While 49% of people worry that AI will replace their jobs, 70% of people would delegate as much as possible to AI to lessen their workloads.
Not many lawyers want to be stuck with dull, repetitive work. With AI-powered Large Language Models (LLMs) trained specifically for legal contract analysis, you no longer have to be.
A recent boom in legal data and the growing use of LLMs in GenAI legal tools are enabling lawyers to significantly accelerate contract analysis. Yet, challenges involving data quality, bias, and privacy remain.
How will you know whether LLMs are helping or hindering your contracts?
The Recent Rise of Legal Data
There’s been a massive surge in the amount and complexity of the data created in the corporate legal industry. Driving this increase are:
- Copious amounts of electronically stored information (i.e., digital data) produced during the regular course of business and in response to litigation or government investigations.
- Contract repositories that hold thousands of digital contracts and related documents. A typical Fortune 1000 company manages between 20,000 and 40,000 active contracts at any given time, at least 10% of which are misplaced, difficult to find, or otherwise unmanaged or forgotten.
- Regulatory filings and compliance requirements. In 2018, researchers found that over a prior 20-year period, the variety of regulations cited in Form 10-Ks tripled while the total volume of citations to regulations quadrupled. New regulations continue to increase corporate compliance requirements.
Legal professionals need help categorizing, reviewing, and analyzing this ever-growing data. Doing so effectively requires using technologies that can reliably, efficiently, and accurately process and learn from legal data — precisely what LLMs do.
Training LLMs on legal data
An LLM is an AI algorithm that can generate text that sounds as if a human wrote it. LLMs learn from good and bad writing examples, using natural language processing to process large data sets.
The surge in publicly available legal data enables widely available LLMs such as GPT-4 and Claude to learn the basic legal nuances of contracts and law. Relying on these LLMs as a foundation, legal technology vendors build and train proprietary LLMsS using extensive amounts of legal data and human lawyer input to specialize them for legal work.
Legally trained LLMs power GenAI tools that automate contract analysis tasks, speeding contract processes and enabling you to make more informed decisions faster and access new insights. Training these LLMs on your company’s internal legal datasets leads to more deeply customized analyses and insights.
LLMs: A Game-Changer for Contract Analysis
When using GenAI tools driven by legal knowledge and a deep understanding of contracts, your legal team can effectively deliver:
Enhanced Efficiency
GenAI tools quickly scan contracts and produce concise analyses and summaries. They automatically:
- Identify, extract, and analyze specific details, including key terms, obligations, dealbreaker clauses, and risks
- Markup contract clauses with redlines, highlights, and one-click comments
- Flag risks with custom notes and tasks in a to-do list
- Suggest alternate and additional clauses from template contracts
- Send custom reports or notifications to contract stakeholders
- Optimize language to meet specific legal and business purposes
High Precision and Accuracy Rates
LLMs trained on legal data can interpret legal language and contexts accurately, significantly minimizing the risk of human error. For one customer, our Lexible Fusion™ AI Engine reviewed complex supply agreements in less than 3 minutes with >90% accuracy. The same contract took qualified lawyers 4 hours to review at an average accuracy rate of 86%.
Extensive, continuous training and testing enhances an LLM's ability to spot errors, omissions, inconsistencies, and ambiguities, improving the overall quality of contract analysis.
Automated Due Diligence & Compliance
Instantly compare contracts to legal, regulatory, and jurisdictional requirements, industry standards, and internal policies. Rely on built-in pre-configured playbooks to improve a variety of common commercial agreement types. And build company playbooks for automated identification of specific clauses, obligations, or risk factors unique to your business.
Using a tool that a vendor continuously trains eliminates the need for you to manually gather and check compliance information. You can rest assured that you're relying on the latest and most accurate information and finding all the relevant details in the contract.
Enhanced Contract Negotiations
Automation reduces contract review processes by over 70%, quickly moving you toward revenue realization. Using GenAI tools, you can:
- Instantly identify negotiation points and potential disputes.
- Share an issues list with colleagues for real-time negotiation and planning.
- View the risk profiles of all signed contracts to improve negotiation guidelines.
The Challenges of LLM-Driven Contract Analysis
Several challenges remain when using LLMs to perform contract analysis surrounding:
- Data quality and bias
- Legal interpretation limitations
- Privacy and security concerns for handling sensitive legal data
LLMs must be trained on high-quality data, which can be time-consuming and costly. That’s why the availability of public LLMs like GPT-4, Claude, Gemini, and others is so exciting. Companies can access models proven to have a base-level understanding of legal concepts and language and then train the models on additional legal data to develop legal GenAI tools that are accurate, precise, and ready for your immediate use.
Even after extensive training, the potential for LLMs to perpetuate existing biases in the training data will always be present. And, just as it is with human lawyers, LLMs can misinterpret ambiguous legal language.
Using diverse data sets, carefully monitoring and rigorously testing the model's performance, and including human verification and instruction by lawyers help minimize these risks. The lawyer’s oversight of the final contract analysis also helps to ensure accurate legal analysis that resolves these challenges.
Vendors who are ISO27001 certified have proven capabilities to adhere to the international standards for information security governance. Other security and data privacy elements to look for include:
- Data encryption at rest and in transit
- Secure authentication, e.g., single-sign-on and multi-factor authentication
- Data sovereignty controls
- 24x7 security monitoring and ongoing testing
Our Hybrid Future of LLM-Driven Contract Analysis
Our future involves a hybrid approach to contract analysis where we combine AI with human legal expertise throughout an LLM’s training and use. Legal departments now use AI to automate routine tasks and rely on human judgment for more complex work.
