Whitepaper

Maximize The Potential of Artificial Intelligence For Your Legal Practice

Artificial intelligence (AI) is gaining greater acceptance among legal professionals for several important reasons. One is that AI can help solve budget and staffing challenges that are often connected with analyzing large sets of electronically stored information. This can, in turn, enable law firms and in-house legal teams to uncover the story that might be hidden within the data as well as more effectively evaluate information to clarify key issues, confidentiality and case relevance.

But to realize these and other benefits, many legal professionals have to solve a pressing challenge: how to evaluate the potential of AI. This includes AI in general, as well as specific AI solutions and how to implement them in a way that effectively supports the practice of law. Legal professionals can meet this challenge through a better understanding of AI solutions and how they can help attorneys advance their day-to-day activities.

Start with Analytics

A good place to start is by concentrating on analytics. The key point is that AI can be used to improve the quality of your data for sound decision-making. This is particularly relevant to the legal field because most attorneys and litigation support staff spend a significant amount of time analyzing data. This can often mean entering into a situation that requires quickly becoming familiar with client data, spanning documents and other elements, and determining how that data might affect a particular matter. Bottom line, dealing with analytics and data is a major part of what legal professionals do.

When considering using AI to enhance your analytics processes, it’s helpful to determine if your application of AI falls into any of these three categories: descriptive, predictive or prescriptive analytics.

Using AI Effectively

In addition to considering which analytics category might be relevant to an AI application, another important issue is clarifying how to ensure that AI will be used effectively. Toward this end, it is helpful for a legal team to think about the three forms of analytics in terms of what the team is trying to accomplish and how AI can enhance the appropriate type of analytics for their needs.

One question for your team is: “How can we incorporate AI into an analytics solution to address our needs concerning a specific legal matter and/or improve specific elements within our practice?” 

An answer to this question is to think back to the process of drafting proofs in geometry class. A geometric proof involves writing reasoned, logical explanations that use definitions, axioms, postulates, and previously proved theorems to arrive at a conclusion about a geometric statement. 

A good proof has an argument that is clearly developed, with each step supported by:

  • Theorems
  • Postulates
  • Axioms

Risk Averse or Risk Aware in Considering AI

Attorneys also face another challenge in choosing the right AI solution for their practice. The challenge is whether to be risk averse or risk aware in considering AI. Law firms tend to avoid risk and use safe, familiar tactics rather than consider new approaches. Consequently many attorneys continue to practice law based on their past experiences, the advice of partners in the firm, and the processes, procedures and strategies that they know well. 

Document review for litigation is a good example. For years partners have assured clients that their firm makes certain attorneys review every document they collect. This assurance has often been characterized by the statement, “There will be eyes on every page.”  Eyes on every page, however, frequently means using temporary attorneys. This practice can be expensive.

Nevertheless, many firms and corporate legal departments are more comfortable knowing that there are eyes on the documents instead of using AI and analytics to manage reviews. Why? The answer often is, “Because that’s the way it has always been done.” But why not have as much trust in technology backed by a rigorous “proof” process as in a temporary attorney?  The response regularly is, “Because I don’t want to be blamed if something goes wrong, especially in discovery.” Consequently many lawyers view integrating AI into their practice as a risky proposition. This is risk aversion. 

In contrast, many corporations understand and accept the risk associated with AI and analytics solutions. This acceptance is based on understanding the potential benefits that can be achieved through AI, such as cost reduction, enhanced efficiency and other gains. This is risk awareness. Many corporate executives are risk aware while many legal professionals are risk averse. 

The tide may be turning, however, with more law firms and corporate legal departments becoming risk aware as they investigate and increasingly embrace the potential of AI and analytics solutions. Rather than a threat, these legal professionals tend to see technology as an opportunity to contain costs, increase efficiency, and deliver enhanced client services. They strive to reap the rewards of technology, as opposed to those who cling to the status quo and run the risk of being left behind.

This whitepaper is not intended to provide any legal advice.

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