Simplify Contract Lifecycle Management With Legal AI

Contracts are rarely created "from scratch." Instead, they are cobbled together from templates and clauses in other successful agreements. By leveraging existing contracts and automating processes, contract lifecycle management (CLM) can generate cost savings by establishing a systematic method to compose a binding document.

Technology plays a critical role in contract lifecycle management. An organization with hundreds of documents requiring drafting, negotiation, and monitoring can use CLM programs to control the tasks. However, much of this software is limited to handling objective issues, like identifying due dates, specific terms, and project statuses. More complex and subjective activities, including review and negotiation, present challenges that standard CLM software cannot overcome. This is an area where legal tech innovation and artificial intelligence (AI) can play key roles in providing a complete end-to-end solution. 

The Components of Contract Lifecycle Management

• Request: The parties make contact to enter a contractual relationship. 
• Draft: One of the parties readies a draft, typically from a template or a prior contract for a similar type of relationship or transaction. 
• Negotiate: The parties make offers and counter-offers before reaching a tentative accord. 
• Review: The parties eliminate any ambiguities, unenforceable clauses, or elements that could void the agreement. 
• Approve: The parties agree to the revised agreement. 
• Execute: The parties execute the agreement. 
• Comply: The parties perform their obligations under the terms of the agreement. 
• Renew: The contract either expires, ending the cycle, or it is renewed.

Nearly every contract will follow these stages. As a result, contract lifecycle management is broadly applicable in any industry. While CLM programs are popular for a wide variety of applications, their effectiveness is often overestimated. 

The Problem With Standard Contract Lifecycle Management Programs 

Most CLM programs incorporate objective criteria related to workflow management. Even the smartest standard programs typically act as nothing more than intelligent data repositories. Attorneys are still required to negotiate terms, understand benefits and risks to the organization, and make counteroffers. 

Since CLM programs are not designed to think subjectively, they fail to address two critical contract management components: negotiation and review. For this reason, corporate legal departments and law firms increasingly utilize AI to optimize their contract lifecycle management technology. 

Using AI to Handle Complex and Subjective Contract Lifecycle Stages 

Establishing a contract's terms and ensuring their representation in the final, executable version can be the most time-consuming process in contract lifecycle management. These are complex and subjective areas, and until recently, technology could not think subjectively. 

Artificial intelligence eliminates that technological barrier. While every program is different, most AI systems combine large amounts of data, natural language processing, and scenario modeling to allow a system to make subjective decisions. As the system's behavior stems from the actions displayed in successful contract negotiations, the program only applies proven concepts. In this way, legal teams can leverage their top attorneys’ performance at speeds augmented by technology. 

The Next Level of Negotiation and Review 

In the future, business negotiations performed by AI programs could recommend mutually beneficial scenarios for all parties. AI-powered contract review and negotiations could be performed in a few minutes, rather than dragging on for weeks or months. 

By harnessing the power of machine learning, the next level of contract lifecycle management enables legal teams to realize significant time and cost savings. Employing the technology in conjunction with a CLM to manage workflow could provide a total solution to contract management. As today's attorneys must do more with less, artificial intelligence bridges the gap.