Accelerating the Future: Leveraging AI for the Transformative Federal Acquisition

Abstract

"The U.S. Department of Defense (DoD) has requested $310.7 billion in funding for Fiscal Year 2025 dedicated to Procurement, Research, Development, Test, and Evaluation (RDT&E). This includes an allocation of $167.5 billion for Procurement and $143.2 billion for RDT&E. As the largest federal contracting entity, the DoD awards contracts across a wide spectrum, from major weapon systems to software development to food services. To support these vast acquisition programs, the DoD relies on a skilled acquisition workforce equipped with the management, technical, and business capabilities needed to oversee these programs and activities from conception to completion. However, the rise of technologically advanced strategic adversaries highlights the need for the DoD to streamline its acquisition practices. Modernizing these traditionally time-consuming processes to include technologies like artificial intelligence (AI) is critical to bolstering acquisition professionals’ efficiency and effectiveness. To address these challenges, The MITRE Corporation and the National Defense Industrial Association’s (NDIA) Emerging Technologies Institute conducted a joint research initiative. In October 2024, MITRE and NDIA ETI co-hosted a symposium on “Leveraging AI in Acquisition,” which explored potential AI applications to enhance the defense acquisition workforce and their processes. Drawing on insights from the symposium and interviews with AI and acquisition experts, the research team identified key acquisition areas where DoD-developed and commercial AI could be applied, as well as the barriers to integrating AI within various federal acquisition phases. These targeted areas for AI application potentially include: • Market Research • Request for Proposal/Quote Creation • Evaluation • Contract Management While the integration of AI holds significant promise for enhancing defense acquisition, certain critical functions must remain human-led. This research offers a range of recommendations to support the transition to a modern, AI-enabled acquisition system and offers strategies to address structural and cultural barriers."