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One of the most time-consuming aspects of legal work is drafting documents. Lawyers must carefully craft everything from contracts and briefs to motions and memos. This meticulous process often involves extensive research, careful wording, and multiple rounds of revisions. According to Clio"s 2021 Legal Trends Report, lawyers estimate spending over 8 hours on average to draft simple agreements.
With AI document automation, the time spent on drafting can be cut dramatically. Lawyers can create templates with blanks for names, dates, and other case-specific details. The AI will then automatically populate the templates to generate complete first drafts within seconds. This is a huge productivity boost compared to the traditional approach of starting from scratch each time.
At legal tech company LawGeex, their AI drafting engine reportedly reduces document creation time by up to 90%. It can generate customized NDAs, contracts, and other documents after asking a few quick questions. Lawyers simply review the draft, make edits where needed, and finalize the paperwork.
Los Angeles-based attorney Stacy Saetta described her experience with LawGeex for Above the Law: "It used to take me a minimum of 90 minutes to review, revise and finalize an NDA. With LawGeex, it takes me less than 10 minutes. The AI is shockingly good"I barely have to make any changes to the drafts it spits out."
Reviewing contracts is another area where AI can significantly boost efficiency for lawyers. Traditional contract reviews are hugely time-consuming, with attorneys painstakingly combing through every line and clause. Most law firms still rely on manual methods, charging hundreds of dollars per hour for associates and partners to scrutinize agreements.
Automated contract review tools like Kira Systems and LawGeex enable firms to speed up this process while reducing costs. Their machine learning algorithms are trained on thousands of contracts, learning to flag important clauses and highlight potential risks. For example, Kira boasts that it can accurately extract 150+ provisions from a 30-page commercial contract in about 60 seconds. This equates to a 50x speedup compared to a human lawyer!
The AI contract review platforms integrate directly with document management systems, allowing attorneys to quickly review the results rather than starting from scratch. The algorithms act like associates who instantly read and analyze contracts, pulling out the most important clauses for senior lawyers to examine. This allows experienced attorneys to focus their expertise only on the sections that require deeper human analysis.
According to Ashley Lipson, CEO of Balance Legal Capital, automated contract review tools have cut the time his firm spends on this process by over 90%. "Where it used to take three to five hours for an attorney to review a stack of contracts, now it takes approximately 15 minutes," he says. This dramatic time savings translates into lower costs for clients. AI review platforms charge a fraction of what law firms bill for manual reviews by associates.
Lawyersspend countless hours researching previous rulings that are relevant to their active cases. With millions of published opinions out there, identifying the most applicable precedents is like finding needles in a haystack. AI-powered legal research platforms accelerate this process by automatically surfacing the most relevant cases based on the facts and legal issues involved.
Ravel Law uses machine learning algorithms to analyze relationships between cases based on citations. Its visualization tools allow lawyers to see how a potential precedent fits within the broader landscape of case law. Attorneys can instantly pinpoint the most influential rulings that judges are likely to consider persuasive.
This prioritization saves huge amounts of time compared to manual research methods. As Rachel Bailey, an attorney at Akerman LLP commented on Ravel"s website, "I cannot imagine ever going back to practicing without it. The hours I save allow me to get more work done and focus my time on more productive tasks."
AI also helps surface precedents that lawyers may otherwise miss. Humans often anchor their research around known cases and established search queries. Algorithms powered by machine learning are not constrained by these biases. They analyze the language used in case descriptions and court documents to draw novel connections.
For example, Casetext's CARA A.I. scans through millions of cases to identify relevant rulings that do not show up in traditional keyword searches. As general counsel Lisa Lee puts it, "CARA often finds cases that I would likely have missed when doing my "human" research, but are actually highly relevant and persuasive. It enhances my work product for clients."
The Canadian legal research platform Blue J Legal goes even further by predicting how likely it is for a judge to rule in favor of precedents highlighted by its AI. This allows lawyers to focus on the cases that have the highest probability of convincing the court based on that judge's past rulings.
Electronic discovery, or e-discovery, is the process of identifying, preserving, collecting, preparing, reviewing, and producing electronically stored information (ESI) relevant to a legal case. With the exponential growth of data from emails, texts, social media, and other digital sources, e-discovery has become increasingly cumbersome for legal teams. AI is transforming this complex and labor-intensive process.
E-discovery software leveraging machine learning can rapidly analyze millions of documents to automatically tag relevant items. This eliminates the need for lawyers to manually sift through mountains of data, enabling them to focus on substantive legal analysis. The algorithms also continually improve through experience, speeding up document review over time.
