In recent years, AI has been able to structure much of the data in contracts, which has greatly helped company operations. For example, AI not only knows what an inflation clause looks like, but can also identify the critical principles that exist in inflation clause variations in tens of thousands of contracts, recognize their natural language patterns, and sum up their relevant principles in plain English for consumption by the diverse user personas participating in the contracting processes. It can then alert the company when a specific increase in the economy’s inflation triggers a price increase and specify the locations of the relevant clauses in all of the contracts. And it can do all of that in a seamless process. – culled from Icertis publication
The terms of commercial agreements can be as ambiguous and obscure. Contract language is sometimes presented in ways that are inexplicit and often subject to legal arguments for proper interpretation. Even lawyers have trouble understanding them. Average procurement professionals rarely apply their terms to daily operations. So, contracts end up residing in repository. However, they are critically important because a business can’t operate without them, but they end up being ignored because people don’t understand them or easily access them.
Some big companies like Google and Microsoft, have thousands of contracts and can execute 150,000 statements of work (SOWs) in one business unit every year while a normal company may have hundreds or even thousands of commercial agreements. Most of these contracts and commercial agreements may have dependent and interlocking clauses that reinforce their validity in so many different ways.
The responsibility of garnering the related content and meaning of these documents is enormous and complex. The challenge even gets more complex in a situation where the persons who have written the contracts have all left the company and their replacements are not up to speed with the contents of the contracts. However, this is usually the case in many companies today, where companies spend a lot of money creating contracts to support their operations, sign them, file them and forget about them.
According to Ashwin Iyer, Vice President of Partner Marketing at Icertis, the typical legal team spends hundreds of thousands of dollars negotiating the best possible terms in contracts to ensure their organization gets the best possible deals. Then what happens to the documents? They sit on hard drives somewhere, and nobody looks at them again unless there’s a problem.
Generative AI (GenAI) simplifies understanding and useability of commercial agreements
Generative AI (GenAI) has the potential to transform the contracting practices of companies by significantly reducing the contract writing and review times as well as making negotiations of commercial agreements more effective. This is a positive development in the slow and often complex contract management process. It may start with the pre-execution of master service agreement (MSA) and continue through the creation of statements of work (SOWs). GenAI ensures that everything that is outlined in the MSAs makes its way into the SOWs.
In practise, the advanced software technology, contract analytics extracts useful information from legal documents. The Natural Language Processing (NLP), analyses language within contracts, highlighting important details and providing a clearer overall picture across a company’s legal portfolio. This Gen AI module, has the capability to access, extract and transform text data from thousands of PDF documents into machine language, creating a single repository of digitalized contracts, centrally stored on the cloud and accessible by GenAI.
With its unique data management capability, GenAI can identify and maximize the opportunities that are hidden in a company’s contracts by facilitating easier access for all teams dealing with legal contract terms, clauses, and obligations. GenAI does this by constantly sifting through the language and making sure that all obligations that were agreed upon are adequately highlighted, as a consequence covered in the process.
GenAI can respond in understandable terms to a question such as ‘Is the contract’s indemnity clause compliant with our company policy. This allows business users to “converse” in natural language with their contract intelligence systems, asking questions about the ramifications of contract terms and receiving productive responses that are not subject to the interpretation of a legal personnel or third party. GenAI transforms static contracts into living entities that operate very much like helpful coworkers.
Seamless smart contract negotiation and composition
GenAI can generate close to 98% of all of the analytical work required to complete a new contract from the scratch because it has access to numerous previous contracts that are similar in terms of suppliers and vendors, it can make valid assumptions and then hand the work over to a human legal team to complete the baseline markups. Thanks to big data!
The technology enables users to ask a series of relevant questions to uncover unexpected risks during negotiations. Examples are: “Is there an indemnity clause? Does it comply with our rules? Is there a protection for personal information? Are we being safe with data?” The answers to the questions will allow GenAI to state the risk level of the contract.
Contracts are the essence of a company but it has been difficult to realize their full value because of their historical vague language and muddled understanding. However, with the emergency of GenAI, contract lifecycle management will be at the centre of business activity as enterprise systems for procurement, finance and sales management continue to converge to become an essential copilot for providing insight that has a direct impact on the bottom line.