AI improves structured and coherent legal systems for better regulation
Regulatory analysis is increasingly supported by AI to map interdependencies within legal frameworks, improving consistency and clarity in legal systems.
A study from Sultan Qaboos University shows how AI can be used to map hidden structural relationships within legal systems, offering new ways to understand how laws interact and evolve.
Published in The Journal of Engineering Research, the research applies natural language processing and network analysis to Oman’s 2023 Labour Law.
The analysis reveals that legal provisions operate as an interconnected system rather than isolated rules. Certain articles emerge as highly influential ‘hubs’, with Article 147 identified as a central node whose modification could generate cascading effects across multiple parts of the legislation.
These interdependencies are visualised through network mapping techniques that highlight structural relationships not easily detected through traditional review.
To construct this model, researchers developed a four-stage methodology combining Arabic-language NLP tools with industrial engineering approaches. Legal texts were mapped using terminology and cross-referencing patterns, with outputs validated by Omani legislative experts to ensure accuracy and relevance.
The study highlights links between labour law and broader regulatory domains, including commercial regulation, social protection, occupational health, and immigration policy.
The findings underline AI’s potential in the regulatory sector to improve coherence, reveal interdependencies, and support scalable, more consistent legal frameworks across jurisdictions.
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