According to legal technology expert Jason Baron, machine learning has reduced document review time by over 50% compared to traditional linear review at some law firms. Others report cutting e-discovery costs by up to 90% after adopting AI tools.
Israeli company Everlaw allows legal teams to continuously train its AI using judged documents from previous cases. Attorney Lisa Rickard notes that Everlaw's algorithms learned to separate key evidence from irrelevant items with over 90% accuracy after just one week of training. This represents a massive time savings compared to having lawyers manually code documents.
Disco Ediscovery provides similar time-saving AI functionalities tailored for lawyers. Its automatic document tagging immediately highlights hot documents most likely to be relevant to the case issues. This enables attorneys to instantly see and focus on the most important data.
According to Laura Kibbe, Disco's Chief Ecosystem Evangelist, one AmLaw 100 firm achieved a 95% reduction in document review time after deploying the platform. The company's managing partner described Disco as "magic" for massively increasing productivity.
For over a century, law firms have relied on hourly billing as the dominant model for charging clients. This familiar "billable hour" approach has attorneys account for time in six minute increments and invoice based on their hourly rates. However, as legal tech powered by AI transforms workflows, the limitations of hourly billing are becoming increasingly apparent. Forward-thinking firms are now shifting towards alternative fee arrangements better aligned with value delivery.
One of the biggest complaints about hourly billing is how it incentives inefficiency. Critics argue it motivates law firms to maximize hours and drag out work, rather than operate efficiently. As Bill Henderson, Professor of Law at Indiana University explains, "Because of hourly billing, the interests of law firms are directly opposed to their clients" interests." The more hours logged, the larger the invoices grow.
This misalignment manifests in the way attorneys approach their work. For example, a 2016 survey by Clio found that 46% of lawyers admitted to double billing and padding hours to inflate revenue. The hourly structure provides little incentive to leverage legal technology and AI capabilities when inefficient manual work generates more billable time.
However, fixed fees based on value delivered rather than hours billed better align law firm and client incentives. Clients care about resolving issues quickly and cost effectively. With flat fee arrangements, firms are motivated to work efficiently and leverage innovations like AI and automation. The quicker they can deliver results, the more profitable their fixed price engagements become.
This is a key reason AmLaw 100 firm Seyfarth Shaw now generates over 75% of revenues from alternative fee arrangements. As chair J. Stephen Poor remarks, "We align our interests with clients" interests. If we can solve a problem efficiently through legal technology innovation, that frees up time to take on more client work." He estimates efficiency gains from legal AI have boosted the firm's profits by about 20%.
Real-time transcription is emerging as a game-changer for legal depositions. This technology provides live text transcripts as the questioning unfolds. Attorneys can view the real-time transcript synced with audio or video recordings to quickly search, annotate, and analyze testimony. The immediate text availability boosts productivity compared to waiting days or weeks for traditional transcripts.
Real-time court reporting has existed for decades. However, recent advances in automatic speech recognition (ASR) technology have made this feasible using just audio recordings. For example, companies like Trint and Descript leverage machine learning to generate accurate live transcripts. Their algorithms train on massive datasets to understand legal terminology and jargon.
Matthew Baer, founder of]),' says Trint's real-time transcription was a revelation for his firm's deposition workflow. "Having the transcript appear in real-time, searchable and annotated, helped us quickly find key pieces of testimony and craft follow-up questions on the fly during the deposition itself. This really changed the game compared to needing to schedule a second deposition after finally receiving a transcript weeks later."
According to Heather Clauson of Littler Mendelson, real-time transcripts enable attorneys to be far more prepared and effective during depositions. "Instead of taking manual notes and hoping I captured the testimony correctly, I can search the transcript and immediately reference exactly what was said. I can also highlight, tag and annotate key statements I want to revisit."
Descript"s audio-synced transcripts take this a step further by allowing lawyers to edit text and audio together. They can delete filler words, fix mistranscriptions, add notes, and create highlights without changing the original audio. This streamlines the process of clipping and sharing impactful deposition clips with colleagues or court.
Third-party legal transcription platforms like GoTranscript and rev.com also advertise fast turnarounds for deposition transcripts. However, those still involve a delay waiting for the files. Real-time ASR solutions eliminate such lag.
The immediacy provides strategic advantages that can shape a case's outcome. Quick analysis of testimony may reveal opportunities to explore further through follow-up questions. Lawyers can immediately identify potential contradictions or inconsistencies to address before the witness leaves.
According to litigation support company OnLine Legal, real-time transcripts lead to more focused depositions by allowing lawyers to continuously review and evaluate the proceedings as they happen. Attorneys can adapt lines of inquiry dynamically rather than just working from pre-planned questions.
