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The legal industry has reached an inflection point with artificial intelligence. While AI is still in the early stages of adoption, forward-thinking firms are embracing automation to work smarter and deliver more value to clients. The rise of AI in law is being driven by several key factors.
First, clients are demanding efficiency. Corporate legal departments face increasing pressure to control costs and get the most bang for their buck from outside counsel. AI tools that speed up legal work and reduce billing hours are thus highly attractive to clients.
Second, the explosion of data in discovery and due diligence is overwhelming lawyers. Technology assisted review using AI algorithms can find relevant information in large datasets faster than human eyes ever could. This makes AI essential for handling document-heavy litigation or M&A deals.
Third, AI excels at pattern recognition and prediction. Identifying risks in contracts, predicting case outcomes, surfacing insights from data - these high-value analytics expand the toolkit of legal services. Clients appreciate counsel that leverages data and technology strategically.
According to one industry survey, over 50% of AmLaw200 firms are already using AI for tasks like legal research, document review, and data analysis. The early adopters are seeing clear benefits.
Latham & Watkins used Neota Logic's AI platform to automate elements of GDPR compliance for clients, reducing manual work by over 95%. Eversheds Sutherland employed Kira Systems machine learning to accelerate contract review time by 20-60%. And Wilson Sonsini Goodrich & Rosati developed an AI tool that quickly analyzes liquidation preferences in financing documents.
While AI is augmenting associates and partners today, the next wave of adoption will be new legal roles like "legal knowledge engineers" focused on maximizing technology. AI expertise will become an important differentiator for leading firms.
One of the most time-consuming aspects of legal work is poring over documents during discovery or due diligence. Associates can spend weeks manually reviewing thousands of contracts, emails, or other files page-by-page. Humans are prone to fatigue during such tedious tasks, which can lead to missed details. AI-powered document review platforms leverage machine learning algorithms to extract key information far faster than any team of lawyers could manage.
Kira Systems is one leading AI provider focused on contract analysis. Its software can be trained to identify standard and non-standard clauses in agreements, pull out important terms like pricing and liability, and flag areas of risk. What used to take junior associates days now happens within hours. This acceleration is crucial when dealing with tight deadlines in M&A deals. As Juan Chaparro, Director of Legal Operations at Takeda explained, "I don't have three weeks for due diligence. I need to get my hands on that information much faster."
For litigation, e-discovery tools like Logikcull utilize AI techniques like predictive coding to quickly filter huge document sets down to the most relevant ones. This shrinks the manual review workload by up to 80%. Lawyers can also use these intelligent platforms to uncover relationships between documents and gain unique insights. As Michael Mills of Neota Logic noted, "There are connections between documents that even the smartest humans would never see."
AI programs continuously improve through hands-on training. The more documents they process, the better they get at extraction and analysis. Firms thus build up valuable AI assets tailored to their needs. And associates are freed from the most monotonous tasks to focus on higher-level legal strategy.
Leading companies outside law are also adopting AI document review to great effect. Deloitte used an AI engine called Argus to analyze over a million accounting memos, reducing manual effort by 230,000 hours. And JP Morgan Chase developed COIN to review commercial loan agreements, learning from past deals to identify risky terms.
As enterprises grow, so does the mountain of contracts they must manage, ranging from vendor agreements to partnership deals. According to one estimate, Fortune 1000 companies handle over 40,000 contracts on average. Reviewing these dense legal documents thoroughly puts immense strain on legal teams. It also carries financial risk, as a single unnoticed clause could lead to liability down the road.
Automated contract analysis solutions leverage natural language processing and machine learning to extract key data points, analyze clauses, and highlight risks in seconds rather than hours. This accelerates review while reducing the chance of human error from fatigue or oversight. As Gabrielle Orum HernÃ¡ndez, VP of Legal Operations at Starbucks explained, "If we can use technology to leverage our time and energy more strategically, that's valuable."
