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Discovery is one of the most labor-intensive and expensive aspects of litigation. Traditionally, attorneys and paralegals must spend countless hours reviewing documents, conducting interviews, drafting discovery requests, and compiling responses. This manual process is not only tedious, but prone to human error.
With the rise of AI technologies like natural language processing, document review and eDiscovery are being transformed. Algorithms can now analyze millions of documents in a fraction of the time it would take humans. This allows firms to handle more cases simultaneously and reduce the army of contractors often needed for major litigation.
According to Casey Flaherty, a lawyer and founder of Procertas, "In using AI, we"ve been able to reduce the amount of active human review on a matter from 25,000 hours to just 100 hours." Technologies like predictive coding also boost accuracy in identifying relevant materials. This improves the quality of discovery and decreases costs associated with producing irrelevant documents.
For David Hechler at Corporate Counsel, implementing AI led to radical time savings: "A review that originally would have required four months and a team of about 50 lawyers and paralegals now requires one month, with a team of 14." This allowed their firm to reduce headcount needs by over 70%.
Besides efficiency, AI can also make discovery less invasive and stressful. Services like Legito use AI to analyze public court documents and generate briefs, reducing the need for depositions. CEO Kim Taylor explains, "The trauma people go through in shareholder litigation is unnecessary. There are public filings to get details needed to plead a case." Avoiding depositions cuts costs and gives clients peace of mind.
While some fear AI may eliminate jobs, its automation of repetitive tasks allows lawyers to focus on higher-value work. Says Ben Allgrove of Baker McKenzie, "The biggest benefit is junior lawyers having more meaningful work. AI reduces the grunt process of reading hundreds of irrelevant documents." Freeing attorneys from this drudgery improves quality of life while letting them concentrate on nuanced legal analysis AI cannot match.
Legal research is the foundation of any case, but combing through statutes, precedents and filings takes attorneys an enormous amount of time. Traditionally, lawyers must painstakingly gather relevant sources, read and analyze them, and determine how they apply to the facts at hand. Not only is this manual process tedious, it's also prone to oversights that could weaken the legal position.
With AI research tools, the grunt work of legal research is being automated to free up attorneys' time for higher-level tasks. Algorithms can rapidly analyze millions of documents, identify the most relevant precedents, and provide summarized briefings on their implications. This allows lawyers to get up to speed on case law exponentially faster. As Deborah Savadra, chief innovation officer at law firm Ice Miller, commented, "Instead of associates standing in front of a copier for four hours or staring at their monitors for days, technology like AI enables firms to redirect resources to more meaningful, impactful tasks."
Toronto-based Blue J Legal, founded by University of Toronto professor Benjamin Alarie, leverages machine learning algorithms to analyze legislation and past rulings. Their AI can then predict how a court is likely to decide on new cases, along with an explanation of the precedents and statutes supporting the outcome. This provides attorneys data-driven insights to buttress their positions instead of relying solely on intuition.
For startups and smaller firms without expansive legal libraries, AI offers affordable access to research capabilities previously out of reach. Casetext's CARA tool, built atop IBM Watson, reads through millions of legal documents to provide lawyers with only the most relevant sources for a particular case. It also asks clarifying questions if the research parameters are unclear. Says Casetext CEO Jake Heller, "We're making law dramatically more understandable through A.I."
One of the most time-consuming aspects of legal work is drafting the mountains of documents and briefs required for each case. Lawyers traditionally spend weeks manually creating custom contracts, settlement agreements, motions, memos and other case filings from scratch.
Now intelligent drafting tools are automating parts of the document creation process to save attorneys time. These AI solutions leverage natural language processing and machine learning to turn legal reasoning into written work product. While not yet advanced enough to fully replace human drafting skills, they aid lawyers by handling rote portions of documents.
Beagle.ai, built by lawyers at leading firm Latham & Watkins, streamlines drafting transactional documents like contracts. Users simply input deal terms and conditions into the platform. Beagle then instantly generates a complete draft agreement reflecting this input. According to Beagle's co-founder Andrew Rabens, "In a matter of seconds, you have a draft based on your deal terms." This exponentially accelerates creation of highly customizable contracts.
For Susan Nash, associate general counsel at Stanley Black & Decker, Beagle has been transformative: "It has easily saved me five to ten hours per week. As a result, I've been able to take on more work." The time savings allow her to focus energy on high-value tasks only humans can handle.
Allen & Overy's Fuse platform takes a similar approach for M&A deal documents like announcements and ancillary deeds. The AI uses deal terms to automatically generate ready-to-send drafts. This reduces document drafting from days to minutes in some cases.
