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What our research covers

We have been studying the effects of generative AI on the legal industry since our company was founded in 2017. Here's a brief summary of what we've worked on:

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De-identification of Contracts (Collaboration with Barclays, Withers, the University of Oxford and Imperial College London)

UKRI awarded a £1.5M grant to ��������Ƶ’s consortium - Barclays, Withers, the University of Oxford, and Imperial College London - to answer two of the biggest challenges to the adoption of AI in Legal services:

• access to confidential data
• understanding the decisions machine learning models make

The project aimed to answer these challenges with the combined capabilities of

• ��������Ƶ’s Legal AI
• Oxford University’s research into robust recurrent neural networks to explain the accuracy of machine learning decisions
• Imperial College’s research into the de-identification of legal contracts to anonymise confidential data while retaining critical information.

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The State of Legal AI

You can for this published on December 12th 2024, or find one of the 92 sections which interests you most using the links below.

Full list of sections

1. The 2024 Legal AI Retrospective:
Key Lessons from the Past Year
2. Current state of Legal AI
3. Brief history of AI in the legal sector
4. Key Challenges and 2025 Outlook
5. Key Areas of Legal AI Development
6. Legal Chatbots and Client Engagement
7. Key Applications of Legal AI
8. Document review and contract analysis
9. AI-Driven Legal Research and Knowledge Management
10. AI in Due diligence and compliance
11. Natural Language Processing in Legal Text Analysis
12. AI in Contract Analysis
13. AI-Enhanced Risk Assessment and Management
14. Automated Regulatory Compliance Monitoring
15. AI in Summarizing Legislation
16. AI for Reacting to Legislative Changes
17. AI for Data Privacy and Security Compliance
18. Automated Due Diligence Reporting
19. Automated trademark infringement monitoring
20. AI-Assisted Legal Communications Drafting
21. AI in Legal and contract drafting
22. AI-Assisted Document Drafting
23. Open Access and Open source Legal AI
24. AI Contract Generators
25. Multilingual Contract Drafting with AI
26. AI-enhanced Contextual Clause Suggestions
27. AI in Data Governance for Legal
28. Changing of the guard
29. Emerging Legal Editors and Drafting Tools
30. Compliance Decisions
31. IP Risk Assessment in Data Flows
32. Data Usage Throughout the Legal Value Chain
33. Multimodal AI Models for Legal
34. Ethical AI and Bias Mitigation in Legal
35. Large Language Models in Legal AI
36. Multilingual NLP for Legal AI
37. Efficient Training and Deployment of Legal AI
38. Explainable AI in Legal Decision-Making
39. Creating Explanations for New Types of Legal AI
40. Evaluating XAI Methods in Legal AI
41. Transformer Architecture Dominance in Legal NLP
42. Supporting Multi-Dimensional Explainability in Legal AI
43. Supporting Human-Centered Explanations in Legal AI
44. Adjusting XAI Methods for Different Legal Contexts
45. Mitigating Negative Impacts of XAI in Legal
46. Improving Societal Impact of Legal XAI
47. AI-Enhanced Contract Drafting, Review, and Analysis
48. Contract Law and Democratizing of Market Standards
49. Standardization of Contract Terms and Clauses with AI
50. Available Legal AI Datasets
51. Improving Current XAI Methods for Legal AI
52. Emerging Trends and Technologies
53. Defining Accuracy in Legal AI
54. Challenges to the adoption of AI in contract law
55. Prompt Engineering for Legal AI
56. Advantages of Legal AI for In-house Teams
57. Increased Efficiency: Time Savings for In-house Legal
58. AI Becomes an In-house Alternative Legal Service Provider
59. Increased Accuracy: More Data-driven Decisions In-house
60. In-house Legal Teams: The Frontier of Legal AI Innovation
61. AI Empowering Strategic Risk Management In-house
62. Junior In-house Legal Roles Evolve into "AI Wranglers"
63. Data Privacy and Security Concerns with Legal AI In-house
64. Concerns and Limitations of Legal AI for In-house Teams
65. Potential for Bias and Errors in Legal AI In-house
66. Ethical Considerations and Accountability of Legal AI In-house
67. AI Hallucinations and Reliability Issues In-house
68. Advantages of Legal AI for Biglaw Firms
69. Enhanced Client Value Through AI-Driven Productization at Biglaw
70. Balancing Legal AI Adoption with Caution In-house
71. Potential for Higher Margins and Competitive Advantage with AI at Biglaw
72. AI Customization and Localization Opportunities for Biglaw
73. In-House Development of Specialized AI Applications at Biglaw
74. Ethical Implications of AI and Time Tracking at Biglaw
75. Concerns and Limitations of Legal AI for Biglaw Firms
76. Data Security and Client Confidentiality Concerns with Legal AI at Biglaw
77. AI Enabling Product-Led Growth and Democratization of Legal Services at Biglaw
78. Accuracy and Reliability of AI-Generated Legal Content at Biglaw
79. AI Hallucinations and False Information in Legal AI at Biglaw
80. Over Reliance on AI and Skill Atrophy at Biglaw
81. Cultural Resistance and Shadow AI Usage at Biglaw
82. Advantages of Legal AI for Small Law Firms and Sole Practitioners
83. AI Enabling Expansion into New Practice Areas for Small Law Firms
84. Enhanced Research Capabilities with AI for Small Law Firms
85. Customized Document Generation with AI for Small Law Firms
86. AI as Cost-Effective Alternative to Additional Staff for Small Law Firms
87. Increased Productivity and Client Capacity with AI for Small Law Firms
88. Concerns and Limitations of Legal AI for Small Law Firms and Sole Practitioners
89. Limited AI Customization for Niche Practice Areas at Small Law Firms
90. High Initial Costs and Implementation Challenges of AI for Small Law Firms
91. Client Perception and Trust Issues with AI at Small Law Firms
92. Industry-wide challenges

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‍Comparisons of Legal AI tools

We haven't published these yet, but we've carried out detailed analysis on the market for Legal AI tools. We researched 80+ legaltech tools claiming to offer AI services, and compare them side-by-side.

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Much more to come

4 years before the world had it's ChatGPT moment, our Co-founder and CEO, Rafie Faruq was writing his thesis on Generative AI. A lot has changed since then, and we have a lot of unpublished research on effective prompting of Legal AI, anonymisation, document transformation, AI negotiation, and much more.

We apply first-principles thinking within our Senior Machine Learning team here, tied to our relentless pursuit of delivering value to our customers.

Use the links below to follow us on our social channels to stay informed on new research and developments.
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Contact us if you'd like more information on any of the research mentioned on this page. community@genieai.co (Alex Denne)