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The legal industry has long relied on tried and true methods for getting work done, but the rise of artificial intelligence is rapidly changing the game. Legal AI refers to the use of machine learning and natural language processing to automate legal tasks like contract review, document drafting, and legal research. While AI won't replace lawyers anytime soon, it is taking over many routine legal jobs, allowing attorneys to focus their skills and efforts on more meaningful work.
The breakthroughs in legal AI can be traced back to IBM's Watson technology, which first demonstrated an ability to understand natural language, generate hypotheses, and provide evidence-based recommendations. Researchers at Stanford and other universities soon realized AI's potential for analyzing legal documents. An early success was ROSS Intelligence, which uses natural language processing to answer legal research questions by combing through millions of pages of case law. ROSS can provide relevant citations faster than a junior associate digging through books in a law library.
Since those early days, investments in legal tech startups have skyrocketed, doubling between 2017 and 2019 to over $1 billion. Industry leaders predict legal AI could be deployed for 30% of legal work by 2030. Law firms have already adopted AI for e-discovery and due diligence, achieving productivity gains of 5-10x over human review. Contract review and analysis is another area seeing rapid AI adoption. LawGeex claims its AI platform can review business contracts 3x faster than lawyers with 95% accuracy. AI-powered solutions from Kira Systems, LegalSifter, and others make light work of mundane contract tasks.
While some fear AI will replace entry-level lawyers, experts say it will actually help young associates avoid drudgery so they can take on more interesting assignments. AI platforms like CaseText Carol and Evisort are making legal research faster and more thorough for all levels of attorneys. Forward-thinking firms understand AI's potential to enhance - not replace - the specialized skills and judgment of lawyers. They are actively training associates to incorporate legal AI into their workflows.
Document review represents one of the most time-consuming and tedious aspects of legal practice. Attorneys may spend weeks or months sifting through boxes of files, emails, and other evidence to identify relevant information for a case. The rise of electronically stored information (ESI) has exponentially increased the volume of documents lawyers must review. One estimate found discovery costs represent between 50-90% of total litigation expenses.
With such a burdensome task at hand, it's no wonder AI-driven eDiscovery tools have been warmly welcomed by many firms. Solutions like OpenText Magellan and DISCO use machine learning algorithms to quickly sort through documents, automatically tagging those most relevant to a case. This allows attorneys to focus their efforts on the subset of files most pertinent to legal strategy.
According to Casey Flaherty, principal at legal tech consultancy Procertas, "In some circumstances, contract review tools can classify more documents in an hour than a human can in a year." AI speeds up document review by continuously learning to recognize phrases and clauses of interest based on user feedback. For example, Beagle by Anaqua employs "active learning" to dynamically improve its contract analysis abilities. Lawyers simply confirm or correct Beagle's assessments, enhancing its skills over time.
Joe Kelly, advisor at legal AI firm Ross Intelligence, shared that "In one case, our attorneys had to review approximately a million documents. Using our AI tools, our team filtered this down to around 4,500 of the most relevant documents." This represents a 99% reduction in review workload. Such efficiency gains allow lawyers to focus on higher-value tasks like crafting legal arguments and strategy.
Contract review and analysis comprises a significant portion of many legal workflows. Yet poured over dense legal prose and highly negotiated terms is hardly the most stimulating task for most attorneys. Enter contract AI - natural language processing algorithms designed to digest contract terms and extract key data points.
Al-powered solutions can chunk through hundreds of pages in hours versus days or weeks for human reviewers. LawGeex claims its AI can review NDAs 3x faster than lawyers with 95% accuracy. Rapid turnaround enables firms to take on more clients and cases.
Unlike humans, algorithms won't get weary or distracted plowing through contract after contract. AI consistency results in fewer missed clauses or provisions. Kira touts its NDA analysis solution catches 18% more issues than human reviewers.
Improved Risk Management
AI tools like LinkSquares prominently flag high risk terms. This protects firms from liability by revealing potential compliance issues, indemnities, limitations of liability and other legal landmines before contract signing.
Today's contract AI excels at structured data extraction, neatly compiling names, dates, governing laws, termination clauses and other key info into reports and databases. Data extraction powers analytics on vendor relationships, contract health, and other insights.
By benchmarking against an enormous corpus of existing contracts and clauses, AI can instantly identify unusual or unfavorable terms for further attorney review. This prevents firms from unwittingly signing problematic agreements.
Rather than wholesale replacement, today's contract AI seeks to augment attorney skills and capacity. For example, Lawyaw uses AI to summarize agreements and highlight action items, providing associates a handy decision assist. attorneys retain control over final work product.