The searchability of real-time transcripts also creates efficiency gains. Finding and revisiting specific exchanges is exponentially faster than combing through audio or video. Transcripts are far easier to skim than recordings.
Matthew Baer says this enables his firm to skip time-consuming deposition review meetings. "Rather than needing to rewatch recordings, attorneys can instantly pull up excerpts from the searchable transcript to discuss, dissect and plan next steps."
For clients concerned about deposition costs, the improved productivity translates into smaller invoices. Less time is wasted on administrative tasks like transcript reviews and scheduling follow-ups. The streamlined workflow allows attorneys to get the information they need faster.
Legal analytics powered by artificial intelligence are transforming how attorneys assess the likelihood of success for cases. Predictive analytics examine variables like past rulings, judge and attorney tendencies, and case characteristics to forecast outcomes. This data-driven approach to case strategy minimizes surprises and allows lawyers to set client expectations accurately.
Lex Machina pioneered legal analytics for intellectual property litigation. Its database covers over 130,000 IP cases, 2,600 attorneys, and 630 judges. Algorithms analyze this robust dataset to predict timelines, damages, findings, and more based on case specifics. The platform boasts that it can forecast injunction outcomes with over 70% accuracy.
Managing partner Owen Byrd describes how data-driven insights guide case strategy for his firm, Lex Machina"s parent company LexisNexis. "We leverage the platform"s predictive analytics to understand what a reasonable settlement range should be based on similar cases. It helps us have productive settlement discussions armed with data rather than just relying on instincts."
Premonition takes a similar data science approach to predict outcomes across various practice areas. It applies machine learning to millions of legal documents and docket entries to generate success likelihood forecasts. Premonition"s algorithms examine connections between attorneys, judges, parties, and facts to calculate "win predictions".
Startup Case Crunch Analytics goes a step further by quantifying the statistical correlations between specific evidence and rulings. Its another-generation AI analyzes millions of lines of case text to determine which evidence types have the biggest impact. This helps attorneys emphasize the most influential arguments and evidence when briefing cases.
According to Casetext CARA product lead Jack Russi, "CARA"s citation analysis algorithms uncovered that California state cases were 7 times more likely to be cited by the appeals court than federal precedent. This insight was key for structuring our legal arguments."
Legal tech company Ravel Law puts a visual spin on data analytics. Its "Outcome Prediction" tool generates interactive maps illustrating the influences and relationships driving a judge"s past rulings. Attorneys gain data-backed insight into judicial tendencies to inform case strategy and arguments.
Laura Safdie, division lead at litigation firm Haight Brown & Bonesteel LLP, remarks: "Ravel"s outcome analysis gave our team critical data predicting which arguments would resonate with the judge based on their unique decision patterns. We could tailor our motion accordingly, improving our chances of success."
The rise of artificial intelligence is transforming how legal services are delivered. One area seeing rapid adoption is legal chatbots - AI-powered platforms that provide basic legal assistance through conversational interfaces. Rather than replacing lawyers, these virtual legal assistants are making legal help more accessible and affordable for everyday issues.
A common use case is enabling visitors to quickly get answers to common legal questions on a law firm's website 24/7. Russia-based AI startup DoNotPay offers a Facebook Messenger bot that has handled over 2 million user queries on topics like flight compensation, credit card disputes, and landlord negotiations. Users describe conversations with the bot feeling like chatting with a real lawyer.
According to CEO Joshua Browder, the natural language processing algorithms powering DoNotPay's chatbot were trained on thousands of legal documents to understand questions and mimic a lawyer's responses. For simple legal matters, the self-service Q&A experience empowers people to get help whenever needed without having to wait for office hours or schedule consultations.
Chatbots are also making legal processes like incorporating a business more efficient. Estonia-based LegalRobot allows entrepreneurs to create customized articles of incorporation and other company registration documents through a conversational interface. Users answer questions about their business needs, which the AI uses to automatically generate tailored legal paperwork. Founder Artjom Kats says this guided Q&A streamlines registrations that previously required hours of legal work.
Within law firms, chatbots are automating client intake processes to save time. Kira Systems' Client Intake solution asks potential clients diagnostic questions about their needs and situation. The natural language processing algorithms analyze responses to assess case details, determine legal issues involved, and recommend appropriate lawyers or practice groups. Attorneys instantly receive vetted intakes rather than having to screen inquiries themselves.
According to LawGeex VP Amber Anand, their client onboarding chatbot creates significant efficiency gains by automatically collecting all necessary information from new clients to begin drafting engagement letters. Rather than playing phone or email tag, the conversational AI obtains details like names, company info, and scope of work within minutes. This allows attorneys to focus on providing legal advice versus administrative tasks.