects fail. Worse yet, the research company predicts that this trend will continue through 2022.

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