AI reveals hidden connections within legal systems

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As governments worldwide explore how artificial intelligence can transform decision-making, a recent study from Sultan Qaboos University demonstrates how AI can uncover hidden connections within legal systems—offering a powerful tool to support smarter lawmaking. Published in The Journal of Engineering Research, the study applies natural language processing (NLP) and network analysis to Oman's Labor Law of 2023, revealing a complex web of interdependencies between its articles that may not be apparent through conventional legal review.

The research shows that certain provisions function as highly influential "hubs" within the law—articles that are extensively referenced and closely connected to others. One example is Article 147, identified as a central node whose amendment could trigger cascading effects across multiple parts of the legal framework.

"Legal systems are not isolated provisions but interconnected networks," the researchers explain. "Understanding these connections is essential for anticipating the broader impact of any legislative change."

To build this insight, the research team developed a four-stage methodology combining Arabic-language NLP tools with industrial engineering techniques. Legal texts were collected from official Omani sources, then processed using customized linguistic models designed to handle the structure of Arabic legal language. Relationships between articles were mapped through shared terminology and cross-referencing patterns, with results visualized using network graphs, clustering diagrams, and heat maps.

The outputs were further validated through expert review involving legal specialists from Oman's State Council, Legislative Chamber, and Shura Council, ensuring both technical accuracy and institutional relevance.

The resulting visualizations make the internal architecture of the law more transparent, allowing policymakers to identify which provisions carry the greatest structural weight—and where unintended consequences may arise if changes are introduced.

Beyond the Labor Law itself, the study highlights how legal reforms are embedded within a broader regulatory ecosystem. The analysis shows strong connections between labor provisions and other domains, including commercial law, social protection systems, occupational health standards, and immigration policies—particularly relevant in contexts with diverse workforce structures.

The researchers emphasize that this AI-driven approach aligns with Oman's Vision 2040, which prioritizes the modernization of governance and legal frameworks. By enabling evidence-based, system-wide analysis, the methodology could help reduce legislative risk and improve policy coherence.

Importantly, the approach is not limited to Oman. The study proposes a scalable model that can be adapted to other legal systems, including those in the GCC and beyond, offering new opportunities for integrating artificial intelligence into legislative design and reform processes.

More information

Mahmood Al Kindi, Utilising AI and Industrial Engineering Tools in Legal Systems: A Case Study on Oman's Labour Law, The Journal of Engineering Research (2025). DOI: 10.53540/1726-6742.1312

Provided by Sultan Qaboos University