Procurement Research
Description
Generative AI is new to the acquisition workforce. User research is needed to determine how to make AI-powered procurement systems easy-to-use, highly functional, and accurate for agency employees performing procurement tasks. Further, there is little research on which AI models are most performant for federal procurement tasks. An objective evaluation is needed to compare commercial AI models and possibly fine-tune or otherwise improve AI models for the federal procurement domain.
Detailed example
Generative AI outputs narrative for procurement documents.
AI / analytics pattern
Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
America’s AI Action Plan, dated July 2025, calls AI procurement toolbox managed by the General Services Administration (GSA), in coordination with OMB, that facilitates uniformity across the Federal enterprise to the greatest extent practicable. This system would allow any Federal agency to easily choose among multiple models. Agencies should also have ample flexibility to customize models to their own ends, as well as to see a catalog of other agency AI uses. Treasury is well-positioned to make a significant contribution and advance the state of the art in AI models used for procurement tasks.
Audit / financial statement impact
Research effort may examine AI bias (e.g. large vs. small business) in drafting procurement documents as market research / proposal evaluation. Research effort and not an operational use case where AI will make or influence government decisions.
Controls / human review
ATO: Not reported; PIA: Not published