AI in Legal Practice

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The legal service sector is one of the largest markets in the world, yet remains very traditional and – by extension – manual. It is, however, starting to adopt new applications and processes to become more efficient and accurate.

The similarities between Law and Machine Learning are greater than you might think, as they both follow similar principles. This becomes clearest through the act of looking at historic examples to create rules, which are then applied to new situations.

As AI is being applied into law, the work of paralegals, litigators and legal researchers are slowly transforming. AI is able to help lawyers with due diligence and research, provide additional insights and increase the automation of tasks. 

How is AI Used in Law and Legal Practice

Contracts

Administrative tasks are famously numerous within the legal sector, and often can be a dreaded task. Creating, negotiating and following up on contracts is a lengthy process, and a client’s changing needs can mean that the entire process has to be restarted multiple times. Natural Language Processing (NLP) has evolved, now being capable of reading contracts and comparing them to a client’s demands, creating a clearer depiction of how beneficial a proposal might be.

Additionally, it can be hard to monitor and track the contract performance to ensure all obligations are being met. Especially in companies that juggle many contracts with different parties, this can prove a lengthy process. AI tools that are powered by NLP provide a solution to this issue. Key terms within the contracts can be extracted and conceptualised, then compared against company metrics. This then shows how contract terms are being followed, and when problems are flagged these can be rectified far quicker.

Here are some companies leading the way in revolutionizing working with contracts:

Legal Research

As already mentioned, machine learning follows the principle of creating new rules and predicting data through analysing past situations. This proves especially useful for legal research – as AI is able to look through thousands of case files with just a few clicks, going beyond traditional keyword searching to a far more in depth method of distinguishing useful cases. 

This would greatly reduce the amount of time and effort required to build cases, and increase the chances of finding far more relevant and accurate information – therefore increasing the chances of success. In addition to reducing the time required, automating the research process would allow firms to give more accurate estimates on the costs of legal fees due to the streamlining of a large portion of case building.

Here are some companies leading the way with revolutionizing Legal Research:

Prediction Technology

AI can predict the outcome of a case based on a data driven assessment including relevant precedent, facts of the case, and prior outcomes. This can help with building litigation strategy, as well as helping investors decide which cases to finance based on the likelihood of success. 

The applications of predictive technology also go beyond simply guessing the likelihood of success in a case, with AI now having the ability to predict a case’s length and funding requirements, as well as giving a more detailed picture of the possible outcomes. 

Here are some companies leading the way with legal Prediction Technology:

Is AI the Future of Law and Legal Practice?

The significant size of the legal market means that there is plenty of opportunity for AI to progress. The field of law will continue to change, as artificial intelligence and NLP continue to grow and create more accurate predictions or reports.

The importance of implementing these technologies will also grow, with the streamlining capabilities of AI meaning that those that utilise this technology effectively will find themselves moving faster, cutting costs and taking on more cases. The changes are already starting to be felt within the Legal sector, and here at Geniusly, we can help you get started on your journey to building a more efficient workplace with AI.

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