It is no secret that the world is heavily investing in Artificial Intelligence (AI) because of the economic and societal benefits that it has the potential to deliver. Last year, President Biden proposed roughly $5.5 billion in government spending and his most recent budget proposal once again prioritized AI investment to ensure the United States’ global leadership in the government’s adoption of AI. Congress has also done its part by funding critical elements, such as the National Institute of Standards and Technology’s (NIST) recently announced AI Safety Institute Consortium that will bring industry together to develop essential AI safety benchmarks, frameworks and techniques. 

Despite the attention that AI is receiving, much of the funding still prioritizes early-stage research, incremental improvements for existing programs, or short-term pilot projects. While these efforts are important, Congress must also fund new, potentially transformative AI initiatives that will unlock the potential economic and efficiency gains.

We cannot afford to wait to invest sufficiently in AI. As Congress begins to debate the FY25 Authorizations and Appropriations, Scale recommends addressing three key items to ensure that the United States remains the global leader in the government’s adoption of AI and to yield the maximum value of its investments for American taxpayers. 

 

Recommendation 1: The government must start to adequately plan for AI costs to truly implement AI. 

If the United States wants to lead the world in the development and deployment of AI across the federal government, then it must start by properly planning for AI program costs, such as training data, in the same way that it plans for more traditional costs like hardware and maintenance.

AI has the potential to improve the efficiency of nearly every government use case. In a matter of years, it is likely to be used in every program in the U.S. government, from building more high-quality algorithms for Department of Defense autonomy programs to accelerating regulatory actions, such as speeding up the rulemaking process. To achieve this vision, however, the President and Congress must include the ongoing sustainment costs for AI in the budgets.

AI systems require constant high-quality data to train, maintain, and improve foundational models so the technology performs reliably for its intended use case. For this reason, the commercial industry has long invested in “AI-ready data” to consistently train and maintain its AI models. While the federal government has long considered AI-ready data to be a “national asset,” the acquisition system, which was set up around maintaining platforms like ships and airplanes, is not well suited to fund a different type of technology that requires ongoing refinement for high-quality outputs.

To truly harness the power of AI, Congress and the White House must create and fund dedicated AI lines in each program that will create, maintain, and enhance effective AI capabilities.
 

Recommendation 2: The government must prioritize implementing and fielding AI, in addition to research.

There is no doubt that some fundamental research gaps exist, particularly around AI safety, and we must adequately fund agencies, such as NIST, to do this crucial work. However, If the U.S. government is serious about deriving economic value and efficiency gains from AI, then it must invest in putting AI capabilities into users’ hands so its true benefits can be realized.

Historically, keeping up with the pace of emerging technologies, like AI, has been a challenge for the U.S government, primarily because funding cycles require budgets to be crafted, in some cases, 18 months before they are approved. Beyond the budget cycle, acquisition programs were designed decades ago to procure legacy systems. For example, the funding levels contained in the FY24 budget, which Congress recently passed in March, 2024, were largely set before ChatGPT thrust the idea of generative AI into the national consciousness.

In reviewing FY24 spending, and as more details related to the FY25 budget become available, it is clear that there is a strong, continued, emphasis on funding AI research and development and short-term pilot programs. While this can be valuable, as history has shown, this strategy often fails at getting AI into the hands of government users and warfighters in a meaningful way.  In the past five years, only one AI effort has fully transitioned from a pilot program to a productive program of record.

 

Recommendation 3: More targeted investment is needed for AI programs, instead of using AI funds on legacy software programs. 

Despite the at least $5 billion per year in reported topline AI funding, the amount of funding available for AI programs is less than it seems as the majority of that money typically is used to fund legacy software and hardware, which may only include a small use of AI. For example, if a program is receiving $350 million for its entire annual budget, but only $10 million of that funding is geared towards AI development and deployment, all $350 million is reported as AI spend. 

There is no shortage of newly launched AI initiatives that have been established across the government. However, the programs are underfunded to achieve the intended outcome. To adequately fund these programs, it is vital that the reported AI funding is going to carry out actual, dedicated AI programs. To do so, Scale recommends that the U.S. government ensures that the entirety of its AI investment truly works to fund AI programs and efforts.