Among the many ways in which artificial intelligence (AI) technologies are enhancing business functions, the inefficiencies and labor-intensive organizational aspects of the contracting process present many fertile opportunities for improvement through the application of AI. A recent article in the Harvard Business Review discusses the contracting challenges current AI technology can help to alleviate and the contracting process changes required to adapt to AI contracting tools, as well as understanding the limits of AI.
Dealing with Contract Volume Using AI
As the article notes, one of the most significant contracting challenges facing organizations is managing a high volume of agreements. Even with a centralized database for contract documents, organizations often have no efficient way to extract data from those contracts or see, for example, how a warranty clause is worded across a number of different customer agreements. AI software tools can extract that data from contract documents and clarify and organize content, which can help organizations contract more efficiently and manage existing contracts more effectively.
Tracking and Enforcing Contracting Language Standards
Another significant challenge in the contracting process, especially for high-volume customer or vendor contracts based on standard templates, is ensuring conformity to template language and efficiently tracking deviations from form language. For instance, if an organization is seeking to impose uniform contract terms around the use of company trademarks and trade names, AI software tools can help track that language across divisions and could be configured to recognize keywords that indicate the trademark usage language is needed in a contract.
AI tools can also automate the task of tracking key contractual obligations, such as agreement expirations, termination provisions, and warranty periods, both to manage variations from the standard form language and to track the organization’s compliance with its contractual obligations. Utilizing AI tools in this way can reduce both the need for large, dedicated contract compliance teams and the overall risk of noncompliance.
As these examples illustrate, AI tools in their current form work best on managing high volumes of relatively uniform agreements. AI and machine learning results are an aid to, but of course not a substitute for, human judgment of compliance and risk.