Generative AI in LegalTech: Automating Document Review and Contract Analysis

A sub-discipline of the Generative AI movement is the creation of new content. Lawyers can now use advanced algorithms and machine learning to automate everyday tasks and improve decision-making processes (and, thus, the quality of services).

The global legal tech market was valued at $27.1 billion in 2022 and is expected to grow to $44 billion by 2028, driven by advancements in AI and automation technologies.

What is LegalTech?

LegalTech is the portmanteau of “legal” and “technology.” This would include everything from legal software to artificial intelligence in the age of the legal industry that looks at work amidst such developments, heightening efficiency and costs while raising the bar on the quality of services delivered in a legal context.

Why could Generative AI be a game-changer for the legal tech industry?

Automation of routine tasks: Because AI can automate routine tasks such as contract review, document analysis, or legal research, lawyers can focus on more complex and strategic work.

LegalTech Research Improvement: AI can scan any amount of data and understand its relevance to case law, thereby giving the lawyer a better insight into how to build a stronger case.

This improves lawyers’ decision-making capability because AI algorithms can analyze data to find patterns and trends that point to possible dangers.

Client Satisfaction: AI-based chatbots and virtual assistants provide fast and accurate legal tech advice, ensuring improved client satisfaction. If the legal profession embraced generative AI, increased efficiency, and provided better-quality services to its clients, that would unlock new opportunities.

Key Techniques

Generative Adversarial Networks
GANs are a compelling technique to generate realistic and diverse data. In the context of LegalTech, GANs are used for the following critical applications:

1. Generate Synthetic Legal Documents: generating almost actual legal contracts, agreements, and other documents to train models.
   
2. Data Augmentation: expanding a limited dataset by creating synthetic data to improve the model’s performance.
3. 
   Anomaly Detection: identification of anomalies within the legal texts, such as fraudulent contracts or clause non-compliance.

Recurrent Neural Networks (RNNs)

• RNNs are a neural network designed to process sequential data like text. Applications of RNNs in LegalTech include:

• Summarizing text documents that are long and full of judicial language into summaries
  Clause identification/extraction within a contract End.

• Predictive Legal Analysis: This uses history and current trends to predict legal outcomes.

Transformers

Transformers are a new class of robust architectures for neural networks that have revolutionized natural language processing. It can be used in LegalTech for:

• Document Classification: It will classify the documents according to their intent and content. Information Extraction: In this, one will extract critical information such as dates, names, and amounts from legal documents.
  
• Legal Question Answering: Answer legal queries by searching large legal databases.

These methods demonstrate how generative AI can significantly increase the accuracy and efficiency of legal procedures, allowing legal professionals to make the most appropriate decisions and provide their clients with better services.

Generative AI in LegalTech

It is one of the smarter subsets of AI channeled into creating new things that change the character of the legal tech industry. Generating attorneys works efficiently by automating routine tasks while providing insightful value.

A 2022 survey by Gartner revealed that 20% of corporate legal departments have already implemented AI tools for document review and legal tech research, with another 40% planning to adopt AI by 2025.

Document Review and Analysis

Reviewing and analyzing documents is one of the most essential uses of generative AI in legal technology.

• Contract Analysis: AI-based solutions can analyze a contract in just a few seconds, extract the key clauses, and identify likely risks. Lawyers save time and run less risk of errors.
  
• Due Diligence: Generative AI can automate the process of due diligence on many documents, review them for inclusions, extract relevant information, and raise potential issues.
  
• State-of-the-art tools for lawyers to do comprehensive legal research, especially using AI, analyze cases’ law and legal precedents for relevant information, and summarize complex documentation.
  

Contract Drafting and Negotiation

Generative AI can also be helpful in drafting and negotiation of contracts:

• Contract drafting by machines: It can draft routine legal tech documents, including NDAs and contracts of sale, based on previously prepared templates and the fulfilled need.
  
• Identifying Negotiation Points: It analyzes contracts so that lawyers can obtain negotiation points and take risks and opportunities in the negotiation process.
• 
  Contract language: AI creates contract language based on specific requirements to save the lawyers time and energy.

LegalTech Research and Analysis

Generative AI can significantly enhance legal tech research and analysis:

The AI will summarize long or complex legal tech documents to make the document’s contents understandable for lawyers.

The most significant aspect to consider is patterns and trends in large databases of legal documents that AI can figure out, which are valuable in contributing to a better understanding of legal tech decision-making.
The facts gathered from the case history can be used to foresee legal tech outcomes, giving lawyers a precise perception of the probability of a positive outcome. This will imply that generative AI transforms the legal tech business from automating routine, mundane work to gaining valuable insights.

As technology advances further, applications in legal tech will continue to grow, leading to efficiency, accuracy, and efficiency over cost.

