Business Use Case of AI in Legal - Contract Review and Due Diligence

Author: Erfan[email protected]
Publish on: 2023-11-04
The application of AI in contract review and due diligence for business legal cases facilitates a more efficient and accurate examination of contractual obligations and risks by automating the scrutiny of terms and conditions, identifying potential liabilities, and ensuring compliance with relevant laws and regulations.
Blog Pic Business Use Case of AI in Legal - Contract Review and Due Diligence

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The integration of artificial intelligence (AI) in the legal domain has become increasingly relevant as firms seek to streamline operations and harness efficiency, particularly in the realms of contract review and due diligence. Amidst a backdrop of economic fluctuations, the drive for operational efficiency has led law firms and legal departments to lean heavily on AI to optimize processes, control costs, and enhance decision-making abilities. This is particularly pertinent in contract analysis, where AI's ability to detect anomalies and inconsistencies offers a safeguard against contractual variations that may carry significant legal or financial implications.

AI's prowess extends beyond simple review tasks to encompass sophisticated analytical roles within legal practices. By tapping into the extensive repositories of contract data, AI algorithms are adept at tagging pertinent clauses and assessing them for fairness and risk, thus acting as an invaluable assistant to legal professionals. This evolution from elementary data sifting to providing actionable insights in contract negotiations and due diligence reflects a broader trend towards the advanced application of AI across all facets of contract analytics within companies.

The transformative impact of AI is evident in its adoption rates, with a notable number of companies incorporating AI for generating and reviewing legal documents, due diligence, and research. As AI technology matures, it holds the promise of redefining the traditional methodologies of the legal sector by augmenting the capabilities of human practitioners, thereby setting a new benchmark for legal due diligence and contract management.

Historical Context

Before the advent of artificial intelligence (AI) in the legal domain, contract review and due diligence were notoriously labor-intensive processes, fundamentally unchanged for centuries. Legal professionals relied on a manual review process, navigating through complex legal documents with diligence to mitigate risk exposure for their clients. The process was structured yet cumbersome, involving multiple tedious stages such as reading and writing, focusing on contract terms, defining review areas, redlining changes, and adding comments or notes to contracts.

The challenges inherent in pre-AI contract review were multifaceted. Complex contract language, scattered across various documents, needed to be manually collated and understood, often resulting in delays, missed obligations, and compliance issues. Moreover, the variability and customization demanded by different contracts and the ambiguity inherent in legal language added layers of difficulty. Professionals had to ensure that every line aligned with company policies and legal requirements, a process that was not only time-consuming but also prone to human error and interpretative subjectivity.

The introduction of computers in the 1980s began to change the landscape slowly, but initially, their role was limited to basic tasks directed by human input. Despite these technological advances, the manual review process continued to be predominant, with AI only beginning to make significant inroads into contract analysis in more recent years. Before AI, the manual process was also costly, affecting deal velocity and slowing down sales due to the need for multiple iterations of review and negotiation.

Advent of AI

Artificial intelligence (AI) has revolutionized contract review and due diligence in the legal domain by addressing the time-consuming and error-prone nature of manual contract management. Here's how AI has helped overcome historical challenges:

1. Efficiency in Review

AI significantly reduces the time lawyers spend on contract review by automating the extraction of key information, enabling rapid comparison and analysis of data across a high volume of documents.

2. Risk Mitigation

AI tools like Document Intelligence use machine learning to discern context and intent, providing reliable data for obligation tracking and risk assessment, which is critical in due diligence.

3. Enhanced Accuracy: By training on diverse datasets, AI models achieve high precision in identifying contract provisions and terms, which helps avoid the inaccuracies and ambiguities associated with manual reviews.

4. Ease of Implementation

The availability of pre-trained AI tools means legal teams can deploy contract review software quickly, shifting focus from administrative tasks to strategic legal work.

