Today, law firms of all sizes are under tremendous pressure to minimize costs, while still providing top-tier client service. This is propelling an “arms race” in implementing innovative technical solutions, and nowhere is this more evident than in the pace of adoption of Machine Learning technologies. Formerly only available to sophisticated BigLaw firms, the market has expanded to include small and medium law firms as well.
For lawyers and their clients, one of the most time-consuming tasks—yet integral to nearly every merger or acquisition—is due diligence, in the form of contract analysis. Contract analysis often becomes a bottleneck that slows down deals and requires time and energy from junior attorneys. Large firms with pools of junior talent are simply able to allocate more brainpower to read through thousands of pages of dense and complex customer and vendor contracts, employment agreements, leases, license agreements and other legally-binding documents that must be reviewed to ensure potential risks associated with the transaction are identified. However, small and medium law firms don’t always have that deep of a bench to spend those hours.
This is where Artificial Intelligence solutions, in the form of Machine Learning, can level the playing field. Contract analysis solutions can analyze hundreds of documents—not just read and search keywords—in less time than it takes a human to finish one. (Try your hand at beating the AI in this example!) A solution that just searches for words is not truly useful in the legal profession where concepts can be expressed in multiple, nuanced ways. A true Machine Learning solution delivers the greatest value because it can be taught to seek out specific concepts.
Let me give an example: when teaching a child the concept of a “cat,” you show them various pictures, cartoons, or videos of cats until they can independently identify a cat when they see one, whether it is orange or striped, sleek or fluffy. By teaching an AI solution the concept of Change of Control (an important provision in an acquisition), which can be expressed in language such as “assignment by operation of law,” “sale of all or substantially all of a company’s assets,” or even “change of control,” it learns from examples and is then able to identify the concept regardless of how it’s expressed or where it might be located in a contract. Instances of the concept are extracted or flagged for further human analysis.
In this context, the highest level of accuracy is achieved when the attorneys and software are working in tandem to keep important information from slipping through the cracks. Attorneys have to be highly detail-oriented and organized, with every instance of a potential sticking point or questionable phrase noted and dealt with. AI is making attorneys more efficient and measurably more accurate, able to find every instance of a concept across many more documents than human limitations would allow staff to review.
Too often, those of us focused on AI solutions hear that our efforts will completely eliminate the need for X, Y, or Z professions. I don’t believe that is the case. Technological advances in the workplace are not new, and given the varied knowledge bases required for most professions, these opinions feel sensationalized. What I do believe is that there are certain tasks that can be automated, made faster and more efficient, but the most successful implementations of AI solutions will continue to augment and complement skilled human knowledge workers, not replace them.
At a time when clients are already putting pressure on law firms related to billable hours for lower-level tasks, reducing the hours associated with the routine elements of due diligence leaves more time for those attorneys to do creative and higher-function work. And if a tool can’t help people do their jobs better, to achieve more, what good is it?
Learn more about AI, Machine Learning and Legal expertise in this interactive infographic.