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Training Data & Generated Content
How can model training data be legally verified, and can AI-generated content be safely commercialized? Verify legal bases for training, fine-tuning and RAG ingestion, preserve human creative input, and manage commercialization, licensing and infringement claims. Procuring or preparing datasets for pre-training and fine-tuning Ingesting client materials, proprietary data or scraped content into RAG systems Commercialising and licensing generated text, images, audio, video or code Receiving copyright infringement notices or detecting substantial similarity risks
Topic guideAgents & A2A
How do authority and legal liability travel across autonomous agents in multi-agent workflows? Clarify legal status among clients, service providers and open platforms, reviewing delegation chains, Agent Card disclosures, task routing and high-impact action guardrails. Personal assistants calling third-party agents via the A2A protocol Agent platforms publishing Agent Cards or admitting external autonomous agents Agents authorized to execute financial transactions, system changes or communications Multi-agent workflows transmitting personal data, trade secrets or transaction orders
Topic guidePersonal Data & Governance
How can enterprises protect proprietary data and personal information from unauthorized secondary training and retention? Trace data flows across foundation models, RAG architectures and third-party APIs, auditing legal bases, notice and consent, retention limits, cross-border compliance and exit terms. Employees entering confidential client data or proprietary documents into public LLMs AI systems processing sensitive personal data, biometric traits or user profiling Procuring overseas AI models, cloud infrastructure, annotation or compute resources Using real production data for model evaluation, fine-tuning or system iteration
Topic guideAutomated Decisions & Scoring
How can organizations fulfill algorithmic explainability and uphold consumer rights to challenge automated decisions? Auditing algorithmic recommendations, ranking, dynamic pricing and automated decisions for transparency, fairness, explainability and human intervention rights. Systems supporting credit underwriting, insurance pricing, risk profiling or qualification scoring Platforms employing algorithms for personalised recommendations, ranking or dynamic pricing Automated decisions producing legal or similarly significant adverse effects on individuals Facing regulatory algorithmic audits, consumer complaints or public scrutiny
Topic guideAI in Employment
What legal duties must employers fulfill when algorithms direct hiring, evaluation and workforce management? Governing AI applications across recruitment, scheduling, task dispatch, performance appraisal and workplace management, ensuring algorithmic transparency, non-discrimination and human oversight. HR systems using algorithms for automated CV screening, AI video interviews or candidate ranking Algorithms directing scheduling, task allocation, performance metrics, discipline or dismissal Procuring third-party HRTech algorithms, assessment tools or employee surveillance systems Workers challenging algorithmic scores, monitoring, task allocation or automated actions
Topic guideAI Evidence & Litigation
How can parties prove the authenticity and chain of custody when AI generates or supports evidentiary materials? Establishing admissibility and probative value of AI-assisted outputs and digital evidence, preventing algorithmic hallucinations, and preserving full audit trails of models, prompts, logs and human verifications. Legal teams utilising generative AI for legal research, comparative analysis, drafting or translation Disputes turning on algorithmic decision logic, system logs, code provenance or synthetic content Opposing counsel introducing unauthenticated, AI-generated or potentially hallucinated filings Urgent need to preserve volatile model weights, RAG knowledge bases and API logs in tech litigation
Topic guideAI & Data Compliance
Map data sources, processing roles, purposes, flows and controls across AI systems. Building a knowledge base with internal data Procuring model APIs, datasets or annotation services Processing sensitive personal information or profiling users Transferring data to overseas teams, vendors or systems Product and business description Architecture and data-flow diagrams Data, model and vendor lists Privacy notices and terms Internal data and security policies Representative prompts, retrievals and outputs
AI and Data ComplianceAgent & A2A Review
Review agent functions and permissions together with the legal issues arising when agents discover, connect to and delegate tasks to one another through A2A. Deploying client-side agents that orchestrate third-party agent services via A2A protocols Operating platform hubs that publish Agent Cards or expose A2A endpoints to external ecosystems Coordinating autonomous agents from multiple enterprises or vendors in end-to-end workflows Exchanging personal data, trade secrets, sensitive files, orders, or payment instructions across agents Agent workflow diagrams and participant role definitions A2A architecture, API specifications, and Agent Card documentation Message, task instruction, file, and result payloads Authentication protocols, credential exchange, and human-in-the-loop settings Third-party agent registry and partnership agreements Test credentials, interaction audit logs, and high-risk scenario cases
AI Agent and A2A ReviewAI Product Compliance
Embed legal review into design, development, procurement, testing, launch, operation and updates. Launching a generative AI feature or foundation-model application Embedding AI into an app, SaaS product or hardware Procuring models, plugins, data or technical services Making major releases or business-model changes Requirements and prototypes Features and user flows Architecture and model plan Business model and user description Terms, policies and operating rules Testing and release plan
AI Product Lifecycle ComplianceGenerated Content & IP
Assess training materials, inputs, outputs, ownership, licensing and infringement response. Commercialising generated text, images, video, audio or code Using protected content for training, fine-tuning or retrieval Operating an AIGC platform or creative tool Responding to rights notices or similar and misleading outputs Training or retrieval material description Licence and open-source terms Generation workflow Terms and platform rules Representative input and output Marketing and distribution plan
Generated Content and Intellectual PropertyModel & Platform Governance
Review admission, risk tiering, content safety, monitoring, audit and accountability for models, algorithms and platforms. Providing model APIs, algorithm services or AI platforms Using recommendation, ranking, decision or generation algorithms Establishing model admission, testing, monitoring and exit mechanisms Preparing for algorithm audit, client assessment or regulatory engagement Model, algorithm and platform inventory Product architecture and responsibility chart Vendor and partner arrangements Security and data policies Testing, monitoring and audit records Complaint and incident history
Model, Algorithm and Platform GovernanceEnterprise AI Governance
Establish enterprise AI planning, tool admission, data permissions, internal policies, training, audit and incident response. Developing an enterprise AI strategy and governance framework Deploying internal knowledge systems, assistants or business agents Managing AI tools procured independently by several departments Preparing for client due diligence, internal audit or regulatory engagement Organisation structure and business plan AI application, model and vendor inventory Use cases and system architecture Data, procurement, security and audit policies Approval processes and permission settings Usage records, complaints and incident materials
Enterprise AI Development and GovernanceAI Contracts & Disputes
Support procurement, development, licensing, investment and disputes involving technology, data and outputs. Procuring models, platforms, agents or custom development Joint R&D, licensing or investment transactions Performance, delivery, data, rights or fee disputes Third-party claims caused by AI outputs Commercial proposal and background Technical requirements Contracts and correspondence Delivery, test and acceptance records Logs and version information Loss evidence and third-party claims
AI Contracts and Dispute ResolutionBeijing AI Text-to-Image Case
