Introduction: AI Knocks on the Door of the Legal Profession

As of 2026, artificial intelligence technology is no longer a story about the future. In particular, Claude AI OPUS 4.6, developed by Anthropic, has captured the attention of legal professionals worldwide with its remarkable reasoning capabilities and sophisticated language comprehension. OPUS 4.6 features dramatically improved logical thinking, long-context retention, and multilingual processing compared to its predecessors, making the potential for legal applications greater than ever before.

The Korean legal market is a massive professional services market with approximately 30,000 practicing lawyers. From major law firms to solo practitioners, the spectrum of legal services is broad, but all share a common investment of significant time in labor-intensive tasks such as large-scale document processing, case law research, and legal analysis. According to a 2025 survey by the Korean Bar Association, approximately 35-40% of lawyers' working hours are devoted to basic research and document review -- an area ripe for AI-driven innovation.

However, the use of AI in the legal field requires particular caution. The phenomenon of "hallucination" -- where AI confidently cites non-existent case law as if it were real -- can pose a critical risk to legal professionals. This article comprehensively examines the specific impact of Claude AI OPUS 4.6 on Korean lawyers' work, the causes of and prevention strategies for AI hallucination, and practical methods for utilizing Anthropic's team collaboration platform, Claude Cowork, in law firm operations.

1. The Impact of Claude AI OPUS 4.6 on Korean Lawyers

1.1 A Paradigm Shift in Legal Research

Legal research is the foundation of a lawyer's work and the area where AI can bring the most dramatic changes. Claude AI OPUS 4.6 has been trained on a vast body of Korean legal knowledge, including the Korean legal system, Supreme Court precedents, Constitutional Court decisions, and lower court rulings, fundamentally transforming lawyers' research workflows.

  • Intelligent Case Law Search: Moving beyond traditional keyword-based searches, OPUS 4.6 can suggest relevant case law through inference when you describe the context of a case and legal issues in natural language. For example, entering "deposit refund dispute after tacit renewal in a lease agreement" yields a systematic compilation of relevant precedents related to Article 639 of the Civil Code and the Housing Lease Protection Act.
  • Revolutionary Speed in Legal Literature Analysis: Tasks that once took a junior lawyer several days to review hundreds of pages of case law can now be classified and summarized by key issues within minutes by OPUS 4.6. This goes beyond mere speed improvement, enhancing both the comprehensiveness and accuracy of analysis.
  • Comparative International Legal Analysis: OPUS 4.6's multilingual capabilities greatly assist Korean lawyers in conducting comparative analysis of legal systems and precedents from the United States, Japan, Europe, and beyond. This becomes a decisive competitive advantage in international transactions, overseas investments, and international arbitration.

1.2 Transformation of Document Drafting and Review

Legal document drafting is one of the core functions of a lawyer's work, and Claude AI OPUS 4.6 is bringing meaningful changes to this area as well.

  • Automated Contract Drafting: By inputting the key terms of a transaction (parties, amounts, duration, obligations, etc.), OPUS 4.6 generates a contract draft tailored to the specific transaction type. While final review and revision remain the lawyer's responsibility, the time required for initial drafting can be reduced by 70-80%.
  • Generation of Complaints, Answers, and Legal Briefs: When provided with a case summary and legal issues, the system generates structured drafts of court filings. It demonstrates particularly high efficiency with repetitive standardized documents.
  • Existing Contract Review and Risk Analysis: When contracts spanning dozens of pages are uploaded, the system automatically identifies potential risk clauses, unfavorable terms, and missing protective provisions, suggesting directions for improvement.
  • Structuring Legal Opinions: When drafting opinions on complex legal issues, it provides a framework that systematically organizes relevant statutes, precedents, and legal scholarship, allowing lawyers to focus on professional judgment.

1.3 Restructuring of Legal Workflow

The emergence of Claude AI OPUS 4.6 is reshaping the very structure of law firm operations. This represents not just the introduction of a new tool, but a fundamental paradigm shift in the legal services industry.

  • Evolving Role of Junior Lawyers: As AI takes over case law research and document drafting -- traditionally the primary tasks of junior lawyers -- they are now required to develop higher-order competencies such as AI output verification, client communication, and strategic thinking. This cascading effect extends to changes in how legal professionals are trained.
  • The AI Gap Between Large and Small Firms: Large law firms are rapidly adopting AI systems backed by dedicated IT teams and budgets, while smaller practices may face slower adoption due to cost and technical barriers. However, cloud-based AI services like Claude AI can help bridge this gap.
  • Democratization of Legal Services: The efficiency gains from AI-powered legal services can ultimately reduce the cost of legal services, promoting a "democratization of law" where more citizens can access quality legal representation.
  • Changes in Fee Structures: The traditional hourly billing model (time billing) conflicts with the efficiency gains brought by AI. Performance-based and project-based fee models are expected to become increasingly prevalent.

