Applications of AI in the Legal Field

Artificial intelligence (AI) is transforming how lawyers and courts operate globally. From automating tedious paperwork to predicting case outcomes, AI-driven tools help legal professionals work faster and smarter. Crucially, these technologies augment lawyers' capabilities rather than replace them, taking over routine tasks so attorneys can focus on strategy, advocacy, and client service. Surveys show that saving time and boosting efficiency are the top reasons law firms explore AI. A majority of legal practitioners believe AI will become central to legal workflows in the coming years. At the same time, the profession remains cautious—accuracy, reliability, and ethics are paramount concerns as AI tools enter everyday practice.

Below, we explore the current applications of AI in law and highlight notable AI-powered tools making an impact. Each section illustrates how AI enhances legal research, contract review, document drafting, litigation strategy, client service, and court operations.

AI in Legal Research and Case Analysis

One of the earliest and most widespread uses of AI in law is legal research. Traditional legal research—sifting through volumes of cases, statutes, and regulations—is extremely time-consuming. AI changes this by rapidly searching vast databases of legal texts and understanding context and intent behind queries. Instead of manually digging through books or databases, lawyers can now use AI-driven research platforms to surface relevant case law and authorities within seconds. These tools not only fetch cases by keyword but also analyze legal language to find patterns or related precedents that simple keyword searches might miss.

How it works: Modern generative AI systems like LexisNexis's Lexis+ AI allow attorneys to ask complex legal questions in plain English and receive conversational answers with cited sources in real time. The system can summarize court decisions in seconds and suggest relevant authorities within a secure, encrypted environment built for legal work.

General-purpose AI chatbots like ChatGPT have similarly been adopted by lawyers for quick research and drafting. In a 2024 survey, over half of firms reported experimenting with ChatGPT or similar AI for legal research tasks. These AI assistants can explain case holdings, compare statutes, or generate memo outlines based on legal questions.

AI systems rapidly analyze vast legal databases to surface relevant case law and precedents

Critical consideration: Accuracy and verification remain essential in AI-driven research. Well-designed legal AI tools address this by providing linked citations and checking outputs against authoritative databases. However, lawyers must carefully validate AI research results to avoid errors. Early incidents highlighted the risks—lawyers who submitted AI-generated case citations that turned out to be fictitious were sanctioned by courts. The lesson is clear: AI can supercharge legal research, but professional oversight is non-negotiable.

When used responsibly, AI research tools help attorneys find on-point authorities faster, ensuring no key precedent is overlooked while freeing up time for deeper legal analysis.

AI in Contract Review and Due Diligence

Reviewing contracts and business documents for risks and details is another labor-intensive task ripe for AI enhancement. AI-powered contract review tools can analyze lengthy contracts or document sets at speeds impossible for humans, identifying key clauses, anomalies, and potential issues with high accuracy. This is transformative for tasks like due diligence in mergers and acquisitions, where attorneys might have thousands of pages of contracts to review under tight deadlines.

Speed

Review contracts in minutes instead of hours

Instant clause extraction
Automated risk flagging

Accuracy

Consistent, legal-grade analysis across documents

Reduced human oversight
Pattern detection

Compliance

Maintain quality control and standardization

Playbook alignment
Regulatory checks

Leading contract review platforms such as Litera Kira and Luminance use machine learning and natural language processing to detect important clauses and deviations. These tools automatically pull out clauses like indemnities, renewal terms, or change-of-control provisions across large document sets, highlighting them for lawyer review. According to users, Kira can "automatically identify and extract key clauses and data points from contracts" without manual review of hundreds of pages.

Luminance uses a "mixture of expert" AI model (its Panel of Judges) to ensure legal-grade accuracy in reviewing and summarizing contracts. In practice, these tools not only speed up review but improve consistency—every document is checked against the same criteria, reducing the chance of human oversight.

AI contract tools extract key clauses and identify risks automatically across document sets

Best practice: Beyond spotting risks, AI contract tools help with compliance and standardization. They compare contract language against a company's playbook or known legal benchmarks, flagging clauses that diverge from preferred wording. Some offer suggestions for alternative phrasing to better protect client interests or ensure consistency with new regulations, assisting lawyers in maintaining quality control across contracts.

By automating the heavy lifting of contract review, AI enables legal teams to handle greater volumes of contracts faster and focus their expertise on negotiating the tough issues. Businesses benefit through reduced transaction times and potentially fewer costly mistakes in contract drafting and review.

AI for Document Drafting and Automation

Drafting legal documents is a core part of law practice—whether it's writing contracts, wills, briefs, or client emails. AI is increasingly being used to generate first drafts of such documents, acting as a productivity booster for lawyers. Using large language models (LLMs) trained on legal texts, AI can produce well-structured drafts that attorneys can then refine. A task that once took hours might be done in a fraction of the time, with the lawyer's role shifting to reviewing and customizing the AI's output for the specific situation.

