7 Best practices to use NLP for contracts

The complexity and volume of contracts has long been a significant bottleneck for in-house legal counsel, often diverting their focus away from participating in business strategy.

Studies reveal that 89% of organizations struggle with managing a high volume of simple contracts. This not only impacts efficiency but also incurs significant costs, with basic contracts averaging $7,000 to create.

Here's where Natural Language Processing (NLP) for contracts emerges as a game changer. By streamlining contract drafting and review processes, NLP is transforming the landscape of legal operations.

In this post, we explore how NLP empowers legal teams to boost efficiency and focus on strategic business roles.

What is Natural Language Processing (NLP)?

Natural Language Processing, commonly known as NLP, enables machines to understand, interpret, and generate human language. In simple terms, NLP gives computers the ability to 'read' and 'understand' human language in a way that is meaningful and useful.

NLP has made significant strides across multiple industries, but it’s in legal tech where it’s really making a mark. In the world of contracts and legalese, NLP becomes a skilled translator, turning complex legal jargon into something more digestible.

Also read: Glossary of AI Terms for Legal

Why traditional contract management is challenging

Contract management is often tedious, given the complexities of contract language and structure. These documents are filled with dense legal jargon, lengthy clauses, and often convoluted sentence structures.

The use of passive voice and inconsistent language only adds to the confusion. Research, including MIT studies, highlights issues like clauses within clauses in contracts, making them hard to follow.

Then there's the volume aspect. Many legal departments handle thousands of contracts, each with its own set of terms and conditions. Managing this high volume, especially routine contracts like NDAs, becomes a monumental task.

Consistency and standardization go out the window when multiple individuals handle these contracts, leading to variations and potential legal risks. Even minor oversights can have major implications, putting a spotlight on the need for more efficient, accurate contract management solutions.

Enter NLP for contracts.

Also read: Smarter Contract Management with SpotDraft AI

Benefits of implementing NLP for contracts

When it comes to contracts, NLP does the heavy lifting of reading and analyzing them. NLP tools streamline contract review, identifying key points and inconsistencies without slogging through dense text. For legal professionals, this means faster, more accurate contract handling and a bit more time for the important stuff.

#1 Efficiently draft contracts while ensuring consistency

NLP aids in drafting contracts more efficiently by offering language suggestions and ensuring consistency throughout the document. It automates standard clauses and terms creation, saving time and reducing manual effort.

#2 Automate and optimize contract review

NLP tools like VerifAI by SpotDraft automate the contract review process, identifying errors and inconsistencies rapidly. VerifAI reviews contracts to match your guidelines, suggesting redlines for non-compliant clauses and answering open-ended questions.

‍See VerifAI in action

#3 Save time and resources by automating tasks

By automating routine tasks, NLP significantly cuts down the time spent on contract management. This allows you to redirect your focus to more strategic tasks, enhancing overall productivity.

#4 Ensure accuracy and compliance

NLP ensures that contracts maintain a high level of accuracy and compliance with legal standards. It reduces human error and ensures consistency in the language and terms used across multiple contracts.

#5 Get valuable insights to improve decision-making

NLP-powered tools analyze and extract structured data from contracts, offering valuable insights. This data analysis can inform decision-making, helping legal teams to understand contractual obligations, risks, and trends.

Also read: Generative AI for Contract Management: Best Practices

7 Best practices to leverage NLP for contract management

Strategically integrating NLP in contract management boosts efficiency, reduces risks, and offers insights for better legal decision-making.

#1 Select the right NLP tool to ensure ease of use

Carefully choose NLP tools that best fit your organization's specific needs. Consider factors like ease of integration, scalability, and the types of contracts you handle.

