<![CDATA[This study aims to find out and analyze the potential use of AI at the pre-drafting stage of law, as well as formulate an initial model of AI integration as an initial testing mechanism for proposed regulations before being included in the National Legislation Program (Prolegnas) and Regional Legislation Program (Prolegda). The study offers novelty through the concept of AI-Legislation, an artificial intelligence-based system designed to automatically and predictively test the feasibility of legal substance before entering the regulatory drafting stage. This research uses a juridical-normative approach that is developed in a reflective-critical manner. Primary data is obtained through laws and regulations, judicial decisions, as well as Prolegnas and Prolegda documents. Meanwhile, secondary data is in the form of scientific articles (journals), books, and other literature materials. The data analysis techniques used are descriptive-critical with a framework analysis approach to build a conceptual framework of AI-Legislation in three layers, namely automatic analysis, policy prediction, and institutional integration. The research findings show that AI can help in mapping regulatory needs, detecting legal conflicts, and harmonizing norms with greater precision. AI-Legislation fundamentally shows a paradigm shift from the classical legislative model to smart-modern legislation. AI implementation faces challenges in terms of digital infrastructure readiness, technological literacy among government officials, and legal validity of AI recommendations. Therefore, the study recommends the integration of the AI testing phase as an initial requirement in the legislative planning process, as well as the need to establish national governance and regulations governing the use of AI in the legislative regulatory development cycle.]]>
