As the volume of data and the number of transactions in public procurement continue to grow, artificial intelligence technologies can become not only a tool for automating oversight, but also an instrument for early risk detection.

In international practice, Machine Learning, LLM, and RPA technologies are being used to analyze tender data, identify suspicious pricing, competitive anomalies, and potential collusion.

For example, Brazil’s “Alice” system analyzed nearly 191,000 procurement procedures in 2023, providing grounds for the initiation of 203 audits*. At the same time, the average time required to initiate an audit* was reduced from 400 days to 8 days.*

The key takeaway for Uzbekistan is that AI should not replace human decision-making, but rather multiply the analytical capabilities of oversight authorities.

Therefore, introducing an AI-based risk analytics module into the public procurement platform would enable the early detection of suspicious procurements, help protect the competitive environment, and direct oversight resources towards cases with the highest levels of risk.