Procurement in the Age of Platforms: AI, Privatization, and Systemic Change in Urban School Districts

• In Event: Urban AI Unlocked: Transforming District Systems for Equitable AI Integration

Abstract

Objectives

This paper examines the evolving landscape of educational privatization in the United States, focusing on district-level spending and procurement processes for emerging artificial intelligence (AI) platforms.

Perspective

Positioned within the context of current policy and research debates, the analysis uses a post-neoliberal lens to understand how privatization operates through overlapping influences including district policy, market dynamics, and technological innovation. Unlike prior models of privatization that emphasized visible, transactional outsourcing, this study explores how AI-driven platforms and service contracts are increasingly embedded within the daily operations of school districts.

Methods

The study is grounded in quantitative trends and enriched by a stratified survey of district administrators.

Data Sources

Drawing on a comprehensive, longitudinal database of procurement and contract documents from over 10,000 local education agencies (LEAs), and enriched by a stratified survey of district administrators, the paper provides new empirical insight across several key dimensions. It investigates how year-over-year spending on AI platforms varies by district characteristics, which vendors are most prominent following advances in generative AI, and how contract terms shape district autonomy, data ownership, and oversight. The analysis, permitting comparisons between contract structures, spending flows, and local perceptions of AI procurement, also examines patterns of market concentration and considers how these changes may influence transparency, equity, and decision-making in both large and under-resourced districts.

Results

From 2018-2025, we observe over $2.04 billion in spending on AI. In this time, the average LEA has spent $185,810 on AI platforms. Findings reveal that while AI spending is rising across many districts, the adoption and governance of these technologies are far from uniform. Opportunities exist for greater efficiency, personalization, and access, but there are also challenges—including disparities in adoption, varying degrees of negotiating power, and concerns over data privacy and long-term vendor dependence.

Significance

Rather than casting AI-driven privatization as inherently problematic or inherently beneficial, the paper takes a balanced approach, highlighting both the benefits and the complexities introduced by new procurement models. Practical recommendations are offered for districts and policymakers, including approaches to negotiating more equitable contracts, increasing transparency over technology adoption, and sharing best practices. Ultimately, this analysis demonstrates that only through the rigorous integration of conceptual insight and empirical investigation can stakeholders fully grasp the complex ways AI is reshaping educational governance and develop informed strategies that balance technological innovation with the preservation of equity, transparency, and public accountability in education.

Authors

• Patricia Burch, University of Southern California

• Junmin Byon, University of Southern California

• Alvin Makori, University of Southern California

• Shelby Leigh Smith, University of Southern California