Can “smart” technology make government, well, smarter? It’s already happening: Through AI-based applications, developers are looking to transform the public sector by automating tasks and much more. But for optimal gain, agencies must make tough choices about where and how to introduce new technologies.
Artificial intelligence already helps run government, with cognitive applications doing everything from reducing backlogs and cutting costs to handling tasks we can’t easily do on our own, such as predicting fraudulent transactions and identifying criminal suspects via facial recognition. Indeed, while we expect AI-based technology in the years ahead to fundamentally transform how public-sector employees get work done—eliminating some jobs, redesigning countless others, and even creating entirely new professions1—it’s already changing the nature of many jobs and revolutionizing facets of government operations.
Agencies today face new choices about whether some work should be fully automated, divided among people and machines, or performed by people but enhanced by machines. Our latest report, AI-augmented government, conservatively estimates that simply automating tasks that computers already routinely do could free up 96.7 million federal government working hours annually, potentially saving $3.3 billion. At the high end, we estimate that AI technology could free up as many as 1.2 billion working hours every year, saving $41.1 billion.
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Cognitive technologies could eventually revolutionize every facet of government operations, from virtual desktop assistants to applications that can govern large, shifting systems.2 Indeed, they are already having a profound impact on government work, with more dramatic effects to come. AI-based applications can reduce backlogs, cut costs, overcome resource constraints, free workers from mundane tasks, improve the accuracy of projections, inject intelligence into scores of processes and systems, and handle many other tasks humans can’t easily do on our own, such as sifting through millions of documents in real time for the most relevant content.
AI’s potential benefits for government are clear. But which functions should be automated or made “smart,” and to what degree? Assessing different options’ business implications involves four main approaches to automation: relieve, split up, replace, and augment.
Relieve: Technology takes over mundane tasks, freeing workers for more valuable work. The Associated Press, for example, uses machines to write routine corporate earnings stories so that journalists can focus on in-depth reporting.22 Her Majesty’s Revenue and Customs Agency has automated the most tedious aspect of its call center work, opening case numbers for advisers so they don’t have to search the database. The agency estimates this has reduced handling times by 40 percent and processing costs by 80 percent.3 The relieve approach allows government to focus on reducing backlogs or shifting workers to higher-value tasks.4
Split up: This approach involves breaking a job into steps or pieces and automating as many as possible, leaving humans to do the remainder and perhaps supervise the automated work. Relying on machine language translation and leaving professional translators to “clean up” the results is one example. For example, at the United Nations, machines could handle live translation of the assembly meetings for spectators, while expert translators could revise transcripts for later release to news outlets. Several federal entities, from the White House to the US Customs and Immigration Services, have chatbots designed to answer basic questions and leave complicated responses to a human.5
Replace: In this approach, technology is used to do an entire job once performed by a human. The US Postal Service uses handwriting recognition to sort mail by ZIP code; some machines can process 18,000 pieces of mail an hour.6 The best opportunities for replace include repetitive tasks with uniform components, decision making that follows simple rules, and tasks with a finite number of possible outcomes. If you’ve ever fought a computer program (maybe on an airline website?) because your situation lay outside the narrow possibilities its designers imagined, you know how frustrating it can be.
Augment: In this approach, technology makes workers more effective by complementing their skills. This is the true promise of AI: humans and computers combining their strengths to achieve faster and better results, often doing what humans simply couldn’t do before. When technology is designed to augment, humans are still very much in the driver’s seat. An example is IBM’s Watson for Oncology, which recommends individual cancer treatments to physicians, citing evidence and a confidence score for each recommendation, to help them make more fully informed decisions.7
For each of these automation approaches, government agencies should consider their priorities. A cost strategy uses technology to reduce costs, especially by reducing labor. A value strategy focuses on increasing value by complementing human labor with technology or reassigning it to higher-value work. Of course, the two can be combined.
Ultimately, cognitive technologies will fundamentally change how government works—and the changes will come much sooner than many think. Strategic workforce planning must evolve beyond a focus on talent and people to consider the interplay of talent, technology, and design. As technologies advance in power, government agencies must bring more creativity to workforce planning and work design. Mission, talent, and technology leaders must work together to analyze the issues and opportunities and propose a path forward.
For our full report on how cognitive technologies could transform the public sector, see AI-augmented government.
