As pioneers of AI contract review and creators of the Contract Review Automation (CRA) category itself, we are always interested in seeing new solutions come to market and their approach to automating the contract review process. In light of the growing number of companies offering varying degrees of contract review capabilities, we received several questions from customers and prospective customers about how these solutions should be evaluated.
Recently, there have been attempts to answer this question by trying to classify the AI capabilities of each solution. We actually believe that this is the wrong approach from a client’s perspective since it is extremely hard for anyone other than the AI provider themselves to truly evaluate what’s “under the hood.” The right approach, in our view, is to put aside the technical jargon and focus on the client’s desired goals and the tool’s ability to actually deliver on them.
To provide some valuable context, LawGeex began seven years ago with the vision to automate the contract review process so that legal teams would be able to completely delegate this type of routine review work to technology, thereby freeing up their time to work on more strategic initiatives. After working with many clients over the years, we realized that the level of accuracy and customization required to delegate entirely to a machine was not quite the right approach. Our experience has taught us that AI alone is not yet sophisticated enough to handle the complex nature of contracts. As is the case with many other fields (e.g., autonomous vehicles, manufacturing robots, creditworthiness, etc.), and with many advanced, well-known AI-based applications including Facebook and Google, actual humans are required to close knowledge gaps and properly train the AI until technology reaches the desired level of maturity.
This realization allowed us to move from an AI-only model to that of “Managed AI,” combining the capabilities of both artificial intelligence and human expertise. This model delivers more accurate results and empowers clients to truly delegate their contract work with complete confidence.
Accuracy is Table Stakes
As a company made up of experienced commercial attorneys and data scientists, and after several years providing solutions for lawyers, we can say that quality is by far the most important criteria. Contracts are complex and sensitive in nature, and lawyers are especially cautious when it comes to contract work. One small error or oversight can have detrimental effects on a company.
While AI-only contract review solutions offer almost instantaneous results, the general consensus among in-house attorneys is that Managed AI solutions are more widely adopted because they provide “peace of mind” to truly delegate contract work. This is supported by many conversations we’ve had with legal teams who say Managed AI gives them “time back” that can then be spent on higher-value work.
It all comes down to accuracy. When the output is not accurate, the legal professional is still required to read the contract from A to Z, fix inaccuracies, and even worse – identify and address legal mistakes. In other words, AI solutions delivering inaccurate outputs just create overhead.
The Managed-AI Advantage
Humans play two important roles in Managed AI. First, they help label the data that will be fed to train the algorithms. Second, they correct any errors made by the AI to improve the accuracy of future results, offering a continuous loop of quality improvement. We employ experienced data scientists and commercial lawyers to train and improve our AI; AI-only solutions mainly rely on their clients to perform this training work.
The bottom line is that with Managed AI CRA, legal teams no longer need to read the whole contract to mitigate risk and ensure there aren’t any red flags hiding in the contract.
Speed to ROI
In addition to being far more accurate, Managed AI solutions are also easier to deploy. They are often “pre-trained” which means the AI has already been taught to identify and understand the various legal concepts and legal nuances using external legal data. Consequently, this creates a quick and seamless onboarding process that only takes a few days/weeks.
To truly evaluate speed, it is critical to take into account the entire lapse of time between the moment the contract is being sent to the AI solution and the moment the contract is actually ready for signature.
Managed AI solutions return superior results from the onset, so the business is not dependent on the legal team’s review, resulting in a much faster overall time to close the deal. This also means other business units can tap into the power of the Managed AI CRA solution directly, to easily send contracts for review and receive redlined contracts back based on the company’s policy, eliminating any legal bottlenecks and accelerating deals.
Similarly, when the redlined contract needs to get escalated to the legal team from the Managed AI solution, the second pass review happens much faster due to the higher accuracy levels. This results in significantly higher time/cost savings for the in-house legal team.
AI vs Lawyer
LawGeex was actually featured in HBO’s “The Future of Work” series in an episode that pitted our AI against an experienced corporate attorney. Spoiler alert: our AI outperformed the human lawyer. The attorney took over an hour to review two contracts which he did with 85% and 83% accuracy, while our AI achieved 95% accuracy on both contracts within 18 minutes.
While it’s true in this case that our AI-alone solution outperformed the attorney, what we have heard from our clients and know to be true ourselves, is that the combination of artificial intelligence and human intelligence (i.e., Managed AI) offers superior accuracy and is far more reliable than AI-alone.
AI as a technology hasn’t fully matured and still needs to be trained. Do you want to train algorithms and supervise AI, or do you want a trusted partner to do the heavy lifting for you? Since AI alone cannot yet achieve the flawless precision legal demands, I think we can agree: Managed AI is the way to go.