Although RPA is efficient and effective, it obviously has its limitations. As a rules-based, deterministic system, RPA can’t make decisions on its own. For that, it needs to team up with machine learning or artificial intelligence. It also relies on structured data. AI offers the potential to replace human interpretation of unstructured data with an automated process.
“Once a machine is stood up, it is deterministic – it does the same automation time and time again,” says Sebastian Schroetel, head of intelligent RPA at software supplier SAP. But in the future, RPA will go “broader and deeper” into business processes, he adds. This could lead to intelligent, or even autonomous enterprise systems, such as ERP. “We may see models that can make intelligent decisions and, step by step, move towards robots that don’t just build cars, but more intelligent ones that run financial processes,” says Schroetel.
This will draw on developments in both AI and supporting technologies. “Across industries, RPA is being leveraged to become more intelligent,” says Jack Watts, head of AI at NetApp. “Computer vision, for example, is being leveraged in a greater way.”
“In the past, this would have been used to recognize characters and numbers on a cheque being paid into a bank. Today, entire invoices, purchase orders and even forms of identity are being ingested into ERP systems.”
The whole invoice-to-payment process can be automated, with limited human oversight. And improvements in computer vision are extending RPA into other fields, ranging from medicine to law enforcement. But perhaps the greatest potential for smarter RPA lies in systems that can learn and improve as they work. More prosaically, systems also use their intelligence to make it easier for humans to automate processes in the first place.
“RPA application vendors have introduced discovery tools as well as process mining solutions for process streamlining and re-engineering,” says Jukka Virkkunen, co-founder of Digital Workforce. “Better functioning and business-supporting processes will continue to operate autonomously and will not require management like the current ones.”
In short, the next generation of RPA will be able not only to automate the mundane tasks but also to autonomously find problems and fix them thereafter.
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