Generative AI Image Copyright Infringement Dispute （2023）京0491民初11279号 Evaluating prompt design, parameter adjustments, and the generation process, the court held that the disputed image reflected the user's intellectual investment and personalized expression, determining copyrightability and ownership on this basis. Copyright China Beijing
China · BeijingShanghai AI Face-Swapping Case
AI Face-Swapping Copyright Infringement Dispute （2024）沪0114民初1326号 A mini-program provided paid generation services by replacing facial features in original videos. The court held that localized face-swapping did not constitute an original adaptation and that the platform's commercial use infringed the right of dissemination through information networks. Copyright China Shanghai
China · ShanghaiGuangzhou Ultraman AI Image Case
"Ultraman" AI-Generated Image Platform Infringement Dispute The defendant connected to a third-party AI image service through an API. Users could generate images substantially similar to the protected Ultraman works. The court classified the defendant as a generative AI service provider and found infringement of the reproduction and adaptation rights. Platform Liability China Guangdong
China · GuangdongUS Thaler Copyright Case
Thaler v. Perlmutter AI-Generated Work Registration Dispute No. 23-5233 The applicant listed an artificial intelligence system as the sole author of a work. The court affirmed the refusal of registration, confirming that current United States copyright law requires human authorship. Copyright United States
United StatesUS Attorney Fictitious Citation Case
Mata v. Avianca Fictitious Case Law Sanctions Dispute 22-cv-1461 (PKC) Attorneys submitted court filings containing fictitious judicial decisions and citations fabricated by generative artificial intelligence, and continued to provide inaccurate materials after being challenged. The court imposed sanctions accordingly. Legal Practice United States
United StatesUK DABUS Patent Case
Thaler v Comptroller-General: AI Inventor Case [2023] UKSC 49 The applicant named the DABUS system as the inventor. The UK Supreme Court held under existing patent law that an inventor must be a natural person. Patent United Kingdom
United KingdomUK Getty Images Case
Getty Images v Stability AI: Training and Model Infringement Case [2025] EWHC 2863 (Ch) Getty Images alleged that Stable Diffusion infringed intellectual property rights through its training, distribution, and outputs bearing Getty Images or iStock watermarks. Before the close of trial, Getty Images abandoned its training, output-copyright, and database-right claims. The court dismissed secondary copyright infringement and found only limited historical instances of trademark infringement. Copyright United Kingdom
United KingdomAir Canada Chatbot Case
Moffatt v. Air Canada: Chatbot Misinformation Case 2024 BCCRT 149 An airline website chatbot provided inaccurate bereavement fare information. The tribunal held that the enterprise is responsible for information provided on its website. Platform Liability Canada
CanadaEU SCHUFA Scoring Case
SCHUFA Automated Credit Scoring Case C-634/21 A credit agency automatically generated credit scores for use by third parties such as banks. The Court of Justice of the European Union held that when a score plays a decisive role in a third party's decision, the scoring activity constitutes automated individual decision-making governed by Article 22 of the GDPR. Data and Automated Decision-Making Germany
GermanyAustralia AI Character Reference Case
DPP v Khan: AI-Assisted Character Reference Case [2024] ACTSC 19 In sentencing proceedings, the court examined a character reference that appeared to have been generated or rewritten with a large language model. Because its preparation could not be established, the court gave it little weight and directed counsel to enquire whether character references were prepared with a large language model or automated translation. Legal Practice Australia
AustraliaBeijing AI Voice Case
AI-Synthesized Voice Personality Rights Infringement Case （2023）京0491民初12142号 Audio recordings were used to create an AI voice product capable of generating arbitrary text-to-speech voiceovers. The court held that voice rights protect AI-synthesized voices when the voice leads the public to associate it with a specific natural person. Personality Rights China Beijing
China · BeijingU.S. ROSS Training Data Case
Thomson Reuters v. ROSS Intelligence AI Training Data Case No. 1:20-cv-00613；No. 25-2153 ROSS used training materials derived from Westlaw headnotes to develop a legal search tool. The district court found numerous headnotes protectable and rejected the fair use defense. The Third Circuit has accepted an interlocutory appeal. Copyright United States
United StatesU.S. Anthropic Book Training Case
Bartz v. Anthropic Book Training and Pirated Repositories Case No. 3:24-cv-05417 The court distinguished model training and the digitization of purchased print books from downloads from pirated repositories before granting final approval to a $1.5 billion class action settlement. The ruling evaluated training activities separately from data acquisition methods. Copyright United States
United StatesU.S. Meta Book Training Case
Kadrey v. Meta Book Training Fair Use Case No. 3:23-cv-03417 Authors alleged that Meta used copyrighted books without authorization to train its Llama models. Based on the evidentiary record, the court granted summary judgment in favor of Meta against certain plaintiffs, emphasizing that market harm evidence remains central to outcomes in related cases. Copyright United States
United StatesU.S. Workday Hiring Algorithm Case
Mobley v. Workday AI Hiring Discrimination Case No. 3:23-cv-00770-RFL Applicants allege that Workday's algorithmic screening tools caused discrimination based on race, age, sex, and disability. The court previously held that a technology vendor performing traditional recruitment functions may act as an employer's agent, and in 2026 confirmed that applicants may pursue disparate-impact claims under the Age Discrimination in Employment Act. Labor and Employment United States
United StatesUS COMPAS Sentencing Case
State v. Loomis: Criminal Sentencing Risk Assessment Case 2016 WI 68 Criminal sentencing materials incorporated a commercial COMPAS recidivism risk score. The court permitted limited consideration of the score, required clear warnings regarding the tool's limitations, and prohibited using the score to determine sentence severity or whether incarceration is warranted. Data and Automated Decision-Making United States
United StatesUS Lovo Voice Cloning Case
Lehrman v. Lovo: AI Voice Cloning Case No. 24-cv-03770-JPO Two voice actors alleged that their voice recordings were used without authorization to develop and commercialize AI voice clones. The court allowed claims for breach of contract, commercial misappropriation of personality under New York law, and consumer protection to proceed, while treating training-stage copies, underlying audio recordings, and synthetic outputs under separate legal frameworks. Personality Rights and Right of Publicity United States
United StatesEU Automated Decision-Making Explanation Case
Dun & Bradstreet Austria: Explanation of Automated Credit Scoring Case C-203/22 The Court of Justice of the European Union ruled that data subjects are entitled to an explanation sufficient to understand and challenge automated decisions. Such explanations must disclose the concrete procedures and principles applied and illustrate how changes in personal data influence the resulting outcome. Data and Automated Decision-Making Austria
AustriaNetherlands SyRI Risk Profiling Case
SyRI: Social Welfare Fraud Risk Profiling Case C/09/550982 / HA ZA 18-388；ECLI:NL:RBDHA:2020:865 The Dutch government integrated multi-agency public data to generate fraud risk profiles for social welfare recipients. The court held that the regulatory regime lacked sufficient transparency and auditability, failing to strike a fair balance in its interference with the right to private life. Data and Automated Decision-Making Netherlands
NetherlandsNetherlands Ola Driver Data Access Case
Ola: Driver Profiling and Automated Deduction Data Access Case ECLI:NL:RBAMS:2021:1019 Ride-hailing drivers sought access to platform data used for scoring, fraud detection, earning profiles, and wage deductions. The court distinguished between general profiling, dispatch algorithms, and automated deductions with significant effects, ordering the platform to disclose specific categories of underlying data. Data and Automated Decision-Making Netherlands
NetherlandsUK Police Live Facial Recognition Case
