Office of Grants Management (PGM) Grants Utility Tool
Description
PGM faced growing operational and compliance challenges across the entire financial assistance lifecycle. Manual processes—project description reviews, pre-award SAM.gov validations, and detailed budget analyses—were extremely labor-intensive, inconsistent across bureaus, and vulnerable to human error. Staff were required to review thousands of records each year, including over 8,000 project descriptions, more than 13,000 pre-award validation actions, and more than 8,000 detailed budget submissions. Each task required extensive reading, cross-checking across multiple systems, and detailed documentation. These demands strained a shrinking grants workforce, delayed internal control reviews, increased the risk of compliance failures under 2 CFR 200, and diverted staff from higher-value oversight activities. The Department needed a standardized, accurate, and scalable way to conduct internal controls testing, ensure timely eligibility checks, and complete budget reviews without overwhelming staff resources or jeopardizing compliance.
Detailed example
The combined AI tools automatically generate standardized compliance outputs across project descriptions, budget reviews, and entity validations, replacing thousands of hours of manual analysis. They produce automated scoring, flags for risks or inconsistencies, cross-walks between budget documents, and complete audit-ready records aligned with internal control requirements. Together, these outputs streamline oversight, strengthen regulatory compliance, and create a consistent, defensible documentation trail for more than 29,000 annual financial assistance actions.
AI / analytics pattern
Agentic AI: AI systems that perform tasks or make decisions autonomously with minimal human intervention.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
Automated analysis increased objectivity, removed inconsistencies in how staff interpreted regulatory requirements, and provided faster, more reliable information to support program decisions.
Controls / human review
ATO: Yes; PIA: Not published
Data needed
Various public sources