GreatNorthCollective/greatnorth-us-federal-ai-inventory huggingface dataset:
US federal AI use case: Policy Knowledge Base
Agency: Department of Veterans Affairs - OEHRM: Office of Electronic Health Record Modernization
Problem addressed: VA cybersecurity staff are challenged of managing and staying updated with an extensive array of documentation related to policies, processes, directives, and frameworks, which are essential for maintaining compliance and ensuring the security and privacy of VA information systems.  VA RMF program continues to rely on human decision-making for risk-based decisions. This human-centric approach requires extensive involvement from various roles and generation/consumption of large amounts of artifacts and staffing resources.
Purpose and benefits: The AI model can help analysts quickly locate and reference the relevant VA policies to validate compliance and identify non-compliance.
Topic area: Cybersecurity
Development stage: Pre-deployment
US federal AI use case: Cyber Authorization Memo Generation
Agency: Department of Veterans Affairs - OEHRM: Office of Electronic Health Record Modernization
Problem addressed: VA cybersecurity staff are challenged with managing and staying updated with an extensive array of documentation related to policies, processes, directives, and frameworks (which are essential for maintaining compliance and ensuring the security and privacy of VA information systems).  The VA Risk Management Framework (RMF) program continues to rely on human decision-making for risk-based decisions. This human-centric approach requires extensive involvement from various roles and generation/consumption of large amounts of artifacts and staffing resources.
Purpose and benefits: This tool will significantly reduce the time required for memo generation, saving hours of work for each memo signed.  By implementing AI in these use cases, EHRM aims to streamline processes, improve efficiency, and reduce the workload on both cyber personnel and administrative staff.
Topic area: Cybersecurity
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Smart Ratings Recommendation
Agency: Department of Veterans Affairs - VBA: Veterans Benefits Administration
Problem addressed: Due to the rating decision's dependence on the preceding steps of the rating process, there is often a backlog of claims and significant rework required to complete a rating on a claim. A need exists for a specialized, automated solution to complete several pieces of the Rating process to expedite the delivery of benefits and awards to Veterans, and to reduce errors and delays resulting from remediation.
Purpose and benefits: Smart Rating Recommendation empowers VSRs in the Ratings workflow to leverage AI-generated ratings of select claim and contention types in order to lower processing times for a Rating Decision to be made. This is done by allowing RVSRs to leverage AI analysis of selected claims and contentions, and provide a proposed Rating to the user to confirm or review manually themselves.
Topic area: Benefits Processing
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Clinical AI Agent
Agency: Department of Veterans Affairs - OEHRM: Office of Electronic Health Record Modernization
Problem addressed: Administrative tasks, manual documentation, and complex workflows within the Electronic Health Record (EHR) cause lower clinical efficiency and operational effectiveness.
Purpose and benefits: By implementing Clinical Al Agent (CAA), VA providers will leverage new technology to decrease time completing documentation and administrative tasks during a Veteran visit. This leads to increased end user satisfaction, reduced provider burnout, and ensures providers are spending time prioritizing Veteran care.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: PII in Foreign Medical Program (FMP) Faxes
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Improve processing speed in identifying and processing multiple language claim forms and improve the speed and accuracy of such claims.
Purpose and benefits: Improves processing speed to ensure the Veteran receives a completed claim in a more timely manner. AI is more cost effective than Optical Character Recognition (OCR).
Topic area: Benefits Processing
Development stage: Deployed
US federal AI use case: Auto Doc ID
Agency: Department of Veterans Affairs - VBA: Veterans Benefits Administration
Problem addressed: The purpose of the tool is to convert inbound images into a standard format that is required for downstream processing for auto document classification and OCR/Data Extraction.  After all document processing is completed and we are preparing the final output the images are converted back into a searchable PDF. Auto Doc ID provides suggestions to operators to decrease turn around time and increase quality.
Purpose and benefits: - Time savings and higher quality
- Improved OCR/Data Extraction Accuracy - clearer, properly aligned images increase recognition success for auto classification of Document ID.
- Standardization for Automation - converting all documents into TIF IV ensures reliable document classification and processing.
- Reduced Manual Corrections - automated alignment, noise removal, and skew correction minimize human intervention.
- Preservation of Original Document Integrity - annotations are applied without altering original text, supporting compliance and readability.