R (Bridges) v Chief Constable of South Wales Police (Live Facial Recognition Case) [2020] EWCA Civ 1058 South Wales Police deployed a live facial recognition system in public spaces. The Court of Appeal held that the criteria for watchlists and deployment locations lacked sufficient legal constraints, and identified deficiencies in the data protection impact assessment and compliance with the public sector equality duty. Data and Automated Decision-Making United Kingdom
United KingdomEwert v. Canada Risk Assessment Case
Ewert v. Canada (Indigenous Recidivism Risk Assessment Case) 2018 SCC 30 The Correctional Service of Canada assessed a Métis inmate using recidivism risk tools developed and validated on non-Indigenous populations. The Supreme Court held that the correctional authority failed to take reasonable steps to confirm the validity of the tools for Indigenous persons. Data and Automated Decision-Making Canada
CanadaJapan DABUS Patent Case
Japan DABUS AI Inventorship Case 2024 (Gyo-Ko) 10006 A patent application designated the DABUS artificial intelligence system as the inventor. The Intellectual Property High Court of Japan affirmed the rejection of the application, and the Supreme Court dismissed the final appeal in 2026, confirming that an inventor under current Japanese law must be a natural person. Patents Japan
JapanSingapore Algorithmic Trading Contract Case
Quoine Pte Ltd v B2C2 Ltd (Algorithmic Trading Contract Case) [2020] SGCA(I) 2 Cryptocurrency transactions were executed automatically by deterministic algorithms programmed by the parties at approximately 250 times the prevailing market price. The Court of Appeal held that valid contracts were formed by algorithmic execution and assessed unilateral mistake based on the programmer's state of mind at the time of coding. Platform Liability Singapore
SingaporeColombia Judicial Use of ChatGPT Case
Constitutional Court of Colombia Decision T-323/24 (Judicial Use of Generative AI) T-323/24 A lower-court judge included ChatGPT responses in the reasoning of a judgment. The Constitutional Court found that the judge had independently decided the matter prior to querying the model, upholding the validity of the proceedings while establishing standards for judicial AI use including transparency, verification, privacy, and human control. Legal Practice Colombia
ColombiaSouth Africa Hallucinated Citations and Attorney Liability Case
Mavundla v. MEC: AI Hallucinated Case Citations Case [2025] ZAKZPHC 2 A legal team submitted appellate filings containing non-existent or inaccurate case citations. The court found that the team failed to conduct basic verification, ordered the law firm to pay the costs of additional hearings, and referred the judgment to the Legal Practice Council. Legal Practice South Africa
South AfricaIndia ANI v. OpenAI Case
ANI Media v. OpenAI: Training Data and News Content Case CS(COMM) 1028/2024 Indian news agency ANI alleged that OpenAI used its news content without authorization to train AI models, raising concerns over model outputs and false attribution. The High Court of Delhi concluded hearings on the interim injunction application, with the substantive decision pending. Copyright India
IndiaFrance Parcoursup Algorithm Case
Parcoursup University Admissions Algorithm Transparency Case No. 433296 Student unions requested universities to disclose local algorithms used to process applications on the Parcoursup platform. The French Council of State distinguished an individual applicant's right to an explanation from public access to source code, requiring universities to publish general evaluation criteria. Data and Automated Decision-Making France
FranceSpain Glovo Couriers Case
Glovo Platform Employment and Algorithmic Management Case ECLI:ES:TS:2020:2924 Glovo organized delivery services through its platform, rating systems, automated order dispatch, and geolocation tracking. The Supreme Court of Spain held that an employment relationship existed between the courier and the platform, citing algorithmic management and the platform's control over essential assets. Labor and Employment Spain
SpainBrazil Metro Facial Recognition Case
ViaQuatro Metro Facial and Emotion Recognition Case Apelação nº 1090663-42.2018.8.26.0100 São Paulo metro advertising displays captured passenger facial features to infer age, gender, and emotional reactions. The court ruled that such processing violated passenger personality rights and consumer rights, upholding an order to cease processing and increasing collective moral damages. Personality Rights Brazil
BrazilBeijing AI Voice Endorsement Case
Unauthorized Use of an AI-Synthesized Celebrity Voice in Product Promotion A book retailer used a public figure's image and a highly similar AI-synthesized voice in promotional videos. The court found infringements of portrait and voice rights and held that a merchant commissioning influencer promotion must review the promotional content. Personality Rights China Beijing
China · BeijingBeijing AI Face-Swap Personal Information Case
Unauthorized Processing of Facial Information in an AI Face-Swap Service A face-swap application turned videos featuring two online models into paid templates. The court distinguished portrait identifiability from the processing of facial and other personal information, finding unauthorized personal information processing. Personality Rights China Beijing
China · BeijingBeijing AI Content Detection Case
Platform Contract Dispute over Algorithmic Detection of AI-Generated Content A platform classified a user's post as unlabeled AI-generated content, hid it, and suspended the account for one day. The court required a reasonable and proportionate explanation of the detection basis and enforcement result. Data and Automated Decision-Making China Beijing
China · BeijingBeijing AI Portrait Parody Case
AI-Generated Derogatory Portrait and Personality Rights Case A person used AI software to turn another group member's profile photograph into a sexually suggestive and degrading image and distributed it. The court found infringements of portrait and reputation rights. Personality Rights China Beijing
China · BeijingBeijing Virtual Human Copyright Case
Copyright Ownership and Infringement of Virtual Human Characters （2024）京0491民初4936号；（2025）京73民终603号 A former employee uploaded and sold two virtual human models on a model marketplace. The courts recognized the original visual designs as works of fine art, found the uploader liable, and held that the marketplace had fulfilled its reasonable duties. Copyright China Beijing
China · BeijingBeijing AI Companion Personality Case
Unauthorized Creation of an AI Companion Based on a Public Figure A mobile application allowed users to create AI companions using a public figure's name, portrait, and persona, while the operator organized, recommended, and expanded those characters through algorithms. The court found infringement of the public figure's personality rights. Personality Rights China Beijing
China · BeijingUK AI False Citation Review
Ayinde and Al-Haroun Consolidated Review of AI-Generated False Citations [2025] EWHC 1383 (Admin) The High Court jointly examined fabricated or inaccurate legal materials filed in two proceedings and set out the duties of solicitors and barristers regarding citation verification, supervision and candour to the court. Legal Practice United Kingdom
United KingdomU.S. Character.AI Product Liability Case
Garcia v. Character Technologies: AI Companion Product Liability Case No. 6:24-cv-1903-ACC-UAM After a minor user's death, his parents brought claims concerning the design, safety controls, and outputs of an AI companion service. At the pleading stage, the court allowed multiple product liability, negligence, consumer protection, and related claims to proceed. Platform Liability United States
United StatesShenzhen AI-Assisted Adjudication System
Shenzhen Courts' AI-Assisted Adjudication System Shenzhen courts have developed an AI-assisted adjudication system and a vertical model for judicial work. Public reports describe its use in assisting more than 600,000 cases and illustrate governance needs for judicial data, access permissions, accuracy, and human responsibility. Judicial Application China Guangdong
China · GuangdongChina: Interim Generative AI Measures
Interim Measures for the Management of Generative Artificial Intelligence Services The measures govern generative AI services offered to the public in China and address training data, generated content, personal information, security and complaint handling. China China Regulatory rule Service providers are responsible for training data, generated content and personal information processing. Training data quality measures should address intellectual property and personal information rights. Providers need operating rules for unlawful content, user complaints, service terms and security.