1.4 Current State of AI Adoption in the Korean Legal Profession

AI adoption is accelerating across the Korean legal profession:

  • Growth of Legal Tech Startups: Korean legal tech companies such as LawTalk, IntelliCon, and LegalMind are expanding the market by offering AI-based legal services. As of 2025, the domestic legal tech market is estimated at approximately 500 billion KRW (roughly 380 million USD), growing at over 30% annually.
  • Korean Bar Association AI Guidelines: The Korean Bar Association published its "Ethical Guidelines for AI-Powered Legal Services" in 2025, establishing ethical standards and quality management measures for lawyers using AI.
  • Digital Transformation of the Court Administration: The National Court Administration has been progressively introducing AI-powered judgment analysis systems and intelligent case assignment systems, contributing to improved efficiency across the entire judiciary.

2. The AI Hallucination Problem and Prevention Strategies

2.1 What Is Hallucination?

AI Hallucination refers to the phenomenon where an AI model confidently generates information that does not actually exist as if it were factual. In the legal field, this problem is particularly critical. If AI cites non-existent precedents, presents incorrect legal provisions, or constructs fictitious legal reasoning, and these are directly incorporated into legal documents, it can seriously damage both the lawyer's professional credibility and the client's interests.

Real Case: Mata v. Avianca (2023, United States)
In New York, attorney Steven Schwartz used ChatGPT to prepare court filings, only for it to be revealed that all six cases cited by the AI were entirely fictitious. The attorney faced sanctions from the court, and the incident became a global wake-up call about the dangers of AI hallucination in legal practice.

2.2 Technical Causes of Hallucination

Understanding the fundamental causes of AI hallucination enables more effective prevention strategies:

  • Probabilistic Text Generation Mechanism: Large Language Models (LLMs) fundamentally generate text by predicting the "most probable next token (word)." In this process, they can produce information that is statistically plausible but factually incorrect. The model's internal mechanism for distinguishing "facts" from "plausible fiction" is not perfect.
  • Training Data Limitations: AI models are trained on data up to a specific point in time. Consequently, they may fail to provide accurate information about recent legal amendments, recent case law, or newly enacted regulations. Additionally, errors or biases present in the training data may be reproduced.
  • Context Window Limitations and Information Distortion: When processing very long conversations or complex legal documents, limitations in the context window may prevent previously provided information from being accurately maintained. While OPUS 4.6 has significantly improved this issue, it has not been entirely resolved.
  • Insufficient Knowledge Boundary Recognition: When an AI model fails to accurately recognize what it does not know, it may present uncertain information in a confident tone. This is particularly dangerous in the legal field.

2.3 Claude AI's Hallucination Prevention Technology

Anthropic has applied several technical approaches to minimize the hallucination problem during the development of Claude AI:

  • Constitutional AI Approach: Claude was trained using Anthropic's proprietary Constitutional AI methodology. This includes a self-improvement process where the AI evaluates and corrects its own outputs according to ethical and factual criteria. In a legal context, this effectively suppresses the AI from presenting uncertain legal information in definitive terms.
  • Uncertainty Expression Mechanism: Claude OPUS 4.6 is designed to actively use expressions such as "this may be the case," "verification is recommended," and "this information may not be current" when dealing with uncertain information. These provide crucial signals for users to assess the reliability of AI outputs.
  • Refusal and Limitation Acknowledgment: Rather than pretending to know what it does not, the model has strengthened behavioral patterns that clearly acknowledge its knowledge limitations and recommend additional verification.
  • OPUS 4.6's Improved Factual Accuracy: OPUS 4.6 has achieved significantly improved factual accuracy compared to previous versions, with particularly notable improvements in structured knowledge (legal provisions, historical facts, etc.). According to Anthropic's internal benchmarks, accuracy on legal-related questions has improved by approximately 25% compared to previous models.

