GSA Generative AI and Specialized Computing Infrastructure Acquisition Resource Guide
GSA-AI-GUIDE-2024 · US
In force since 2024-09-24. A Policy statement from US. Procurement-focused operational guide accompanying OMB M-24-10 and the broader EO 14110 / EO 14179 federal-AI policy stack. Provides agencies with: (1) market intelligence on the GSA Multiple Award Schedule special item numbers covering AI services (54151S IT Professional Services + the newer AI / Generative AI SINs); (2) sample acquisition language for responsible-AI requirements (bias-testing, transparency, evaluation, security); (3) supply-chain risk-management considerations including model-provenance and dependency disclosure; (4) requirements derivation guidance for safety- and rights-impacting AI per OMB M-24-10 Attachment 1. The guide is non-binding on its own but agencies typically incorporate its language into solicitation packages.
Key finding
Federal procurement guide for generative AI + specialised compute; sample responsible-AI clauses, supply-chain risk, and Multiple Award Schedule SINs for agencies.
“Agencies should incorporate responsible-AI requirements directly into solicitations for generative AI services.”
Coverage at a glance
Coverage fingerprint — color = verdict, height = confidence. One tick per tracked topic.
Key finding
Federal procurement guide for generative AI + specialised compute; sample responsible-AI clauses, supply-chain risk, and Multiple Award Schedule SINs for agencies.
“Agencies should incorporate responsible-AI requirements directly into solicitations for generative AI services.”
intro · Primary source
Reviewed by Editorial board (in formation) (Policy Window) · · Editorial board
Scope and obligations
Procurement-focused operational guide accompanying OMB M-24-10 and the broader EO 14110 / EO 14179 federal-AI policy stack. Provides agencies with: (1) market intelligence on the GSA Multiple Award Schedule special item numbers covering AI services (54151S IT Professional Services + the newer AI / Generative AI SINs); (2) sample acquisition language for responsible-AI requirements (bias-testing, transparency, evaluation, security); (3) supply-chain risk-management considerations including model-provenance and dependency disclosure; (4) requirements derivation guidance for safety- and rights-impacting AI per OMB M-24-10 Attachment 1. The guide is non-binding on its own but agencies typically incorporate its language into solicitation packages.
GSA Generative AI and Specialized Computing Infrastructure Acquisition Resource Guide addresses 3 contested AI-governance topics explicitly, 3 via general principles,.
Topics governed
- governsFoundation Models / GPAI— Sections covering generative AI vendor evaluation + model-provenance disclosure requirements in solicitation language
Generative AI acquisition guidanceparaphraseFaithful summary: the guide treats generative-AI and foundation-model acquisition as a discrete category, with sample solicitation language for evaluating model provenance, capabilities, and vendor documentation.
- governsCompute-Threshold Reporting— Guide enumerates GSA Multiple Award Schedule SINs covering AI / Generative AI services so agencies can report on AI acquisitions through the SIN structure
GSA MAS AI SINsparaphraseFaithful summary: the guide enumerates GSA Multiple Award Schedule Special Item Numbers covering AI and generative-AI services so agencies can route and report AI acquisitions through the SIN structure.
- governsTransparency Obligations— Sample solicitation language requires vendor disclosure of training-data provenance, evaluation results, and model documentation
Vendor disclosure / evaluation criteriaparaphraseFaithful summary: sample solicitation language directs agencies to require vendor disclosure of training-data provenance, evaluation and benchmarking results, and model documentation as part of AI acquisition.
- implicitIndividual Redress— Guide references OMB M-24-10 Attachment 1 minimum practices including human-consideration + remedy for rights-impacting AI
- implicitTraining-Data Rights— Supply-chain risk-management considerations include training-data provenance + dependency disclosure
- implicitNational Security Carveouts in AI Regulation— Guide references existing federal supply-chain risk-management framework (FAR Part 4 Subpart 4.21) which carries national-security overlays
Cross-jurisdiction comparison
How peer instruments treat the topics GSA Generative AI and Specialized Computing Infrastructure Acquisition Resource Guide governs.
