In the generative artificial intelligence era, every industry will likely reap new efficiencies.
Unlike previous iterations of AI, which focused on predictive or discriminative inference, generative AI can understand subtleties and nuances, and then create outputs atop them.
That capability — and capacity — has implications within the legal field and across business operations, James Clough, chief technology officer and co-founder of Robin AI, told PYMNTS during a conversation for the “AI Effect” series.
The transformative power of generative AI technology allows for more accurate and scalable automation of previously manual legal processes, such as contract review and analysis.
“Most legal teams, when they’re doing work, what is the output of their work?” Clough said. “It’s not just a prediction, it’s generated text. They want to get something written as an output that they can send to somebody else in an email, or that they can use to add a comment or an edit to a document, or to answer somebody’s question.”
Historically, the complexity of legal work has deterred the use of technology because tools to organize and interpret it were unavailable.
The ability of generative AI models to generate text and enable the automation of complex legal tasks is already poised to make legal work more efficient and accurate — even for businesses without a legal department.
Small businesses, for example, can benefit from using generative AI to draft employment contracts or review supplier agreements while in-house legal teams, on the other hand, can take advantage of the technology to streamline workflows and increase efficiency, Clough said.
But that’s just a hint of the coming paradigm shifts that generative AI systems will bring to the legal industry.
Read also: Legal Tech Firm Robin AI Raises $26 Million
At its core, legal work demands attention to detail, extensive research and nuanced argumentation — intellectually rigorous and time-consuming tasks.
That’s in part why PYMNTS Intelligence found that 72% of lawyers doubt their field is ready for generative AI.
As Clough noted, historically, the legal industry has experienced promises of AI-driven transformations, but progress has been hindered by false starts and unfulfilled potential.
He explained that Robin AI has been bringing to market its generative AI product, which is built atop Anthropic’s Claude foundation model, by primarily targeting in-house legal teams because they possess the advantage of owning the data they work with, facilitating better integration and customization of AI models.
Moreover, the incentives for innovation are clearer in the in-house setting, where efficiency gains directly contribute to unblocking the main revenue-generating activities of the business.
“Law firms will adopt this technology and become more innovative, but there are a few more blockers, and it’s a little bit harder to make the business case when they’re using the billable hour approach where it is less clear how doing the work faster is better,” Clough said.
As per the partnership with Anthropic, “the Anthropic philosophy of being focused on safety and reliability aligns nicely with the way we want to think about applying AI into the legal industry as well,” he said.
The long context window of Claude, which allows for the analysis of lengthy contracts, has also proven to be an asset, he added.
“The legal industry is a naturally quite conservative one with respect to bringing in new technology,” Clough noted, emphasizing that to overcome the behavioral speed bumps associated with adopting generative AI it is crucial to start small and find demonstratable value through tangible, scalable results.
“The only way we will learn with AI is by actually deploying it in real-world scenarios and using that experience to build something better,” he said.
By identifying specific projects where generative AI can deliver value, companies can build trust and expand its use gradually, he added, explaining that: “In 2024, we’re going to shift from a world where it was a risk to try using generative AI to become more efficient, into a world where there is actually a bigger risk of being left behind if you don’t try it.”
“What will feel risky will be sticking to this old way of working while seeing all of your competitors racing ahead of you by using AI to be more efficient, and all the best talent preferring to go to work for firms where they aren’t stuck doing the most tedious, repetitive and manual work and they can focus on strategy,” Clough said.
As for whether AI will replace lawyers any time soon, Clough said he doesn’t see it happening.
“Lawyers who use AI are going to replace lawyers who don’t, rather than AI replacing all lawyers,” he said. “…That’s why it’s called a co-pilot, right? Because a co-pilot implies the existence of a pilot, and it’s still the pilot who’s in control. It’s the pilot who’s setting the direction. It’s best thought of as a person and machine partnership rather than a replacement.”
Looking ahead, Clough predicted a shift from chat-based interfaces to more agentic AI models. These models will not only provide answers to questions but also perform tasks on behalf of lawyers, further increasing efficiency and productivity. The focus will be on reliability and ensuring that AI-generated answers are not only accurate but also trustworthy.
“It won’t be something you ask and get an answer back, but a system you can ask to do things for you,” he said. “…Instead of just drafting that email, it might draft the email and get the attachment and put it in your outbox and then click send as well. I think that shift from chats to agents is one of the most exciting things we’ll see in the next year.”
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