BRANDON CROSBY, NATHAN THOMPSON, LISA M. HARRINGTON, DANIEL B. GINSBERG
Modernizing Department
of Defense Civilian Human
Resources
Harnessing AI for Transformative
Change
H
aving the largest number of civilian employees in the federal government, the U.S. Depart-
ment of Defense (DoD) has a pivotal opportunity to modernize its workforce management.
Although defense conversations often center on warfighting capabilities, the performance
of the civilian workforce—more than 770,000 strong—is essential to meeting the depart-
ment’s strategic and operational goals. Across DoD components, the pace of technological advance-
ment, the growth of workforce demands, and persistent process inefficiencies have prompted a
search for innovative approaches to workforce management.
Artificial intelligence (AI) is increasingly viewed as a potential tool to improve efficiency, con-
sistency, and decisionmaking across human resources (HR) operations. AI refers to computational
(i.e., not human) systems or techniques that can perform tasks that have limited human oversight.
AI systems exhibit human-like qualities, such as learning from experience, reasoning, and decision-
making, by analyzing large volumes of data to improve their performance over time (Slama, Lim,
and Yeung, 2024). In workforce contexts, AI systems—especially those built on machine learning,
deep learning, and large language models—enable powerful functionalities, such as pattern recogni-
tion, classification, prediction, and content generation. These capabilities are central to many appli-
cations in defense human resource management (DHRM).
Framework and Scope
Our project applied a flexible framework as a broad guide on potential use cases and implementa-
tion issues. Our framework captures how DHRM involves central components, including personnel
plans (e.g., staffing, requirements), development (e.g., training, education), and engagement (e.g.,
compensation, benefits, acquisition through recruiting and retention). Figure 1 illustrates these
Research Report