Legal research is the backbone of sound legal advice and strategy. Yet wading through volumes of case law and dense statutes to find the right precedents remains one of the most labor-intensive and fatigue-inducing components of an attorney's workload. Even the most seasoned lawyers risk overlooking relevant cases or misinterpreting a key provision late into the night before a filing deadline.
This is why AI-powered solutions aim to supercharge legal research with machine learning algorithms that identify ideal precedents and extract pinpoint answers from the vast corpus of existing law. As Matthew Berland, VP of sales from legal tech startup Blue J Legal noted, "We saw that legal research was ripe for innovation. Technology finally allowed us to organize the law into its logical structure so that AI could understand precedent the same way lawyers do."
By digitizing legal texts and training algorithms to extract relationships between fact patterns, rulings, and citations, AI legal research platforms build vast knowledge graphs. This enables them to analyze the impacts of previous rulings on new hypothetical fact patterns. While Computer Assisted Legal Research (CALR) solutions like Westlaw and LexisNexis rely on brute keyword searches that often yield incomplete results, AI takes legal reasoning to the next level.
For example, when attorneys ask a question of legal AI solution Clarilis, its algorithms mine a graph of over a billion US and EU legal concepts to generate a custom precedent brief to support its conclusions. The system even highlights the passages most relevant to the attorney's question within each precedent. Legal research that once took days or even weeks now takes minutes without the fatigue-induced oversights to which humans are prone.
As Zack Hutto, Innovation Counsel at Fenwick & West LLP described, "I tried sentence queries comparing a past case to a current case, and the CALR results were random...But with legal AI, I can instantly pull up a focused set of relevant cases." By staying apprised of emerging precedents and rapidly comparing them to new matters, attorneys gain confidence they have the strongest legal footing for arguments. AI frees up their time for more strategic aspects of case planning and advising clients.
Legal drafting is ripe for enhancement through AI. While attorneys pride themselves on crafting persuasive legal arguments, few relish spending hours wordsmithing contracts and other transactional documents. Enter solutions like LawGeex, Kira Systems, and Evisort that use natural language generation (NLG) to automate drafting and revision of all manner of legal prose.
Relieving Drafting Drudgery
Junior associates often find themselves saddled with routine legal drafting tasks like research memos, discovery responses, and basic contracts. This involves tedious cutting and pasting from templates followed by many rounds of proofreading - hardly the career that law students envision. AI-powered solutions like CaseText Compose promise to lift the burden of basic drafting and revisions, allowing associates to tackle meatier assignments.
Augmenting Human Drafting
Rather than full automation, today's legal drafting AI seeks to collaborate with attorneys. For example, ThoughtRiver employs supervised learning algorithms. It proposes draft language to users who provide feedback on which sections are on point and which need revision. Through these interactive loops, ThoughtRiver continuously refines its drafting abilities while still keeping the attorney in the driver's seat.
Speeding Document Turnaround
AI can generate an initial draft far faster than an attorney typing from scratch or trying to modify a template. This accelerates document completion. For things like sales contracts, AI wordsmithing shaves hours off turnaround. Fast document generation allows firms to handle a higher volume of transactional work.
Unlike humans, algorithms won't forget to include certain clauses or inadvertently introduce ambiguities when tired or rushed. AI adherence to templates and drafting rules enhances document consistency across an organization. This reduces risks from errors and omissions.
Many individuals and small businesses can't afford attorneys to handle routine legal documents. AI document creators like LegalZoom allow anyone to generate customized wills, contracts, and other documents online for a fraction of the cost. While attorney review is still recommended, AI makes basic legal drafting more accessible.
eDiscovery, the process of identifying and producing electronic information for legal cases, remains one of the most costly and time-intensive aspects of litigation. Yet the rise of AI-powered review tools promises to significantly streamline eDiscovery workflows.
According to Casey Flaherty, principal at legal tech consultancy Procertas, "In some circumstances, contract review tools can classify more documents in an hour than a human can in a year." By using machine learning to continuously improve its ability to identify relevant phrases and clauses, AI can plow through massive document sets far faster than human attorneys.
This offers huge time and cost savings compared to traditional manual review. Dera Nevin, director of discovery services and senior counsel at Promontory Financial Group, shared that "In one matter, the former way of doing things would have taken eight associates working eight hours a day, five days a week, for five months at a projected cost of $1.6 million. With predictive coding, it was two associates for two months at a cost of around $240,000."
Joe Kelly, advisor at legal AI firm Ross Intelligence, described another success story: "In one case, our attorneys had to review approximately a million documents. Using our AI tools, our team filtered this down to around 4,500 of the most relevant documents. This represents a 99% reduction in review workload."
