Our Story

Business Partners from Day One
Concannon Business Consulting was founded to address the growing need for experienced project and program management teams across a variety of industries. Our team is comprised of experienced resources that deliver immediate project impact and value for our clients, with the mission of 100% customer satisfaction. Our company has grown from two business partners to dozens of consultants servicing clients in the automotive, financial, high-tech, hospitality, retail, and consumer packaged goods industries.

Locations

» Los Angeles
» Dallas

Latest News

inquire@concannonbc.com

+1 949 419 3801

Top

Contracts Management Artificial Intelligence: What’s Actually Possible?

Concannon Business ConsultingContracts Contracts Management Artificial Intelligence: What’s Actually Possible?

Contracts Management Artificial Intelligence: What’s Actually Possible?

With all the buzz around Artificial Intelligence (AI)-driven technologies for autonomous vehicles, chat bots, translation engines, drones, and robots, it’s easy to forget that AI technologies have strong potential in the document management space.  However, for professionals who draft, manage, negotiate, and review contracts and supporting documents on a regular basis, the topic of AI within the industry has probably come up in conversations recently. In just the last two years, a host of companies with AI-driven tools have popped up with promises of streamlining workflows, automating reviews, and lowering the number of legal staff needed to handle contract workloads.  But how much of this is actually possible today vs. just wishful thinking? Based on an extensive review of available tools and trends, in this article we’ll provide insight on what’s possible today, what should be possible in the near future, and what the industry will still be working toward years from now.

 

How It Works

First, it is important to understand at a high level how new software tools enabling contract management actually work.  The technology in AI software available today uses a combination of Natural Language Processing (NLP), Machine Learning, and various data models to learn and improve over time. The tools are reliant upon data – lots and lots of data – which is used to train the software. In order to perform contract management tasks, the software must be fed hundreds to thousands of example contracts or documents.  This sample data is processed and used to train a model that incorporates business rules and term recognition. Through this learning, the software understands similar terms such as “breach” and “default”, that otherwise might be missed when searching for one or the other. On top of this processing, many tools also leverage configurable business rules to create action steps (ex. Which state(s) are valid for governing law).  The software essentially is only as good as the data it receives and the rules that are added.

 

Capabilities Today

AI-driven contract tools from providers such as Kira Systems and LawGeex have a number of capabilities that can help procurement and legal teams today.  Although these tools are still quite far from a true hands-off system managing complex contracts processes, several benefits can still be realized from implementing these tools in the right context.  We roughly bucket current capabilities into three categories:

 

Clause Management

Most organizations that handle large numbers of contracts develop a library of common clauses that are used across contracts, vendors, and clients.  While there might be informal processes for implementing, tracking, and updating these clauses, it’s fairly rare for teams to have any assistive tools or formal processes in place to make the most of this knowledge capital.  AI-driven tools today can process and organize contracts by common clauses, allowing for ease of reference and contract comparisons across multiple documents. Formal clause management can make it easier for teams to use standard, recommended language when authoring contracts, and also make updating contract language and terms simpler in the future.

 

Retrospective Analysis

Many of today’s software tools are targeted at helping organizations manage large repositories of contracts, enabling automated analysis and processing with low effort.  For example, automated analysis of contract metadata and terms using NLP can quickly categorize contracts by type, client, risk level, renewal date, etc. Automated tooling in this space can help teams uncover gaps and inconsistencies in existing contracts that need to be rectified, flag contracts that are out of compliance with updated corporate policies, and can also speed up information discovery for future negotiations and renewals.

 

Simple Contract Review

Although today’s tools are still far from being able to handle highly complex or poorly structured contracts, they are becoming increasingly capable of assisting in reviews of simpler contracts that come up often.  Standard template contract types, such as Non-Disclosure Agreements (NDAs) and Master Services Agreements (MSAs) can be trained into AI-driven tools to enable automated first-pass reviews. This typically involves a combination of non-standard language flagging, compliance checking against procurement and legal policies, and case-based clause recommendation.  In many cases, these tools can speed up contracts review workflows for simpler contracts, even though a final human review is usually required prior to sign-off.

 

Future Potential

Thanks to rapid development in the AI space, new tools and technologies are gaining momentum with the potential to bring even more automated capabilities to contracts management processes.  Based on the state of the art today and development roadmaps in the space, we see three key areas of potential being developed in the next few years:

 

Automated Standard Clause Development

Especially for smaller organizations that might not have large legal teams developing standard language for all types of contract clauses, AI-driven tools will soon be able to help.  By analyzing existing contracts, learning from human inputs, and drawing from industry best practices, software can help establish standard contract clauses and recommend or enforce their use in future contracts. This is a natural extension of today’s tools that often require manual input of standard language.

 

Advanced Proactive Analysis

Some of today’s tools can already make certain proactive suggestions during contract reviews, such as recommending preferred language, flagging missing policy inclusion, and noting non-standard terms.  As software continues to improve, a combination of NLP and Machine Learning (both supervised and unsupervised) will be able to assist with more advanced contract review prior to execution, allowing contracts professionals to focus on negotiation and risk rather than basic compliance.

 

Flexible Contract Type Processing

Since AI-driven tools by their nature become more capable as they are exposed to more data and are trained on new models, it is only natural that these tools will gain the ability to process more and more types of contracts over time.  Rather than being limited to specific contract categories and standardized structures, future contracts management automation tools will be more flexible both in the types of contracts they are able to handle and in the level of language they are able to accurately assess.

 

Looking Forward

The use of AI is a promising development in the contracts management space, and one that we are excited to see continue to evolve every year.  It is important to remember that no tool now or in the near future will be able to completely replace contracts professionals, but it is becoming increasingly clear that the right application of AI-driven tools can have a positive impact on contracts workflows and team throughputs.  When paired with the right people and processes, these new tools should definitely be on the radar for procurement and legal teams.

Tricia Go