Extending the capacity for rapid automation with AI

According to Gartner, hyperautomation is a business-driven, disciplined approach that organizations use to rapidly identify, vet, and automate as many business and IT processes as possible. Hyperautomation involves the orchestrated use of multiple technologies, tools, or platforms, including artificial intelligence, machine learning, robotic process automation, business process management, low-code / no-code tools, and more.

Hyperautomation often starts with robotic process automation, implementing software robots to emulate human activities such as repetitive computer tasks. Next, artificial intelligence technologies such as analytics, machine learning, and process mining are implemented to identify, automate, and monitor many other processes. This expands automation to knowledge work processes such as the reading and understanding of document content.

Hyperautomation software such as Intelligent Document Processing solutions enable robots to effectively process documents, and make decisions regarding the content, the way that a human would. Process mining tools contribute to hyperautomation potential by discovering and analyzing processes to identify where the best opportunities for automation are. Process analytic software can help to measure the return on investment of automation technology, tying them to business outcomes.

Any organization looking to decrease costs, improve process efficiency, or reduce errors can benefit from hyperautomation. At the employee level, hyperautomation tools such as RPA can reduce the burden of repetitive, manual tasks and free employees to focus on high value, and more personally rewarding, work.

Hyperautomation is used by organizations of all sizes in various industries, including, Financial Services, Transportation & Logistics and Supply Chain, Insurance, Healthcare, Retail, BPO, Customer Service, and more.

The AI (artificial intelligence) used in Hyperautomation helps the automation tools to become “smarter” through understanding cognitive tasks—those that require the processing of novel information or data, often contained in documents. Examples include optical character recognition (OCR), natural language processing, and computer vision. These advancements allow for the bots to convert text on paper or on a screen into language they can understand, to better comprehend written or oral human speech, and to see and recognize the context of actions performed by business users on screens.

Talk to ABBYY about process mining, Intelligent Documenting Processing, machine learning, RPA technologies, and more.