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Hyperautomation: Combining AI with RPA to Improve Processes and Drive Efficiency
Robotic Process Automation (RPA) is automation that combines the scanning of paper and the scraping of screens, with optical recognition and forms processing rules to read, map and route data into repositories and process workflows. RPA has gradually become a common element of business back-office processing, particularly for financial companies and businesses that do a large amount of form processing. The successor to RPA is hyperautomation.
Artificial Intelligence and Machine Learning are now being integrated into RPA to create a kind of super-smart automation, something that Gartner called ‘hyperautomation’ in 2019. Gartner says that within the next two years 70 percent of large global companies will have hyperautomation initiatives. The driving factor behind this is that it is expected that hyperautomation can lower operational costs by at least 30 percent compared to the manual processes that they replace.
An article by Gartner said that “business-driven hyperautomation requires a disciplined approach to rapidly identify, vet and automate as many business processes as possible. The opportunity is twofold. On one side, there is an extensive and expensive set of business processes — across many functions of the end-to-end supply chain — that still require humans to perform manual tasks and mundane decisions. On the other, the massive and growing amounts of data that are being created each and every moment around global supply chains, make it impossible for humans to perform sensible, fact-based decisions unless augmented by technology.”
Cathy Tornbohm, research vice president at Gartner, said that “the shift towards hyperautomation will be a key factor enabling enterprises to achieve operational excellence, and subsequently cost savings, in a digital-first world.”
