AI Built for the Practice of Law

How AI is transforming the practice of law for attorneys 

Ask any lawyer what the practice of law involves on a day-to-day basis and you will get an answer that goes far beyond writing briefs or reviewing contracts. You are likely to hear about a variety of judgment calls that involve deciding how to approach a matter, choosing which legal strategies to deploy, determining the best way to tackle a specific task, or how to make sure that legal work can withstand scrutiny from clients, opposing counsel, courts and regulators. 

Understanding that range of daily activity is more important than ever right now because the technology entering legal workflows is increasingly powerful — but that tech needs to be aligned with how legal work actually gets done. 

This is the second post in a four-part series exploring how LexisNexis is redefining the standard of legal practice in the age of AI. The first post introduced the series and outlined three pillars shaping that new standard. Here, we take a deeper look at the importance of building AI that is purpose-built for how lawyers actually work. 

How the practice of law is changing with AI 

The core of legal practice has always been built on a progression: a lawyer assesses the situation, applies the relevant expertise and data, follows a structured legal process, and then delivers a defensible work product. Whether the task is drafting a motion, analyzing a contract or preparing for trial, that sequence is what has always separated competent legal work from guesswork. 

What has changed in recent years is the speed and scale at which these steps can be augmented by technology, with a sea change occurring since the widespread availability of artificial intelligence tools. Seven in 10 attorneys now use AI at least once a week in their legal practice, according to a Law360 Pulse report in March 2026, with double-digit growth in use for research, document summarization and drafting. 

But adoption alone doesn’t tell the full story. The Law360 Pulse survey also revealed a rising discomfort that many of them share over whether the necessary safeguards around those tools have kept pace, with 44% saying they now see both the pros and cons of AI adoption in the legal industry. That was in sharp contrast to last year’s survey, where 73% of frequent AI users held a positive view of the technology. 

“Attorneys who frequently use artificial intelligence tools are starting to feel less positive and more neutral about the technology’s adoption in the legal industry,” reported Law360. 

Why generic AI falls short in legal work 

Legal work requires tools that understand the difference between a first draft and a defensible document. It demands technology that can Shepardize a citation, extract a clause in context or validate an argument against secondary sources — not just produce text that reads like it might be correct. The ongoing list of risks assumed by attorneys who placed their trust in work product created by general-purpose AI tools is serious. 

This mismatch isn’t just organizational, it’s architectural. Most AI tools available today were built for use by individuals and small businesses who need assistance with answering questions, drafting emails or summarizing text. They are impressive at generating language. But generating language is not the practice of law. 

This is where purpose-built legal AI separates itself from the pack. Rather than retrofitting general-purpose models to handle legal tasks, purpose-built tools are designed from the ground up around the key aspects of the practice of law. The best of these tools were developed according to a time-tested understanding of specific skills, data requirements and workflows that define how lawyers actually do their jobs. 

Three key elements of AI built for the practice of law  

At LexisNexis, we have focused on three core concepts that mirror how legal work gets done: 

1.Legal skills in AI for lawyers 

These are the discrete capabilities required to handle specific tasks with trusted data. For example, they might include summarizing a deposition transcript, extracting key terms from a contract, Shepardizing a citation or running a conflict check. These are not generic writing tasks, they are specialized functions that require domain-specific training and access to authoritative legal content. 

2.Legal workflows and AI automation 

These are repeatable, multi-step legal processes that chain those skills together. Drafting a legal memorandum, for example, isn’t a single action so much as it is a sequence of actions: research the issue, analyze the relevant authorities, draft the argument, review and validate the citations. A technology platform designed for the practice of law understands that sequence and supports it end to end. 

3.AI agents for legal tasks 

These are goal-driven systems that can take on a request, figure out the steps required, and use the available skills and workflows to complete it. For example, when a lawyer asks an AI assistant to analyze a contract and redraft several clauses based on their organization’s playbook, the system needs to plan the work, execute each step in the right order and refine the output. It’s not good enough to use an AI tool to produce a block of text and then hope for the best. 

This layered architecture of Skills, Workflows and Agents is what makes AI feel less like a chatbot and more like a capable associate who understands how legal work actually gets done. 

What’s next for AI in the legal industry 

In the next post in this series, we’ll explore the second pillar of the standard of legal practice in the age of AI: why trust in legal AI must be built on authoritative data … and what happens when it isn’t. 

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