IMPROVING THE EFFICIENCY OF FINANCIAL RESOURCE ALLOCATION FOR FUNDING CIVIL SOCIETY INSTITUTIONS THROUGH ARTIFICIAL INTELLIGENCE TECHNOLOGIES

This article examines how artificial intelligence can improve the efficiency of financial resource allocation to civil society institutions. Using official data from Uzbekistan's 2026 state grant competitions, the study assesses funding coverage, reviewer workload, and allocation risks. A human-in-the-loop model encompassing needs mapping, application screening, scoring support, monitoring, and outcome-based learning is proposed. Three practical recommendations focus on data management, governance, and phased implementation.