Several federal agencies have embraced artificial intelligence, machine learning, robotic process automation and digital process automation to streamline processes and optimize efficiency, but few have put all of the pieces together to adopt hyperautomation.
“In the commercial world, there’s a lot of interest and investment in hyperautomation for the returns that it can provide,” says Jason Payne, CTO for Microsoft Federal. “The federal government doesn’t quite have the same motivators as large multinational corporations, but the outcomes are just as valuable.”
Payne believes that the core tenets of hyperautomation — bringing together multiple technologies cohesively to optimize process improvements, drive speed and accuracy, and improve deliveries — have “taken off broadly” in the federal government.
The U.S. Navy, for example, used artificial intelligence to marry multiple IT systems and fragmented data sources to improve fleet readiness. The IRS partnered with IBM to use AI and automation to digitize tax returns and speed up refunds. And the Department of Health and Human Services has incorporated machine learning and AI to better detect and prevent Medicare and Medicaid fraud.
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On their own, AI, machine learning, robotic process automation (RPA) and digital process automation (DPA) offer significant benefits, including freeing up federal workers to focus on higher-value tasks. Hyperautomation takes those benefits up a notch.
Instead of using AI to simply analyze forms, Payne notes that hyperautomation uses RPA- and DPA-driven processes to pull digital content and metadata from the forms and route it through multiple federal systems to improve overall efficiency.
“Hyperautomation can be a labor force multiplier, enable speed and agility, improve cybersecurity, greatly improve business process effectiveness and reduce costs,” adds Terry Halvorsen, general manager for IBM Federal. “It isn’t just about making the current process more efficient but really looking at how to transform the process — and potentially the data — to deliver a much more effective and efficient outcome.”
70%
The percentage of organizations expected to have structured automation in place by 2025
Source: gartner.com, “Gartner Survey Finds 85% of Infrastructure and Operations Leaders Without Full Automation Expect to Increase Automation Within Three Years,” Oct. 3, 2022
Hyperautomation Can Come With Multiple Challenges
Implementing hyperautomation is not easy. Halvorsen notes that federal agencies must “review business and mission processes and the associated data, and understand the desired outcomes,” and employees must be willing to rethink processes. Legacy IT infrastructure can be slow and expensive to innovate, and implementation requires significant investment.
Fragmented data landscapes can also make it difficult to optimize operations, advance process improvement, share data, pursue efficiencies, and organize and gather data insights to inform where and how to prioritize action and decisions, Halvorsen adds.
Despite the challenges, Payne believes federal agencies should consider hyperautomation an essential part of their digital transformation journey and integral to improving mission outcomes and citizen services.
“As more of our customers adopt cloud technologies, we’ll see an acceleration of hyperautomation,” he says. “Cloud platform capabilities really provide the foundation for that agility and automation that customers are looking for to make a direct impact.”
MORE FROM FEDTECH: Some agencies are attempting to catch up on machine learning integration.
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