China · Regulatory ruleChina: AI Content Labelling Measures
Measures for Labelling Artificial Intelligence-Generated or Synthetic Content Providers, content distribution platforms and application stores must apply, verify and preserve explicit and implicit labels for AI-generated or synthetic content. China China Regulatory rule Explicit labels vary by text, image, audio, video and virtual-scene formats. Implicit labels must be embedded in metadata or other prescribed locations. Platforms must verify labels, obtain user declarations and address suspected AI-generated content.
China · Regulatory ruleChina: Algorithmic Recommendation Provisions
Provisions on the Administration of Algorithmic Recommendations in Internet Information Services The provisions govern generation, personalised recommendation, ranking, search filtering and scheduling algorithms used to provide internet information services in China. China China Regulatory rule Providers need internal review, technology ethics, user registration and information publishing controls. Users receive information and choice rights, including an option to disable personalised recommendations. Qualifying services must complete algorithm filing and security assessment procedures.
China · Regulatory ruleChina: Deep Synthesis Provisions
Provisions on the Administration of Deep Synthesis in Internet Information Services The provisions regulate services that generate or edit text, images, audio, video and virtual scenes through deep learning, virtual reality and related techniques. China China Regulatory rule Providers must authenticate users and manage accounts. Operational controls cover misinformation, complaints, logs and data security. Content that may confuse or mislead the public requires a conspicuous label.
China · Regulatory ruleEU Artificial Intelligence Act
Regulation (EU) 2024/1689 — Artificial Intelligence Act The AI Act uses a risk-based framework for prohibited practices, high-risk systems, general-purpose AI models and transparency duties, including rules that reach some providers outside the EU. European Union Europe Legislation The Act prohibits defined AI practices that create unacceptable risks. High-risk systems require risk management, data governance, technical documentation, logging, human oversight and conformity assessment. General-purpose AI providers face documentation, downstream information, copyright-policy and systemic-risk obligations.
European Union · LegislationCouncil of Europe AI Framework Convention
Council of Europe Framework Convention on Artificial Intelligence and Human Rights, Democracy and the Rule of Law The Convention creates a treaty framework for public- and private-sector AI activities and requires domestic measures addressing human rights, democracy and the rule of law. Council of Europe International organisations International convention AI activities must be consistent with human rights, democracy and the rule of law. Parties must address transparency, oversight, accountability, remedies and procedural safeguards. Risk and impact identification, assessment, prevention and mitigation form part of the framework.
Council of Europe · International conventionCanada: Automated Decision-Making Directive
Directive on Automated Decision-Making The Directive governs federal administrative decisions made fully or partly by automated systems and scales transparency, review and human-intervention requirements through an Algorithmic Impact Assessment. Government of Canada North America Policy Departments complete and publish an Algorithmic Impact Assessment before production use. Peer review, notice, explanation, testing and human intervention increase with the impact level. Departments monitor outcomes and preserve recourse and review routes.
Government of Canada · PolicyNIST AI Risk Management Framework
NIST Artificial Intelligence Risk Management Framework 1.0 The framework organises AI risk work around Govern, Map, Measure and Manage and can support product development, procurement, deployment and continuing monitoring. United States North America Governance guidance Governance covers accountability, policy, staff capability and organisational culture. Risk mapping considers intended use, stakeholders and possible impacts. Testing, metrics, monitoring and response records support continuing improvement.
United States · Governance guidanceUK AI Regulation White Paper
A Pro-Innovation Approach to AI Regulation The United Kingdom uses cross-sector principles implemented by existing regulators, with a focus on safety, transparency, fairness, accountability and contestability. United Kingdom Europe Policy Existing regulators apply common principles in their own sectors. The framework addresses safety, appropriate transparency, explainability, fairness, accountability and redress. Businesses should follow the sector-specific positions of each relevant regulator.
United Kingdom · PolicySingapore: Generative AI Governance Framework
Model AI Governance Framework for Generative AI The framework addresses accountability, data, trusted development, incident reporting, testing, security and content provenance across the generative AI supply chain. Singapore Asia-Pacific Governance guidance Responsibilities should be allocated across model developers, application deployers and users. Governance should address data, trusted development, testing and security. Content provenance, incident reporting and industry cooperation support deployment controls.
Singapore · Governance guidanceJapan: AI Guidelines for Business
AI Guidelines for Business, Version 1.2 The guidance supports risk-based governance for AI developers, providers and business users, with attention to transparency, fairness, safety and continuing improvement. Japan Asia-Pacific Governance guidance Responsibilities are organised around developer, provider and business-user roles. Risk identification, communication and monitoring should reflect the specific use case. Management participation, internal systems and stakeholder engagement support implementation.
Japan · Governance guidanceAustralia: Guidance for AI Adoption
Guidance for AI Adoption The guidance helps organisations assign accountability and establish proportionate risk, data, testing, transparency and monitoring controls when adopting AI. Australia Asia-Pacific Governance guidance Assign internal accountability and adopt an AI risk-management method. Address data governance, testing, monitoring, transparency and stakeholder communication. Scale controls to the use and impact and retain evidence of implementation.
Australia · Governance guidanceKorea AI Basic Act
Framework Act on the Development of Artificial Intelligence and Establishment of Trust The Act establishes national AI governance and industrial support and creates transparency and safety duties for generative and high-impact AI. Republic of Korea Asia-Pacific Legislation Generative and high-impact AI systems are subject to defined transparency duties. AI systems meeting statutory conditions require safety measures. Qualifying overseas businesses must appoint a domestic representative.
Republic of Korea · LegislationOECD AI Principles
OECD Principles on Artificial Intelligence The principles provide a shared foundation for trustworthy AI through inclusive growth, human-centred values, transparency, safety and accountability. OECD International organisations Governance guidance Promote inclusive growth, sustainable development and well-being. Respect the rule of law, human rights, democratic values and fairness. Support transparency, explainability, robustness, security and accountability.
