Cookie Consent

By clicking “Accept”, you agree to the storing of cookies on your device to enhance site navigation, analyze site usage, and assist in our marketing efforts. View our Privacy Policy for more information.

In recent times, Artificial Intelligence (AI) has proven to be a game-changer in contract review processes. Its ability to quickly spot risk areas and offer viable suggestions has helped legal teams hit unprecedented levels of productivity.

However, the prospects of reviewing contracts with AI have been met with mixed feelings from experts in the legal industry. Indeed, while AI is capable of producing accurate results at impressive speed and scale, there are also inherent possibilities of occasional errors and ethical issues that can have significant legal implications.

To strike the much-needed balance between speed, accuracy, and ethical use, human oversight remains indispensable.

In this guide, we will go through how you can create a perfect mix of AI-led performance and manual validation to achieve consistently high productivity levels in contract review processes.

Understanding AI in contract review

At its core, AI-powered contract review draws from Natural Language Processing (NLP) and Machine Learning algorithms to analyze the content of legal agreements with speed and accuracy. 

Trained on vast datasets of historical contracts, these tools are built to identify patterns, extract key information, and flag potential issues. This includes detecting missing or inconsistent clauses, highlighting ambiguous language, and pinpointing clauses that might expose a party to undue risk.

Among other things, its incredible speed and high accuracy promise to help legal teams review more contracts in far less time, allowing them to focus on strategic and value-driven areas of their responsibilities.

Also read: How AI Contract Review Tools are Transforming Legal Workflows

While the massive potential of AI in contract review is undeniable, it does come with some limitations that must be put into consideration.

AI lacks the nuanced understanding of legal context and intent that human lawyers possess. While it can identify potential inconsistencies, it cannot interpret the underlying purpose and implications of language in the same way a human lawyer can. 

Moreover, the effectiveness of AI in contract review is contingent on the quality and diversity of its training datasets. Biases present in the AI training data can inadvertently be perpetuated by the tool, potentially introducing new risks and inequities into the legal process.

This highlights the importance of human oversight in AI-driven contract review. By fostering a synergistic relationship between humans and machines, contract review processes will be more efficient, reliable, and scalable.

All hands on deck: the need for manual validation

In a study by Harvard involving 1500 companies, experts concluded that AI systems are more efficient when combined with human expertise.

While AI offers unparalleled speed and efficiency in contract review, its limitations necessitate the inclusion of human oversight. Manual validation, performed by experienced legal professionals, ensures that AI outputs are contextually accurate, reliable, and ethically sound.

Here, we discuss the reasoning behind this.

#1 Deeper understanding and context

Human lawyers possess a nuanced understanding of legal context, intent, and precedent that AI simply cannot replicate. They can analyze the contract in light of the specific situations and priorities of the parties involved, ensuring that outputs are not solely identified based on patterns but are thoroughly understood in their specific context.

Additionally, manual validation allows for a more holistic assessment of the contract. Lawyers can consider the agreement not only in isolation but also in the context of the broader business relationship and the overall legal landscape.

#2 Improved accuracy and risk mitigation

AI is trained on historical data, and while it excels at identifying common patterns, it may struggle with uncommon or evolving legal scenarios. Human expertise is essential for recognizing novel situations, adapting to legal developments, and providing insights that AI may not have encountered in its training data.

Also, while AI can flag potential issues with impressive speed, manual validation plays a crucial role in verifying and refining those flags. Human lawyers can assess the identified risks in the context of the entire contract, industry standards, and relevant legal precedents.

Also read: Legal Risk Management: From the Playbook of 11 GCs & Leaders

This deeper understanding allows them to differentiate actual risks from false positives, evaluate the severity of identified risks, and develop effective mitigation strategies.

“To me, a risk only matters if it's material. If it’s immaterial, I don’t care about it. If it's likely to occur but it's not very costly, I probably don't care. If it's unlikely to occur but, man, if that meteor hit the earth today, it would be bad — I also don't care. It's just not likely to happen.”

Jonathan Franz, Head of Legal at Crunchbase
Navigating Economic Turbulence and Thriving in Chaos

#3 Enhanced collaboration and trust

The collaboration between AI and human lawyers fosters a symbiotic relationship that capitalizes on the strengths of both entities. Legal professionals can leverage AI's speed and scalability to process a large volume of contracts, allowing them to allocate more time to complex and strategic aspects of their responsibilities.

This collaboration builds trust within legal teams and organizations as it demonstrates a commitment to thoroughness and due diligence. Clients and stakeholders can be assured that a comprehensive and multi-faceted approach, combining the efficiency of AI with the expertise of human professionals, is applied to the contract review process.

#4 Continuous improvement of the AI over time

Manual validation serves as a vital feedback loop for AI contract review tools. Human users can identify instances where the AI misinterprets language, flags false positives, or overlooks valid concerns.

This feedback is then reused as part of the AI’s training set, refining its capabilities, addressing gaps, and improving overall performance over time.

This iterative process results in a dynamic and evolving AI system that aligns more closely with the changing needs of legal professionals.

#5 Greater transparency and accountability

The integration of AI into contract review raises questions about transparency and accountability. By involving humans in the validation process, organizations can maintain a clear chain of command and ensure that all decisions are ultimately made by qualified legal professionals.

Human reviewers can document their reasoning behind accepting or rejecting AI flags, providing a transparent audit trail of the review process. This transparency facilitates trust with stakeholders and ensures that all parties understand the rationale behind the final contract agreement. 

Additionally, manual validation helps to hold the AI accountable for its outputs, ensuring that any errors or biases are identified and addressed promptly, minimizing the potential for legal ramifications.