Australian startup Luminance goes beyond drafting to analyze documents' contents using natural language processing. Their software reviews contracts and other materials to highlight key clauses, identify risks, and suggest edits to attorneys. This allows lawyers to rapidly validate that documents align with a client's interests before finalizing.
Analyzing the contents of legal documents like contracts is a complex, yet critical task. Attorneys must thoroughly review agreements to ensure favorable terms for their clients and identify any risks or loopholes. This traditionally requires meticulously combing through endless pages of dense legalese. Even the most diligent review is prone to overlooking key clauses in the sea of text.
With AI document analysis tools, machine learning algorithms can rapidly digest contracts' contents to assist human lawyers. They scan materials for anomalies, buried terms of interest, and evidence that could strengthen or weaken a client's position. This augments attorneys' capacity to validate legal documents align with a deal's parameters and their client's interests.
Kira Systems, founded by a team of University of Toronto professors, employs AI to analyze business contracts. Their software reads agreements to extract key information like termination clauses, jurisdictions, and liability limits. It also flags unusual terms compared to similar contracts it has reviewed. Kira's algorithms learn to identify risks and opportunities from past document analysis experience.
According to Kira CEO Noah Waisberg, "We find strange clauses that humans would never find. The AI spots hundreds of things lawyers don't see because they have blinders on." This empowers attorneys to negotiate improved terms and avoid pitfalls that may haunt clients down the road.
For multinational engineering firm AECOM, adopting Kira led to major efficiency gains in reviewing their 17,000+ active contracts. AECOM's legal chief counsel Peter Meier explained: "Our lawyers have about 25-50 percent more time. They can now get contracts reviewed, signed and recorded much faster." Besides speed, he reported Kira boosted contract quality as lawyers now carefully scrutinize novel terms flagged by the AI.
LawGeex takes a similar approach, using NLP algorithms to review business contracts for issues like missing clauses, vague terminology, and conflicts with prior agreements. Their software analyzes documents in seconds versus the hours it takes lawyers. It also constantly learns to identify risks from past reviews, improving over time.
The ability to forecast how a judge or jury will decide a case is invaluable in litigation. Traditionally, lawyers rely on intuition from past experience to predict outcomes. However, this leaves much to chance. Even seasoned attorneys can make faulty assumptions that undermine cases. Now, AI is bringing data-driven insights to outcome prediction.
By analyzing troves of past rulings, AI tools can identify patterns in how different judges rule on various issues. This allows them to provide statistics-backed probability assessments for upcoming case decisions. Attorneys can leverage these AI predictions to tailor legal strategies and arguments to a judge's leanings.
One pioneer in legal outcome forecasting is startup Lex Machina. Lex Machina's algorithms mine data from over one million court documents to predict outcomes and timelines for cases in areas like patent and antitrust law.
For high-stakes cases, accuracy is everything. LawGeex CEO Noory Bechor explained how AI outcome analysis influenced strategy for a major pharma patent dispute: "We changed our whole approach after the judge-specific analytics showed a 100% historic rate siding with generic manufacturers." By predicting the likely pro-generic ruling, the legal team adjusted arguments versus relying on past experience arguing before other judges.
Outcome analysis is also vital in planning appeals. After an unfavorable judgment, Ravel Law's AI pores over the judge's past decisions to assess if an appeal is worthwhile. Says Ravel Law's Monica Bay, "Lawyers may say, 'let's appeal it.' Our technology allows them to see new factors, such as the history of appeals from this judge. The data may show it's not worth the time and expense if the judge's rulings are rarely overturned."
E-discovery, short for electronic discovery, is one of the most vital yet painstaking steps in litigation. It involves identifying, collecting, and reviewing electronic materials relevant to a legal case. Traditionally, attorneys and paralegals must sort through enormous volumes of emails, texts, audio files, social media posts, and other digital documents to isolate evidence. This manual review process is incredibly time-consuming, as modern cases often have hundreds of thousands of documents from multiple sources. It is also prone to human error that can lead to missing key evidence or exposing irrelevant materials.
Now AI is transforming e-discovery by automating parts of the process to boost speed and accuracy. Algorithms can rapidly filter datasets to isolate materials likely to contain relevant evidence based on keywords, metadata, dates, and people involved. This dramatically narrows down what documents require attorney review from say one million to only ten thousand " a 95% reduction. An Deloitte survey found this use of AI speeds document review tasks by over 70%. Faster review allows firms take on more cases without ballooning headcount.