Leading platforms like Kira Systems, eBrevia and LawGeex train algorithms on large sets of sample contracts to build domain expertise. From this, the AI learns to identify standard vs. non-standard terms, pull out salient details like pricing and liability caps, and evaluate risks in areas like dispute resolution and intellectual property. It goes far beyond simple keyword searches to deliver true comprehension. As one general counsel noted, "I don"t need a machine to find a word. I need it to read like a human."
The benefits for legal teams are multi-fold. Associates spend less time on routine contract reviews, freeing them to focus on high-value advisory work. Partners can delegate document analysis to AI and spend their time crafting negotiation strategy. Risk exposure is reduced through continuous automated monitoring of existing contracts. And analysis of past deals enables better commercial terms in future negotiations.
Beyond accelerating routine legal work, AI's pattern recognition capabilities allow it to derive unique insights from data that would elude human analysis. The vast volumes of information generated during discovery and due diligence processes contain value that firms have only begun to tap.
AI tools specializing in legal analytics can process millions of documents and identify correlations, trends and outliers that lawyers may miss, even after weeks of poring over the same material. These data-driven insights strengthen case strategy and settlement negotiation leverage.
As Connie Brenton, Chief of Staff at NetApp, commented, "Legal teams have access to a treasure trove of company data. AI lets you exploit that asset in ways not previously possible."
For example, Ravel Law mines PACER data and legal filings to predict litigation outcomes. Its AI analyzes variables likejudge history, damages awarded, procedural events and settlement rates to forecast win probability. This empirical perspective supplements lawyer intuition.
Other firms use AI-powered data analysis to size up opposing counsel and determine their usual tactics. By examining past cases and filings, the AI uncovers tendencies that lawyers can exploit during litigation.
In M&A, AI tools from companies like Kira Systems and LawGeex help assess value and risk by extracting insights across entire contract datasets. The AI can identify standard deal terms, evaluate negotiating history, and estimate potential liabilities. This high-level view informs better deal strategy and valuation.
Data-driven insights also aid in regulatory compliance. For financial firms, AI can analyze trading data to detect risky patterns and prevent fraud. In healthcare, AI examines patient records and treatment data to highlight compliance issues before they become HIPAA violations.
The global consultancy McKinsey & Company developed an AI tool called Musk that performs robust analysis of contracts, work orders and other documents. As McKinsey's Catrina Taylor stated, "Musk allows us to extract insights at a pace and depth not otherwise possible."
Law firms bill clients by the hour, so any tools that reduce hours spent on legal work directly translate to bottom line savings. AI automation is shrinking the man hours required for common tasks like contract review, document management, and basic litigation functions. Forward-thinking firms are embracing these technologies not only to boost efficiency, but also to deliver added value to clients through innovative services.
According to a survey by Clio, over 70% of lawyers report spending too much time on administrative tasks. Nearly half say this repetitive work saps time they could otherwise spend advising clients. AI legal assistants like Ross Intelligence's legal research robot and Thomson Reuters Contract Express for automated contract creation help trim the tedious hours associates log. Partners at firms using these tools estimate a 10-15% reduction in associate time spent per client matter. For a big litigation or transaction, that can equal hundreds of hours and tens of thousands in fees.
As Stacy Stern, General Counsel at Dow Jones, commented, "I love that I now get the same amount of legal work done for a lower price thanks to the AI assist." LawGeex founder Noory Bechor estimates that top firms using its AI platform for contract review can cut the grunt work in half, with 85% less time spent by junior associates. This boost in efficiency pleases cost-conscious clients.
AI also allows partners to delegate basic legal work and focus their expertise on high-level counseling. David Cambria, Global Operations Director of Legal Operations at Archer Daniels Midland, noted that "AI reduces the repetitive grunt work so lawyers can spend more strategic time with clients." Canadian firm McCarthy Tetrault assigns its AI legal assistant CLAIRE routine litigation tasks like document organizing and chronologies. This specialization lets associates prioritize strategy and client interactions.
