Automation Mismatch: How Contractor AI Adoption Challenges Institutional Procurement Norms at U.S. Customs and Border Protection (CBP)

Abstract

This letter explores a growing strain in the U.S. federal procurement: the automation mismatch between AI-powered proposal development by contractors and the regulation-bound evaluation systems at agencies like U.S. Customs and Border Protection (CBP). Tools like Vultron and Unanet AI have enabled federal contractors to increase proposal submission volume, yet institutional constraints such as data sensitivity, budget limitations, and cultural barriers have hindered equivalent modernization on the government side. This article leverages institutional theory and prior research to analyze this disparity, highlighting how legal and cultural factors limit AI integration in procurement. Detailed analysis of these regulatory and cultural influences is essential to understanding and navigating the future of AI in procurement