The Insolvency and Bankruptcy Code, 2016 (IBC) was introduced to promote time-bound and efficient resolution of corporate insolvency in India, with the Corporate Insolvency Resolution Process (CIRP) expected to be completed within 330 days. However, the ground realities indicate a significant gap between statutory timelines and actual performance. The Procedural delays in the admission of insolvency applications, verification of claims, approval of resolution plans, and overburdened benches of the National Company Law Tribunal (NCLT) has remained as a persistent challenge. These inefficiencies often result in erosion of asset value, stakeholder dissatisfaction, and increasing liquidation rates. In this context, the integration of Artificial Intelligence (AI) into the workflows of regulatory and adjudicatory bodies such as the NCLT and the Insolvency and Bankruptcy Board of India (IBBI) offers transformative potential. The study aims to analyse current procedural delays, identifies pain points, and evaluates the feasibility of AI-based tools for document analysis, case triaging, timeline monitoring, and resolution plan vetting. Drawing from global best practices and inputs from insolvency professionals, judges, and policymakers, the paper aims to propose a regulatory technical roadmap for AI adoption in the insolvency ecosystem of India.
Dr. Rohit Tiwari (Sun,) studied this question.