Leaders should keep in mind that IA can mean jarring changes for their agencies.
It’s the stereotype that won’t die: the rise of soulless, artificially intelligent machines that will steal jobs from honest, hard-working Americans.
While that idea might make for good science fiction, it’s a far cry from the real nature of automation, especially as it applies to government.
The fact is, intelligent automation (IA) is not about labor arbitrage, it’s about labor augmentation. Intelligent automation is about removing the mundane, routine tasks that employees prefer not to do, and redirecting their efforts to more satisfying tasks that require human judgment and experience.
So why is intelligent automation so important to government? The short answer is that government faces urgent challenges that intelligent automation can help address, including reduced budgets, declining workforces, and increased demands and citizen expectations.
It’s a good time for government to seize the opportunity and some agencies are doing just that. For instance, some are wisely starting their IA journey by establishing advisory committees on automation and building proofs-of-concept to determine their return on investment, while developing IA roadmaps.
Other agencies are even further along. My firm has worked with a federal health care agency to deploy automation to improve the efficiency and quality of its data collection process—freeing employees to focus on more valuable, customer-facing tasks. The General Services Administration is using a chat bot to onboard new employees. The National Institutes of Health is using cognitive computing as a way to help it determine where and how to direct research funding. The Food and Drug Administration is automating certain data sets.
There are a few things agency officials, particularly chief information officers, should keep in mind before jumping into IA. The first is to determine which of the three classes of IA to pursue. To automate routine, repetitive tasks, such as cutting and pasting data from one form to another, consider the entry-level class: robotic process automation. RPA tools can work with existing IT architecture and can serve as a good launch point as agencies gain sophistication.
For agencies ready to move up the IA food chain, the next class is cognitive automation. This class includes a range of tools and technologies, including natural language processing, which can address a large number of complex transactions, requiring a deeper level of analytics of both structured and unstructured data. These tools can potentially transform back office operations, but they require integration with an agency’s existing architecture. One example is the use of a chat bot on an agency’s website that can help a citizen gain information through text or voice chat.
The highest level of sophistication is reasoning cognitive automation, which holds the promise of learning and solving problems using artificial intelligence, machine learning and natural language processing. Can you imagine having IBM Watson at your side when facing a highly complex problem, such as examining large data sets and looking for patterns that might indicate possible fraud, or trying to assess the best approach to a cybersecurity problem?
For any agency planning the leap into IA, the key is to start small. Choose a particular process to automate and get the right tool for the job. Once that process works well, scale it across the organization and then tackle more complex processes.
Finally, leaders should keep in mind that IA can mean jarring changes for their agencies, which argues for addressing cultural and governance issues up front. IA is more than a technology issue and leaders from across an agency should participate in the planning. And of course, clear, honest communication with the agency’s workforce to describe changes and why they’re occurring is required.
Intelligent automation has the potential to generate incredible value in government services. By harnessing data and technology to engage more citizens, augment workforce capabilities, and improve employee satisfaction, intelligent automation can pave the way for government of the future: innovative, exciting, and increasingly more in touch with the citizens it serves.
Kirke Everson is the government intelligent automation lead at KPMG LLP. Tony Hubbard is the government security practice leader at KPMG LLP. The views expressed are theirs alone and do not necessarily represent those of KPMG LLP.
NEXT STORY Breaking Down What DevOps Means