The Tenth Annual Workshop on Applications of Artificial Intelligence in the Legal Industry

The legal industry faces significant challenges due to the exponential growth of data, resulting in increasingly complex legal cases that require accurate and efficient processing of vast amounts of information. Legal professionals have turned to AI technology to streamline workflows and improve work quality. However, the sheer volume of data involved in modern legal matters can be overwhelming, with over 350,000 docketed cases filed annually in U.S. courts and typical antitrust or regulatory investigations involving terabytes of data. This data must be processed and analyzed to extract insights, support sound judgment, and develop effective legal strategies. To address these challenges, the legal industry has increasingly embraced AI technologies such as natural language processing and machine learning to efficiently process and analyze large-scale legal data, deliver legal services at reduced costs, and improve turnaround time. Advancements in AI—including machine learning, natural language processing, speech and image processing, and big data analytics—are transforming the legal industry. Applications range from automated contract drafting and predictive coding to judicial analytics, litigation outcome prediction, and intelligent case management. Recent breakthroughs in Generative AI (GenAI), Large Language Models (LLMs), and Agentic AI systems represent a new paradigm in legal technology. Agentic AI extends traditional AI and GenAI capabilities by enabling autonomous, goal-driven agents that can plan, reason, coordinate actions across multiple tools, and iteratively execute complex legal tasks with limited human intervention. In the legal domain, Agentic AI shows promise in orchestrating end‑to‑end legal workflows such as multi‑stage eDiscovery, internal investigations, regulatory compliance monitoring, contract lifecycle management, and litigation preparation. As AI systems become more autonomous and deeply embedded in legal decision‑making processes, concerns regarding transparency, accountability, explainability, data privacy, and ethical use are increasingly prominent. These concerns have triggered regulatory scrutiny aimed at mitigating unintended social and legal consequences while preserving the economic and competitive advantages of AI‑driven innovation. With the growing prevalence of AI, Generative AI, and Agentic AI in legal big data applications, a disconnect remains between legal practitioners and academic researchers developing these technologies. This workshop seeks to bridge that gap by fostering collaboration between industry and academia, promoting responsible and effective use of advanced AI systems in legal big data analytics, and encouraging open, thoughtful dialogue on technical, ethical, and regulatory considerations. Building on the success of prior workshops, our goal is to stimulate further research and practical exploration of AI, GenAI, and Agentic AI applied to legal data—particularly novel, real‑world use cases that demonstrate measurable impact. This workshop provides a platform for legal professionals, academics, and AI practitioners to share insights, examine emerging technologies, and advance the future of AI‑enabled legal services.

Research topics:

• • Natural language processing and understanding in the legal industry.
  • Intelligent legal information retrieval.
  • Legal text summarization, extraction, and classification.
  • Knowledge graphs and automatic reasoning in the legal domain.
  • Speech and image recognition applications in the legal industry.
  • Machine translation of legal text.
  • Intelligent advisory and automatic question answering in the legal industry.
  • Explainable AI for the legal and compliance industries.
  • Deep learning applications in the legal industry.
  • Privacy issues related to AI applications.
  • Applications of AI to electronic discovery.
  • Applications of AI to contract automation and management.
  • Applications of AI to litigation support and outcome prediction.
  • Ethical and regulatory considerations in the use of AI in the legal industry.
  • Generative AI capturing and organizing privileged information.
  • Generative AI summarizing and classifying legal text.
  • Applications of AI in construction dispute litigation and delay identification.
  • Agentic AI systems for autonomous legal workflow orchestration
  • Integration of Agentic AI with knowledge graphs, tools, and enterprise legal platforms

Important dates

• • Oct 1, 2026: Due date for workshop papers submission
  • Nov 4, 2026: Notification of paper acceptance to authors
  • Nov 25, 2026: Camera-ready of accepted papers
  • Dec 14-17, 2026: Workshops (Phoenix, AZ, USA)

Paper submission instructions:

Full papers — up to 10 pages — should be submitted via the conference workshop online submission system. We also encourage submission of shorter papers (up to six pages) reporting works in progress. The submission deadline is Oct 1, 2026. All papers accepted will be included in the conference proceedings and published on IEEE Xplore Digital Library.

Organization Committee:

• Peter Gronvall – Ankura
• Nathaniel Huber-Fliflet (Co-chair) – Ankura
• Robert Keeling – Redgrave LLP
• Christian Mahoney – Cleary Gottlieb Steen & Hamilton LLP
• Jianping Zhang (Co-chair) – Ankura

Program Committee:

• Arthur Carvalho – Assistant Professor, Miami University
• Ali Hadjarian – Principal, PwC
• Jiepu Jiang – Assistant Professor, Virginia Tech
• Hongfei Lin – Professor, Dalian University of Technology
• Huan Liu – Professor, Arizona State University
• Yue Pan – Senior Partner, Dezhi LLP
• Han Qin – Senior Director, Ankura