Artificial Intelligence

Contracts are a significant part of the modern world of business. Depending on the size of the company, contracts could number in the hundreds if not thousands. Among those, each has unique rights, obligations, and timeframes. Companies face an overwhelming burden to manage compliance with all those contracts.

While many businesses still adhere to a traditional approach to contract compliance, innovative ways to manage this process more efficiently are emerging.

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The Traditional Approach

The traditional approach is badly broken. Typically, contracts are drafted and negotiated with the assistance of legal counsel. Once signed, it's up to the company to manage it. Various groups may be tasked with this management, including compliance, finance, and executive leadership. In-house counsel manages outside legal services but doesn't necessarily participate in contract management. Law firms are usually not in the business of administering contracts post-signing either.

If businesses use an ad hoc way to manage contracts and don't have a system in place, things can get chaotic quickly. While there may have been substantial expertise poured into crafting the contract at its inception, once it's actually in place, there is a considerable gap in accountability that can lead to challenges.

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The Innovative Approach

The model most companies operate under emphasizes getting deals done—not managing what happens next. It's not effective in the long-term, nor is it scalable. It's time to change the post-deal model so that businesses can effectively manage contracts at scale.

The key steps in this post-deal contract management approach are:

  • Extracting key contract provisions that require actions by either side or contain key dates or trigger events;
  • Building a database to capture the provisions in data format, and making it accessible to internal stakeholders;
  • Establishing a reverse engineering feedback loop: current and future transactions can be informed by the insights gathered from previous contracts and is stored and analyzed in the database; and
  • Standardizing legal text to be put into future contracts.

With this new pattern, the approach is now holistic (full cycle contract management), rather than transactional and focused on inception. The foundation focuses on repeatable steps that can prevent breaches or loss of rights.

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Leveraging Legal AI in Contract Management

To build this new system, technology tools are imperative—one of those being artificial intelligence (AI). To extract important language from the mountain of contracts, AI can significantly reduce the time and costs of the process. It does not do the work for you but is what makes the project manageable.

The alternative to AI is a manual process undertaken by junior associates or in-house attorneys. This process requires a substantial amount of time and is prone to errors. If there are multiple people engaged in the activity, the output likely won't be consistent either.

AI speeds up the extraction part of the model, enabling a greater emphasis on analysis. But it's only as good as the project design, which must be focused on which questions can be asked of the data, what format it needs to be in, and which types of provisions and answers are possible as concepts.

This data then rests in a database, collected into a central hub. Users have access to a dashboard within the database, which can automate flagging of relevant provisions and trigger alerts to specific people. This type of system also offers the opportunity to run reports and statistics as well.

Legal AI doesn't replace the role of an attorney but is instead a vital tool for attorneys to use in managing data.

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Analysis and Understanding Enables Reverse Engineering

Once a company has a database in place and has gone through the contract data extraction process, it's not only in a better position to manage contract compliance but can also reverse engineer the process. It can use the data to determine the right approach to contract drafting and negotiations going forward and can use its database to help make decisions in negotiations. These insights feed into a better approach to the fundamentals of contracts, providing an advantage.

One example of this approach is how it's being applied to high volume contracts such as NDAs, which some companies are outsourcing the project to specialty firms. But with this new approach, businesses can both monitor compliance (e.g., sending return or destroy notices and checking new hires against a non-solicit database), as well as streamline the process with a playbook designed to assist with negotiating them. The net result is a consistent approach that requires less judgment applied to one-off questions by the company and is faster and less expensive as a result of how it can then be process managed.

Christopher S. Harrison is the founder of Sterlington. He is focused on innovation in law through the use of process management, data analytics, and technology-enabled services. He comes to the firm with profound experience, having managed billions of dollars in successful investment transactions during his eight years at Cravath as well as his role as Co-Head of the market-leading asset management M&A practice of Schulte. If you are interested in learning more about Legal AI, contact compliance, contract data extraction, or NDA outsourcing, Contact Chris Harrison at 212-203-2191 or [email protected].