Artificial intelligence isn't just another fleeting trend—it's a seismic shift that's transforming the very nature of legal work. As we enter 2025, understanding AI's capabilities, limitations, and practical applications isn't optional; it's an absolute necessity. In this deep dive, we'll explore how AI is reshaping the legal landscape and what it means for your practice.

The AI Paradigm Shift

Consider the tools you rely on every day: Word, Outlook, Excel, Westlaw. Over the past decades, these have revolutionized legal practice, but they all share one key characteristic: they execute specific commands based on predefined rules. AI represents a dramatic departure because it can analyze, reason, and provide insights before taking action—much like a savvy associate who thoughtfully considers context and implications.

Traditional tools operate on straightforward logic, finding exact matches for citations or keywords. AI, by contrast, grasps context and nuance. When you search for "board duties in merger cases," keyword searches look for those precise words, while AI understands the concept and identifies relevant cases even when they use different terminology. This contextual understanding is game-changing across the entire legal workflow.

Key Concepts Every Lawyer Must Know

To harness AI effectively, it's crucial to understand several key concepts:

• “Generative AI” refers to AI systems that create entirely new content, rather than primarily analyzing or processing existing information. For example, in litigation, generative AI can draft original briefs or discovery requests tailored to the specific case at hand. It can also analyze vast troves of transcripts to surface potential contradictions, summarize themes, and identify credibility issues. On the transactional side, generative AI can produce first drafts of agreements based on a term sheet, compare agreement versions to identify and summarize substantive changes, analyze multilingual due diligence materials, and check for consistency across global document sets. In short, generative AI is unique in its ability to actually create new, customized work product that would typically require substantial attorney drafting and analysis time.

  
  

• Large Language Models (LLMs)" are exactly what their name suggests: AI systems trained on massive amounts of text data (Large), focused on understanding and generating human language (Language), and built in different variations each serving distinct purposes (Models). Much like vehicles optimized for specific needs, each model type excels at different legal tasks. Just as you wouldn't race a pickup truck or go off-roading in a sports car, different AI models are specialized for particular purposes - some built for rapid document review, others for intricate contract analysis or creative drafting. Crucially, these models can be fine-tuned on your firm's documents and precedents to supercharge their effectiveness.

  
  

• Ever wonder how AI processes text? The secret lies in “tokens” — the basic units of language, which may be words, word fragments, or even punctuation. Understanding tokens helps you work with AI more effectively, especially when handling complex documents or analyses.

  
  

• “Context windows,” which determine how many tokens (text) AI can process at once, are expanding at a remarkable rate. What began as a few pages' worth of text can now encompass entire agreements or multiple documents simultaneously—with rapidly improving capabilities to enable increasingly comprehensive analysis.

  
  

• “Hallucinations” occur when AI confidently generates incorrect information, usually when asked about facts it can't access or verify, like citing a court decision it hasn't been trained on. Given the paramount importance of accuracy in legal work, we'll take a deep dive into managing and preventing AI hallucinations in a dedicated article.

Real-World AI: The LVMH-Tiffany Case Study

The landmark dispute between LVMH and Tiffany over their $16 billion merger during the height of COVID-19 offers demonstrates just how dramatically AI capabilities have evolved—and why staying current is absolutely critical.

In 2020, LVMH, the French luxury goods conglomerate, sought to back out of its agreement to acquire iconic American jeweler Tiffany & Co. for $16.2 billion. LVMH claimed that Tiffany had suffered a material adverse effect (MAE) due to the pandemic, allowing LVMH to terminate the deal under the MAE clause in the merger agreement. Tiffany countered that the pandemic fell under a carve-out to the MAE clause and sued to enforce the agreement.

The case hinged on the interpretation of the MAE clause, which essentially said:

• Tiffany suffering a material adverse effect on its business would allow LVMH to terminate the deal.

• However, general economic downturns, pandemics, and other broad risks would not count as MAEs and could not be used by LVMH to back out.

• The exception to this exception was if these events disproportionately affected Tiffany compared to other similar companies.