Global Adoption Examples

Law firms worldwide have begun embracing generative AI assistants for drafting. A notable example is the global firm Allen & Overy, which deployed an AI platform called Harvey (built on OpenAI's GPT model) to help lawyers with document drafting and research. In trials, 3,500 lawyers at the firm used Harvey to generate drafts and answer legal questions, reportedly saving each of them "a couple hours a week" on routine work. The firm's leadership suggested that not adopting such AI would become a competitive disadvantage over time.

In one pilot project, a law firm used an AI system to draft litigation documents (like complaint responses) and saw the time to prepare a draft plummet from 16 hours of associate time to about 3–4 minutes. That is a 100x increase in productivity, illustrating how automating initial drafts frees up lawyers to focus on higher-level analysis and advocacy.

How It Works

Importantly, the AI's output serves as a starting point—a human lawyer always reviews and finalizes the document. This human-in-the-loop approach is key to maintaining quality and ethical standards.

LexisNexis reports that its new AI drafting tool can produce contract clauses or client advice letters from a simple prompt, integrated with its research database to ensure suggestions come with supporting authority. These tools also assist with document automation beyond contracts – generating tailored court forms, assembling boilerplate sections of briefs, or writing polished emails to clients.

AI generates initial document drafts in minutes, freeing lawyers for higher-value analysis

Key consideration: While AI-generated drafts accelerate the writing process, attorneys must still apply their judgment. AI might draft a grammatically perfect contract, but it's the lawyer's job to ensure the substance is right for the client's needs and that no nuance is lost. With thoughtful use, AI drafting tools act like tireless junior associates, producing initial versions of documents in moments.

This not only saves time but can improve consistency (by drawing on approved templates or language) and reduce drafting errors. As the technology improves, we can expect AI to handle more of the heavy lifting in document creation, from court submissions to internal legal memoranda, always under lawyer supervision.

AI in E-Discovery and Document Management

Litigation and investigations often involve e-discovery – the process of sifting through troves of emails, documents, and data to find relevant evidence. AI has become a game-changer by automating much of the document review and data analysis that used to consume massive attorney hours. Machine learning-based e-discovery tools (sometimes called "TAR" for Technology Assisted Review) can quickly classify which documents are likely relevant to a case, flagging important items and filtering out duplicates or irrelevant material.

AI can "automate processes, enhance eDiscovery, identify relevant case law, and analyze large legal databases in minutes" – tasks that collectively help build well-supported cases more efficiently.
— American Bar Association

Advanced e-discovery platforms like Logikcull and Everlaw use AI to not only find documents but also to summarize them and spot patterns. Everlaw's software can automatically generate document summaries and assist with constructing a case narrative by extracting key facts across documents. These summaries let lawyers grasp the gist of a document set without reading every page, focusing their attention on the most crucial evidence.

Document Classification

AI quickly tags and organizes electronic documents, separating relevant from irrelevant material. It extracts entities like names, dates, and places, helping lawyers drill down on who did what and when.

Document Summarization

Lengthy reports or emails are distilled by AI into concise summaries highlighting main points. This makes it easier to prioritize which documents need in-depth review.

Discovery Automation

Generative AI drafts boilerplate sections of discovery responses or initial deposition outlines by analyzing the document set for patterns.

Translation & OCR

AI tools translate foreign-language documents on the fly and convert scanned images or handwriting into searchable text, greatly expanding what can be reviewed.

AI in E-Discovery and Document Management

AI-assisted e-discovery automates document classification and analysis at scale

Proven advantage: Studies have found that AI-assisted review can actually be more accurate than purely manual review, because algorithms don't tire or lose focus and can catch subtle patterns humans might miss. Implementing AI in e-discovery requires robust procedures (and sometimes buy-in from opposing counsel and courts), but it offers immense benefits: reduced costs, faster turnaround, and the ability to handle exploding volumes of data in modern litigation.

With AI taking on the heavy document crunching, legal teams can devote more effort to crafting case strategy and less to laborious document dumps.

AI for Predictive Analytics in Litigation

Beyond crunching text, AI is being used to analyze legal data for patterns and predictions. In litigation especially, both law firms and corporate legal departments are interested in tools that can predict case outcomes, estimate likely duration or cost, or identify trends in how particular judges rule. These insights, often termed legal analytics, help lawyers make data-driven decisions—such as whether to settle a case, what arguments might resonate, or which venue is most favorable.

