AI Reshaping Legal Services
In the private legal sector, AI is emerging as a strategic tool for law firms. For Shanghai Xinghan Law Firm, for instance, AI is not for replacing lawyers but rather assisting in rethinking the business model of legal services. The core logic behind AI empowerment for lawyers is centred on improving efficiency, deepening expertise, and innovating services. From the efficiency perspective, AI changes traditional workflows by quickly identifying key information from vast datasets and using generative tools to drastically cut legal research time. It also precisely generates legal documents, reducing human error, and improving contract review through intelligent risk detection, shortening review cycles. In terms of expertise, AI extends a lawyer’s capabilities: litigation prediction tools analyse historical cases and judge tendencies to assist in formulating the best litigation strategy. In complex tasks like due diligence, algorithms surpass human limits. Service innovation is seen in tools like the mini-programme developed by Xinghan Law Firm, which transforms case-specific experience into reusable client solutions. Therefore, by taking on standard tasks aforementioned AI will free lawyers to focus on complex dispute resolution and multi-disciplinary innovation. This change in the business model of legal services will reshape a product-oriented, value-generating industry.
However, AI in legal tech must adhere to ethical guidelines. Lawyers must independently verify the legal accuracy of AI-generated outputs and, in certain cases, disclose AI tool usage to clients and courts. They must also obtain explicit consent before inputting client information and assume responsibility for overseeing AI tool use within their teams.
AI Enhancing Judicial Efficiency
In the field of judicial practice, two outstanding AI applications were presented. The first is the award-winning “Supervision Model for Cases Involving Excessive Mining” used by the Qingyuan Municipal People’s Procuratorate. It represents a system that applies AI to monitor and limit activities of illegal mining. In Qingyuan procuratorate system, AI applications focus on the goal of “handling every case with high quality and efficiency.” Committed to the principle of safety, fairness, and public order, the system integrates human-machine collaboration. Key applications include “one-click generation” of criminal prosecution documents and intelligent generation of administrative prosecution papers, significantly enhancing work quality and efficiency.
Another example of AI application is the “Shaoxing Digital Prosecution Model”, developed by the Shaoxing Municipal People’s Procuratorate. This model demonstrates how AI-powered framework supports the full cycle of procuratorial work – from the preparation of documents to the supervisory investigation and even recommendations regarding sentencing. These models thus show how AI can improve the quality, accuracy, and control of procuratorial work.
Toward Integrated Legal Knowledge Systems
AI service providers, such as PKULAW, stressed the need for a unified AI ecosystem comprising large AI models, scenario-specific applications, and legal knowledge bases. Such an all-in-one setup is key to using AI effectively in legal work and advancing the digitalised rule of law.
Future Challenges
Speakers from Europe and Asia discussed global concerns around algorithmic bias, data security, and transparency. Prof. Leendert van der Torre, the Associate Dean of the Faculty of Computer Science and Professor of Artificial Intelligence at the University of Luxembourg, forecasted that the AI legal tech market will reach $3.5 billion by 2030. He outlined four main challenges in integrating AI with law: the vast scale of legal data, the complexity of legal entities, the difficulty in interpreting legal systems, and conflicts of interest between various stakeholders. Dr. Yu Liuwen discussed the current sandbox mechanism for AI regulation in the legal sector. She also analysed the significant challenges posed by generative AI, including risks of coercive self-protection, self-replication, and inconsistent actions and words. She stressed the importance of building a dedicated sandbox for generative AI and using neuro-explainable technologies to address the “black box” issue, ensuring better management of risks such as self-deception in AI.
The Secretary-General and Chief Financial Officer of the International Association for AI and Law, and Assistant Professor at the Department of Legal Theory at the Faculty of Law and Administration, Jagiellonian University in Kraków, Poland, Michał Araszkiewicz presented the results of the first international study on the use of AI in the legal industry conducted in over 200 law firms globally. The report demonstrates that the utilisation of AI by law firms and in-house legal departments is increasing. Main concerns were also pointed out, including data protection and privacy issues, over-reliance on AI, lack of AI transparency, AI biases, and ethical issues. He stressed the importance of lawyers becoming AI literate in order to make ethical and effective use of AI tools.
As a high-end dialogue platform, the GAITC 2025 Law & AI forum showed China’s progress in the integration of law and technology. Through interdisciplinary and inter-institutional collaboration, the forum demonstrated AI’s promise to improve judicial efficiency, power legal innovation, and shape the future of global legal practice.
References
[1] PKULAW is one of the most comprehensive bilingual database for searching PRC laws and regulations (since 1949), cases, as well as secondary legal sources such as journal articles, gazettes, and more.
