In our previous blog[1] published on September 3, we discussed Georgia’s efforts to develop Artificial Intelligence (AI) prototypes for managing the risk of erroneous treasury payments. Since then, Georgia has made notable progress in implementing the solution. On March 15, 2025, the Treasury went live with its AI model[2] designed to flag high-risk payment transactions (the “red channel”).[3] Over the first three months of deployment (March–May), the model reviewed over 800,000 payment transactions, and its performance, when benchmarked against decisions made by Treasury staff in finding a risky invoice, showed promising results:
With over 95 percent of decisions in finding erroneous payment orders aligning with those of experienced Treasury officers, the model demonstrates its potential to meaningfully support expert review. Continued training of the model will help close these existing gaps. Today, the model operates in real time and is under continuous monitoring. Based on performance, it is periodically retrained and updated with new data.
Challenges Encountered:
The journey from prototype to production was, however, not without obstacles. Several practical and institutional challenges had to be addressed along the way:
These challenges were addressed through close collaboration, careful testing, and commitment to iterative improvement, and have provided invaluable lessons for building a resilient and adaptive AI-supported Treasury system.
Lessons Learned
The following main lessons can be distilled from Georgia’s experience:
Next Steps
Encouraged by the results of AI and its impact on the PFM process efficiency, the Treasury is also planning to expand the use of AI in the processing of “Green Channel” payments and use latest AI technologies like Generative AI[4] to further improve the accuracy of the existing models by analyzing electronic documents. Beyond transaction processing, the Treasury aims to deploy AI solutions in other core activities, including cash management, accounting/financial reporting and enhancing consultancy services for public sector entities served by the Treasury. These efforts will further integrate AI into the broader Treasury ecosystem, improving service delivery and operational efficiency across multiple functions.
[1] AI-Powered Treasury: Georgia’s Innovative Approach to Managing Payment Risks (by Davit Gamkrelidze, Giorgi Mchedlishvili, Graham Prentice, Alok Verma, September 3, 2024). Available at: https://blog-pfm.imf.org/en/pfmblog/2024/09/ai-powered-treasury
[2]An AI model is a computer program trained to learn from data and make decisions or predictions based on patterns it finds.
[3]Red channel transactions are reviewed centrally by Treasury staff before payment instructions are sent to banks, while green channel transactions are sent directly to banks without Treasury review
[4]Generative AI is a type of artificial intelligence that can create new content—such as text, images, music, or code—by learning patterns from existing data and generating original outputs that resemble human-made work