Such dramatic efficiencies enable legal teams to handle more cases and accelerate time-to-trial. Nevin explained, "Where review used to be 70 percent of the budget and 70 percent of the time, now it represents 30 percent of the budget and 30 percent of the time."
Leading corporate legal departments are also waking up to AI-powered eDiscovery. Nicole Clark, discovery counsel at Apple, shared that their legal team uses predictive coding for the majority of second level reviews, allowing attorneys to focus on high-value strategic tasks.
Al algorithms offer more than just speed. Consistency and accuracy are also improved compared to fatigue-prone human reviewers. In one case, an AI system achieved a 97 percent recall rate in identifying relevant documents compared to only 74 percent for contract attorneys. Robert Keeling, partner at Sidley Austin LLP, remarked that "computers simply don"t forget what they have been taught."
Law firms have traditionally relied on armies of junior associates to handle routine legal tasks under the guidance of senior attorneys. Yet extracting the full value from these eager new recruits has never been easy. Associates fresh out of law school require close supervision, lest they miss important details or precedents that could undermine a case. Partners must constantly review associate work products and frequently end up re-doing shoddy first drafts. This ties up valuable partner time that would be better spent advising clients and developing strategy.
Enter AI solutions that allow attorneys to delegate repetitive legal tasks to algorithms rather than associates. For instance, products like Beagle and Kira were expressly designed to take on early-stage document review, surfacing only the most relevant files for attorney consideration. Partners can trust algorithms will thoroughly and consistently identify pertinent information.
Joe Kelly, Advisor at legal AI firm Ross Intelligence, explained how their Legal Research product frees associates from late nights down the rabbit hole of case law: "We had a junior associate spend three days researching an issue, only for a partner to determine the research was off-base and barely usable. Now we can have an associate frame an initial question then turn to our legal AI to generate the precedent brief in minutes. This allows associates to move on to more impactful work."
In this way, AI delegation enhances associate development and job satisfaction by focusing their efforts on assignments that build legal skills rather than burnout-inducing grunt work. As Kelly put it, "AI helps avoid throwing young lawyers into the deep end of the pool before they can swim."
Delegation to AI also facilitates collaboration between senior and junior attorneys. For example, Clarilis AI automatically highlights the most relevant passages of precedents to annotate generated briefs. Partners can review these AI "explanations" alongside associates, using them as teaching moments to hone associates" ability to identify meaningful arguments and judicial reasoning.
According to Zack Hutto, Innovation Counsel at Fenwick & West, enhanced delegation through AI allows his firm to "pendulum swing" routine work away from associates and onto technology so that associates get exposure earlier in their careers to sophisticated legal work. This transforms the role of associates from under-utilized legal researchers to valued members of client engagement teams.
As legal artificial intelligence continues maturing, forward-thinking law firms are not just incorporating AI into current workflows but proactively redesigning their workflows and organizational structures to fully leverage AI"s capabilities.
According to Mark Cohen, founder of Legal Mosaic consulting, "The confluence of pandemic, economic and technological change, and client pragmatism have accelerated wholesale changes in legal delivery and law firm workflow." Many firms are decentralizing traditional service delivery models optimized for brute force human capital rather than technology and collaboration.
For example, Reed Smith launched Gravity, an multidisciplinary group combining technologists, project managers, and lawyers. Gravity relies on task-specific AI applications and agile collaboration between professionals with complementary skill sets. This enhances the overall quality, speed, flexibility, and cost efficiency of services like contract analysis, IP review and litigation support. Gravity operates independently from fixed practice groups to facilitate fluid formation of customer-centric teams.
Littler Mendelson PC, the world"s largest employment and labor law firm, created a similar program called CASE (Compliance | Analytics | Strategy | Execution), integrating monitoring software, data analysts and attorneys to rapidly address client needs using technology-driven workflows. Their CASE Share product analyzes employment policies and handbooks across all locations and subsidiaries of an enterprise, flagging potential compliance issues and automatically generating standardized global employment templates.
According to Gloria Fuentes, Chief Innovation Officer at Littler, "Re-architecting workflow is about more than squeezing efficiency from current tasks. It"s about how we integrate emerging tech capabilities to add more value for clients."
The innovative workflow redesign extends beyond surface level deputization of discrete tasks to AI. As Conor McDonough, Chief Architect of Legal Solutions at iManage explained, forward-looking firms are "taking a holistic view across people, processes and technology to engineer more meaningful attorney experiences and client outcomes."