| Topic | EU-AIA-2024 | US-EO-14110 | US-EO-14179 | UK-WHITEPAPER-2023 | CN-GENAI-2023 | G7-HIROSHIMA | OECD-AI-PRIN | COE-AI-CONV | UN-RES-2024 | NIST-AI-RMF | BLETCHLEY-2023 | SEOUL-2024 | NIST-AI-RMF-GENAI | CA-SB-1047 | IN-DPDP-2023 | BR-AIBILL-2024 | ASEAN-AI-GUIDE-2024 | AU-AI-STRATEGY-2024 | ANTHROPIC-RSP-2024° | OPENAI-PREPAREDNESS-2023° | DEEPMIND-FSF-2024° | META-FRONTIER-2024° | UK-US-AISI-MOU-2024 | WH-VOLUNTARY-2023 | SG-MODEL-AI-2024 | JP-METI-AI-2024 | NYC-LL-144-2021 | CO-SB-24-205 | IL-HB-3773-2024 | EU-GDPR-2016 | EU-GPAI-COP-2025 | EU-AIA-DELEGATED-ART51 | OMB-M-24-10 | FAR-PART-39 | DOD-RAI-2022 | FEDRAMP-AI-2024 | DFARS-252-204 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Foundation Models / GPAI | governs | governs | silent | implicit | governs | governs | implicit | implicit | silent | governs | governs | governs | governs | governs | implicit | governs | implicit | silent | governs | governs | governs | governs | governs | governs | governs | governs | silent | silent | silent | silent | governs | silent | implicit | implicit | implicit | implicit | implicit |
| Compute-Threshold Reporting | governs | governs | silent | silent | silent | silent | silent | silent | silent | silent | implicit | implicit | silent | governs | silent | silent | silent | silent | implicit | implicit | silent | silent | silent | implicit | silent | silent | silent | silent | silent | silent | silent | silent | governs | implicit | implicit | implicit | implicit |
| Transparency Obligations | governs | implicit | silent | implicit | conflicts | governs | governs | governs | implicit | governs | implicit | governs | governs | implicit | implicit | governs | governs | silent | governs | implicit | implicit | governs | implicit | governs | governs | governs | silent | silent | silent | governs | governs | silent | governs | implicit | governs | governs | silent |
°= industry self-imposed voluntary framework. Comparing a voluntary code's "governs" tint with a binding regulation's "governs" tint flattens the legal-force distinction; use the instrument-page banner for the operative status of each.
How to cite this article
APA 7
Policy Window. (2024). GSA Generative AI and Specialized Computing Infrastructure Acquisition Resource Guide [Wiki article — Instrument]. https://policywindow.org/wiki/gsa-ai-acquisition-guide
Chicago 17
Policy Window. 2024. "GSA Generative AI and Specialized Computing Infrastructure Acquisition Resource Guide." Wiki article (Instrument). https://policywindow.org/wiki/gsa-ai-acquisition-guide.
BibTeX
@misc{policywindow-gsa-ai-acquisition-guide,
title = {GSA Generative AI and Specialized Computing Infrastructure Acquisition Resource Guide},
author = {Policy Window},
year = {2024},
howpublished = {GSA, Generative AI and Specialized Computing Infrastructure Acquisition Resource Guide (Sept. 24, 2024)},
url = {https://policywindow.org/wiki/gsa-ai-acquisition-guide},
note = {Primary source: https://www.gsa.gov/technology/government-it-initiatives/artificial-intelligence/ai-acquisition-resources}
}References
- GSA, Generative AI and Specialized Computing Infrastructure Acquisition Resource Guide (Sept. 24, 2024)
- Sections covering generative AI vendor evaluation + model-provenance disclosure requirements in solicitation language
- Guide enumerates GSA Multiple Award Schedule SINs covering AI / Generative AI services so agencies can report on AI acquisitions through the SIN structure
- Sample solicitation language requires vendor disclosure of training-data provenance, evaluation results, and model documentation
- Guide references OMB M-24-10 Attachment 1 minimum practices including human-consideration + remedy for rights-impacting AI
- Supply-chain risk-management considerations include training-data provenance + dependency disclosure
- Guide references existing federal supply-chain risk-management framework (FAR Part 4 Subpart 4.21) which carries national-security overlays
Cite this article
6 formats · 1-click copyPersistent identifier: https://policywindow.org/wiki/gsa-ai-acquisition-guide — committed-stable URL with content-versioning via ?asOf= (rollout pending per methodology §7). DOIs via Zenodo are on the roadmap.
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Per-audience views
- Provisions →Article-by-article obligation breakdown for procurement + RFP authors.
- Disclosure form →Vendor-disclosure questionnaire derived from this instrument's operative obligations.
- Harm narratives →Documented harms relevant to this instrument's topics, for civil-society advocacy.
- Briefing pack →Journalist-ready summary with quotes + dates + primary-source links.