The legal industry had been technology laggards until now, but the pandemic situation, ever-increasing pressure, and rising expectations from the clients have compelled legal firms to automate legal processes, adopt new technology tools and a new generation of legal professionals are willing to embrace technology and rethink the conventional way of doing business.
As the world is increasingly adopting technology, legal service delivery is changing its service models, delivery programs, and business structures in order to adapt to new demands. Business model innovations are firms building captive ALSPs, creating consulting and software lines of business, and creating client client-facing portals and chatbots to automate self-service delivery of legal expertise.
Adoption of Contract Management (Post-Execution) AI Platforms:
ILTA’s 2020 Technology Survey showed an uneven distribution of legal tech adoption by type of application, while Blickstein Group’s research found that eDiscovery and legal research were the applications that are further along the adoption curve, followed by pre-and post-signature contract analysis tools. Suppose we deep-dive into the post-execution contract management tools. In that case, they are used to gain visibility into contract repositories, accelerate, improve the accuracy of contract review and mitigate the risk of errors in the contracting process.
While AIs enhance visibility, they cannot perform on their own. They need a human element to ensure accuracy and consistency in their AI predictions, which is more supervised learning. In addition, the AIs need to be trained by humans to improve their accuracy, adapt to the changes in the legal provisions, and more. For this, legal AI companies partner with ALSPs to help them deliver and train their AI/ML systems.
How Lawyers in the loop add value to AI?
A lawyer can train AI contract management software to classify contracts. To do this, the lawyer provides a training set, such as a large number of purchaser and supplier contracts, to the AI. Next, the lawyer identifies the contracts for the AI. Then the AI gathers information from the training set to help it classify future contracts. Another scenario could be where a lawyer trains the AI (through annotation) to extract key data from contracts to provide an overview of important terms.
Cenza has deep domain knowledge and technical expertise and has long-standing work experience working with AI companies, particularly in the post-execution stage. We train AI and ML to extract raw, unstructured data and transform it into meaningful training datasets. Our AI training includes contract data annotation and contract type classification. Also, we train the AI to identify concepts, boundaries, and obligations with the human-in-the-loop process.
While legal firms have adopted AI or are considering the adoption of AI, they will need the training to learn about extracting contract data, pulling up vital information from legacy contracts to complete tasks with greater efficiency and effectiveness.