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Predictive analytics
Introduction
The legal industry which has always been considered as one of the industries that are not keen on changes and technologies is going through a significant change with the help of Artificial Intelligence and Machine Learning strategies. The application of AI and ML in predictive analysis is fast growing due to the fact that legal professionals are looking for ways through which they can add value through efficiency and reduced costs. Predictive analysis is the use of artificial intelligence and machine learning to evaluate previous information with a view of making a guess of the future outcome, a technique that is useful in the hands of legal experts. All the same, this transformation is not without its problems and this article discusses these problems as well as the opportunities that AI offers, the advantages that come with the use of AI and some examples of application.
Challenges
There are however several challenges that hinder the integration of AI and ML in the practice of predictive analysis in the legal industry. The first challenge is that the legal community has always been conservative and has not been keen on changes or innovations and many lawyers are not comfortable with the idea of being replaced by algorithms. Another challenge is that while implementing AI, the problem of how to deal with the issue of legal language and the complexities of its interpretation by the AI systems remains a challenge. In addition, there is a question of data privacy and security since legal data is often considered to be very sensitive. Finally, one can list such obstacles as the expenses that are necessary for the integration of these technologies and the absence of the necessary expertise in the field.
AI Solutions
Despite these challenges, there are a number of AI solutions that are being developed to implement the use of predictive analytics in the legal industry. ROSS Intelligence and LegalMation are examples of platforms which apply artificial intelligence to legal research and analysis of the legal outcomes, thus decreasing the time and money spent on the process. Likewise, predictive coding tools have been adopted in eDiscovery for the task of document review. Some of the companies that are integrating artificial intelligence in the legal industry include Casepoint and Relativity to help legal teams to identify patterns and relationships in data in order to easily and efficiently identify relevant documents. Also, there are other AI tools such as Blue J Legal’s Tax Foresight that is used in determining how courts will rule in tax law cases giving lawyers an idea on what has been done before.
Benefits
There are many advantages of using AI and ML in predictive analytics for the legal industry. These technologies can help in performing boring tasks which lawyers can then use for more important tasks. They can also help in making better estimates of the legal results thus allowing lawyers to better counsel their clients and themselves. In addition, these technologies can greatly cut on the costs as they can work through large amounts of data much faster and with higher precision as compared to humans. They can also help to ensure equality in the provision of legal services as AI legal solutions can as well be made available to people at a relatively cheap cost.
Return on Investment
It is possible to achieve a high ROI when implementing AI and ML for predictive analytics in the legal industry. For example, a study by McKinsey published in 2019 revealed that AI has the potential of reducing costs by 10% through process automation in the legal industry. Furthermore, a report published by Market Research Future state that the global legal tech market which includes the use of AI and ML is anticipated to grow at a CAGR of 37.5% from 2020 to 2026 which means a good ROI for firms that decide to use these technologies.