by Larry English

In 2019, a McKinsey report found that only 55% of organizations found success with their automation program. Robotic process automation (RPA) promised a big ROI, but for some companies, capturing that value proved elusive. Fast-forward to today, and the meshing of RPA with AI technology— hyperautomation, or the marriage of multiple automation capabilities— has opened a whole new world of automation.

Much of the pre-AI trouble with RPA comes down to the complexity or variability of seemingly simple tasks.

For example, say you want a bot to analyze invoices and send them to the right contacts at your organization. Seems simple enough, right? Think again. Before the bot can handle the task, you'd need to standardize every invoice, or you'd have to program the bot to know how to handle dozens of different document variations. Suddenly, this "simple" RPA initiative became headachingly complex and expensive.

AI contributes a layer of intelligence to RPA that wasn't previously possible. RPA on its own is limited to straightforward, structured and objective tasks. AI expands the possibilities to include capabilities with nuanced, subjective or unstructured data. By combining RPA and AI tools, you can automate a bigger chunk of your processes.

For instance, my company, Centric Consulting, recently partnered with UiPath, the world's largest RPA vendor, to help World Wide Technology (WWT) apply hyperautomation to better manage the company's high volume of purchase orders. Those purchase orders come in numerous formats and languages.

Without a standard template, RPA alone could not "read" and sort the documents without a separate setup for every format. With AI, however, it was another story.

We trained an AI tool on over 100 purchase orders from one of WWT's vendors. By combining RPA with AI, WWT has successfully automated a process that previously required significant back-end work. This has been a strategic part of WWT's hyperautomation journey.



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