Document management is the way in which companies or organisations classify, secure, approve and complete elements related to the management of the company or organisation. Legal and HR teams in companies manage a large number of documents every hour, every day and almost every minute. Document management is time-consuming and, in the face of high workflows, leads teams to perform less efficiently and make mistakes.
Legal operations refer to the operations necessary for a functional legal department. These operations ensure that legal departments can provide more effective legal services.
According to many business forecasters and market statistics, Legal tech has been receiving a massive amount of investment worldwide. This makes us wonder what does it really mean for the Legal professional and how is that money being spent?
We can all agree that Artificial intelligence, better known as AI, is one of the most trending topics in 2020. However, due to the complexity of AI and its vastly broad horizon, the technology can be hard to understand. And this false perception of AI has made individuals become skeptical and made those who don’t understand it fearful.
Not only that, but the idea that sci-fi movies have portrayed about AI over the years has majorly confused many of us.
The innovation in technology has definitely changed the way tasks are performed within many different industries. Technologies like artificial intelligence, document automation or blockchain, have heavily disrupted how daily regular tasks are performed within companies and organizations.
Artificial Intelligence systems are becoming significantly important to Legal technologies nowadays. We can all see how AI has already found a way to support advocates and clients positively and efficiently. At the same time, the investments in the legal tech are skyrocketing and that is mainly because the demand for new innovative tools that enhance the legal process is higher than ever.
In fact, investment in LegalTech skyrocketed to $1 billion in 2018 - and much of this funding was injected into AI and machine learning platforms.