A Simple Guide to Contract Automation

Contract Automation

A contract is at the core of most business deals. But despite its significance in transactional workflows, many firms haven’t changed how they review them, primarily following manual approaches. Consequently, reviewers spend more time skimming through and extracting data to design and negotiate contracts of different complexity levels while shielding their clients from risk.

Savvy professionals now leverage contract review automation tools to make contracting faster, more predictable, and more precise. In fact, a recent report by Gartner predicts that by 2024, cutting-edge AI contract review solutions will cut the manual effort by 50%.

But what does automated contract reviewing entail, and what makes this AI contract technology a more attractive option for experts seeking to enhance their contracting? This guide will shed more light on contract review ai tools and how it’s revolutionizing business transactions.  

The Hurdles of Manual Contract Review

Compared to AI contract technology, manual contract review has several nuances. The most common hurdles at different stages of contract review include:

Difficulty in Finding Information

The answers to a particular question are not always where you might anticipate, but can be found in several locations within a contract or across different documents that are related. Searching becomes even more complicated when you scale to hundreds or thousands of contract negotiations a year. When clauses are in various documents or locations, their initial meanings can be altered or superseded; hence the need to identify logical relationships between references.

Varying Legal Language and Meanings

When going through a contract, you must look beyond the plain text to compare what the phrases mean, not just language. But interpreting legal meanings isn’t always cut and dried, and some attorneys might determine that the differently expressed meanings are effectively similar. Also, two lawyers may fail to agree on an interpretation or meaning.

The Context-Awareness Hurdle

Any contract evaluation is aimed at understanding its meaning. Reporting is the ultimate end goal, not review. Every transaction’s context affects risk, so the report must translate legal language into a business language to clarify materials and risks and match the policy position into your playbook. 

These are the primary hurdles associated with manual contract review, but you can go around them by leveraging automated contract review. 

What is AI Contract Review?

Lawyers and contract negotiators spend lots of time handling transactional and post-transactional stuff. When a task consumes a huge chunk of their workweek, there’s always an opportunity to ease the burden through contract automation.

In essence, this is a tech-assisted process where you’ll use contract software to assess and remediate a contract. This process takes a fraction of the time you’d take when doing the same task via the manual approach.

The primary motivation to shift to contract software is to tackle existing and new hurdles around workflows, risks, and reporting. You can easily access and extract data and clarify content, allowing you to review documents faster, lower the likelihood of contract disputes, and increase the number of contracts you can negotiate and execute.

What makes AI legal document review unique is its ability to create new models and algorithms using the available data to “instruct” the computer on how to boost tasks and applications without the need for new code. The availability of more data means it can refine its actions; hence AI can be beneficial when handling the nuances of contract reviews.

What Can Contract Review AI Tools do?

Generally, contract automation comes through by untangling the complexities of contract review by:

  • Identifying relevant legal language notwithstanding the location of information within a legal document
  • Comparing the legalese to previously defined terms or standard text
  • Checking for variation and consistency of legal language across a pile of documents
  • Enhancing context-awareness by comparing the liabilities and obligations of each party

You can achieve these opportunities to streamline the contract review process by teaching the automation technology the right skills. This means that you should match relevant automation techniques to the intended results. 

How Does AI Contract Software Work?

Legal AI software uses the following four techniques to review transactional documents:

Unsupervised Learning

Contract data is usually unlabeled, and the software will automate information discovery and mapping. It also extracts information, including facts, definitions, named entities, and clauses using regular or naïve expression rules or complex, deep learning networks.

Supervised Learning

Automated contract review solutions have search capabilities that use pre-mapped data inputs labeled by humans to identify relevant information to address specific questions. This may include discrete extraction and interpretation of legal language from contracts in mass.

Language Modeling

Attorneys must evaluate and regulate crucial entities and different facts like financial data, dates, organizations, and people’s names. The search capability isn’t prediction-based, but a precise value of specific facts.

Understanding the contract context deeply and semantically requires going beyond identifying shadow connections between the search query and potential answers. It should also determine how much a crucial section of the contract differs from the standard language in a similar context other than the textual and syntactic similarity.

This should begin with identifying answers to crucial questions, not just identifying clauses. Contract review automation tools then use discreet legal language in the form of linguistic content matching. This compares contractual language to client playbooks, positions, standard terms, or negotiating knowledge bases.

The last phase involves deviation analysis. This highlights notable differences, identifies the areas that need obligation change, and assists the reviewer in managing liability and risk assessment.

Self-Teach

This approach enables in-house model training, machine learning, and data science iterations. You must first identify appropriate data within the contract repository before AI tools can take the chosen document and recommend any annotations.

Doing this eliminates the need to meticulously review a long contract and identify the items to be annotated. All marked-up agreements are then entered into a model training component. Finally, the process loop concludes with evaluating user satisfaction levels to ascertain the model’s readiness or the need for more training data.

Get Yourself a Reliable AI Contract Review Software

It’s clear that contract software is transforming how businesses operate. But for the best results, you must always rely on the best software technology. Fortunately, you don’t have to search for long.

BlackBoiler’s AI technology is the only patented contract review software that instantaneously reviews and redlines legal documents as a human would. Request a demo today and see how it works.

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