The pandemic has seen accelerated interest in process automation as organizations have scrambled to overhaul business processes and double down on digital transformations in response to disruptions brought about by COVID-19.
And for IT leaders stepping into or already steeped in such modernization efforts, artificial intelligence — mainly in the form of machine learning — holds the promise to revolutionize automation, pushing them closer to their end-to-end process automation dreams.
But for now, AI-powered process automation remains a piecemeal approach, in which AI is involved in individual tasks but not across the entire process chain. Regardless of how vendor’s spin it, fully intelligent automation has not yet arrived — but organizations working to fill the gaps are finding innovative ways to this promising concept closer into being.
The current state of intelligent automation
A typical use case for AI in automation includes the following: instead of requiring someone to manually re-key information from a PDF into a form, an AI is trained to do it for them. Or, when an employee would normally hunt through corporate documents to answer a customer question, an AI suggests possible answers.
As for the rest of the process, humans are at the core. A human business analyst figures out what goes into a particular process. Developers use robotic process automation (RPA) systems to create process flows. More business analysts monitor the performance of the process, seeking to find bottlenecks and to come up with ideas for other steps that could be automated either through traditional scripting or with AI augmentation.