OECD · Governance guidanceChina: SPC Opinions on AI Disputes
Supreme People’s Court Opinions on Adjudicating Disputes Involving Artificial Intelligence Issued as Fa Fa [2026] No. 10, these judicial policy opinions contain 24 provisions in five parts covering AI-related torts, intellectual property, technology contracts, evidence and adjudication mechanisms. The text specifies no separate commencement date. This English overview is an editorial summary; the linked on-site text is the official Chinese original. China China Judicial policy Liability follows the applicable legislation. Fault-based liability applies where the law does not expressly provide for strict liability or presumed fault, with the application context, risks and preventive measures considered. The opinions address face and voice synthesis, privacy infringements, the use of publicly available personal information for training, and providers’ responses to infringement notices. Copyright liability depends on factors including training data sources, participation and safeguards. Developers asserting a non-infringement defence must provide supporting material such as data sources and training records. Open-source software, patents, technology contracts and data disputes require assessment of licence terms, human creative contributions, contractual commitments and lawful data acquisition. Courts should scrutinise electronic and AI-generated evidence. Participants using AI-generated litigation materials must verify legal references and cases before filing and disclose the use of AI assistance to the court.
China · Judicial policyChina: PIPL Automated Decision-Making Rules
Personal Information Protection Law, Article 24 — Automated Decision-Making Article 24 requires transparent, fair and impartial automated decision-making and creates safeguards for recommendation, marketing and decisions with a significant impact on individual rights. China China Legislation Automated decision processes must be transparent and their results fair and impartial. Recommendation and marketing services must offer a non-personalised option or a convenient refusal route. Individuals may request an explanation and refuse decisions made solely through automation where the decision has a significant impact.
China · LegislationChina: Science and Technology Ethics Review Measures
Measures for Science and Technology Ethics Review (Trial) Organisations conducting life-science, medical or AI research must establish ethics review arrangements and review projects that raise sensitive ethical issues. China China Regulatory rule Qualifying organisations establish an ethics review committee and application, review, re-review and supervision procedures. Reviews address necessity, risk and benefit, informed arrangements, fairness, privacy and data security. Algorithms with public-opinion or social-mobilisation attributes and highly autonomous safety or health decisions may require expert re-review.
China · Regulatory ruleChina: AI Safety Governance Framework
Artificial Intelligence Safety Governance Framework, Version 2.0 The framework supports graded risk identification and treatment across models, data, systems, networks, ethics and applications for AI development, deployment and use. China China Governance guidance Risk levels reflect likelihood and impact and should be updated as technology and use change. The framework covers intrinsic, application, cognitive and ethical safety risks. Technical, organisational, coordinated-governance and international measures support risk treatment.
China · Governance guidanceEU GDPR Automated Decision-Making Rules
General Data Protection Regulation — Profiling and Automated Decision-Making The GDPR sets legal-basis, transparency and safeguard requirements for profiling and solely automated decisions that produce legal or similarly significant effects. European Union Europe Legislation Significant solely automated decisions require a permitted basis, such as contractual necessity, legal authorisation or explicit consent. Privacy information should explain the use, meaningful logic and expected consequences. Applicable safeguards include human intervention, an opportunity to state a position and a route to contest the decision.
European Union · LegislationEU Product Liability Directive
Directive (EU) 2024/2853 on Liability for Defective Products The revised Directive brings software and AI systems within the product-liability framework and updates defect, responsible-party, evidence-disclosure and causation rules. European Union Europe Legislation Software, AI systems and certain digital manufacturing files may qualify as products. Updates, learning capability and related digital services can be relevant to the defect assessment. Courts can order evidence disclosure and may apply presumptions in technically complex cases.
European Union · LegislationEU General-Purpose AI Code of Practice
General-Purpose AI Code of Practice The Code gives general-purpose AI model providers practical approaches to transparency, copyright and systemic-risk management under the EU AI Act. European Union Europe Governance guidance The transparency chapter provides model-documentation and downstream-information tools. The copyright chapter supports a policy for compliance with EU copyright law. The safety and security chapter addresses evaluation, mitigation, incident reporting and model security for systemic-risk models.
European Union · Governance guidanceUK Automated Decision-Making Rules
Data (Use and Access) Act 2025 — Automated Decision-Making The Act restructures UK data-protection rules for automated decisions, broadens some permitted uses and retains notice, challenge, human-intervention and special-category-data safeguards. United Kingdom Europe Legislation A new statutory structure applies to significant automated decisions and treats special-category data separately. Individuals receive information and may make representations, challenge the outcome and request human intervention. Organisations should update privacy information, decision workflows, human review and evidence records.
United Kingdom · LegislationAmerica’s AI Action Plan
Executive Order on American AI Leadership and America’s AI Action Plan The executive order and action plan direct federal work on AI innovation, infrastructure and international engagement and require review of measures that conflict with the current policy. United States Federal Government North America Policy Federal agencies review and revise earlier measures against current policy objectives. The action plan organises work around innovation, AI infrastructure, and international diplomacy and security. Businesses should monitor follow-on rules for procurement, exports, data centres, model evaluation and sector regulation.
United States Federal Government · PolicyUS OMB AI Governance Memoranda
OMB Memoranda on Federal AI Use and Procurement OMB memoranda M-25-21 and M-25-22 govern federal-agency AI use and procurement, including accountability, high-impact uses, risk practices and contract terms. United States Federal Government North America Regulatory rule Agencies appoint a Chief AI Officer and maintain AI governance and inventories. High-impact AI requires testing, monitoring, human oversight and risk treatment. Procurement addresses data rights, portability, interoperability, vendor lock-in and performance evaluation.
United States Federal Government · Regulatory ruleUS Intimate Deepfake Law
TAKE IT DOWN Act The Act criminalises defined publication of non-consensual intimate images, including digital forgeries, and requires covered platforms to operate a notice-and-removal process. United States North America Legislation The Act prohibits intentional publication of covered non-consensual intimate imagery, including qualifying digital forgeries. Covered platforms must provide a clear notice-and-removal process. After a valid notice, platforms generally have 48 hours to remove the image and take reasonable steps regarding identical copies.
United States · LegislationTexas Responsible AI Governance Act
Texas Responsible Artificial Intelligence Governance Act Texas regulates certain government and healthcare AI disclosures, prohibited uses, regulatory-sandbox participation and enforcement, including some developers and deployers serving the state. Texas, United States North America Legislation Government agencies and healthcare providers make defined disclosures in certain consumer interactions. The Act restricts manipulation, social scoring, unlawful discrimination and certain biometric uses. The Texas Attorney General enforces the Act, which also creates an AI regulatory sandbox.
Texas, United States · LegislationCalifornia AI Transparency Act
California AI Transparency Act The Act requires qualifying generative AI providers to offer a content-detection tool and apply manifest or latent provenance disclosures to generated content. California, United States North America Legislation A free, publicly available AI-content detection tool is required. Generated content must carry prescribed provenance disclosures and users must receive relevant options. Providers must take prescribed licence action when a licensee removes the disclosure mechanism.
