Generative AI systems offer unprecedented capabilities for addressing access to justice challenges through their ability to understand and generate human-like text. This chapter examines how large language models (“LLMs”) can bridge the language gap between laypeople’s factual descriptions and legal concepts, providing personalized legal information and assistance with legal tasks.

The analysis explores several applications, including the automated provision of legal information using retrieval-augmented generation (“RAG”), streamlined legal intake processes, intelligent form completion assistance, and AI-enhanced mediation. These systems show promise for identifying legal issues from plain language descriptions, assisting with the drafting of legal documents, and supporting dispute resolution processes.

However, significant challenges remain, particularly regarding hallucinations where models generate convincing but incorrect information, algorithmic bias that may perpetuate existing inequalities, and transparency concerns inherent in black-box AI systems. While generative AI holds promise for democratizing legal assistance, implementation with robust safeguards, continuous evaluation, and human oversight is essential to ensure these tools enhance rather than undermine access to justice.