Generative artificial intelligence is supercharging legal analytics
Generative artificial intelligence is revolutionizing the field of analytics by assisting lawyers with tasks ranging from fee setting to research. (Photo illustraton by Sara Wadford/Shutterstock)
Generative artificial intelligence is revolutionizing the field of analytics by assisting lawyers with tasks ranging from fee setting to research.
According to a 2023 Goldman Sachs report, 44% of legal tasks can be automated by AI, saving firms time and money.
Traditional data analytics relied heavily on structured data and predefined models, requiring significant manual effort to identify patterns and to extract insights, explains Stephanie Corey, the CEO and co-founder of UpLevel Ops in Redwood City, California. Predictive AI is more advanced than traditional analytics—but it’s confined to specific algorithms tailored for particular tasks and often demands considerable setup and customization, Corey says.
Then there’s generative AI.
“Generative AI represents a significant leap forward,” Corey says. “Unlike its predecessors, generative AI can process unstructured data, including texts, emails, voicemails and videos—offering a more comprehensive and nuanced view of legal matters.”
Its analytics can help to predict case outcomes and future legal costs based on conversational input. Instead of being limited to a finite number of data analytics reports, generative AI can dive deeper into data to obtain insights specific to your case’s needs, says Nicole Black, a Rochester, New York-based lawyer and principal insight strategist with AffiniPay, the parent company of MyCase and LawPay.
This capability improves the accuracy of outcome predictions and also uncovers potential risks and opportunities that might remain hidden with traditional analytics. This enhanced risk management allows for early identification of potential issues, preventing expensive litigation and settlement costs, Corey says.
Uses for generative AI
Corey suggests firms use generative and predictive AI to assist with a variety of legal purposes.
In litigation strategy, she says, generative AI can analyze past cases and outcomes to help construct a new plan. The information obtained can be used to personalize legal solutions or make proactive updates on legal changes. By predicting client needs and preferences, generative AI can improve satisfaction and retention rates.
Generative AI could also be used for predicting how judges might rule. For example, Corey says, some law firms are setting up custom GPTs modeled after specific judges, loaded with their legal decisions.
“By simulating the decision-making patterns of particular judges, firms can better predict judicial rulings and tailor their arguments accordingly,” Corey says. “This capability allows firms to anticipate opposing counsel’s moves and to develop more robust strategies, ultimately leading to better case outcomes.”
While many firms are concerned with the reliability and accuracy of generative AI, the tool can enhance regulatory compliance by monitoring and analyzing ever-changing regulations. It can automatically track updates from regulatory bodies, flagging changes. Or, firms can use it to analyze their existing documents and procedures to ensure they align with the latest regulatory requirements, Corey says.
“This proactive monitoring helps law firms stay compliant, reduce the risk of legal violations and provide timely advice to clients about regulatory changes that may affect their businesses,” she says.
Additional perks of generative AI
Not all firms are comfortable using generative AI, says Kevin Doran, the founder and senior consultant at Legal Tech Chicago, an all-purpose trial tech consulting company based in Chicago.
But, Doran adds, the savings on workforce alone justify its use for all firms—if they understand how to prompt generative AI effectively.
When Dennis Kennedy, the Ann Arbor-based director of the Michigan State University Center for Law, Technology & Innovation, operates generative AI, he uses the expert prompt approach.
“I give it a persona that says, ‘You’re an experienced expert in data analytics,” he says. “Then, I give it context that I want, and I specify the output that I want: Chart? Narrative?” Kennedy says.
For each suggestion generative AI provides, Kennedy asks the system to “show their work,” so he can understand how it constructed the answer, along with the assumptions it made. He also uses generative AI to determine his firms’ costs by detailing an idea for a new service offer and requesting price ranges.
Generative AI is able to provide insight and predictions about litigation and pricing using a firm’s historical data and other available data, such as court data, Black explains. It can even predict whether a firm should consider adding new practice areas based on market trends, she says.
Client retention could be enhanced, as clients are more likely to remain with firms offering new innovative, cost-effective and reliable legal services, Black says.
“Additionally, by improving the accuracy of outcome predictions, generative AI reduces the likelihood of legal missteps,” Corey adds.
See also:
Some law firms are thinking about AI all wrong
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