California, United States · LegislationCalifornia Training Data Transparency Rules
California Generative AI Training Data Transparency Law Developers publicly offering generative AI systems or services in California must publish a high-level description of training data and update it after substantial modifications. California, United States North America Legislation Publish a high-level description of datasets or training-data sources. Disclose prescribed points such as source, type, time range and inclusion of personal or copyrighted material. Prepare and update documentation before public release or a substantial modification.
California, United States · LegislationIllinois AI Employment Rules
Illinois Human Rights Act — Artificial Intelligence in Employment Illinois regulates employer use of AI in recruitment, hiring, promotion, training, discipline and termination, with a focus on protected-class discrimination and notice. Illinois, United States North America Legislation AI use may not cause unlawful discrimination based on a protected characteristic. Employers provide notice of AI use as prescribed by the rules. ZIP codes and other proxies may not be used to produce protected-class discrimination.
Illinois, United States · LegislationColorado AI Act
Colorado Consumer Protection for Artificial Intelligence Systems Act Colorado’s 2026 law governs automated decision technologies that materially influence consequential decisions and creates developer documentation, deployer notice, correction, human-review and recordkeeping duties. Colorado, United States North America Legislation Developers provide documentation on purpose, limitations, training data, performance, risk and human review. Deployers notify consumers before use and explain an adverse outcome in plain language. Consumers can correct data and request human review or reconsideration in covered circumstances.
Colorado, United States · LegislationNew York City Automated Hiring Tools Law
New York City Automated Employment Decision Tools Law New York City requires bias audits, public summaries and candidate or employee notices before employers and employment agencies use automated employment decision tools for hiring or promotion. New York City, United States North America Legislation An independent bias audit must have been completed within one year before use. A summary of audit results and information about data distribution must be public. Candidates or employees receive advance notice about the tool and the job qualifications it assesses.
New York City, United States · LegislationQuebec Automated Decision Rules
Quebec Private-Sector Privacy Act — Automated Decisions Quebec requires businesses making decisions based exclusively on automated processing to notify the individual and, on request, explain the information, reasons, principal factors and review route. Quebec, Canada North America Legislation Tell the individual, no later than the decision, that it was based exclusively on automated processing. On request, disclose the personal information used, the reasons and the principal factors and parameters. Provide a correction route and an opportunity to make representations to a staff member able to review the decision.
Quebec, Canada · LegislationOntario AI Hiring Disclosure Rules
Ontario AI Disclosure Rules for Publicly Advertised Job Postings Ontario requires employers above the employee threshold to disclose AI used to screen, assess or select applicants in public job postings and to keep related records. Ontario, Canada North America Legislation Public job postings disclose whether AI is used to screen, assess or select applicants. The posting rules also cover expected compensation, vacancy information and post-interview notices. Employers retain postings and related application forms for three years.
Ontario, Canada · LegislationJapan AI Act
Act on the Promotion of Research and Development and the Utilisation of Artificial Intelligence-Related Technologies Japan’s AI Act creates a national basic plan, an AI Strategic Headquarters and government inquiry powers and sets basic responsibilities for research bodies, businesses and the public. Japan Asia-Pacific Legislation The government prepares a basic AI plan and coordinates research, facilities, talent and international cooperation. Business operators cooperate with national measures and promote appropriate use under the basic principles. The government may investigate AI research or use that harms citizens’ rights and issue guidance or other measures.
Japan · LegislationVietnam AI Law
Law on Artificial Intelligence No. 134/2025/QH15 Vietnam’s standalone AI law creates risk classification, human-oversight, provider and deployer, synthetic-content and cross-border rules and gives existing systems a transition period. Vietnam Asia-Pacific Legislation Governance measures scale with risk; high-risk systems require assessment, registration and continuing monitoring. Providers and deployers address transparency, human oversight, data governance, safety and incidents. Generated content is labelled under the rules, which also define prohibited AI activities.
Vietnam · LegislationSingapore Personal Data and AI Guidelines
Advisory Guidelines on Use of Personal Data in AI Recommendation and Decision Systems The PDPC explains how Singapore’s personal-data law applies when organisations develop, customise or deploy AI recommendation and decision systems. Singapore Asia-Pacific Governance guidance Assess the available personal-data basis for business improvement, research, contractual performance and other uses. Document data source, selection, quality, provenance and alignment with the model purpose. Give meaningful information to individuals and allocate data-protection duties in supplier contracts.
Singapore · Governance guidanceSingapore Agentic AI Governance Framework
Model AI Governance Framework for Agentic AI, Version 1.5 The framework addresses AI agents that plan, call tools and perform tasks through use-case boundaries, meaningful human accountability, lifecycle controls and user transparency. Singapore Asia-Pacific Governance guidance Define appropriate agent use cases, permissions and risk boundaries. Set meaningful human accountability, checkpoints, suspension and takeover mechanisms. Manage lifecycle risks across models, tools, memory, third-party agents and multi-agent coordination.
Singapore · Governance guidanceMalaysia AI Governance and Ethics Guidelines
National Guidelines on Artificial Intelligence Governance and Ethics Malaysia’s guidance uses seven responsible AI principles to support policymakers, developers, providers and users with governance, risk and ethics practices. Malaysia Asia-Pacific Governance guidance The principles cover fairness, reliability and safety, privacy and security, inclusion, transparency, accountability and human benefit. Organisations can build internal governance around the use, impact and sector context. Risk assessment, stakeholder engagement and continuing monitoring support implementation.
Malaysia · Governance guidanceIndonesia AI Ethics Circular
Ministerial Circular No. 9 of 2023 on Artificial Intelligence Ethics Indonesia’s communications authority sets ethical responsibilities, internal-policy expectations and risk controls for AI programming businesses and electronic-system operators. Indonesia Asia-Pacific Regulatory rule AI activities should reflect inclusion, humanity, security, accessibility, transparency, credibility and accountability. Businesses establish internal policies covering data and AI ethics. Development and use address intellectual property, personal data, risk management and social impact.
Indonesia · Regulatory ruleNew Zealand Public Service AI Guidance
Responsible AI Guidance for the Public Service The guidance provides a common approach to generative AI assessment, approval, procurement, privacy, security, transparency and continuing oversight across the public service. New Zealand Asia-Pacific Governance guidance Appoint a senior accountable official and establish use approval, risk assessment and governance. Complete appropriate privacy-impact, security and supplier assessments. Provide suitable transparency, challenge routes and human oversight for affected people.
New Zealand · Governance guidanceHong Kong AI Data Protection Framework
Artificial Intelligence: Model Personal Data Protection Framework The PCPD provides personal-data and governance recommendations for organisations procuring, customising, implementing and using AI systems. Hong Kong, China Asia-Pacific Governance guidance Establish an AI strategy and governance structure with clear management and role accountability. Conduct risk assessment and set the level of human oversight to match the risk. Govern customisation, implementation, data, testing and monitoring and communicate with stakeholders.