Traditional Approach

Experience-Based Decisions

Rely on attorney experience and gut feeling
Limited historical data access
Inconsistent case assessment
Higher settlement uncertainty

AI-Powered Approach

Data-Driven Decisions

Analyze millions of court decisions
Identify judge-specific patterns
Predict outcomes with statistical basis
Informed settlement strategies

One pioneering tool in this space is Lex Machina, which analyzes millions of court dockets and decisions to spot patterns. Lex Machina can predict the behavior of courts, judges, opposing counsel, and parties by mining historical data. Lawyers use it to answer questions like: What are the chances of winning this type of case? or How has Judge X ruled on similar motions? By seeing the statistics (for example, that Judge X grants 80% of summary judgment motions in employment cases, or that Company Y tends to settle trademark disputes early), attorneys can adjust their strategy and better manage client expectations. These AI-driven predictions reduce risk in litigation strategy by providing an empirical basis for decisions that were once guided mainly by experience and intuition.

Another example, Blue J Legal, focuses on predictive analytics in tax and employment law. Blue J's AI analyzes factors from past rulings to predict how a new scenario would likely be decided, boasting over 90% accuracy in its predictions for tax case outcomes. In a partnership with a Big Four firm, this AI was used to instantly determine complex tax classifications (like whether a worker is an employee or contractor for tax purposes), a question that normally would require many hours of research – the AI could answer it in seconds, giving the professional a huge head start. Such tools are essentially providing a form of augmented legal opinion, where the AI suggests the probable result and the lawyer then verifies and builds on it.

AI for Predictive Analytics in Litigation

Predictive analytics help lawyers assess case outcomes and judge behavior patterns

Important limitation: Predictive AI has constraints. It can only base predictions on past data – if a case involves a novel legal issue or unique facts, historical patterns may be misleading. Critics point out that current AI models might not capture nuances like unpublished settlements or the "human element" of persuasiveness in the courtroom. Public databases also lack information on disputes that never went to court and don't reflect late-breaking changes in the law. Therefore, while an AI might say a plaintiff has a 70% chance of winning based on precedent, a skilled lawyer will still analyze the specifics and may see reasons the case at hand could buck the trend.

Still, even with those caveats, predictive analytics are proving valuable. They enable data-driven decision making in law: helping lawyers choose jurisdiction, tailor their arguments, or advise clients when to settle. Over time, as AI models get more sophisticated and incorporate larger datasets (perhaps even spanning arbitration outcomes or administrative decisions), their predictive power will grow. Used wisely, these tools give legal teams an analytical edge – a sort of legal "weather forecast" – that, combined with human judgment, can lead to more strategic and informed choices in litigation.

AI-Powered Legal Chatbots and Virtual Assistants

AI isn't just working behind the scenes; it's also facing clients and consumers through legal chatbots and virtual assistants. These AI chatbots simulate human-like conversations and can handle a variety of law-related tasks, from answering basic legal questions to guiding someone through a legal form. Law firms are deploying chatbots on their websites to improve client service, while legal aid organizations and even courts experiment with chatbots to expand access to justice.

Client Intake

24/7 engagement and lead pre-screening

Instant responses to inquiries
Automated information gathering
Lead qualification

Knowledge Management

Internal support and document retrieval

Fact-checking assistance
Precedent searching
Case history lookup

Document Generation

Interactive drafting and automation

Questionnaire-based drafting
Template customization
Deadline reminders

One common application is client intake and FAQ automation. Law firms often use chatbots to engage website visitors in real time – 24/7 – even when staff are unavailable. A chatbot can greet a potential client, ask a few questions about their issue, and gather contact information and case details. This helps pre-screen leads and collect information so that when a lawyer follows up, they already have key facts in hand. For straightforward queries, the chatbot can provide instant answers. For example, if someone asks "What are your business hours?" or "Do I have a case for a traffic ticket?", the AI can respond immediately with the relevant info or a few qualifying questions, rather than making the person wait for a call back. By automating these routine interactions, lawyers save time and clients get faster responses, improving satisfaction.

Modern legal chatbots go beyond simple scripts thanks to advanced NLP (natural language processing) and integration with legal databases. Some are trained on specific legal domains or even a firm's internal knowledge base, enabling them to handle more complex tasks. For example, chatbots can now summarize documents and provide case insights on demand. Imagine uploading a 100-page contract and asking the chatbot, "What are the main termination clauses here?" – the AI can quickly generate a summary of the termination provisions and any unusual terms. Chatbots can also assist lawyers internally by fact-checking and knowledge management: an AI assistant can quickly search through a firm's past cases or memos to answer a lawyer's question ("Have we ever handled a case involving X?") or to pull up a needed document. Global law firms have even built proprietary GPT-based chatbots for their attorneys to query firm documents or precedents in natural language.