Besides accelerating document review, AI also improves its precision. Predictive coding algorithms learn to flag documents that warrant inclusion as evidence based on past attorney feedback. This reduces mistakenly culling important materials that may decide a case. According to Casey Flaherty, a lawyer and founder of Procertas, "In using AI, we"ve been able to reduce the amount of active human review on a matter from 25,000 hours to just 100 hours." Higher precision cuts follow-up costs of supplementing discoveries.
For client Wiley Rein, implementing AI in e-discovery saved over 50% in outside counsel fees. Says Wiley Rein's Robert Bahu, "We no longer have 25 attorneys billing us on a weekly basis for document review." AI shrinks the army of outside lawyers needed for discovery. It also frees up internal resources for high-value tasks only humans can handle.
A fundamental tenet of the legal system is that all people should have access to legal services and representation, regardless of their financial means or social status. However, the high costs of legal help and confusing judicial processes often prevent underprivileged groups from exercising their rights. AI is increasing access to legal services to help close this justice gap.
By automating document generation, research, and other rote tasks, AI makes legal help more affordable. Traditional full-service representation requires lawyers billing hundreds of dollars an hour. Lower income individuals frequently cannot afford this, forcing them to represent themselves in complex legal proceedings. However, AI-powered legal tech tools like DoNotPay provide personalized legal help and document drafting at a fraction of the cost.
DoNotPay, created by Stanford undergraduate Joshua Browder, was originally designed to fight parking tickets. Drivers simply chat with the AI bot to generate appeal letters. The bot's success rate in overturning 300,000 fines sparked Browder to expand its services. Now, DoNotPay helps users with everything from flight refunds to asylum applications.
For those who can't afford a lawyer for housing disputes, DoNotPay's AI landlord negotiation service levels the playing field. As Browder explains, "I want to enable anyone to have that power, even if they don't have the money." By replacing costly attorney time with automated knowledge, people gain affordable access to legal resources previously out of reach.
Besides cost, confusing bureaucracy and paperwork often blocks people from accessing their rights. Here too, AI is helping cut through the red tape. Chicago's Cook County now uses AI to assist citizens filing for property tax appeals, which many struggled to complete alone. Users answer questions in plain English, which the algorithm translates to correctly formatted appeals documents.
Prior to implementing the AI tool, the county only heard 3,500 property tax appeals a year. Now with AI simplifying the process, appeals have surged to over 133,000. As the county's Fritz Kaegi summarized, "We are using technology to massively simplify a bureaucratic process and give people back time " the most precious resource." Removing bureaucratic obstacles helps open legal avenues to all.
Law firms have traditionally been conservative when it comes to adopting new technologies and ways of working. Many still operate much as they did decades ago - leveraging support staff for administrative tasks while attorneys focus on billable client work. However, AI and other emerging technologies are prompting forward-thinking firms to reimagine how they function. This tech-fueled shift promises to boost efficiency and quality while positioning firms for the digital future.
According to Deloitte"s 2022 Legal Management Consulting Outlook, 77% of law firms have increased technology investment since 2019. Much of this aims to supplement staff with AI that can automate repetitive tasks. LawGeex"s CEO Noory Bechor explained how AI solutions enable firms do more with less: "Any activity or process that is repetitive or manual, or that doesn"t require subjective human analysis, is ripe for automation."
Document review and drafting are prime examples. Beagle CTO Samir Rabia reported their AI drafting software cuts contract creation from 5 hours to 30 minutes. These time savings accumulate across cases, allowing firms to take on more work without expanding headcount. Says Rabia, "We"ve seen 50-70% increases in per-lawyer productivity."
By handling repetitive grunt work, AI also lets firms better utilize talent. Osborne Clarke"s UK managing partner Ray Berg commented: "AI won"t replace lawyers, but will allow us to focus on more meaningful work." Freeing lawyers from drudgery improves job satisfaction while directing their skills where clients get most value.
Many firms now integrate AI directly into workflows instead of separate support tools. Baker McKenzie"s Fuse and Eversheds Sutherland"s Kira were built atop the contract analysis platforms to simplify adoption. Ilya Kirshin of Kira Systems explained: "Integrating AI through existing interfaces drives higher and more consistent usage." Avoiding disruption eases change management.
Full integration also enables creative new service models. Eversheds Sutherland offers an "AI lawyer" providing clients predictive insights and documents instantly anytime. Ilya Kirshin believes such tech-powered accessibility is the future, saying: "Clients expect 24/7 availability. AI integration delivers this while managing firm resources efficiently."