Hong Kong, China · Governance guidanceDIFC Autonomous Systems Data Protection Rules
DIFC Data Protection Regulations, Regulation 10 — Autonomous and Semi-Autonomous Systems DIFC Regulation 10 governs autonomous and semi-autonomous systems that process personal data and addresses deployer, operator, governance, certification and officer arrangements. Dubai International Financial Centre Middle East Legislation Deployers and operators identify their respective responsibilities for system processing. Systems follow applicable data-protection principles and relevant ethical and trustworthy-system standards. Qualifying organisations appoint an Autonomous Systems Officer and maintain certification and oversight.
Dubai International Financial Centre · LegislationSaudi AI Ethics Principles
Saudi Arabia AI Ethics Principles SDAIA’s national reference helps public and private organisations address fairness, privacy, safety, transparency, accountability and societal value across the AI lifecycle. Saudi Arabia Middle East Governance guidance Principles cover fairness, privacy and security, reliability and safety, transparency and explainability, accountability, and human, social and environmental values. Identify stakeholders, impacts and controls throughout the project lifecycle. Use the principles in internal policy, risk assessment, procurement and system oversight.
Saudi Arabia · Governance guidancePeru AI Law and Regulation
Law No. 31814 Promoting the Use of Artificial Intelligence and its Implementing Regulation Peru’s Law No. 31814 and its 2025 regulation create a human-centred, safe, transparent and risk-based framework for AI development and use. Peru Latin America Legislation Governance and oversight measures reflect system risk and impact. High-risk uses receive stronger human-oversight, transparency, safety and rights safeguards. Public and private actors implement responsibility, recordkeeping and incident measures under the regulation.
Peru · LegislationArgentina Trustworthy AI Recommendations
Recommendations for Trustworthy Artificial Intelligence Argentina’s recommendations guide the national public sector through problem definition, data, model development, testing, deployment, transparency, human oversight and accountability. Argentina Latin America Governance guidance Define purpose, necessity, affected groups and accountability at the start of the project. Development and deployment address data quality, fairness, privacy, security, explainability and traceability. Provide human oversight, continuing assessment, challenge routes and accountability records.
Argentina · Governance guidanceBrazil AI Bill
Brazil Bill No. 2338/2023 on Artificial Intelligence The Bill would create a risk-based AI framework covering rights, high-risk assessments, governance duties, generated content and regulatory enforcement. Brazil Latin America Legislative proposal The draft classifies prohibited, excessive and high-risk uses and assigns different obligations. High-risk systems would be subject to impact assessment, governance, records, transparency and human oversight. Congress is still considering the Bill, so final wording, regulator and commencement dates may change.
Brazil · Legislative proposalChile AI Bill
Chile Bill Regulating Artificial Intelligence Systems Chile’s consolidated bill would classify AI systems by risk and regulate prohibited uses, high-risk systems, transparency, governance and competent authorities. Chile Latin America Legislative proposal The bill would classify systems by risk and prohibit certain unacceptable uses. High-risk systems would face risk, data, documentation, record, transparency and human-oversight requirements. The Senate is still considering the bill and may change its wording and timetable.
Chile · Legislative proposalAfrican Union Continental AI Strategy
African Union Continental Artificial Intelligence Strategy The continental strategy promotes development-oriented and inclusive AI governance, capacity, data foundations, innovation, investment and international cooperation. African Union Africa Policy The strategy sets continental directions for governance, infrastructure, data, talent, research, innovation and investment. Human rights, inclusion, equity, safety and African development needs shape the approach. Member States can use the strategy to develop national policy, institutions and roadmaps.
African Union · PolicySouth Africa Draft AI Policy
Draft National Artificial Intelligence Policy South Africa published a draft national AI policy covering governance, innovation, infrastructure, data, skills and public services. The responsible department withdrew the draft after confirming unreliable references, and this record now documents that policy process. South Africa Africa undefined The draft used common principles and sector collaboration to set a national policy direction. Research, compute, data, talent, public services, inclusion and risk governance were core areas. The withdrawal ended the consultation on this text; future policy should be checked against newly issued government documents.
South Africa · undefinedUNESCO AI Ethics Recommendation
UNESCO Recommendation on the Ethics of Artificial Intelligence The Recommendation gives Member States and AI actors a global ethics framework covering human rights, impact assessment, data governance, the environment, gender, education, labour and public governance. UNESCO International organisations Governance guidance Human rights, dignity, environmental and ecosystem well-being, diversity and inclusion form the value base. The framework promotes ethical impact assessment, oversight, audit, transparency, responsibility and remedy. Policy actions cover data, education, research, culture, labour, health and social well-being.
UNESCO · Governance guidanceUN Resolution on Safe, Secure and Trustworthy AI
United Nations General Assembly Resolution 78/265 on Safe, Secure and Trustworthy Artificial Intelligence The Resolution promotes safe, secure and trustworthy AI for sustainable development and encourages digital inclusion, human-rights protection and international cooperation. United Nations International organisations Policy Promote safe, secure and trustworthy approaches across the AI lifecycle. Respect international law, human rights, privacy, fairness, inclusion and sustainable development. Support capacity building, knowledge sharing, developing-country participation and cross-border cooperation.
United Nations · PolicyG7 Hiroshima AI Code of Conduct
Hiroshima Process International Code of Conduct for Organizations Developing Advanced AI Systems The Code asks organisations developing advanced AI to take lifecycle action on risk identification, testing, incident reporting, security, content authentication, research and international standards. Group of Seven International organisations Governance guidance Identify, assess and mitigate risks during development, deployment and post-deployment operation. Publish information on capability, limitations and appropriate use and operate incident-reporting channels. Protect model weights, data and infrastructure and support generated-content provenance.
Group of Seven · Governance guidanceAI Legal Research Center
Research team and collaboration
TeamLong An Guangzhou Hosts Second AI Internal Sharing Session on AI Agents
On September 2, Long An Guangzhou held the second AI internal sharing session, where lawyers Li Boyang and Zhan Shangli explained practical AI Agent legal tools and office workflows.
2026-09-04A New Journey Begins: Li Boyang Promoted to Senior Partner, Li Dingbang and Liu Xiaoli Promoted to Partners
Recently, Longan Guangzhou announced a new round of internal promotions: Li Boyang has been promoted to Senior Partner, and Li Dingbang and Liu Xiaoli have been promoted to Partners. With years of deep experience in artificial intelligence and data compliance, family wealth management and succession, and criminal defense and civil/commercial dispute resolution, the three lawyers are recognized for their professional expertise and strong track records. The promotions reflect Longan Guangzhou's continued commitment to building a specialized talent pipeline and opening clear career pathways for young lawyers.
2026-09-04Join Us | Case Source Support × AI Empowerment × Special Fund Support: Longan Guangzhou Redefines Lawyer Empowerment
If you hold the ideal of the rule of law and aspire to grow both professionally and strategically; if you pursue excellence and refuse to let your talent be consumed by solitary struggle; if you are looking for a platform that pairs robust enablement with human warmth—Longan Guangzhou is here for you. We sincerely invite like-minded lawyers to join us and build an extraordinary career together.
