Inefficient contract management is expensive. KPMG estimates that up to 40% of a contract’s value is lost during its lifecycle. The International Association for Contract & Commercial Management (IACCM) found that a company puts up to 9% of its bottom line at risk with poorly managed contracts.
The challenge many face when it comes to managing their contracts arises from the large volume that exists in multiple places throughout the organization. Most large companies regularly manage between 20,000 and 40,000 contracts, according to a study by PricewaterhouseCoopers. This has to be put in context with the cost of contract processing, which according to a recent study is in the range of $6,900 for each document. Technological advancements in contract lifecycle management and artificial intelligence (AI) offer effective platforms for organizations to build efficient business processes that can significantly reduce contract value leakage and the cost of contract management.
The earliest Contract Lifecycle Management (CLM) systems started out as a centralized contract repository. The value gains from simply gathering an organization’s contracts from filing cabinets and desk drawers and uploading them into one database are significant. Once digitized they can easily be analyzed, compared, monitored, and business decisions can be automated. Moreover, contract management systems are pivotal to the standardization of the contracting process across the organization, which is a major driver of quality, efficiency, and risk mitigation for legal departments.
The major share of the cost to negotiate and maintain a contract is attributed to poor coordination between departments inside the organization. Modern CLM systems have added comprehensive workflow automation facilities and sophisticated features to streamline contract negotiation. Standardization and compliance can now be enforced with highly customized automated workflows. These use intelligence from the contract repository as input for decision making and the management of review, approval, and escalation procedures. This can significantly speed up contract processing, reduce friction in the organization, and increase contract quality and standardization.
Even with a contract repository and workflow automation, companies are still faced with challenges. While templates and standard language are preferred to create easy-to-maintain contracts, many contracts are actually based on the other party’s template, which can make them difficult to negotiate and maintain.
In recent years AI-based Natural Language Processing (NLP) systems have seen significant investments and today AI capabilities are available that can extract attributes like effective dates and contracting parties from a wide range of contracts with confidence. State-of-the-art AI capabilities can also recognize legal language variations and make recommendations to support the company’s standard position. This technology is an integrative component of state-of-the-art CLM systems. It is used to automate the import of contract documents and to facilitate contract review, contract risk evaluation, and the maintenance of organizational compliance.
The efficiency gains from using AI in contract negotiations are significant. A study by LawGeex found that on average AI outperforms human contract review accuracy by more than 10%, while being about 100 times faster.
The fast-paced technological advancements in NLP have led to a certain level of euphoria. There are occasions when the promises of efficiency gains from using AI in contract management come close to magic. It is important to take such promises with a grain of salt and to evaluate the usefulness of an AI system in combination with improvements in the organization’s processes and the skills and interactions of the people who drive them.
AI has yet to pass the Turing test and therefore, for best results, it is important to evaluate AI as one more component in the CLM toolbox. When used correctly, a modern, AI-augmented CLM system contributes significantly to the company’s bottom line by reducing value leakage, making contract management more efficient, and mitigating contract risk.