Robotic Process Automation, the New “It” AI in Federal Government
What is Robotic Process Automation?
Robotic process automation (RPA) is an artificial intelligence (AI) technology that utilizes machine learning software (ML), a category of algorithm making applications more accurate in predicting outcomes without being explicitly programmed to do so. The basic premise of ML is to build algorithms that can receive input data and use statistical analysis to predict and update an output as new data becomes available.
Imagine an important agency contractor’s address has changed. This address has been entered in various software programs and offices within your agency. With RPA software, a single agency employee can initiate a single address update in a single software program. The RPA software will then make the exact change immediately and across all engaged programs and offices within the agency
Five minutes versus fifty minutes. Task efficiency and precision are RPA’s primary enticements.
Key Benefits of RPA in Federal Government
RPA software, once implemented, observes repetitive digital tasks performed by employees, then replicated by the software in the graphical user interface (GUI). The RPA uses structured data to mimic human performance, automating highly repetitive digital tasks such as data manipulation or data entry. It is a cross-platform application that tech and federal agency leaders say will improve employee work-life balance while streamlining repetitive “low-value” tasks.
Three Key benefits of RPA include:
Cost reductions. According to TimelinePi, a process intelligence company, “companies that have repetitive tasks that are also high-frequency can expect to see a 50-70% cost savings with RPA successfully in place.” Deloitte also noted that quality/accuracy was improved by 90%.
Labor and time savings. A recent study found that where RPA is not being utilized, 50% of automation opportunities are being missed. RPA systems can reduce tasks that take minutes to mere seconds.
Reduced operational risks. RPA uses dependable data to reduce risk, increase compliance and enhance scalability. There are two common types of RPAs that are typically utilized, giving businesses options in how they can best address operational risks.
Where RPA is Going
In 2019, GSA is focusing RPA development on “higher level” areas such as data entry, a shift that will save employees time and allow for “reskilling,” further enhancing employee work-life experience.
RPA is spreading as the “it” AI in federal government and for this reason agency leaders, such as Ed Burrows, RPA Program Manager at the General Services Administration (GSA) , are calling for a community of practice (CoP):
"I realized there was a real need across the government for information sharing in particular and developing best practices and having some type of written implementation and operations guide that would really help agencies," says Burrows. “So we're going to try to address that need in a couple of ways."
One of these key ways is through Digital.gov, a digital “hub” created by GSA that serves as a source of innovation ideas, events and resources. The website helps connect various federal agencies, allowing for knowledge sharing and continued development of technologies like RPA.
Burrows predicts a robust future for both agencies and employees, shifting their work efforts from “low-value to high-value” and maximizing employee’s time on complicated functions rather than on mundane and tedious tasks. “We shouldn’t be hiring for positions that can be automated. That becomes a dead-end job,” Burrows says. “We should think about automation first.”
RPA as Empowerment
A common concern with RPA, as with many artificial intelligence technologies, is the elimination of jobs; however, elimination isn’t necessarily a problem. With proper agency support, RPA transition will empower agency employees rather than harm them. Private sector companies, such as Amazon, have covered 95% of reskilling costs offering employees in “low-value” positions, such as data entry, opportunities for more invigorating, “high-value” positions within fields such as nursing and mechanical work.
The goal of RPA, and any AI in federal government, is to provide human employees with supportive technology, improving employee work life balance while increasing task efficiency and strategic operations with new decision-making tools. With AI, not only will work-flows be smarter and faster, work-flows will reinvent themselves creating new pathways and cross-disciplinary approaches through CoPs, advancing agency missions, today, and into the future.