Here’s how you can make the best choice:

Identify the specific challenges you face in contract management. Are you dealing with high volumes of contracts, complex legal language, or a need for faster turnaround times?
Look for tools that can handle your contract types and complexity. Does the tool support different contract structures and legal jargon pertinent to your industry?
Ensure the tool can seamlessly integrate with your existing systems, like CRM or document management systems. Check for compatibility and any required technical adjustments
Consider if the tool can scale with your business. Can it handle an increasing volume of contracts without compromising performance?
Choose a tool that is easy to use and understand. A steep learning curve can hinder adoption among your team
Look for tools that allow customization to meet your specific contract management needs
Utilize free trials or demos to test the tool in real-world scenarios. This helps in understanding its practical utility and effectiveness
Check the level of customer support and training offered by the provider. Good support can significantly smoothen the transition to a new tool
Weigh the cost of the tool against the expected benefits in terms of time savings, efficiency, and risk reduction

Also read: 8 Best Contract Management Software for 2023

#2 Customize and integrate the tool with current systems

Tailor NLP solutions to align with your existing contract management processes. Seamless integration is key to maximizing efficiency.

Here are some ways you can ensure integration:

Analyze your current contract management workflow to identify areas where NLP can enhance efficiency. Look for repetitive tasks, bottlenecks, and common errors
Match the features of the NLP tool with specific needs in your workflow. For instance, if your challenge is in contract review, focus on NLP capabilities that automate and streamline this process
Check that the NLP tool can work with the formats of your existing contracts and data. It should be able to read and process documents in the formats you commonly use
Collaborate with IT to integrate the NLP tool with existing systems like document storage and CRM. Seamless integration is crucial for smooth operation
Before full deployment, conduct a pilot test of the NLP integration in a controlled environment. This helps in identifying any issues and ensures that the tool functions as expected
Set up appropriate access levels and permissions for different team members. Ensure that everyone who needs to use the NLP tool can do so easily
After integration, closely monitor how the NLP tool impacts your contract management processes. Be prepared to make adjustments for better alignment with your workflow

Also read: 6 Must-Have CLM Integrations with Business Tools

#3 Train your team to use the NLP tool for contracts effectively

Ensure your legal and contract management teams are trained to use NLP tools effectively. Understanding the capabilities and limitations of these tools is crucial.

Here's how to ensure effective training:

Create a training plan that covers both the basics of NLP and specific functionalities of the chosen tool. Include practical examples and use cases relevant to your organization's contracts
Recognize that people learn differently. Combine written materials, hands-on workshops, and video tutorials to cater to various learning preferences
Use actual contract scenarios from your organization for training sessions. This makes the learning process more relevant and engaging
Ensure that the team understands what the NLP tool can and cannot do. This knowledge is critical to avoid over-reliance on the tool and understand when human judgment is needed
Technology evolves rapidly, so regular training updates are crucial. Keep your team informed about new features and best practices
Create an open environment where team members can ask questions and provide feedback on the tool. This can also help in identifying any gaps in training
Have a team member who is particularly skilled with the tool act as a go-to expert. This person can provide ongoing support and tips to the rest of the team
Use metrics like user adoption rates, speed of contract processing, and error rates to gauge the effectiveness of the training program

Also read: 4 Crucial Contract Management KPIs to Track for Legal Success

#4 Regularly update and maintain the tool

Keep your NLP tools updated with the latest advancements and legal standards. Regular maintenance and data updates are essential for accuracy.

Here's how to manage this:

Set a regular schedule for updating the NLP software. This includes not only the main application but also any plugins or additional tools it uses
Keep abreast of changes in legal standards and regulations. Ensure your NLP tool is updated accordingly to reflect these changes
Regularly monitor the tool's performance. Look for any signs of issues, such as decreased accuracy or slower processing times
Feed new and varied contract data into the system regularly. This helps the NLP tool learn and adapt to changes in language and contract formats
Regularly review the tool's effectiveness in your contract management process. Make adjustments as needed for improved performance
Maintain regular communication with the tool's vendor for technical support and to stay informed about upcoming updates or enhancements
After applying updates, train relevant team members on new features and functionality changes

#5 Monitor performance and gather feedback

Continuously monitor the performance of NLP tools and gather feedback from users. This helps in identifying areas for improvement.