Best practices for integrating AI and manual validation in contract review

Integrating AI and manual validation in contract review can offer significant benefits, but it's crucial to do it right, as missing critical steps can be counterproductive. Here, we’ve detailed some best practices you should keep in mind.

#1 Choose an AI tool that’s right for your organization

The quality of your AI tool is directly proportional to the quality of your contract review processes. Choosing the wrong tool means spending extra hours correcting errors, dealing with false positives, and ultimately reverting to the trenches of manual reviews.

Make sure the AI tool is scalable, customizable, built by a reputable brand, recommended by industry experts, and compatible with existing systems within your organization.

Also read: How to Choose the Best AI Contract Review Software

VerifAI is one such tool that meets the criteria above. Powered by a robust repository of up-to-date, lawyer-approved playbooks, VerifAI rapidly scans your contracts against established guidelines, detects risk areas, and proffers the right redlines.

Thanks to its NLP capabilities, VerifAI allows you to interact with it in a conversational manner. That way, you can submit open-ended questions and get reliable answers. Overall, the platform has proven to save an average of 15 hours per week on contract review tasks.

That said, remember that by adopting AI, you're not replacing humans but augmenting their capabilities. Choose an AI contract review tool that complements your team's strengths, not compete with them.

#2 Define your contract review workflow

Establish a clear and well-defined contract review workflow that delineates the responsibilities of AI and human validators. Ideally, your AI should handle routine and high-volume tasks while your human team focuses on more complex and contextual aspects that require their expertise. 

This division of labor ensures optimal utilization of AI and human capabilities, enhancing overall efficiency in the contract review process.

“Artificial Intelligence just may well be the final frontier in terms of how legal services are utilized and provided.  As in-house counsel, don’t run away from it and don’t ignore it.  Rather, embrace it as, ultimately, it will allow you to do thing things lawyers love to do: thinking, analyzing, and counseling, while leaving the “grunt” work to the computer.”

Sterling Miller, CEO and Senior Counsel for Hilgers Graben PLLC
Ten Things: Artificial Intelligence—What Every Legal Department Really Needs to Know

#3 Leverage the expertise of external legal professionals

“One of the most important tasks faced by in-house lawyers is deciding what work will be done in-house and what gets sent outside.”

Sterling Miller, CEO and Senior Counsel for Hilgers Graben PLLC
Ten Things: When To Send Work To Outside Counsel (And When To Bring It In-House)

Collaborating with external legal professionals can provide a fresh, unbiased perspective on AI-reviewed contracts.

External experts bring diverse experiences and insights and can identify potential issues that in-house teams may inadvertently overlook. This external validation ensures a comprehensive and objective assessment, contributing to the overall robustness of the contract review process.

Lex by SpotDraft offers such opportunities for organizations looking to explore external expertise in areas like contract review. With Lex, you get access to a team of legal experts who can help handle a wide variety of routine tasks for your organization. This encompasses full-cycle contract management services, implementation of AI technology, advisory and consultation services, and reporting, among others.

This can help you achieve up to a 60% increase in contract compliance and a 65% increase in turnaround times.

#4 Work with a checklist

Create a comprehensive checklist that aligns with your organization's legal standards and requirements. Use this checklist to cross-reference the outputs generated by the AI tool. 

This ensures that no critical details are overlooked and provides a systematic approach for human validators to review and confirm the accuracy of AI-generated results.

Also read: The Perfect Contract Review Checklist for Commercial Contracts

#5 Implement a feedback loop for continuous improvement

Establish a structured feedback loop to capture insights from manual validation. Encourage legal professionals to provide feedback on AI-generated outputs, highlighting areas of improvement and potential misinterpretations.

This feedback loop serves as a valuable mechanism for refining the AI system, addressing gaps, and enhancing its overall performance over time.

#6 Maintain continuous training for your legal team

“If you think that you're doing everything perfectly, you're not going to grow. There's always an opportunity for self-improvement.”

Doug Luftman, ex-DGC, DocuSign
The Key to Success as an In-House Legal Counsel & Leader

Invest in ongoing training programs for legal professionals involved in the manual validation process to keep them abreast of the latest developments in AI and legal technology. 

This ongoing training ensures that human reviewers stay abreast of changes that may not be adequately covered in AI training data, enhancing their ability to identify emerging risks and novel situations.

#7 Implement proper documentation for transparency

Document the rationale behind accepting or rejecting AI-generated flags during the manual validation process. This documentation serves as a transparent audit trail, offering visibility into the decision-making process.

Maintaining transparency builds trust with stakeholders and ensures accountability in the contract review process.

Wrapping up

It is true that AI can review contracts at impressive speed and scale. But to achieve a well-rounded contract review output that strikes a balance between accuracy, efficiency, and compliance, a synergistic combination of AI and human expertise must be incorporated.

AI can handle the initial heavy lifting, identifying potential risks and highlighting key clauses, while human reviewers provide in-depth analysis, judgment, and decision-making to ensure accuracy and compliance.

By leveraging the strengths of both, you can achieve a faster, more accurate, and compliant review process that protects the interests of your organization and its partners.

Need help with manual validation? Feel free to get in touch with Lex by SpotDraft. Click here to book a free consultation.

Try VerifAI: Free AI Powered Contract Review Tool

Download the Free Template

Email me the free Business Contract Template

Download the Free Template

Download the Free Template

Download the Free Template

Download the Free Template

Download the Free Template

Download the Free Template

Download the Free Template

Download the Free Template

Download the Free Template

Download the Free Template

Download the Free Template