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April 30 - May 1, 2025
North Javits Center | New York City

4 Ways the U.S. Government is Leveraging Data and AI in a Quest for Efficiency

Reputationally, the provision of services by governments at every level in every jurisdiction is subpar compared to the private sector. Torturous lines at the DMV, years-long delays in road and infrastructure repair, and interminable waits for passports and visas are only some of the horror stories surrounding government services. Stories of the graft, nepotism, inefficiency and incompetence of government employees and systems are legend. But because of their scale, especially at the federal level, governments have more opportunities to fix some of those efficiencies by implementing improved data storage, management and analysis techniques and technology.

The United States Federal Government employs nearly three million people—almost a million more than Walmart, the U.S.’s second-largest employer. And, despite its reputation, various administrations and agencies have begun to embrace the power of data. To guide them in this effort, under the General Services Administration, a Data & Analytics Center of Excellence was established in 2017 and a playbook released.

Here are some case studies from the U.S. government’s own files that indicate how that effort is progressing, how it is thinking about data, and provide some implementations that are finding success and could serve as harbingers of more to come:

  • In the 1980s, the U.S. Geological Survey and the U.S. Census Bureau joined forces to build the first national digital database of roads and boundaries. That collaboration grew to include every level of U.S. geography and serves ad the basis for the ecosystem of companies providing GPS and other geographic information systems. The database—updated continuously with data shared from tribal, state, and local government partnership programs—serves as the basis for the authoritative National Map
  • The National Institute of General Medical Sciences (NIGMS), a unit of the National Institutes of Health deployed Natural Language Processing (NLP) and Machine Learning (ML) to automate the process by which it receives and internally refers grant applications. The NIGMS AI team trained an NLP ML algorithm to process the applications and determine associations between the application text and referral choices. The average referral time for an application has been cut from 2-3 weeks to less than a day.
  • The Federal Chief Data Officer’s Council recently released a report on how NLP can be used to streamline the regulatory process by enabling automated review and response to public comments. Accepting public comment is a vital part of putting regulations into effect, and required by law. The government receives millions of public comments on pending regulations each year and the CDO report explores implementing AI technologies to introduce more automation in that process in every federal agency. The report estimates that for every 1,000 comments, the system will save 125 hours.
  • NASA researchers and data scientists used AI to build an automated tagging system to make finding structured and unstructured information that exists in disparate sources easier. The model was trained on a database of 3.5 million manually tagged research reports, articles, papers, blogs and other content making it easier for workers who need the information to access it. The system serves as an example of how other agencies can use their own unstructured data to improve information accessibility and promote data reuse.

Ultimately, the data gathered, stored, processed and analyzed by different agencies of the United States federal government is done so in the service of the country’s citizens. While the case studies cited above will result in efficiency and productivity gains, those gains are not simply for the sake of having a well-run organization or for profit. According to the Federal Data Strategy framework launched in 2021, the primary reason for the government to implement the most advanced ways to leverage data is to “maintain its role as a preeminent supplier and sophisticated and ethical user of data,” fulfilling its duty to the public.

Through the initiatives described here, and many others, the U.S. federal government seeks to create a “robust, integrated approach to using data to deliver mission, serve the public, and steward resources.”