Blog Post

AI in the Legal Industry: 3 Impacts and 3 Obstacles

February 19, 2021

In-house counsel have always had an edge compared to their peers in law firms. Outside of the rigid law firm culture and compelled by their organization’s need to stay competitive, legal departments are better positioned to embrace change. That’s why any in-house counsel needs to keep their finger on the pulse of how artificial intelligence (AI) is affecting the legal industry.

In this article, we’ll talk about three current impacts AI has had on the legal industry as well as three obstacles it needs to overcome before we see widespread adoption.


1. Document analysis is no longer tedious

At one point, AI capabilities like natural language processing (NLP) and optical character recognition (OCR) only existed in university research labs. But now, they’re making the identification, understanding and analysis of text trivial — and as a result, contract review, eDiscovery, document review, due diligence and other document analysis tasks are quickly becoming yesterday’s work. Consequently, counsel will have more time to be proactive in identifying high-level threats to their organizations, to contribute to strategy and to accelerate the pace at which their business makes deals.

Today, the biggest use case for AI in document analysis is in technology-assisted review, or TAR. This technique uses machine-learning algorithms to support litigation attorneys during the time-consuming eDiscovery process by learning which characteristics make a given document relevant or not. With TAR, tens of thousands of documents can be accurately coded in weeks rather than months.

But eDiscovery is just the tip of the iceberg. AI is making all kinds of legal document analysis fast and uncomplicated.

Consider JPMorgan’s Contract Intelligence (COIN) software. Rather than rely on lawyers to pour over their commercial loan contracts, the banking giant now uses COIN to review these documents for risk, accuracy and eligibility. Not only does this save JPMorgan 360,000 hours per year in contract review, it also results in fewer errors. One can also look to major law firms like DLA Piper, which now regularly rely on AI for M&A due diligence. At Exigent, we’ve had first-hand experience using AI to support document analysis for our clients as well.

2. Effective legal operations is within reach

Legal operations has always suffered from a catch-22: Lawyers tend not to listen to non-lawyers on how to perform their work, and lawyers have neither the time nor the inclination to study operations management.

AI lowers the barrier to entry for effective operations management that accounts for the legal department’s unique needs. Rather than rely on dedicated personnel, much (though not all) of a legal department’s operational needs can be addressed by software with that essential operations knowledge baked in.

With the right data on hand, legal professionals can more easily plan for capacity in the legal department. Using an individual counsel’s hourly rates, past performance and areas of expertise, AI can recommend the optimal team member based on their availability and the task’s complexity, domain and priority.

Legal departments are also able to make better-informed decisions when managing their legal spend and law firm panel. With access to data on net promoter scores, past performances, quoted vs. actual prices, industry benchmarks and even prior case notes, legal departments can select law firms, individual lawyers or other vendors that best fit the task at hand.

Project management, capacity planning, vendor management and other legal ops tasks are well-suited for AI. Legal professionals are used to a high level of autonomy; having a data-driven system that provides evidence for why one method of working is more effective than another will go a long way towards improving project management in the legal department.

3. AI-powered legal research and predictions are becoming an indispensable tool

AI is already capable of performing sophisticated legal tasks like sourcing relevant cases, identifying precedents and predicting litigation outcomes. As the technology matures, using AI to conduct legal research and predict the likelihood of a lawsuit’s — or even a motion’s — success will become commonplace.

Consider the multiple university researchers that have constructed AI models that successfully predicted up to 75 percent of Supreme Court decisions using nothing more than the basic facts of the matter. Or FaXin, an AI tool that the Supreme People’s Court in China uses to identify precedents. Litigation funding companies already use similar tools to assess the likelihood that a litigant will be successful, helping them identify promising cases to fund.

We can expect these and other AI tools to speed up the pace of legal work, enabling senior lawyers to devote their attention to higher-level strategy and decision-making, while more junior members work on building up their knowledge and expertise.


These innovations are already taking hold in the legal industry to one degree or another; whether or not they achieve total penetration depends on how well the industry overcomes the following key obstacles.

1. Data privacy and security takes priority

The trouble with AI in the legal industry is that it depends on access to data. AI needs to be “trained” on datasets; before an AI algorithm can identify what characteristics make a given litigation outcome likely or what features make a contract high-risk for an organization, it needs to ingest data on the facts of the litigation or the terms and clauses of a contract.

The existence of this data isn’t the problem. In fact, legal departments are sitting on top of a mountain of data in their contract portfolio and business systems. Rather, accessibility is the problem.

Much of this data is confidential, subject to data privacy regulations, too sensitive to use in external systems or simply unstructured and difficult to work with. Before it can be used, there must be agreements with customers and partner organizations on what data can be used and how, a robust compliance program and effective cybersecurity in place.

2. Legal departments need to build cross-functional expertise

Given the amount of education that it takes to become a lawyer, there isn’t much appetite for learning new skills or entrusting non-legal experts with key elements of the legal department’s operations. And yet, bringing greater diversity into the legal department is essential if the efficiencies promised by AI in the legal industry are to be realized.

Fortunately, some legal departments have begun to bring data scientists on board in addition to lawyers. And the industry is beginning to open up to hybrid roles, like legal technologists, legal knowledge engineers, legal analysts and other cross-functional experts. It’s clear that a greater diversity of skills are in the legal department’s future; it’s just a matter of how smoothly the transition goes.

3. The legal culture needs to change

Lawyers are highly autonomous in their work and are authority figures by dint of their specialized skill set. What’s more, much of that skill set hinges upon their ability to minimize risk. And many in-house counsel are expats from law firms, where the focus is very much on the success of individual partners rather than that of the firm as a whole. Add these factors together, and you get a culture that’s about as resistant to change as possible.

Legal departments do have several advantages over law firms in this respect, however. For one, legal departments are part of a larger organization instead of a fully autonomous unit like a law firm. Thus, legal departments are under pressure to evolve and adapt along with their broader organization. And, perhaps most importantly, legal departments aren’t beholden to the billable hour — becoming more efficient isn’t going to cut into their profitability like it would a law firm’s.

Still, in-house counsel are going to need a push if they’re to adopt any new technology. Arguably, changing the culture is the most important factor in speeding the adoption of AI in the legal industry. Culture drives motivation and goals — with the right culture, hiring diverse skill sets, building up security infrastructure and ensuring access to data won’t be significant challenges in the slightest. Without the right culture, these obstacles might ensure that the legal department falls out of step with the rest of the business world.

For in-house counsel wondering how they can start changing their department’s culture, we’ve developed a guide to communicating technology needs. If you need to make the case for AI-backed contract management systems, analytics solutions or other technologies, we encourage you to read through it. Minimizing risk is all well and good, but it shouldn’t come at the cost of opportunity.