Heritage in the Shattered Mirror of Data: Analyzing the Discourse of Artificial Intelligence and Spatial Governance Gaps in Iran

Document Type : Original Research Paper

Author

Department of Geography and Urban Planning, Faculty of Humanities, Tarbiat Modares University, Tehran, Iran; and Expert at the Deputy of Cultural Heritage, General Directorate of Cultural Heritage, Tourism, and Handicrafts of Alborz Province

10.22035/isih.2026.5772.5318
Abstract
ABSTRACT

Global discourse increasingly positions Geospatial Artificial Intelligence (GeoAI) as an inevitable horizon for the smart conservation of cultural heritage. Yet this technology-centered discourse presupposes the existence of governed data infrastructures and faces substantial challenges when translated into contexts such as Iran. Drawing on an interdisciplinary and critical framework that brings together critical geography and spatial studies, public administration and public policy, and critical Science and Technology Studies (STS), this article argues that the central challenge in the management of cultural heritage in Iran lies not in the absence of sophisticated technologies, but in the lack of governed data infrastructures as the fundamental precondition for digital transformation. This study adopts a qualitative approach and employs methodological triangulation through critical discourse analysis of policy documents, particularly the National Artificial Intelligence Strategy; analysis of institutional performance data; and field observations conducted within the governmental body responsible for cultural heritage management. The findings show that the structural absence of integrated and standardized databases has reduced the discourse of heritage smartification to a “Smartification Illusion,” producing a condition conceptualized here as the “Pre-Data Stage”. In response to this structural misalignment, the article proposes a phased framework of heritage data governance in which the establishment of governance arrangements, standards, and institutional capacities is treated as a prerequisite for investment in advanced analytical tools. It concludes by emphasizing the need to redirect attention and resources away from performative technological initiatives and toward the foundational task of building robust data governance structures.

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Articles in Press, Accepted Manuscript
Available Online from 31 July 2026

  • Receive Date 08 February 2026
  • Revise Date 29 July 2026
  • Accept Date 31 July 2026