Define clear metrics to evaluate the performance of the NLP tool. These could include accuracy rates, time savings, or error reduction in contract processing
Conduct regular assessments to check if the NLP tool meets these metrics. Analyze trends and patterns in its performance over time
Regularly solicit feedback from the team members using NLP for contracts. Their insights are invaluable for understanding practical challenges and opportunities for improvement
Implement a system where users can report issues or suggest enhancements easily. This continuous feedback loop can drive incremental improvements in the tool's functionality
Track how often and in what ways the tool is being used. Low engagement might indicate usability issues or a need for additional training

#6 Ensure compliance to data security and privacy

“The most inexpensive way to help prevent a data breach is by properly training your workforce. This includes training on creating proper passwords (along with having technology that requires those passwords to meet certain criteria and be changed frequently); how to spot social engineering attempts (e.g., “Phishing”); what to do with suspicious emails (i.e., don’t click on the links and report it to IT office immediately); and how to be alert for industrial espionage (unauthorized visitors, picking up strange USB flash drives and plugging them into your computer to see what’s on them, etc.).”

~ Sterling Miller, CEO of Hilgers Graben PLLC
Ten Things: Things In-House Counsel Should Be Doing Before a Data Breach Occurs

Ensure that NLP tools comply with data security and privacy laws. Safeguarding sensitive contract information is paramount.

Stay informed about data protection laws like GDPR in Europe and HIPAA in healthcare relevant to your region and industry
Select NLP tools that are known to comply with these data security and privacy standards. Check for certifications or compliance badges
Regularly audit the NLP tool and related systems for any potential security vulnerabilities
Implement strict access controls in the NLP tool to restrict sensitive contract data access to authorized personnel only
Ensure that all sensitive contract data processed by the NLP tool is encrypted, both in transit and at rest
Train your team on best practices for data security and the importance of maintaining the confidentiality of contract data
If your NLP tool is cloud-based or involves third-party vendors, regularly review their security practices and compliance

Also read: In-House Legal Guide to Safeguarding Company Data

#7 Analyze and adapt NLP for contracts to refine templates

Use the insights gained from NLP to refine contract templates and negotiation strategies. Adapt your approach based on data-driven insights for continual improvement.

Use NLP tools to analyze contract data, identifying common terms, clauses, and negotiation points
Use these insights to update contract templates with commonly used language and clauses, aligning with industry norms and business goals.
Analyze trends in contract negotiations and outcomes. Use these insights to refine your negotiation strategies
Identify patterns in NLP data for improvement areas, like often contested clauses or terms causing misunderstandings
Adjust your contract management processes based on these insights and track the impact of these changes over time
Encourage your team to continually learn from the data and adapt their strategies for better outcomes

Also read: Understanding The Role of AI In Contract Analysis

VerifAI: The best NLP tool for contract review

VerifAI is a dynamic Microsoft Word Add-in by SpotDraft that is revolutionizing contract review processes. Here's how it stands out as an invaluable tool for legal professionals:

#1 Enables fast and intuitive review

VerifAI leverages generative AI to rapidly review contracts against customized guidelines, streamlining the review process significantly.

#2 Allows for customization with expert insights

The tool empowers lawyers to encode their unique approach into the review process, using plain English to set personalized guidelines. It can instantly highlight non-compliance and key risks, making contract reviews more accurate and lawyer-centric.

#3 Suggests redlines according to your guidelines

VerifAI actively suggests language changes, adds comments for clarity, and makes edits in track changes. This feature benefits from top legal professionals' expertise, ensuring practical and relevant suggestions.

Also read: Contract Redlining: Definition, Tools, & Benefits

#4 Offers flexibility in guideline checks

For focused contract analysis, it offers an Instant Check feature. This feature lets lawyers test contracts against individual guidelines, helping to develop comprehensive playbooks for various contract types over time.