A key benefit of AI in law is its ability to automate repetitive, low-value tasks like contract review and document management. This alleviates associates from the most tedious legal work, freeing them to focus on high-level strategy and client counseling. Clients today expect outside counsel not just to handle grunt work, but also provide strategic insights that drive legal and business goals. AI enables firms to move legal staff up the value chain and deliver what clients really want - strategic thinking.
According to Connie Brenton, Chief of Staff at NetApp, "The more we leverage tech, the more we can focus on strategy." AI tools handle the data extraction and analysis that used to occupy associates for days. Lawyers now use that time for client strategy sessions, scenario planning and settlement negotiations.
At Latham & Watkins, attorneys rely on machine learning for GDPR assessment and compliance monitoring. Partners estimate this saves over 100 hours per matter that can instead be allocated to strategic advice in areas like cross-border data transfers. Eversheds Sutherland's AI-based Data Privacy Adviser provides customized recommendations on privacy practices, freeing lawyers to craft tailored client guidance.
UnitedLex's litigation analytics platform helps firms quickly identify the strongest arguments by assessing past briefs and rulings. Attorneys gain data-driven insights to hone legal positioning from the start, instead of wading through documents. This proactive strategic focus resonates with clients. As Jim Michalowicz of UnitedLex stated, "Clients value lawyers who understand their business and bring ideas to the table."
AI also enables better alignment between legal strategy and business objectives. Neota Logic created an expert system for Johnson & Johnson that analyzes various risks and costs to recommend optimal paths for clinical trials. This model accounts for legal, regulatory and business concerns for holistic advice. Such tools help lawyers evaluate legal options through a business lens.
Forward-looking firms recognize AI as an investment in high-value capabilities rather than just cost savings. Partners redeploy time gained from AI into long-term firm assets like industry and client expertise, specialized practices, and tech fluency. These strategic capabilities differentiate firms as clients prioritize outside counsel that deliver both efficiency and foresight.
Automation makes space for innovation as well, as lawyers can pilot creative service offerings based on AI insights. For instance, Baker McKenzie now provides compliance risk analysis by running client data through its AI platform. UnitedLex and Davis Polk developed tools that predict litigation outcomes to inform settlement strategies. Without AI shoulders to stand on, few firms could explore such offerings.
The most strategic law firms will embrace emerging roles like legal knowledge engineers who specialize in maximizing AI. JD Match predicts new legal jobs like AI trainer, annotator, auditor and developer will rise. Firms able to attract top talent in these areas will maintain their strategic edge. AI natives who grow up embedded in technology will bring fresh strategic thinking.
The future promises ever-wider adoption of AI in the legal realm to drive greater efficiency, insight, and innovation. As AI capabilities grow more powerful and nuanced, few areas of legal work will remain untouched by automation and augmentation. The question forward-thinking firms must ask is not whether to use AI, but how best to integrate it across operations and services.
Leading companies in other industries provide a blueprint. Amazon leverages AI ubiquitously to predict demand, optimize logistics and tailor recommendations. Autodesk employs generative AI to automate repetitive design tasks so engineers can create and innovate. Likewise, legal AI has graduated from narrow applications like contract review into diverse use cases ranging from predictive analytics to automated drafting.
According to Bloomberg Law"s 2022 Legal Operations Survey, 71% of legal departments already use AI for tasks like discovery and due diligence. The plurality expects to expand AI over the next three years, with contract analysis, document automation and legal research emerging priorities. As Kent Butterfield, General Counsel of Qualcomm stated, "If you"re not looking at or using AI, you"re behind."
Law firms are wise to develop specialized AI tools tailored to particular practice areas and even individual clients. For example, Baker McKenzie created an AI engine exclusively for Mexican government procurement contracts. Such custom solutions deliver high value to clients. Partners should also strengthen core AI skillsets within their teams, as fluency in augmenting legal work with technology will soon be mandatory.
In the future, AI will move beyond supporting specific applications to being integrated directly into workflows and processes. UnitedLex"s Leo platform allows lawyers to access AI capabilities on demand to enhance thinking. Development of "smart" interfaces that contextually serve up relevant insights will minimize friction in legal work.