2026-08-31Longan Guangzhou Partner Yu Yao Shares at Game IP Judicial Protection Symposium
At the recent Game New Business Formats Intellectual Property Judicial Protection Symposium co-hosted by the Guangdong High People's Court and the Guangdong Game Industry Association, Longan Guangzhou partner Yu Yao was invited to attend and deliver professional insights on AI-related legal challenges, gray industry governance, and overseas rights protection.
2026-08-21Longan Guangzhou Hosts AI Legal Sharing Session
On August 12, Beijing Longan (Guangzhou) Law Firm held the first session of its AI series internal sharing event, themed 'From Asking AI to Having AI Deliver', with nearly eighty colleagues attending online and on-site.
2026-08-13Lungan Updates | Lungan Guangzhou joins hands with UK’s Belgravia Law Firm to explore new opportunities in cross-border sanctions compliance and AI regulations cooperation
Recently, Beijing Longan (Guangzhou) Law Firm and the UK Belgravia Law Firm jointly organized a special seminar on cross-border legal services. The event was held successfully and yielded fruitful results. During the seminar, both parties engaged in professional discussions on three key topics: sanctions compliance practices, cross-border case collaboration, and AI regulatory cooperation. They also exchanged practical experiences and explored potential areas for cooperation...
2026-04-21Long'an News | Lawyer Ou Yingshi, a partner in Long'an Guangzhou, has been invited to attend the Hong Kong forum on “Reconstruction of the Underlying Framework in the AI Era and New Paradigms for Going Global”.
Recently, the “Reconstruction of the Underlying Framework and New Paradigms for Going Global in the AI Era” forum, jointly organized by the Tencent Cloud Accelerator and Hong Kong Digital Port, was successfully held at Hong Kong Digital Port. The forum brought together over 200 professionals from industries such as AI, investment, law, and cross-border e-commerce. Partner of Beijing Longan (Guangzhou) Law Firm, and a member of the sanctions and counterfraud commission...
2026-03-27Lawyer Updates | Lawyers Li Boyang and Ye Junxi from Longan Guangzhou were invited to Hunan to conduct specialized training on artificial intelligence in legal practice
Recently, a specialized training on “The Application of AI Tools in Legal Practice (Mediation)” and the 8th Mediation Practitioner Lecture Series of the Changsha Intermediate People’s Court, jointly organized by the Hunan Lawyers Association and the Changsha Intermediate People’s Court, with the cooperation of the Mediation and Arbitration Law Committee and the Corporate Law Committee of the Hunan Lawyers Association, was successfully held in Changsha. This...
2025-10-13Long'an News | Long'an Guangzhou Successfully Hosted Special Event on “AI Empowerment for Young Lawyers and Thinking Logic and Follow-up Strategies in B-Side Scenarios”
On September 17, 2025, a special event titled “AI Empowerment for Young Lawyers and Thinking Patterns and Follow-up Strategies in B-side Scenarios” was successfully held in Longan Guangzhou. The event was co-hosted by the Young Lawyers Working Committee of the Guangzhou Lawyers Association and Longan Guangzhou Law Firm, with the support of Weco Xianxing Law Firm. Ge..., Deputy Director of the Longan Guangzhou Management Committee and Senior Partner, attended the event.
2025-09-17Long'an Honors | Lawyers Li Boyang and Ye Junxi from Long'an Guangzhou won the second prize in the first AI Innovation Competition for the Lawyer Industry in Guangdong Province.
On September 8th, the final round of the First Guangdong Lawyers Industry AI Innovation Competition, organized by the Guangdong Lawyers Association, hosted by the Foshan Lawyers Association and the Informatization Work Committee of the Guangdong Lawyers Association, and supported by the Foshan Judicial Bureau, successfully concluded in Foshan. 15 outstanding teams competed fiercely in the final, focusing on innovative achievements that integrate AI and law. North...
2025-09-09Luangan Honors | Luangan Guangzhou Yunshan Team and AI Research and Development Team won the first prize in the 2025 “Luangan Cup” National AI Legal Intelligent Agent Competition.
On August 16, 2025, the final of the 2025 “Longan Cup” National AI Legal AI Agent Competition, organized by Longan Law Firm, co-organized by WELEGAL Law Alliance and Mista Technology, and hosted by Beijing Longan (Guangzhou) Law Firm, was held grandly at the Marriott Hotel in Guangzhou. This competition included pre-event activities, a launch ceremony, specialized training, and...
2025-08-18Lungan Honors | Lawyers Li Boyang and Ye Junxi from Lungan Guangzhou were successfully promoted to the final of the first Guangdong Province Lawyer Industry AI Innovation Competition!
On July 13, the second round of the First Guangdong Province Lawyer Industry AI Innovation Competition was successfully held in Zhuhai. 30 participating teams competed in innovative applications of AI technology in legal services across five practical areas: legal representation strategies, the use of legal documents, case file organization, legal education and promotion, and law firm branding. In the end, Li... from Beijing Longan (Guangzhou) Law Firm won the competition.
2025-07-14Long'an Cup, but not just Long'an! Registration for the 2025 “Long'an Cup” National AI Legal AI Contest has begun.
The disruptive AI technologies in the National AI Legal Intelligent Agent Competition are driving a revolution in the efficiency of legal services and their accessibility for all. This is leading the industry structure toward a dual evolution of “intelligence + professionalism”, and enabling lawyers to transform into strategic advisors and providers of innovative solutions. In this context, Longan Law Firm, along with WELEGAL Law Alliance, aims to explore “AI + law...
2025-05-08Long'an Updates | Long'an Guangzhou Successfully Hosted a Special Sharing Event on “How Lawyers Can Use DeepSeek to Handle Cases Efficiently”!
On February 13, 2025, in order to better understand the application of artificial intelligence in legal services and to enhance lawyers' knowledge and interaction with AI tools, Longan Guangzhou Law Firm, in collaboration with the Longan Bay Artificial Intelligence Law Research Center, organized a special sharing event titled “How Lawyers Can Use DeepSeek to Handle Cases Efficiently”. This event was organized by Longan…
2025-02-13Long'an News | Long'an Guangzhou lawyers are invited to attend NIO Radio 2024 “Annual Sound Creator Conference” and share insights on AI creation compliance.
On April 13, 2024, at the invitation of NIO Car, lawyers Zeng Yue and Cai Mengfei from Beijing Longan (Guangzhou) Law Firm attended the NIO Radio 2024 “Annual Voice Creators Conference”. They shared relevant knowledge on compliance and copyright issues related to using AIGC in creative work with numerous creators present. This voice creation...
2024-04-19New Book Release | In the Sora Era, How Legal Professionals Can Avoid Being Eliminated by AI
In the Sora era, how can legal professionals avoid being eliminated by AI? Recently, several lawyers from Longan (Guangzhou) Law Firm in Beijing provided their answers. The book “Guidelines for Legal Professionals on Using ChatGPT” was written by lawyers from the Longan Bay Artificial Intelligence Law Research Center and Tang Jianjie.
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