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The legal profession stands at a historic inflection point as artificial intelligence fundamentally disrupts and reshapes how lawyers research, analyze, and deliver legal services. From routine document review to complex legal analysis, AI platforms like Vincent AI are transforming traditional legal workflows in ways that were unimaginable only a few years ago.

We're thrilled to share that vLex's VP, Solutions Champion, Damien Riehl, recently joined The Agile Attorney Podcast with John E. Grant. Throughout the conversation, Damien shared an insightful perspective on how small and mid-sized law firms can effectively implement AI today, skipping past the usual ethical debates and hallucination concerns to focus on practical applications that improve client service and profitability.

Listen to the full podcast: The Agile Attorney Podcast: Episode 60 - Practical Uses for Legal AI - No Hype, No Fear with Damien Riehl

AI is Here to Stay: Moving Past Initial Hesitations

To get the conversation started, John and Damien addressed why it's time to move beyond debates about ethics and hallucinations in legal AI.

"Ethics is something we shouldn't talk about. Hallucinations are things we shouldn't talk about," Damien noted. "One of the reasons we shouldn't talk about them is because they're an easy no button. Lawyers can easily put their head in the sand and say, no, because it's unethical, no, because it's hallucinations, therefore I'm not even going to think about AI."

“But if we were to say,” explained Damien, “and it's a true thing, that you can ethically use tools like Vincent that are secure, and it's not going to train on your data, and we reduce hallucinations to pretty close to zero. Then, yes, we should not talk about them today because they are largely solved problems. And they are largely excuses for people to be able to not use generative AI and put their heads in the sand. So let's not talk about those.”

John then shared that this debate on the ethics of leveraging GenAI “reminds me of the debates that we had around cloud computing 10 and 15 years ago.”

“That's exactly right,” said Damien “You'll never put me in the cloud because you'll take my server out of my cold, dead hands. And everybody knows that I'm never going to use eDiscovery because every human eye needs to be on every document. And now if you don't use eDiscovery, you're often violating your ethical duties.”

Harkening back to his law school days, Damien shared, “Even further in 1999, when I was going to law school, my law librarians told me, do not trust Westlaw because there were errors in the Westlaw version that were not present in the book.”

“So they said, go to the stacks,” recalled Damien. “And I spent a lot of time trudging to the stacks. But did that make me a better lawyer? It wasted my time. And so I think we're at that separate time right now with AI, with the things that AI can do for us. Are we requiring people to trudge to the stacks and waste their time? Or are we going to practice law like we should in the 21st century?”

How AI Transforms Legal Work Today

In the podcast, Damien provides compelling examples of how AI is already transforming daily legal work. These aren't speculative future applications—they're delivering measurable results for attorneys right now.

Backward and Forward-Looking Legal Analysis

Damien explains that lawyers typically engage in two types of work, both of which AI can enhance dramatically:

"Most of what we do is backward looking. We apply facts to law. That is, here's my client's new facts. Here's the law that applies. So let's take the law and apply the facts or vice versa," Damien explains. "Whether you're a litigator saying, what's my risk of getting sued for this, or whether I'm a transactional lawyer saying, can I include this in a contract or not? Will this violate EU antitrust law or will this violate employment law?"

But AI also excels at "forward-looking ideation" – generating novel insights and connections. Damien shared how AI helped him tackle a question about affective computing – technology that interprets human emotions – for an insurance company:

"I went to the large language model and I said, tell me about affective computing as it's being used in an insurance call center... Then I said, tell me how it could be used. What are the legal implications for these things? And they said, have you thought about privacy law? Did somebody actually give you permission to analyze their emotions? Tell me about whether that complies with GDPR."

This showcases AI's ability to connect concepts and generate insights that weren't explicitly part of its training data.

Transforming Research Efficiency and Improving Client Value

One of the most dramatic examples Damien shares is how AI tools are transforming the time-value equation in legal work:

"I, as a new litigator 15 years ago, would often spend eight hours or so researching cases, reading through hundreds of cases, maybe landing on the 20 that are actually relevant, and then drafting a memo that would actually be helpful to my client. But Vincent does all those things, that eight-hour task, and shrinks it down to a minute and a half. If there were a hundred cases and only 20 of them were relevant, it reads through the 80s so you don't have to."

This efficiency gain presents lawyers with two options: (1) Reduce billable hours for the same work, or (2) Provide substantially more value in the same time. As Damien highlights, "You can now actually go to ask question number two and question number five and question number 20. And now you spend the same eight hours, but now you've given the client a much better output."