Future of Generative AI in LegalTech: Emerging Trends and Applications

Emerging Trends and Applications

The future potential that generative AI holds for LegalTech is immense. Some emerging trends and applications include:

Enhanced contract analysis:

• Smart contracts: The execution of contracts where the predefined conditions are followed.
• Predictive analytics: Forecasting legal tech risks and opportunities with advanced legal tech research.
  

Advanced Legal Research:

• Semantic Search: Searching more accurately for relevant legal tech documents and case laws.
• Knowledge Graph: Providing the means for interlinked knowledge bases that can be used in legal reasoning.
  

AI-Powered Assistants in the Legal Profession:

• Virtual Paralegals: Doing the menial work of reviewing documents and entering information.
• Intelligent Legal Advisors: Giving instant legal advice and guidance.

The Impact on Legal Experts

The integration of generative AI into LegalTech will significantly impact the role of legal tech professionals:

• Increased Efficiency: Automation of routine tasks will free up lawyers to focus on higher-value activities.
• Improved Decision-Making AI Suggestive Tools Can Provide Numerous Insights.
• New Opportunities: AI legal services will open new job markets and career opportunities.
• Ethical Concerns: Legal professionals should know the ethical considerations underlying AI and ensure it is used appropriately.

Legal Services Using AI: Ethical Issues.

With the growing popularity of generative AI, it’s time to reflect on the ethical aspects of AI-powered legal tech services in general. Why?

• Bias and Discrimination: AI models will perpetuate the training data’s biases, leading to unfair outcomes.
• PRIVACY Issues: AI in legal tech services raises many data privacy and security issues.
• Job Displacement: Legal tasks are automated, a possible threat to the employment of people in legal professions.
• Accountabilities Questions on liability in case of error or mistake with AI-powered systems.

Ethical considerations regarding using AI in legal services must be developed to overcome these risks. Careful consideration must also be given to developing proactive steps to face moral challenges: generative AI must be used for the good of society.

Conclusion

Legal Generative AI will disrupt this industry by automating routine tasks, increasing efficiency, and making better decisions. LegalTech professionals can work on high-value endeavors like strategic thinking and counseling clients.

With the progress made by generative AI, even more innovative applications will rise in the legal field. From contract review to predicting legal analytics, AI-powered tools will revolutionize how legal tech services are delivered.

Only by accepting this technology and furthering research and development will legal tech professionals be able to fully utilize the possibilities of generative AI.

LegalTech professionals will only maintain their position if they are up-to-date with innovations and use the most recent tools that infuse AI. For a rapid future of LegalTech, embracing the power of AI is imperative for creating new routes to the future, not just merely becoming faster and more efficient.

FAQs

What is Generative AI? 

Generative AI is artificial intelligence that can create new content, such as text, images, and code. It uses advanced techniques like neural networks to learn patterns from existing data and generate new, original content.

How can generative AI be used in legal tech? 

Generative AI can automate tasks like contract review, due diligence, and legal research and generate legal documents such as contracts and briefs.

What are the benefits of using Generative AI in LegalTech? 

Generative AI can improve efficiency, reduce costs, and enhance the accuracy of legal work. It can also help lawyers to focus on more complex and strategic tasks.

What are the challenges of using Generative AI in LegalTech? 

Some challenges of using generative AI in legal tech include the need for high-quality training data, the risk of bias in AI models, and the ethical implications of using AI to make legal decisions.

How can [x]cube LABS Help?

[x]cube has been AInative from the beginning, and we’ve been working with various versions of AI tech for over a decade. For example, we’ve been working with Bert and GPT’s developer interface even before the public release of ChatGPT.

One of our initiatives has significantly improved the OCR scan rate for a complex extraction project. We’ve also been using Gen AI for projects ranging from object recognition to prediction improvement and chat-based interfaces.

Generative AI Services from [x]cube LABS:

• Neural Search: Revolutionize your search experience with AI-powered neural search models. These models use deep neural networks and transformers to understand and anticipate user queries, providing precise, context-aware results. Say goodbye to irrelevant results and hello to efficient, intuitive searching.
• Fine-Tuned Domain LLMs: Tailor language models to your specific industry for high-quality text generation, from product descriptions to marketing copy and technical documentation. Our models are also fine-tuned for NLP tasks like sentiment analysis, entity recognition, and language understanding.
• Creative Design: Generate unique logos, graphics, and visual designs with our generative AI services based on specific inputs and preferences.
• Data Augmentation: Enhance your machine learning training data with synthetic samples that closely mirror accurate data, improving model performance and generalization.
• Natural Language Processing (NLP) Services: Handle sentiment analysis, language translation, text summarization, and question-answering systems with our AI-powered NLP services.
• Tutor Frameworks: Launch personalized courses with our plug-and-play Tutor Frameworks, which track progress and tailor educational content to each learner’s journey. These frameworks are perfect for organizational learning and development initiatives.

Interested in transforming your business with generative AI? Talk to our experts over a FREE consultation today!