Role of AI in Combating Corruption in the U.S. Federal Government: Case Study 2019–2024

This study investigates how U.S. federal agencies have employed artificial intelligence (AI) to advance governance and combat corruption following the 2019 American AI Initiative. Drawing on an original dataset of 1,757 AI applications across 37 civilian agencies, researchers offer the first comprehensive analysis of AI's role in federal integrity systems. While 21 agencies deployed AI for anticorruption purposes, such as fraud detection, risk scoring, process automation, and transparency reporting, 16 agencies showed little or no engagement. Study findings reveal that AI is increasingly used to detect financial irregularities and strengthen oversight, particularly in high-risk policy domains like healthcare and homeland security. However, adoption is fragmented, with agencies developing isolated tools absent a coordinated governance framework. This uneven implementation raises concerns about equity, effectiveness, and accountability. The authors propose a federal AI governance model for anticorruption that prioritizes transparency, algorithmic standards, and strategic investment in vulnerable programs. The analysis highlights both the promise and limitations of AI as a tool for ethical public administration, to support responsible implementation and to address the institutional and normative challenges of integrating AI into public integrity efforts.