•	Overall, the impacts are limited to operational efficiency and data accuracy. Correct extraction reduces manual data entry for document classification. The AI has no role in determining eligibility, adjudicating claims, or making benefit decisions"
Topic area: Admin Functions
Development stage: Deployed
US federal AI use case: EEV/OHI Document Types
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Increase the speed and accuracy of identifying document types and routing thereof.
Purpose and benefits: Enhance Veteran and Veteran Family Member experience with claims processing to ensure timely and accurate claims resolutions.
Topic area: Benefits Processing
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Laboratory Procedure AI Search Assistant
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Artificial intelligence is set to reduce the time needed to find a procedure and, within that procedure, an answer to a posed question.
Purpose and benefits: The use of artificial intelligence for contextual searches of our procedures boosts efficiency. This increased efficiency indirectly enhances patient outcomes by reducing downtime and shortening the laboratory decision-making process.
Topic area: Health and Medical
Development stage: Pre-deployment
US federal AI use case: Electronic Mammogram Reporting (eMAMR)
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Clinical data extraction from diverse and unstructured sources remains a bottleneck for healthcare providers and agencies. For example, providers may need to re-enter the same patient information across different consults, which is inefficient and takes away valuable clinical time. Existing processes are manual, time-consuming, and prone to errors, which leads to delays in integrating critical patient information (such as PDFs and scanned records) into Electronic Health Record (EHR) systems like CPRS/VistA. This limits care coordination, slows decision-making, and increases administrative workload.

The proposed AI solution will automate the workflow for clinical data extraction and integration using OpenAI’s GPT-4o API for computer vision and generative tasks. Leveraging Databricks and AWS, the system processes PDFs and images—extracting clinical data, converting it to structured formats (JSON), and transforming it into standardized clinical notes (TIU/SMART notes) for seamless integration into CPRS.
Purpose and benefits: - Efficiency Gains: Automation dramatically reduces manual data entry and reconciliation, saving time for clinical staff.
- Improved Data Quality: AI-driven extraction increases accuracy, consistency, and completeness of patient records.
- Faster Care Coordination: Rapid data integration leads to quicker and more informed clinical decisions, supporting timely patient care.
- Higher Scalability and Support of VA Mission: For VA, these outcomes will directly advance its mission to provide faster, safer, and more connected healthcare to the Veterans.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: CCN Provider Directory
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: Reduce the need for manual review of a large (1.5M+ providers, 9M+ provider services) dataset of provider information to categorize or perform data governance functions.
Purpose and benefits: Maintaining a highly accurate and properly categorized dataset of VA and Community Providers actively providing healthcare to our Veterans ensures accurate and timely Veteran referrals, appointment scheduling, and facilitation of healthcare program service authorization. Additionally, applying AI to the consolidated Provider dataset allows critical federal review of provider activity and enables discovery of fraud, waste, and abuse for the program.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: AI-Enhanced Call Center
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
US federal AI use case: Employee Transactions for HR Decision-Making
Agency: Department of Veterans Affairs - HRA: Human Resources Administration
Problem addressed: AI is intended to automate repeatable tasks, improve efficiency, measure employee performance, support onboarding, improve customer experience, improve user adoption, and improve analytics and reporting to further support decision-making and personalize experiences.
Purpose and benefits: - Increase efficiency of Core Human Resources (HR) and Payroll
- Enhance employee and veteran outcomes e.g., improve customer experience and improve user adoption
Topic area: HR
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: CHAMPVA Automation
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: The AI solution is designed to eliminate the manual data entry burden associated with processing CHAMPVA applications. Each application previously required up to 61 administrative steps, contributing to a backlog of over 70,000 unprocessed applications and delays of up to 162 days. The AI automates data extraction from VA Form 10-10d PDFs and streamlines ingestion into the Claims Processing and Eligibility (CP&E) system, significantly reducing processing time and administrative workload.
Purpose and benefits: Increased Efficiency: Automating data extraction and processing reduces time spent on manual tasks.
Cost Savings: Reduces labor costs associated with manual data entry and backlog management.
Improved Service Delivery: Accelerates application processing, allowing Veterans and their families to receive benefits faster.
Enhanced Staff Productivity: Frees up staff to focus on eligibility determinations and higher-value tasks.
Supports VA’s Mission: Strengthens the VA’s commitment to serving Veterans and their families with timely and effective healthcare benefits.
Topic area: Admin Functions
Development stage: Deployed