By automating "administrative" tasks, AI enables lawyers to concentrate on the substantive legal analysis and strategic aspects of contract review, increasing the overall quality and speed of legal services. This transformation addresses not just the efficiency of contract review but also the strategic management of due diligence processes.

Real Life Application of AI

Here are five real-life case studies demonstrating how AI has aided companies with contract review and due diligence in the legal domain

1. Unilever's M&A Transaction Due Diligence

Unilever needed to review around 18,000 contracts for an M&A transaction, a task that would typically require 9,000 hours of human review. By using DocuSign Insights for initial AI review and layering human QA over it, Unilever managed to save about 6,500 human hours, increased the accuracy of party data point extraction to 98%, and completed the review 70% faster than possible with human review alone.

2. Thomson Reuters' Remediation Process

Thomson Reuters enhanced the remediation process efficiency by 30% using a machine-learning contract analytics platform. This improvement not only sped up the process but also likely contributed to cost savings and improved accuracy for their clients.

3. Osler, Hoskin & Harcourt LLP's Document Review

This law firm increased document review efficiency by using Kira Systems' document analysis software to extract relevant information from contracts. The use of AI-driven platforms enabled faster and more accurate reviews compared to manual processes.

4. British Telecom's Cost Savings

British Telecom saved an estimated £100 million annually by employing RAVN's automated contract analysis platform. The AI system helped in ensuring compliance and meeting contractual obligations efficiently.

5. Dell's Contractual Obligation Management

Dell leveraged contract analysis automation to reduce costs and ensure that contractual obligations were fulfilled accurately, demonstrating the cost-saving and risk-reducing benefits of AI in legal operations.

These case studies represent a cross-section of industries and legal tasks where AI has not only streamlined the tedious process of contract review and due diligence but has also provided significant economic benefits and risk mitigation. They highlight the practical value AI brings to legal departments and firms in handling large volumes of documents with speed and precision.

Future Trend

The future of contract review and due diligence in the legal domain is influenced by several emerging trends facilitated by AI and technology advancements.

1. Digital Transformation

AI is central to more efficient due diligence, using advanced analytics, machine learning, and other tools for faster and more in-depth analysis.

2. Cybersecurity

With rising cyber threats, there's a trend toward integrating cybersecurity risk assessments in due diligence processes to protect against data breaches and reputational damage.

3. ESG Due Diligence

ESG factors are becoming critical, with due diligence increasingly focusing on a company's social and environmental impact, corporate responsibility, and sustainability practices.

4. Supply Chain Analysis

Post-pandemic, there's a move towards a more integrated approach in supply chain due diligence, emphasizing resilience, sustainability, and cybersecurity.

5. Geopolitical Risk Assessment

Assessing country-specific and geopolitical risks is becoming essential for organizations to make informed decisions in uncertain markets.

6. Human Rights Considerations

Human rights due diligence is gaining prominence, with businesses assessing the impact of their investments on labor standards and ethical practices.

These trends point toward a future where due diligence is more comprehensive, integrated, and aligned with global standards and ethical practices, driven by technological innovations.


In conclusion, the integration of AI into contract review and due diligence represents a paradigm shift in the legal domain. It offers a promising glimpse into a future where legal professionals can leverage technology to enhance accuracy, efficiency, and strategic decision-making. The adoption of AI has shown to not only streamline complex and voluminous tasks but also to introduce a new depth of analytical prowess to legal proceedings. By doing so, AI is setting new standards for risk assessment, due diligence, and contract management, reflecting the evolving landscape of legal services.

Looking forward, the legal industry is poised to continue its trajectory toward increased digital transformation, with AI at the forefront of this evolution. The continued emphasis on cybersecurity, ESG compliance, supply chain integrity, geopolitical awareness, and human rights due diligence will shape the way legal professionals approach their work. As AI and machine learning technologies become more sophisticated and pervasive, their role in driving the legal domain towards greater innovation and responsible business practices cannot be understated. This alignment with technology ensures that the legal field remains adaptable, resilient, and prepared for the challenges of a dynamic global environment.