Issue Spotting and Automated Legal Analysis

The automated identification of legal issues stands as one of AI's most transformative capabilities for legal practice. In the podcast, Damien describes a sophisticated workflow he's developing that fundamentally changes how attorneys analyze client information:

"I was building a tool to take this MP3 interview or this audio recording or this video recording, transcribe that audio recording, and then do issue spotting," he explains.

This multi-step process involves:

• Audio-to-text conversion: Converting client interviews into searchable, analyzable text
• Jurisdictional analysis: Identifying relevant legal jurisdictions for each issue
• Automated issue identification: Recognizing potential causes of action across practice areas
• Jurisdiction-specific legal application: Applying the relevant law for each jurisdiction to the facts

The results are remarkably comprehensive. As Damien notes, the technology can identify "potential causes of action in a litigation matter" or relevant "family law matters that we should be thinking about in your jurisdiction in California or in New York or in Texas."

What truly distinguishes this advancement is how it's evolving beyond requiring specialized AI expertise. "You won't have to be a prompt engineer," Damien explains, echoing Sam Altman's vision that prompt engineering should eventually disappear as a distinct skill. Instead of attorneys needing to learn complex prompting techniques, the system itself guides the analysis.

Perhaps most impressive is the system's ability to handle complex, multi-jurisdictional analyses. Damien illustrates this capability: "We say, what jurisdictions is this? And for the breach of contract claim, it's California law, but for the trade secret claim, it's under New York law, we issue spot." The technology doesn't stop at identifying issues—it proactively suggests strategic next steps by generating "questions to ask their client to help them win."

This revolution in issue spotting transforms what was once a heavily experience-dependent task into a systematic, technology-enhanced process. For attorneys at all experience levels, it means more thorough analysis with fewer blind spots, allowing them to redirect their expertise toward strategy and client counseling rather than preliminary issue identification. The technology doesn't replace legal judgment, but rather elevates it by handling the foundational analytical work that previously consumed substantial attorney time.

The Future of Legal Education and Practice

As AI reshapes the practice of law, Damien sees profound implications for legal education and professional development. In the podcast, he delivers a compelling challenge to traditional law school curricula that focuses heavily on doctrinal knowledge.

"I've spoken to many law schools and I've told them just that," Damien explains. "You're teaching doctrinal things and Vincent can do doctrinal questions in seconds. So if you're teaching to be able to read the 100 cases to land on the 20 that are most relevant to then be able to draft a memo that turns into a complaint, I can already do that. So what are you training for?"

This fundamental question strikes at the heart of legal education. If technology can now handle much of the doctrinal analysis that once defined legal practice, what skills should future lawyers be developing? Damien frames this as a choice between past and future approaches: "Are you training your lawyers for a 20th century workflow? Are you training lawyers for a 21st century workflow where the doctrinal things are largely covered and the humanity is what's left?"

The answer, he suggests, involves refocusing legal education on uniquely human capabilities that complement rather than compete with AI. "You should be doing more, how do I be able to speak with a good bedside manner to my client? How can I be able to bring work in to be able to then actually have a reasonable business model rather than the old model?"

This shift extends beyond law schools to practicing attorneys who must recalibrate their value proposition. As AI systems like Vincent increasingly handle risk assessment and complexity navigation, the attorney's role evolves toward delivering wisdom and human connection.

"All that's left is the humanity," Damien emphasizes. "That is that human layer up top... Vincent is gonna tell you the legal risk. It's going to tell you the complexity, and it's gonna simplify that complexity by saying, now explain this at an eighth grade reading level."

The attorneys who thrive in this evolving landscape will be those who recognize that their greatest value lies not in information processing but in judgment, empathy, and contextual understanding. "We'll both assess the risk, number one, and also provide the simplicity to the complex," Damien notes. "What's left is that human layer for you to be able to deliver it. And at what cost can you deliver that at scale? That's for all of us to figure out."

For forward-thinking law firms and legal educators, this represents both a challenge and an opportunity. Those who embrace this new paradigm—focusing on developing the human elements of legal practice while leveraging AI for doctrinal analysis—will likely find themselves at a significant competitive advantage in the coming years. As Damien concludes, "I think that parts of humanity and the business model are where law schools that get it are gonna be doing and for the lawyers that get it are gonna be making more money than their competitors who don't."

Transform Your Workflows with AI Engineered for Lawyers

Thanks to John Grant and The Agile Attorney Podcast for hosting Damien for this enlightening conversation on practical AI applications for law firms, how AI is transforming legal workflows, and how forward-thinking attorneys can leverage these tools to deliver better client outcomes with greater efficiency.

Want to learn more about how you can elevate your practice and enhance your client service with AI engineered for lawyers?

Schedule your personalized demo of Vincent AI today and empower you and your team to do more.

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Authored By

Jeff Cox