Legacy Procurement Practices Shape How U.S. Cities Govern AI: Understanding Government Employees' Practices, Challenges, and Needs
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Most AI tools adopted by governments are not developed internally, but instead are acquired from third-party vendors in a process called public procurement.In this paper, we conduct the first empirical study of how United States cities' procurement practices shape critical decisions surrounding public sector AI.We conduct semi-structured interviews with 19 city employees who oversee AI procurement across 7 U.S. cities.We found that cities' legacy procurement practices, which are shaped by decades-old laws and norms, establish infrastructure that determines which AI is purchased, and which actors hold decision-making power over procured AI.We characterize the emerging actions cities have taken to adapt their purchasing practices to address algorithmic harms.From employees' reflections on real-world AI procurements, we identify three key challenges that motivate but are not fully addressed by existing AI procurement reform initiatives.Based on these findings, we discuss implications and opportunities for the FAccT community to support cities in foreseeing and preventing AI harms throughout the public procurement processes.
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In the US, the private sector currently exerts disproportionate influence over the AI systems purchased by the public sector, including their capabilities and technical specifications.
“A recent study in the US context finds that the private sector currently exerts disproportionate influence over the AI systems that are purchased by the public sector, including their capabilities and technical specifications [94].”
From “It’s Just a Wild, Wild West”: Harnessing Public Procurement as an AI Governance Mechanism (2026) · cites this paper as [94]
The Introduction says most AI systems used by U.S. governments are developed and acquired from private vendors. Sections 5.1 and 5.2 report that vendors shape cities’ understanding of AI use cases, withhold technical information, and sometimes introduce features cities struggle to disable. These findings support substantial vendor influence, but the paper does not establish disproportionate influence over technical specifications across the U.S. public sector; its empirical findings concern interviewed cities. (LLM, conf=0.84)
Experimental — accuracy not yet measuredThe public sector rarely exercises its procurement power effectively; rigorous procurement processes are often bypassed through informal purchasing routes, and suppliers frequently withhold information or resist contractual changes.
“Another US study confirms this trend, showing that the public sector rarely exercises its procurement power effectively: rigorous procurement processes are often bypassed through informal purchasing routes. Even when formal procurement takes place, suppliers frequently withhold information or resist contractual changes, which impacts the leverage of public authorities [94].”
From “It’s Just a Wild, Wild West”: Harnessing Public Procurement as an AI Governance Mechanism (2026) · cites this paper as [94]
The Conclusion reports that most AI technologies in the studied cities were acquired through alternative pathways rather than formal solicitation. Section 5.2 reports that AI vendors frequently withheld information, resisted changes to contract terms, and left city employees feeling they lacked leverage. The citing sentence extends these findings about municipal AI procurement to the public sector generally, which this study does not establish. (LLM, conf=0.87)
Experimental — accuracy not yet measuredPublic procurement could position the public sector as a gatekeeper, ensuring AI systems purchased by government agencies are better aligned with the public interest.
“According to these works, public procurement could position the public sector as a gatekeeper, ensuring that AI systems purchased by government agencies (where such systems typically have direct societal impact) are better aligned with the public interest [13, 94].”
From “It’s Just a Wild, Wild West”: Harnessing Public Procurement as an AI Governance Mechanism (2026) · cites this paper as [94]
An imbalance in which the private sector exerts disproportionate influence may lead to procurement of systems that prioritise corporate interests over those of citizens.
“Such an imbalance may lead to the procurement of systems that prioritise corporate interests over those of citizens.”
From “It’s Just a Wild, Wild West”: Harnessing Public Procurement as an AI Governance Mechanism (2026) · cites this paper as [94]
AI systems used in the public sector are often purchased from or outsourced to the private sector.
“Often, such systems are purchased from private sector organisations [9, 94].”
From “It’s Just a Wild, Wild West”: Harnessing Public Procurement as an AI Governance Mechanism (2026) · cites this paper as [94]
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“It’s Just a Wild, Wild West”: Harnessing Public Procurement as an AI Governance Mechanism
Hudig, A. I., Kallina, E., & Singh, J. (2026) · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791968 · Cited by 3 · see citing works
Disclosure or Marketing? Analyzing the Efficacy of Vendor Self-reports for Vetting Public-sector AI
Kuehnert, B., Johnson, N., Dotan, R., & Heidari, H. (2026) · Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency · doi:10.1145/3805689.3812220
Self-citation
- Authors
- Johnson, N., Silva, E., Leon, H., Eslami, M., Schwanke, B., Dotan, R., & Heidari, H.
- Affiliations
- Carnegie Mellon University (US)
- University of Pittsburgh (US)
- TechBetter, Pittsburgh, PA, USA
- ORCID
- Venue
- Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency
- Publisher
- ACM
- Published
- 2025-06-23
- Pages
- 772-789
- OpenAlex
- W4411541888
- Cited by
- 12
- References
- 12
- Citations by year
- 2026: 10 · 2025: 1 · 2024: 1
- FWCI
- 11.17
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- ACM Conference on Fairness, Accountability, and Transparency (FAccT) (publishedVersion, cc-by)
- arXiv (Cornell University) (submittedVersion, cc-by)
- arXiv (Cornell University) (cc-by)
- Funders
- National Science Foundation (IIS2229881)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Business, Management and Accounting › Strategy and Management › Public Procurement and Policy
- Social Sciences › Political Science and International Relations › E-Government and Public Services
- Keywords
- public procurement, AI procurement, municipal government, algorithmic harms, AI governance, third-party vendors, procurement reform, public sector employees, decision-making power, American cities
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