Another powerful use is automated document generation through chat. Some chatbots help draft routine legal documents interactively. For instance, Assembly Software's case management chatbot can automatically generate common documents like NDAs, demand letters, or engagement agreements based on information in the system. A lawyer or client could essentially fill out a questionnaire via chat and have the first draft of a document produced instantly, with the AI pulling the exact case or client data needed into the right places. This kind of automation ensures consistency and saves time on repetitive drafting tasks. Additionally, chatbots are used for reminders and internal support – they can monitor case deadlines, answer "where do I file this?" questions for staff, or help check that all necessary documents have been collected in a matter.

AI-Powered Legal Chatbots and Virtual Assistants

Legal chatbots provide 24/7 client support and automate routine legal tasks

Implementation note: AI chatbots act as tireless virtual assistants. They improve responsiveness (no waiting for simple answers), streamline intake and scheduling, and can even help with legal research and drafting in a conversational way. As with all AI, they must be deployed carefully – ensuring they don't stray into giving unauthorized legal advice without oversight and that they maintain client confidentiality. Done right, however, they offer a scalable way to handle many inquiries and tasks simultaneously.

This is especially promising for bridging the access-to-justice gap: a well-designed chatbot could help individuals fill out court forms or guide them through filing a small claim, without needing a lawyer's constant involvement. Law firms benefit too by capturing more leads and freeing up lawyers' time for higher-value work. The key is that these chatbots are legal-specific (trained on the language and rules of law) and integrated with human lawyers for the hard stuff, which is exactly where the industry is heading.

AI in Courts and Judicial Systems

AI's influence in law isn't confined to law firms and clients—it's also emerging in courtrooms and judicial administration around the world. Courts in various countries are experimenting with AI tools to increase efficiency and manage heavy caseloads, while ensuring the integrity of justice.

Argentina: Prometea

A virtual assistant for judges and clerks that drafts routine decisions and prioritizes cases. Impact: increased case processing from 130 to nearly 490 cases per month—a 300% productivity increase.

Egypt: Speech-to-Text

Courts began using automated speech-to-text transcription in 2024 to create real-time records of proceedings, speeding up trials and improving accuracy of court records.

Translation Services

Some courts use machine translation AI to provide instant translation of hearings, helping non-native speakers understand proceedings.

Dispute Resolution

Pilot programs in Estonia and some U.S. jurisdictions explore AI-assisted dispute resolution for small claims or traffic fines, with algorithms recommending outcomes for human review.

Courts worldwide are adopting AI to reduce backlogs and improve judicial efficiency

At the same time, the rise of AI in justice has prompted serious discussions about ethics and oversight. Judges and legal experts stress that AI should support, not supplant, judicial decision-making. A vivid example of the pitfalls came when a few lawyers attempted to submit briefs full of AI-generated citations that turned out to be nonexistent cases – an incident that wasted court time and led to sanctions. High-ranking judges have warned that misuse of AI, such as unchecked reliance on AI outputs, could undermine public confidence in the justice system.

Critical safeguard: This has spurred efforts to establish clear guidelines. UNESCO released new international guidelines for AI in courts in late 2025 to help judiciaries adopt AI in an ethical, human-rights-respecting way. These guidelines emphasize principles like transparency, data security, auditability of AI systems, and the necessity of human oversight on all AI-informed decisions. The goal is to harness AI's benefits (speed, consistency, data insight) while safeguarding fairness, accountability, and the human element fundamental to justice.

In summary, AI's application in courts is still in early stages but shows great promise in tackling systemic challenges like case backlog and access to information. Whether through AI assistants drafting judicial documents or automated tools handling administrative tasks, the potential to deliver justice more efficiently is being tested worldwide. As we integrate these technologies, it's reassuring to see the global legal community actively shaping frameworks to ensure AI strengthens rather than undermines the rule of law. The coming years will likely see more courts adopting AI for mundane tasks and data analysis, always with a judge's watchful eye providing the final say.

Notable AI Tools for Legal Professionals

As AI permeates the legal industry, a variety of specialized tools and platforms have emerged. Below is a list of notable AI tools and applications in the legal field (global in scope), each helping lawyers and legal organizations in different ways:

Available Resources

5 items

Lexis+ AI

AI-powered legal research & drafting tool

Application Information

Developer	LexisNexis (a RELX company)
Supported Platforms	Web-based platform Desktop browsers (Windows, macOS) Tablet browsers
Language & Availability	Primarily English; available in the United States and selected jurisdictions where LexisNexis content is licensed
Pricing Model	Paid subscription required; limited trials may be available for eligible organizations

Overview

Lexis+ AI is an advanced AI-powered legal research and drafting platform built into the Lexis+ ecosystem by LexisNexis. It combines authoritative legal content with generative AI to help legal professionals research faster, draft with confidence, and analyze documents more efficiently. Designed for attorneys, law firms, and in-house legal teams, Lexis+ AI enables users to ask legal questions in natural language and receive context-aware, citation-supported results grounded in trusted primary and secondary legal sources.