Artificial intelligence (AI) technology is transforming the practice of law and many in the legal profession are leveraging this disruptive tech to reduce time and costs while increasing accuracy. That said, some areas of law are more affected by this shift than others. In this article, we unpack how AI, when combined with lawyers in the loop, is altering the foundations of legal practice and delivery while addressing the looming challenges that firms encounter while implementing this technology.

Today, more than 80% of senior lawyers consider AI and machine learning criticalto the future success of their firms. However, this interest doesn’t translate into actual deployment, with 54% of all law firms indicating that they are not presently pursuing AI options for their legal practice.

One of the reasons why the legal sector has considered AI technology as a red herring is that AI might make lawyers obsolete, which couldn’t be further from the truth. Current AI technologies, when combined with lawyers in the loop, help accomplish narrowly defined work and automate repetitive and time-consuming tasks at lesser cost while adding value that machines lack i.e. critical thinking and cognitive function.

On top of that, the pandemic has altered the fundamental way the legal industry operates. Firms of all sizes have been forced to take a keen, hard look at their business models and embrace agility, accelerating AI adoption across the board.

In this article, we discuss the challenges in implementing such tech, lawyers in the loop, and, how companies like Cenza help Legal AI companies increase the tech adoption rate with successful implementation.

Top 3 challenges of implementing AI in legal firms

While COVID-19 marks a tipping point in the use of AI technology in law firms and legal, the shift also means several challenges that must be overcome to ensure long-term success. Here are the top three challenges of implementing AI in the legal industry:

1. Resource allocation for AI training  Training the AI can be a long and cumbersome process, requiring heavy resource allocation on the part of legal firms. A team of specialists with the technical know-how and business understanding need to be assembled to train the AI for accuracy.  This combination is hard to come by since there is a knowledge gap in the legal sector in terms of AI use cases and the mechanisms that power it.
2. Vendor assessment vendors who can show tangible proof of their AI/ML expertise i.e. case studies. With hard data on how they helped similar clients in the past, you’ll be able to accurately assess if they can address and resolve your pain points and successfully implement AI technologies for your firm.
3. Integration challenges Integrating AI into existing systems can be a complicated process. By relying on specialists, you ensure that the AI capabilities are top-notch, and the data or feedback loop is built to account for continual system updates.

Current application of AI in legal services

1.  Document Review Research reveals that due to outsourcing or automation at larger law firms, lawyers now only spend 4 percent of their time on document review. ML algorithms, trained on large volumes of documents, case files, and briefs, can identify and prioritize relevant sources, reducing the time and cost of document review, while increasing its accuracy.
2. Contract Drafting and Review AI tools can create form contracts with standard terms and conditions with the help of predefined parameters, usually set by a legal department. Additionally, AI can analyze contracts by reviewing large numbers, organizing contract data, and locating data. 
3. Legal Research Instead of spending unnecessary time on legal research, AI enables lawyers to find relevant cases, including regulations, case law, secondary sources, and more. It is important to remember that there is a monumental gap in the AI and human intelligence, and one cannot replace the other.

Legal AI still needs Lawyer-in-the-loop

As the term suggests, a lawyer in the loop system means having a human legal review team closely integrated with your AI initiative. One must understand that AI doesn’t replace the role and function of lawyers, but augments their performance.

This approach ensures low-level tasks are executed primarily by the AI. Sometimes, AI will do the whole task, with a responsible lawyer retaining oversight. On other occasions, the AI will simply prepare work for the lawyer to do, thereby improving efficiency. When applied successfully, this approach can allow the tech and the lawyers to learn from each other.

However, since most corporate law departments are understaffed, establishing a formidable AI initiative in tandem with lawyers in the loop could prove to be a handful. This is where legal outsourcing companies or managed legal service providers come to the rescue.

For example, Cenza worked closely with a US-based company that provides AI-powered contract management and analytics tool for in-house legal and finance teams. The client was looking for assistance in developing accurate machine learning models, with a low margin of error.

Cenza developed seamless integration with the client’s AI platform, completing multiple layers of review on a diverse set of over 100,000 contracts, and annotating more than 1 million key terms within a three-month timeframe. Our fully qualified lawyers who are experts in contract management, helped in contract data annotation, thereby creating training data/ground truth data for machine learning.

With the help of our Lawyers in the loop, the machine learning accuracy was improved for the client and the system was successfully implemented with better results.

Final thoughts

Law firms need to embrace AI to remain competitive in the industry, freeing themselves from mundane work and focusing on what matters more: client relationships. By partnering with a company like Cenza, you can accelerate the learning curve of your AI platforms and set yourself on a path to success.