Budget, Territory, and Public Decision-Making: An AI Tool to Improve Equity in Decentralized Forest Management

Abstract

This article addresses a recurring challenge in public budget management in Peru: the concentration of spending at central levels, in contrast to the operational demands of decentralized units responsible for executing key functions in the territory. This phenomenon, observed across various public institutions, reveals tensions between financial planning and the decentralized mandates of many state entities. As a representative case, the forest sector is examined, where these gaps become particularly evident.

Based on open data analysis and supported by language models powered by artificial intelligence, a technical proposal is presented to simulate budget redistribution scenarios, assess financial efficiency alternatives, and generate recommendations aimed at achieving a more equitable and strategic allocation of resources. The proposed tool enables the visualization of impacts, the construction of performance indicators, and the support of human expert judgment in decision-making processes. The approach is replicable in other public entities with similar structures and challenges, promoting the responsible use of artificial intelligence to strengthen decentralized public management.