The 2024 Legal AI Retrospective: Key Lessons from the Past Year
The State of Legal AI
You can for this published on December 12th 2024, or find a link to each of the 92 sections as individual blog posts in the section 'Full list of sections' below.
I. Executive Summary
This report is the result of the extensive research, feedback, conversations and direct input from industry leaders. We extend our sincere gratitude to all who have contributed.
Where can I get the report?
You can download
Why another report on Legal AI?
We recognize that the majority of research into Legal AI falls into one of three categories.
• Written by legal journalists (simplified - often lacking in technical depth)
• Written by legal vendors (biased - often highlighting their own successes)
• Written by scholars, engineers and researchers - (academic - often more theoretical than practical)
This leaves a gap for deeper, unbiased, and more practice-oriented reporting, which we have worked hard
to fill.
Who should read this report?
This report provides in-house legal teams and law firms—particularly those in corporate and commercial law—with a valuable resource to navigate the rapidly evolving landscape of Legal AI
Our unique approach
As we are one of the longstanding vendors in this space, we have taken an unusual approach:
• We call out and applaud our competitors for their successes! (A rising tide lifts all boats, after all).
• We don't try and sell our products or services to you at any point.
(We are here to learn, just like everyone else).
Rather than attempting to distill the complex and far-reaching impact of AI into a few key findings, we instead invite you to explore the full breadth of 200+ insights, 100+ topics, 60+ cited studies and 30+
comments from industry leaders. All the references featured throughout this 50-page report are from 2024 where possible, and 2023 otherwise.
Report Structure
1. Key Areas of Legal AI Development, and their practical applications.
2. The Emerging Trends and Technologies, and their current limitations for legal use cases
(also, some prompt engineering tips for you).
3. Pros and Cons of Legal AI by Legal Team Type
(in-house counsel, Big Law, and small/solo law firms).
Our sincere hope
By engaging with the full range of topics and perspectives presented in this report, you will gain practical insights into implementing Legal AI effectively within your organization. You'll stay ahead of emerging trends, and understand the specific advantages and challenges to your legal team.
If you would like to join our panel of experts and contribute to upcoming reports, please reach out to us via community@genieai.co.
Sincerely,
Alex Denne, Head of Growth @ Ƶ
“AI's impact on legal practice and operations is undeniable and
transformative. It's not just about automating tasks; it's about leveraging technology to drive growth, enhance client services, and modernize law firms. As our law firm clients integrate AI into our strategic processes, we see significant improvements in efficiency and profitability. This is why I advocate for law firms to proactively evaluate and leverage these technologies. The future of legal
services is shaped by our ability to adapt and innovate, ensuring that we not only meet but exceed the evolving demands of our
clients and the market.”
Dan Safran, President and CEO, Unbiased Consulting LLC;
Adjunct, University of Illinois College of Law, USA
Full list of sections
- The 2024 Legal AI Retrospective: Key Lessons from the Past Year
- Current state of Legal AI
- Brief history of AI in the legal sector
- Key Challenges and 2025 Outlook
- Key Areas of Legal AI Development
- Legal Chatbots and Client Engagement
- Key Applications of Legal AI
- Document review and contract analysis
- AI-Driven Legal Research and Knowledge Management
- AI in Due diligence and compliance
- Natural Language Processing in Legal Text Analysis
- AI in Contract Analysis
- AI-Enhanced Risk Assessment and Management
- Automated Regulatory Compliance Monitoring
- AI in Summarizing Legislation
- AI for Reacting to Legislative Changes
- AI for Data Privacy and Security Compliance
- Automated Due Diligence Reporting
- Automated trademark infringement monitoring
- AI-Assisted Legal Communications Drafting
- AI in Legal and contract drafting
- AI-Assisted Document Drafting
- Open Access and Open source Legal AI
- AI Contract Generators
- Multilingual Contract Drafting with AI
- AI-enhanced Contextual Clause Suggestions
- AI in Data Governance for Legal
- Changing of the guard
- Emerging Legal Editors and Drafting Tools
- Compliance Decisions
- IP Risk Assessment in Data Flows
- Data Usage Throughout the Legal Value Chain
- Multimodal AI Models for Legal
- Ethical AI and Bias Mitigation in Legal
- Large Language Models in Legal AI
- Multilingual NLP for Legal AI
- Efficient Training and Deployment of Legal AI
- Explainable AI in Legal Decision-Making
- Creating Explanations for New Types of Legal AI
- Evaluating XAI Methods in Legal AI
- Transformer Architecture Dominance in Legal NLP
- Supporting Multi-Dimensional Explainability in Legal AI
- Supporting Human-Centered Explanations in Legal AI
- Adjusting XAI Methods for Different Legal Contexts
- Mitigating Negative Impacts of XAI in Legal
- Improving Societal Impact of Legal XAI
- AI-Enhanced Contract Drafting, Review, and Analysis
- Contract Law and Democratizing of Market Standards
- Standardization of Contract Terms and Clauses with AI
- Available Legal AI Datasets
- Improving Current XAI Methods for Legal AI
- Emerging Trends and Technologies
- Defining Accuracy in Legal AI
- Challenges to the adoption of AI in contract law
- Prompt Engineering for Legal AI
- Advantages of Legal AI for In-house Teams
- Increased Efficiency: Time Savings for In-house Legal
- AI Becomes an In-house Alternative Legal Service Provider
- Increased Accuracy: More Data-driven Decisions In-house
- In-house Legal Teams: The Frontier of Legal AI Innovation
- AI Empowering Strategic Risk Management In-house
- Junior In-house Legal Roles Evolve into "AI Wranglers"
- Data Privacy and Security Concerns with Legal AI In-house
- Concerns and Limitations of Legal AI for In-house Teams
- Potential for Bias and Errors in Legal AI In-house
- Ethical Considerations and Accountability of Legal AI In-house
- AI Hallucinations and Reliability Issues In-house
- Advantages of Legal AI for Biglaw Firms
- Enhanced Client Value Through AI-Driven Productization at Biglaw
- Balancing Legal AI Adoption with Caution In-house
- Potential for Higher Margins and Competitive Advantage with AI at Biglaw
- AI Customization and Localization Opportunities for Biglaw
- In-House Development of Specialized AI Applications at Biglaw
- Ethical Implications of AI and Time Tracking at Biglaw
- Concerns and Limitations of Legal AI for Biglaw Firms
- Data Security and Client Confidentiality Concerns with Legal AI at Biglaw
- AI Enabling Product-Led Growth and Democratization of Legal Services at Biglaw
- Accuracy and Reliability of AI-Generated Legal Content at Biglaw
- AI Hallucinations and False Information in Legal AI at Biglaw
- Over Reliance on AI and Skill Atrophy at Biglaw
- Cultural Resistance and Shadow AI Usage at Biglaw
- Advantages of Legal AI for Small Law Firms and Sole Practitioners
- AI Enabling Expansion into New Practice Areas for Small Law Firms
- Enhanced Research Capabilities with AI for Small Law Firms
- Customized Document Generation with AI for Small Law Firms
- AI as Cost-Effective Alternative to Additional Staff for Small Law Firms
- Increased Productivity and Client Capacity with AI for Small Law Firms
- Concerns and Limitations of Legal AI for Small Law Firms and Sole Practitioners
- Limited AI Customization for Niche Practice Areas at Small Law Firms
- High Initial Costs and Implementation Challenges of AI for Small Law Firms
- Client Perception and Trust Issues with AI at Small Law Firms
- Industry-wide challenges
Interested in joining our team? Explore career opportunities with us and be a part of the future of Legal AI.