Automated Legal Document Drafting in the Indian Judicial System: A Survey of AI-driven Approaches

The Indian judicial system faces many challenges which slow down legal document preparation because of the complex procedures that is present in judicial system, numerous cases and language differences. The process of manual transcription of different languages, extraction of entities and court standard compliance formatting needs help of lawyers to spend a lot of time which results in late and incorrect work. The research states that we have done evaluation of 20 academic papers from 2017 to 2025 which aims to investigate Automatic Speech Recognition (ASR), Natural Language Processing (NLP) and transfer learning models for legal systems. The research shows that Whisper ASR models achieve a high level performance with help of 55.2% error reduction from previous models but these improvements focus on Western regions that use languages with a lot of resources. Our current state-of-the-art models show very low applicability for Indian legal systems because they were developed for Western jurisdictions with high-resource languages. The current systems does not have essential features because they do not handle issues like overlapping speech and they do not integrate multiple techniques like multilingual transcription, speaker diarization, legal entity extraction and jurisdiction- aware template generation. The Indian judicial system requires solutions to these problems because they create problems for the public access to justice and prevent judicial advancements.