2.4 Hallucination Prevention Strategies for Legal Practitioners

Despite Claude AI's technical improvements, the use of AI in legal practice must always be accompanied by systematic verification processes:

5-Step Hallucination Prevention Checklist
1. Cross-verify all case numbers and legal provisions in AI output against legal databases (Supreme Court Comprehensive Legal Information System, LawNB, etc.)
2. Verify the accuracy of specific factual details such as dates, party names, and ruling summaries
3. Confirm whether statutes cited by the AI are currently in effect (check for amendments or repeals)
4. Independently evaluate the validity of the logical reasoning process
5. Mandatory review by an experienced attorney before final document submission
  • Utilizing RAG (Retrieval-Augmented Generation): Rather than relying solely on its own training data, applying the RAG approach -- where the AI retrieves information from trusted legal databases in real-time before generating responses -- can significantly reduce hallucination. Using Claude integrated with legal databases is the ideal setup.
  • Prompt Engineering Techniques: Including specific instructions when querying the AI, such as "always cite your sources," "indicate when information is uncertain," and "limit your response to Korean law," can reduce the probability of hallucination.
  • Step-by-Step Verification Approach: Rather than using AI output as a final product in one shot, it is important to progressively refine quality through the stages of research, draft generation, fact-checking, revision, and expert review.
  • Cross-Verification with Multiple AI Systems: For critical legal research, it is advisable to compare and verify Claude's results against those from other AI models or traditional legal databases.

3. Innovating Legal Work with Claude Cowork

3.1 What Is Claude Cowork?

Claude Cowork is a team collaboration-based AI platform provided by Anthropic. Unlike the individual version of Claude, Cowork is designed for organization-level AI utilization, offering features such as shared AI conversations among team members, project-based knowledge management, and role-based access control.

Cowork is particularly valuable for law firms because it aligns perfectly with the collaborative nature of legal work, where multiple attorneys work together on a single case. It eliminates the inefficiency of manually sharing individual AI conversation results, allowing the entire team to collaborate within a unified AI workspace.

The key differentiators of Cowork include:

  • Shared Project Spaces: Create projects for each case and manage related materials, AI conversation histories, and analysis results in one place
  • Team AI Conversations: Team members can participate in the same AI conversation to discuss and analyze legal issues in real-time
  • Knowledge Accumulation: AI analysis results from past projects are accumulated as organizational knowledge assets, available for reference when handling similar cases
  • Audit Trail: All AI usage records are preserved, enabling post-hoc verification of legal ethics compliance

3.2 Cowork Use Cases in Law Firms

Here are specific scenarios for utilizing Claude Cowork in law firm settings:

  • Case Analysis Workflow: When a new case is accepted, a project is created in Cowork and the case summary is entered. Claude automatically identifies legal issues and suggests relevant statutes and precedents, creating a collaborative flow where the assigned attorney team reviews and refines these findings.
  • Team-Based Legal Research Collaboration: In complex cases where multiple attorneys each handle different issues, integrating their individual research results and AI analyses in Cowork's shared space prevents duplicate work and maximizes synergy.
  • Automated Client Consultation Preparation: Before client meetings, attorneys can use Cowork with AI to organize the latest developments, anticipated issues, and strategic options related to the case, preparing systematic consultation materials.
  • Litigation Strategy Brainstorming: Team members can use Cowork with Claude to review various litigation strategies and simulate potential opposing arguments and counterarguments in advance.

3.3 Practical Application Guide: Step-by-Step Implementation

Here is a guide to the specific steps for adopting and applying Claude Cowork in law firm practice:

5 Steps to Implementing Claude Cowork in Legal Practice

Step 1: Enter Case Summary and Organize Issues - Input the basic facts of the case, party information, and client requests into a Cowork project. Claude automatically identifies initial legal issues, and the team reviews these to finalize the issue list.

Step 2: AI-Powered Search for Relevant Precedents and Statutes - For each confirmed issue, request Claude to search for relevant precedents and statutes. Specify conditions such as "focusing on Supreme Court precedents," "within the past 5 years," and "including lower court decisions."

Step 3: Generate Legal Opinion Draft - Based on the collected precedents and statutes, request Claude to draft a legal opinion. Specifying the structure -- introduction, issue-by-issue analysis, and conclusion -- yields a more systematic draft.

Step 4: AI-Assisted Team Review and Feedback - Team members jointly review the generated draft in Cowork. Each team member verifies the accuracy of the AI analysis in their area of expertise and leaves comments on items that need supplementation.

Step 5: Finalize the Document - Incorporate team review feedback to complete the final document. During this process, apply the hallucination prevention checklist to verify the accuracy of all citations.

