DOI: 10.1108/jedt-05-2026-0336 ISSN: 1726-0531

Strategic BIM adoption in Kuwait: a policy-led roadmap for digital transformation in the AEC industry

Mohammad Sadeq Abdullah, Mohamed Salem, Abdullahi Saka

Purpose

This study investigates strategic drivers and barriers to building information modeling (BIM) adoption within the Kuwaiti architecture, engineering and construction industry. It aims to develop a policy-led roadmap to bridge the digital divide in emerging Gulf Cooperation Council economies.

Design/methodology/approach

This research uses a qualitative multi-method design, interpreted through combined technology-organization-environment and institutional theory lenses. First, a systematic literature review of 35 records (34 peer-reviewed articles and 1 policy report) mapped global trends. Second, these findings were triangulated with ten semistructured interviews with BIM experts and stakeholders. Data were analyzed using hybrid codebook thematic analysis.

Findings

Results indicate that government funding and regulatory mandates are primary adoption catalysts. Conversely, fragmented policies, high implementation costs and organizational resistance act as significant barriers. The study highlights that BIM integration, facilitated by AI analytics and digital twins, critically enhances prefabrication efficiency and sustainability.

Practical implications

This study proposes a phased national strategy involving unified standards, robust institutional oversight and sustained financial incentives. The findings provide a transferable framework for policymakers to align construction practices with Kuwait Vision 2035 and regional digital transformation goals.

Originality/value

By synthesizing global literature with regional expert insights, this research provides a Kuwait-specific, evidence-grounded policy synthesis for BIM institutionalization. Its value lies in filling a critical knowledge gap in an under-studied Middle Eastern context and offering a methodologically transparent mapping of policy pillars to empirical data.

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