Harnessing AI for Risk Management and Contract Review in Publishing

Posted on : November 12th 2024

The publishing industry is built on complex contracts, with each agreement covering a web of legal obligations, deadlines, copyright terms, quality standards, and more. For publishers, managing these detailed contracts is essential not only to maintain operations but also to mitigate risk. However, traditional contract management methods are time-consuming and prone to human error, potentially exposing publishers to legal disputes and financial setbacks.

In recent years, AI-driven solutions have emerged as powerful tools to streamline contract review processes, increase accuracy, and enhance risk management. As demonstrated in Straive’s recent case study, AI can revolutionize the way publishers manage and protect their contractual interests, providing a real-world example of how the integration of advanced technology can mitigate risk, improve efficiency, and safeguard data privacy.

Challenges of Traditional Contract Management in Publishing

Publishing contracts are nuanced and legally intricate, covering a range of terms that, if overlooked, can have serious implications. When contracts are managed manually, certain challenges are almost unavoidable:

1. Time-Consuming Processes: Reviewing each contract line-by-line takes time, slowing down publishing workflows. Legal professionals and contract managers may have to sift through thousands of contracts, identifying and verifying essential terms, which can be an inefficient and resource-intensive process.
2. Risk of Human Error: Contract managers and legal professionals are trained to spot inconsistencies, but even the most meticulous reviewer may overlook clauses or fail to catch ambiguities. This risk is heightened when dealing with multiple contracts at a high volume, increasing exposure to potential legal issues.

3. Inconsistent Risk Management: Each contract can vary greatly in complexity, and without a systematic, comprehensive approach, identifying clauses related to copyright, liability, breach of contract, and other critical terms can be inconsistent.

4. Data Privacy and Security Concerns: Contract management involves sensitive information that must be safeguarded, especially when publishers work with high-profile authors, intellectual property, or confidential material. Manual processes are more prone to data mishandling, making privacy a concern.

Given these challenges, AI-driven contract analysis offers a solution that significantly enhances both the accuracy and efficiency of contract review.

The Role of AI in Enhancing Contract Review and Risk Management

AI-driven contract analysis tools bring automation, speed, and intelligence to the contract review process, tackling the unique challenges faced by publishers:

1. Automation and Efficiency: AI algorithms can quickly scan, interpret, and categorize clauses, reducing the time required for manual review. This means that contracts, no matter their length or complexity, can be analyzed in a fraction of the time it would take a human. For instance, a case study by Straive highlighted that implementing AI-driven contract review solutions resulted in a more than 50% reduction in contract analysis time, allowing legal teams to focus on strategic tasks rather than exhaustive clause-checking.

2. Enhanced Accuracy: Advanced AI models can achieve accuracy levels of 94%1. This remarkable precision is achieved through natural language processing (NLP) and machine learning (ML) techniques that “understand” the context and relevance of legal language. The technology can identify missing terms, highlight inconsistencies, and flag ambiguous language, resulting in a review process that’s far more accurate than traditional methods.

3. Consistency in Risk Management: With AI, publishers can implement a standardized review process across all contracts. By creating templates that identify high-risk areas and key clauses, AI ensures consistent oversight, identifying critical risks like breach terms, copyright ownership, and liability clauses every time. This automated diligence creates a stronger risk management framework, helping companies avoid issues that might otherwise be missed.

4. Data Privacy and Security: AI-driven solutions today, such as those powered by private large language models (LLMs), ensure data privacy by processing contracts in a secure environment. Straive’s solution, for instance, uses private LLMs that protect client data, ensuring compliance with privacy regulations while keeping sensitive information safe. This added layer of security is crucial for publishers handling high-stakes contracts that involve intellectual property and other sensitive information.

Embracing AI for a Future-Ready, Smarter Contract Management

As AI-driven contract analysis continues to evolve, the potential applications for publishing and beyond are vast. The technology can adapt to handle new regulations, changing contract structures, and evolving risk profiles, enabling publishers to remain agile in a dynamic industry. Additionally, with continuous advances in AI, contract review processes may soon extend to more advanced predictive capabilities, where AI can assess contract risks based on historical data, emerging legal precedents, and evolving business priorities.

AI-driven contract analysis offers publishers a path forward to manage complex contracts with greater confidence and accuracy. By automating repetitive tasks, enhancing accuracy, ensuring consistency, and upholding data privacy, publishers can mitigate risk, improve efficiency, and maintain a secure, streamlined approach to contract management.

About the Author

Srinivasan Govindarajan

Business Head, Digitalized Operations, Straive