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Augmented territorial development (ATD): Toward a place-based AI?

Tariq Laajini

Local Economy2026https://doi.org/10.1177/02690942261433813article
AJG 2ABDC C
Weight
0.50

What the paper says

Can artificial intelligence (AI), a global technology produced by transnational corporations, be transformed into a specific territorial resource in Pecqueur’s (2005) sense? This article proposes the concept of augmented territorial development (ATD) to address this question. Using Jabareen’s (2009) conceptual analysis protocol, we construct this concept as a process through which AI amplifies the endogenous capacities of territories—cognitive, relational, and institutional—without dissolving their specificities or creating new forms of technological dependence. Distinguished from the often technocentric and top-down “Smart City” approach, ATD requires active appropriation that converts generic technology into situated territorial intelligence. The theoretical contribution lies in bridging proximity theories ( Torre and Rallet, 2005 ) with emerging literature on AI urbanism ( Cugurullo et al., 2023 ), and in identifying three dimensions of augmentation illustrated through Moroccan case studies (AgriEdge, Atlan Space, UM6P digital twin). The article concludes with the notion of territorial cognitive sovereignty as an essential condition for AI to become a lever of specific development rather than a vector of dependence.

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https://doi.org/https://doi.org/10.1177/02690942261433813

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@article{tariq2026,
  title        = {{Augmented territorial development (ATD): Toward a place-based AI?}},
  author       = {Tariq Laajini},
  journal      = {Local Economy},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/02690942261433813},
}

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Augmented territorial development (ATD): Toward a place-based AI?

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.