AI Isn’t the Future of Law: AI-Assisted Lawyers Are

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Corporate legal departments (CLDs) are meant to advise organizations on how to manage risk effectively while ensuring corporate compliance. But sometimes, teams find themselves spending inordinate amounts of time consumed with tasks that inhibit productivity, forward thinking, and the ability to contribute positively to their companies’ core goals. Put another way, advisors need advice too.

Artificial intelligence is here to help—“help” being the key word. According to a survey from Wolters Kluwer ELM Solutions, lawyers are showing an increased appetite for new technology, with more than 42% seeing AI as providing an opportunity for lawyers to focus more on high-value, strategic legal work. AI has the potential to touch almost all corners of CLDs and improve numerous processes and workflows—efficiencies that translate to lower costs, more money for a better bottom line, and better litigation and risk management outcomes.

Yet the application of AI must be done correctly to be effective – AI for AI’s sake will just result in lost time and frustration, without any meaningful impact. Fundamentally, AI must be supported by a large amount of data that is curated from a wide range of sources by experts and situated as part of ongoing feedback loops. Additionally, it’s ideal when some of these data sources come from large and broad data sets aggregated across multiple companies.

Finally, AI cannot operate independently. It must be paired with seasoned professionals to parse the information gleaned from AI and make it actionable and valuable to legal teams.

In short, AI-assisted attorneys—not just AI—are the future. With that in mind, here are three specific ways AI is helping CLDs—and the lawyers who comprise their teams—evolve.

1. Contract creation.

A constant workflow of any CLD is creating contracts, and much of the time spent creating contracts is extremely repetitive work. Junior attorneys spend copious hours looking for standard language to repurpose or recreating the wheel to avoid the search process. Neither option is efficient. AI can automate routine tasks like this for legal teams, allowing attorneys to focus on higher value work.

To be clear, AI doesn’t just automate the contract process by generating a document based on past agreements and pre-approved language; it can go far beyond that, actually tracking what kinds of clauses tend to get disputed by counter-parties. Using that information, AI can suggest initial and fallback clauses that won’t trigger pushback. It can also compare legal arguments and clauses against contracts for similar topics to create the most holistic clause possible. Having a machine do this work saves a great deal of time and money—and results in a contract with better, more consistent safeguards and provisions.

Of course, lawyers must still go through and make changes as needed to finalize the process. But complex contracts start at a much more polished state; major sections don’t have to be replaced because of nuance or complexity. And AI can improve the workflow component as well, finding clauses that need to be reviewed and facilitating internal approvals. More specifically, AI can classify work items into high, medium, or low complexity and route them to the appropriately skilled people, who can then complete tasks more efficiently and effectively. Using AI in this way makes much better use of your highly skilled experts and gives them insights at their fingertips to help them provide the best possible counsel.

2, Predicting outcomes.

Algorithms can also help predict the outcome of litigation and determine the status of cases. Data on past cases—particularly ones with similarities in terms of jurisdiction or other factors—can be used to identify the costs and chances of success, and even provide an analysis of the best time to settle or move ahead with litigation.

AI can learn from past data to spot when a case is about to “go sideways” and alert lawyers to any potential issues. Any individual lawyer likely has a large number of cases and might not be privy to hidden information in the data that shows something is about to go wrong. But AI can catch it and notify the attorney so they can address the situation before it becomes a problem.

3, Bill review and analysis.

Invoice review processes can be extraordinarily time consuming and often do not result in the desired outcomes or savings. Plus, manual reviews can be error-prone and confusing; billing guidelines can be misinterpreted, for example, leading to discrepancies that can make bill analysis and evaluation difficult. This can result in slower payments and frayed relationships between reviewers and law firm partners.

AI has an edge over human experts in the invoice review process because it is able to identify trends by looking for billing patterns at the timekeeper and/or at firm level. But humans are at better at understanding the context behind a particular line item or invoice. When you combine these two powers through AI-enabled bill review, the end outcome is far superior than each one on its own.

Where we go next

Although the many benefits might make AI seem like a no-brainer, the change management process can be daunting. People are often resistant to change, and even the smallest changes can result in pushback. The move to AI is a fairly big cultural, process and technological change that may initially be a tough sell to internal constituents. However, many technology partners can help with the transition, so be sure to take advantage of their experience and any guidance they have in implementing a new AI-enabled process.

So, no, AI will not replace lawyers. Instead, it’ll make them better lawyers.

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