| Titre : | Governing artificial intelligence for sustainable territorial development in fragile contexts: insights from North Lebanon (2026) |
| Auteurs : | C. Khneyzer ; Z. Boustany ; J. Dagher |
| Type de document : | Article |
| Dans : | Administrative Sciences (vol. 16, n. 3, March 2026) |
| Article en page(s) : | p. 130 |
| Langues : | Anglais |
| Langues du résumé : | Anglais |
| Catégories : |
Catégories principales 05 - DEVELOPPEMENT RURAL ; 5.1 - DéveloppementThésaurus IAMM DEVELOPPEMENT TERRITORIAL ; DURABILITE ; INTELLIGENCE ARTIFICIELLE ; LIBAN |
| Résumé : | Sustainable territorial development seeks to balance economic growth, social well-being, and environmental preservation across spatial contexts. In fragile and resource-constrained regions, achieving this balance remains particularly challenging. With the growing diffusion of artificial intelligence (AI), digital tools are increasingly presented as potential enablers of sustainability-driven territorial strategies. This study explores the role of AI in supporting sustainable territorial development across rural and urban areas of North Lebanon, a region characterized by infrastructural deficits, governance constraints, and socio-economic vulnerability. Adopting a qualitative research design, the study draws on semi-structured interviews with five key stakeholders from the public sector, civil society, business, and sustainability expertise, complemented by an illustrative case study of the proposed AI-enabled redevelopment of Klayaat (René Mouawad) Airport. The findings reveal that while stakeholders recognize AI's potential to enhance resource optimization, smart agriculture, urban mobility, and disaster preparedness, its effective adoption remains constrained by limited digital infrastructure, insufficient policy frameworks, funding shortages, and gaps in digital literacy. Interpreted through the lenses of the Triple Bottom Line and Diffusion of Innovation theories, the results show that AI-driven sustainability outcomes in fragile territorial contexts are highly conditional on institutional readiness, governance capacity, and contextual alignment. The study contributes to the literature by providing context-specific insights into AI-enabled sustainable development in a developing and crisis-affected region, highlighting the need to complement technological innovation with policy reform, capacity building, and inclusive territorial governance. |
| Cote : | En ligne |
| URL / DOI : | https://doi.org/10.3390/admsci16030130 |
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