AI and RPA in federal government: The time is right

Here's why AI and RPA are priorities in federal government IT – and how we're planning the journey
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Artificial intelligence (AI) is of great strategic importance to the United States. We are recognized as the current leader in the space, and as such, are investing in capabilities and opportunities to ensure we are progressing AI forward across the country. AI is instrumental in providing the country with a competitive advantage. If we’re not raising the bar in the United States, other countries will become more adept leaders in the space. 

AI is instrumental in providing the country with a competitive advantage.

AI is a top priority at the federal level right now. The President recently signed an executive order on AI to articulate the investments that are needed for technology breakthroughs and to reduce barriers to entry for firms entering into the AI space. The executive order also addresses the reskilling necessary for the workforce to deliver on AI, as well as building trust in the space around how decisions are made. This executive order is also key to enabling the country to participate in AI at an international level. 

[ Read also: AI vs. machine learning: What’s the difference? ]

This, along with the President's Management Agenda — which addresses leveraging data as a strategic asset — recognizes that AI is a capability that the country needs. Not only is it instrumental in improving the experience and effectiveness of citizens’ engagement with federal services, it also enables core capabilities that strengthen our national security and defense. 

Harnessing AI’s opportunities 

The opportunities in AI are significant, and they’re possible thanks to the function of three things: the growth and explosion of data; the availability of technologies that enable capabilities like text, speech, and visual analytics; and, the data science techniques of machine learning. These have all made AI more practical, usable, and executable.

At the federal level, a number of agencies are exploring uses for AI tools. Several examples exist where agencies are leveraging Internet of Things sensors, machine learning algorithms, visual pattern recognition, and text and speech analytics in support of their missions. Agencies are beginning to deal with issues related to data quality, explainability of algorithms, privacy, governance and scalability. The time is ripe for the Federal government to take advantage of these technologies in order to better serve the American public. 

Many civilian and federal agencies’ use of information processing, process improvement, and intelligent character recognition have led to the use of AI in robotic process automation (RPA). There’s a significant opportunity to use AI and RPA to automate processes around antiquated systems without the expense associated with replacing the legacy platforms. 

[ Need a primer? Read also: How to explain Robotic Process Automation (RPA) in plain English. ]

Inside our AI framework 

In thinking about how to apply RPA and intelligent process automation (IPA), the General Services Administration developed a three-phased framework. In the first Evaluation phase, we look at the end-to-end processes in an agency to determine where critical pain points exist. In this evaluation phase, the agencies will consider whether a particular process or pain point actually needs to be automated or eliminated. Second, there’s the application of the process automation tools - whereby the actual bots are implemented. This is followed by a third phase of monitoring and iteration of the automation bots. 

The benefit of using an RPA approach is that you’re not completely replacing the legacy platform, you’re building a layer on top of it to enable automation across those legacy platforms.

When agencies follow this framework, they typically find that they have legacy platforms in the process that are causing pain points. The benefit of using an RPA approach is that you’re not completely replacing the legacy platform, you’re building a layer on top of it to enable automation across those legacy platforms. That’s what’s attractive about RPA: Rather than spending five plus years replacing a legacy platform, you can build process automation across legacy platforms using RPA techniques in just a few months. 

Another benefit is the cost avoidance of the actual expenses associated with manual fixes around outdated, broken, or legacy systems: There’s automation of controls, automation of reconciliation packages, and a number of other benefits like better accuracy, improving cycle time, and improving the speed of the actual operations. 

We believe that the majority of these RPA bots will evolve to be governed by AI, including rule-based decisioning. This is evidenced by RPA tool providers in the market building partnerships and APIs with AI software providers. The confluence of these two technologies is extremely useful for the IT modernization of federal technologies where we have a large number of legacy platforms. 

The Role of TTS 

The Technology Transformation Services (TTS) seeks to improve the way federal agencies buy, build, and share technology to enhance the public’s and federal employees’ experience with government. 

There are four offices within TTS:

  • 18F, which is a digital consulting office that partners with agencies to help them build or buy digital services;
  • IT modernization Centers of Excellence, which is a centralized team of technical experts that accelerate agency-wide IT modernization;
  • the Presidential Innovation Fellowship, which is a program that pairs innovators from the private sector with top civil-servants to spend 12 months tackling some of the nation’s biggest challenges;
  • and, the Office of Products and Programs, which has a diverse portfolio of mature products and services that help agencies improve delivery of information and services to the public. 

Given the work we do at TTS, we are really well-positioned to help agencies think about, conceptualize, and drive AI. We’ve ascertained that we should create a solution area, or Center of Excellence (CoE), that focuses on AI starting first with RPA — particularly intelligent process automation (IPA) that integrates AI techniques with RPA. We will use this Center of Excellence to deliver solutions across the federal government. 

In addition, in partnership with other parts of GSA, we’ve created a community of practice to promote RPA. The community of practice works across all agencies to share solutions, ideas, capabilities, and reusable platforms. For example, one day, we might discuss the challenges each of us are facing, while another day, we discuss the successes we’re seeing. 

The AI Center of Excellence will build on this community of practice. In addition, the AI CoE will consist of practitioners, reusable templates, code, and methods that can be leveraged in any agency’s AI implementation. 

Our RPA journey

The time is ripe for the use of AI across the federal government. TTS is well positioned to help federal agencies in this journey. We are starting down this path by creating an AI solution area - focused initially on robotic and intelligent process automation. This isn’t something that’s only applicable to the federal government, either — it’s something any CIO can do. AI is a journey of learning and building the right models to analyze data that generates actionable insights. RPA is a great way to start on that journey – and the time is now. 

[ How can automation free up more staff time for innovation? Get the free Ebook: Managing IT with Automation. ] 

Anil Cheriyan
Anil Cheriyan is Cognizant’s Executive Vice President, Strategy and Technology. Overseeing all aspects of Corporate Strategy, Global IT and Global Security, Anil is responsible for Cognizant’s strategy, alliances and business development, and for strengthening the company’s global IT and security capabilities.