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Saudi Arabia’s traditional industrial cities, comprising Riyadh Industrial City, Jeddah Industrial City, Dammam Industrial Cities, and Jubail Industrial City, are recognized as the cornerstone of national manufacturing, logistics, petrochemicals, and industrial services.
With the acceleration of digital transformation by the Vision 2030 agenda(Saudi Vision 2030. n.d), these cities are under escalating pressure to modernize legacy systems and adopt Industry 4.0 technologies (Kagermann et al., 2013; Lu, 2017) is being experienced by these cities.
Enterprise Architecture (EA) across these environments remains fragmented, outdated, and dominated by manual documents that hinder architectural visibility and impede modernization (Lankhorst, 2017).
In this Action Research study, investigation was conducted into how artificial intelligence (AI) can be deployed to improve EA practices, diminish technical debt (Ozkaya, 2021), and improve decision support in many industrial cities.
By using iterative Plan → Act → Observe → Reflect cycles (Reason & Bradbury, 2018), this study implemented AI for architectural discovery, dependency analysis, predictive technical debt modeling, and dynamic visualization dashboards across 11 industrial cities. The interventions achieved a 70-plus percent decrease in architectural mapping time, raised the accuracy of documentation from 60 to 92 percent, and a marked increase in cross functional collaboration (Accenture, 2023; McKinsey & Company, 2023).
Organizations showed increased preparedness for modernization initiatives, better alignment with demands of Industry 4.0, and better governance maturity.
AI-driven EA has been identified as a strategic enabler to support industrial modernization: more than just a technical upgrade: an analysis of this approach concluded that the EA.
A replicable template for industrial clusters was offered through this approach aiming to strengthen architectural governance, spur digital transformation, and cultivate long-term operational resilience (Ross et al., 2006; Kruchten et al., 2012).
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