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AI vs. ML in CLM: Making Sense of Contract Management Technology

Sarvarth Misra. AI, ML, CLM …the world of contract management has found itself inundated with technology terms. Ultimately, this is good news: 9.2% of revenue is lost by organizations resulting from poor contract management and oversight, both problems that can be alleviated by using technology that improves the contract management process. Even better, making sense of the terms behind this technology doesn’t have to be rocket science.

Before we dive into the details, let’s do a quick review. CLM stands for Contract Lifecycle Management, a software that can be powered by Artificial Intelligence (AI) and Machine Learning (ML) to improve the contract management process for in-house legal counsel teams.

Read more: Seizing Artificial Intelligence’s Opportunities in the 2020s

What’s the Difference Between Artificial Intelligence and Machine Learning?

If a CLM is powered by both ML and AI, what’s the difference? Essentially, ML is a subset of AI.

When someone says that a machine uses Artificial Intelligence, what they mean is that the computer system is able to perform tasks that normally require a human. From a contract management perspective, AI is like the human brain reading and interpreting a contract. It’s picking up key aspects like a contract’s clause, statement or part of the agreement.

ML, on the other hand, is the study of algorithms a computer uses to perform tasks without explicit instruction. It’s like the tutor to AI’s brain, training the AI of a CLM on how to read contracts and what to keep an eye out for.

Why Is It Important to Understand AI and ML?

If both AI and ML improve the contract management process, why does it matter how they are different?

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As it pertains to CLM, the nuances between AI and ML can impact the amount of work required of a legal counsel team.

A CLM that only incorporates ML will require the general counsel, legal operations team or contract manager to train the models. Since it doesn’t incorporate AI, it’s like having a tutor without a brain. To create the intelligence required to ultimately be more efficient, the general counsel will have to feed the software a large volume of contracts and spend a minimum of six months testing, training and retraining the system.

A CLM that incorporates AI, on the other hand, will also automatically include ML (since ML is a subset of AI) and is delivered pre-trained. This is like bringing an extra brain to your team, which is equipped with experience evaluating hundreds of thousands of contracts and legal documents.

If AI Must Be Trained, How Is It Trained?

Just like you’d evaluate a new hire for your team, you’ll want to get a sense of the experience behind AI’s brain. A CLM can have the AI trained using a few resources:

  • A public/subscribed libraries of templates
  • A set of contracts and unique templates from your specific general counsel
  • By specialists like legal engineers, who understand the subtleties of ML as it pertains to the legal space

Once trained, either with or without resources from your general counsel, a CLM is ready to be used right away. That being said, like any brain, it’s helpful to encourage it to keep learning. Using a legal engineering team to adapt and retrain the AI on an ongoing or periodic basis ensures the system will continue to evolve with your needs.

Remember: Both AI and ML Are Essential for Simplified Contract Management

Your in-house legal team is incredibly intelligent, so it is essential to select a CLM that’s just as savvy. Like any brain, it’s helpful to have a tutor, which is why identifying a CLM that uses ML to train its AI is the most effective. As you prepare to manage tens of thousands of legal contracts on an annual basis, you may forget all the subtleties between the technology. Don’t worry, it’s simple: it’s best when everything is working together.

Read more: Leveraging Kubernetes to Fuel Intelligence Everywhere

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