Abstract:
Moldova's 31.6% poverty headcount (2023) and GDP per capita of USD 7,618 (2024) underscore urgent needs for smarter social assistance. This paper presents a conceptual simulation framework for integrating AI - machine learning, predictive analytics, and NLP - into Moldova's welfare system. Four scenarios project 12–22% reductions in exclusion errors and up to 25% cost savings, with policy implications for policymakers and development partners
Description:
CIOBANU, Mihail. AI and Poverty Reduction in Moldova: A Conceptual Simulation Framework for Social Assistance. In: Beynəlxalq dəyirmi masanin materiallari, 10 fevral 2026-cı il. Bakı: “Apostrof-A”, 2026, pp. 518-524. ISBN 978-9952-607-75-8.