#5 Comes with ready-to-use playbooks

VerifAI offers pre-vetted, industry-leading lawyer-prepared guidelines for key contracts, catering to the fast-paced legal environment. This feature is particularly useful for companies that may not have a playbook for every contract type.

#6 Responsively handles queries

VerifAI can answer open-ended, free-form questions about contracts, providing precise responses to specific queries raised during the review process.

#7 Has high security standards

SpotDraft, the platform behind VerifAI, emphasizes cutting-edge security and compliance, ensuring the safety and confidentiality of sensitive contract data.

Also read: Introducing: VerifAI by SpotDraft

How to address the potential risks of NLP for contract management

“You are not going to be rewarded for making smart business decisions that no one will ever see. When you mitigate risk, when you avoid a problem, no one is ever going to say, ‘good job,’ for avoiding that problem because the problem never came to fruition. But that's doing a good job. You're making good, ethical, smart decisions.”

~ Charlotte Morgan, CLO & CAO, Adore Me
Leveraging Entrepreneurial Experience as a CLO

While NLP offers a transformative solution for contract management, it's crucial to recognize and address its inherent risks and challenges.

Challenge #1: Ambiguity and complex legal language

The complex terminology and ambiguity of legal documents challenge NLP tools, which are typically designed for simpler language processing.

Solution:

Continuously feed NLP systems with updated legal dictionaries and case law to ensure they understand the latest legal jargon and phrases
Develop customized language models that cater specifically to the legal domain, incorporating nuances and structures typical in legal documents
Implement advanced NLP techniques that not only parse text but also understand the context and intent behind legal clauses

Challenge #2: Ensuring data privacy and security

Handling sensitive contract data through NLP tools raises significant concerns regarding data privacy and security. In an era where data breaches are not uncommon, this challenge is paramount.

Solution:

Choose NLP tools compliant with relevant data protection regulations like GDPR, HIPAA, and others specific to your region and industry
Use state-of-the-art encryption methods to protect data both in transit and at rest, ensuring unauthorized parties cannot access sensitive information
Establish stringent access controls and authentication protocols within the NLP system, limiting access to sensitive contract data to authorized personnel only
Conduct frequent security audits and vulnerability assessments to identify and rectify potential security weaknesses in the NLP system

Challenge #3: Overlooking critical contract nuances

Over-reliance on NLP technology can lead to overlooking critical contract nuances, potentially resulting in errors or misinterpretations.

Solution:

Encourage a balance between automated NLP analysis and human oversight in contract review processes
Educate legal professionals about NLP capabilities and limitations, emphasizing the importance of manual review for critical contract aspects

Challenge #4: Keeping pace with technological advancements

The rapid evolution of NLP and AI technologies means you need to stay informed about the latest developments. Failure to do so may result in outdated or less effective NLP systems.

Solution:

Foster a culture of continuous learning to keep legal teams updated on the latest NLP and AI advancements
Stay proactive by regularly upgrading your NLP systems to incorporate the latest features and improvements
Conduct periodic audits to assess the effectiveness and accuracy of your NLP systems, making necessary adjustments to align with technological advancements

The best way to address these challenges would be to have an AI policy in place. Not sure how to create one for your organization? Download our AI policy playbook built by legal experts here.

Unlock the future of contracts with NLP

In a world where contracts rule the business landscape, NLP is your ally. Its ability to swiftly analyze, interpret, and enhance contracts is reshaping how legal professionals operate.

However, it's crucial to strike a balance between technology and human expertise, recognizing that NLP complements rather than replaces legal insight.

Looking ahead, NLP's evolution in the legal tech landscape promises even greater efficiency and precision. The future holds even smarter, more intuitive tools that will redefine how we navigate the legal tech landscape.

Ready to dive into the new world of contracts with NLP? Take VerifAI for a spin and witness the magic for yourself.