Beyond the hype: A sociotechnical perspective on AI's potentials and constraints in bridging the gap to basic-needs sustainability in higher education institutions

Artificial intelligence (AI) is increasingly deployed in higher education institutions (HEIs), yet its role in addressing basic human needs remain poorly understood. This study examines how AI enables and constrains progress toward Sustainable Development Goals 1 (No Poverty), 2 (Zero Hunger), and 3 (Good Health and Well-Being) by analysing 27 international case studies based on secondary institutional data sources through a sociotechnical lens. The findings show that AI contributes to basic-needs sustainability through three mechanisms (data visibility, institutional mediation, and capability amplification) that translate technological capabilities into social outcomes. A central insight is the role of redistributive governance, whereby HEIs deliberately redirect AI-generated operational efficiencies toward student support initiatives such as scholarships, food programs, and well-being services. These dynamics generate cross-SDG spillovers and give rise to three institutional roles for HEIs: (i) microcosms of sustainability systems, (ii) redistributive infrastructures, and (iii) capability-building ecosystems. The study contributes to the literature on AI and sustainable development by demonstrating that AI-driven sustainability outcomes emerge from sociotechnical interactions between digital technologies and institutional governance structures. The findings provide guidance for policymakers and university leaders seeking to align AI adoption with equity-oriented development strategies. • HEIs act as microcosms where AI solutions model broader sustainability transitions • Redistributive governance converts AI efficiencies into basic-needs support • Cross-SDG spillovers show AI generates cascading benefits across HEI ecosystems • AI drives SDG gains only when integrated into coordinated institutional systems • AI strengthens key competencies for food, health, and poverty-related capabilities

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Publication Details

Journal
Technological Forecasting and Social Change
Published
2026-04-13
DOI
https://doi.org/10.1016/j.techfore.2026.124681
Primary Topic
Sustainability in Higher Education
Type
article
Field-Weighted Citation Impact
0.00

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article

Beyond the hype: A sociotechnical perspective on AI's potentials and constraints in bridging the gap to basic-needs sustainability in higher education institutions

Izabela Simon Rampasso, Rosley Anholon, Antonis Skouloudis, Tiago F. A. C. Sigahi et al.
Technological Forecasting and Social Change
Sustainability in Higher Education
article

Beyond the hype: A sociotechnical perspective on AI's potentials and constraints in bridging the gap to basic-needs sustainability in higher education institutions

Izabela Simon Rampasso, Rosley Anholon, Antonis Skouloudis, Tiago F. A. C. Sigahi, Walter Leal Filho
article en

Abstract

Artificial intelligence (AI) is increasingly deployed in higher education institutions (HEIs), yet its role in addressing basic human needs remain poorly understood. This study examines how AI enables and constrains progress toward Sustainable Development Goals 1 (No Poverty), 2 (Zero Hunger), and 3 (Good Health and Well-Being) by analysing 27 international case studies based on secondary institutional data sources through a sociotechnical lens. The findings show that AI contributes to basic-needs sustainability through three mechanisms (data visibility, institutional mediation, and capability amplification) that translate technological capabilities into social outcomes. A central insight is the role of redistributive governance, whereby HEIs deliberately redirect AI-generated operational efficiencies toward student support initiatives such as scholarships, food programs, and well-being services. These dynamics generate cross-SDG spillovers and give rise to three institutional roles for HEIs: (i) microcosms of sustainability systems, (ii) redistributive infrastructures, and (iii) capability-building ecosystems. The study contributes to the literature on AI and sustainable development by demonstrating that AI-driven sustainability outcomes emerge from sociotechnical interactions between digital technologies and institutional governance structures. The findings provide guidance for policymakers and university leaders seeking to align AI adoption with equity-oriented development strategies. • HEIs act as microcosms where AI solutions model broader sustainability transitions • Redistributive governance converts AI efficiencies into basic-needs support • Cross-SDG spillovers show AI generates cascading benefits across HEI ecosystems • AI drives SDG gains only when integrated into coordinated institutional systems • AI strengthens key competencies for food, health, and poverty-related capabilities

Technological Forecasting and Social ChangeVol. 228
Manchester Metropolitan University (GB), Universität Hamburg (DE), Universidade de São Paulo (BR), Universidade Estadual de Campinas (UNICAMP) (BR), Instituto Butantan (BR), WSB Merito University in Wroclaw (PL), HAW Hamburg (DE), Universidade Federal de São Paulo (BR), University of the Aegean (GR)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Openalex Percentile: Top 17%
Sustainability in Higher Education
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