3.4 Security and Confidentiality Considerations

One of the most critical considerations when using AI in legal work is security and confidentiality:

  • Attorney-Client Privilege: The duty of confidentiality under Article 26 of the Attorney-at-Law Act applies equally when using AI tools. When entering client information into an AI platform, it is essential to verify that the platform's data processing policies are compatible with confidentiality obligations.
  • Cowork Security Features: Anthropic has implemented SOC 2 Type II certification, data encryption (both in transit and at rest), and a policy of not using user data for AI model training for enterprise Claude Cowork. These measures substantially meet law firms' security requirements.
  • Personal Information Protection Act Compliance: When entering client personal information into AI, the provisions of the Personal Information Protection Act must be observed. Pseudonymization, the principle of minimum collection, and prohibition of use beyond the stated purpose must be rigorously applied.
  • Establishing Internal AI Usage Guidelines: It is important for law firms to establish their own AI usage policies, clearly defining what types of information may be entered into AI, under what circumstances AI usage is restricted, and related matters.

4. Future Outlook: A Korean Legal Profession Coexisting with AI

4.1 Redefining the Role of Lawyers

With the emergence of advanced AI like Claude AI OPUS 4.6, the role of lawyers is transitioning from "collectors and processors of legal information" to "architects of legal strategy and AI supervisors":

  • AI Supervisor: Lawyers serve as supervisors who evaluate the quality of AI-generated legal analyses and documents, verify their accuracy, and render final legal judgments. This is a new competency that simultaneously requires deep understanding of AI and legal expertise.
  • Creative Legal Strategist: As routine research and document drafting are delegated to AI, lawyers can invest more time in devising creative solutions to complex legal problems and developing unprecedented new legal theories.
  • Ethical Judgment and Human Empathy: The most essential value of lawyers that AI cannot replace is ethical judgment and human empathy toward clients. Law is not merely the application of rules but a process of realizing justice in human society, and the role of human lawyers in this process will become even more important.

4.2 The Direction of Change in Legal Education

To train lawyers for the AI era, fundamental changes in legal education are necessary:

  • AI Literacy Education: Law school curricula must include mandatory education on AI principles, applications, and limitations. The introduction of AI proficiency assessment components in the bar examination should also be considered.
  • AI Legal Ethics: Specialized education on ethical issues in AI-powered legal services (errors caused by hallucination, bias, privacy breaches, etc.) is essential.
  • Practice-Oriented AI Training: Beyond theoretical education, practical training courses should be introduced that cover AI-assisted research, document drafting, and strategy development using real legal cases.

4.3 Institutional Challenges

There are also significant institutional challenges to address for the coexistence of AI and law:

  • Regulatory Framework for AI-Powered Legal Services: As AI becomes more deeply involved in legal services, a clear regulatory framework is needed to define the legal status of AI, liability attribution, and quality standards.
  • Attorney-at-Law Act Amendment Discussions: The current Attorney-at-Law Act was enacted at a time when AI participation in legal work was not anticipated. Legal discussions are needed regarding the relationship between the prohibition of non-attorney legal practice (Article 109 of the Attorney-at-Law Act) and AI, as well as the scope of legal services delivered through AI assistance.
  • Legal Validity of AI-Generated Legal Documents: Legal standards must be established regarding the legal validity of AI-drafted legal documents (contracts, opinions, etc.) and the attribution of liability when errors occur.
  • Establishment of an AI Ethics Committee: A dedicated body within the legal profession is needed to establish and monitor ethical standards for AI utilization.

Conclusion: Technology as the Tool, Justice as the Goal

The emergence of Claude AI OPUS 4.6 is bringing unprecedented change to the Korean legal profession. Innovation in legal research, automation of document drafting, and restructuring of workflows are already underway, and this trend will only accelerate. However, such technological progress is a double-edged sword. AI hallucination is a particularly dangerous pitfall in the legal field, and mastery of systematic verification processes and prompt engineering techniques to prevent it is becoming an essential competency for modern lawyers.

Claude Cowork is a powerful platform that can elevate AI utilization from individual effort to organizational capability. By systematically integrating AI into team-based legal work, it is possible to enhance both the quality and efficiency of legal services simultaneously. However, it must always be remembered that the security of client information and adherence to legal ethics are non-negotiable principles under any circumstances.

Ultimately, AI is not a replacement for lawyers but a tool that amplifies their capabilities. Using technology as a tool while keeping justice as the goal -- this is the most important principle that Korean lawyers must uphold in the AI era. Law exists to maintain order in human society and to realize justice, and this fundamental mission cannot be fulfilled by even the most advanced AI. Lawyers in the AI era must find a wise balance between technology and humanity, efficiency and ethics -- and at that balance point, a new future for the Korean legal profession will unfold.