PERSPECTIVE article
Front. Sustain.
Sec. Modeling and Optimization for Decision Support
Reconceptualizing Poverty in the Digital Era: AI-Enabled Mapping and the SDG 1 Agenda
Provisionally accepted
- Marian College Kuttikkanam Autonomous, Kuttikkanam, India
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In this paper, a conceptual framework of AI-enabled digital poverty mapping is formulated to promote Sustainable Development Goal 1 (SDG 1), which aims at eliminating poverty. The framework combines various data sources: satellite imagery, telecom data, household surveys, and administrative data with the latest AI tools representation learning, multimodal machine learning, geospatial analysis, and large language models to generate fine-resolution and multidimensional poverty maps and predictive indices. Comprising a recent policy change, such as UNDP programs and UN Pact of the Future, and case studies of India and Kenya, the framework targets both economic and digital deprivation. It also provides ways of inclusive monitoring of poverty and focusing on ethical protection. The next step to be made in the future is pilot-testing, comparative research, and incorporation of this method with the UN system of monitoring poverty to track it globally and allow fair development.
Keywords: AI-enabled Poverty Mapping, Devolpment, Digital exclusion, SDG 1 (No Poverty), sustainability
Received: 19 Oct 2025; Accepted: 29 Jan 2026.
Copyright: © 2026 Monica George and R. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Alain Monica George
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