The actual MAE clause read as follows:

"'Material Adverse Effect' means any event that would reasonably be expected to have a material adverse effect on the business, financial condition, or results of operations of the Company; provided, however, that none of the following shall constitute a Material Adverse Effect:

(i) changes in general economic conditions;(ii) any epidemic, pandemic or disease outbreak (including COVID-19);

(iii) acts of war or terrorism;except to the extent that any such event has a disproportionate adverse effect on the Company relative to other industry participants."

Just months ago, asking AI "How would Delaware courts interpret this MAE provision?" would yield a generic overview of MAE clauses and deal termination rights, perhaps citing a few high-profile cases, as seen in this example output: Just months ago, asking AI "How would Delaware courts interpret this MAE provision?" would yield a generic overview of MAE clauses and deal termination rights.

The analysis is surface-level at best, providing no real insight into the specific LVMH-Tiffany deal or the unique language of their MAE clause. But ask that same question today, and the results are staggering, as illustrated in this current AI-generated analysis.

As you can see, the AI is now able to:

• Synthesize relevant Delaware case law on MAE provisions, identifying key principles and fact patterns most analogous to the LVMH-Tiffany dispute.

• Analyze the specific carve-outs in this provision (general economic changes, pandemics, etc.) in light of those precedents.

• Assess how the "disproportionate effect" language could be interpreted and might shift the analysis.

• Suggest additional questions or areas for further factual development to evaluate the strength of arguments on both sides (not reproduced above as the output was too long).

The difference is night and day. AI can now provide detailed, case-specific analysis that would have been unimaginable just months ago. It's not just summarizing general principles, but actually applying them to the unique facts and language of this particular deal.

And remember - this analysis comes from a general-purpose AI model, not one specifically trained for legal work. When an AI model is trained for that specific purpose, however, comprehensively analyzing agreements, reviewing case files, drafting and responding to discovery requests, are all well within the ambit of a model’s capabilities. With the right implementation and specialized legal AI solutions, this level of sophisticated analysis can be applied across your entire practice.

Perhaps even more significant than the specific output is the fact that you are now engaging in a substantive legal discussion about a nuanced issue with an AI, just as you would with a colleague. You may agree or disagree with the AI's analysis, but the very fact that you're having this kind of in-depth, back-and-forth dialogue about a complex MAE provision is a testament to how far the technology has come. It's no longer just a tool for simple tasks, but a thought partner capable of meaningfully engaging with the intricacies of legal reasoning.

The AI Transformation: Litigation, Transactions, and Beyond

From document review to depositions, contract drafting to due diligence, AI is making its mark across every practice area. Innovative firms are discovering new ways to leverage these tools for maximum impact.

In litigation, attorneys are using AI for:

• First-level document review completed in hours, not days

• Rapid identification of key documents

• Automated privilege log generation

• Deposition prep that cross-references all prior testimony

• Outline generation from vast case records

On the transactional side, AI is powering:

• Tailored first drafts generated from deal parameters

• Identification of missing or nonstandard clauses

• Rapid review of diligence materials

• Multilingual document analysis

• Consistency checks across global deal documents

The possibilities are endless: AI solutions can be tailored to specific practice groups, workflows, or partner preferences for unparalleled and flexible results. The key is pinpointing where AI can add the greatest value for your practice.

The Future of Law: AI Edition

Blink and you'll miss it: the legal sector's AI adoption skyrocketed from 19% in 2023 to a staggering 79% in 2024, with 53% of Am Law 200 firms investing in legal AI. This isn't about incremental efficiency gains—it's about remaining competitive in a world where the game is changing daily.

AI models considered cutting-edge just six months ago? They're table stakes now. Client expectations are evolving just as rapidly, with growing scrutiny of billing for tasks AI can handle deftly. The implications couldn't be clearer.

Seize the AI Advantage—Today

This isn't a gradual evolution that firms can adapt to leisurely, it's a tectonic shift happening in real time. The chasm between AI-powered and traditional practices is widening exponentially. Firms harnessing these tools thoughtfully are already reaping tremendous benefits.

But the flip side is equally crucial to recognize: attorneys and firms taking a wait-and-see approach risk rapidly falling behind. In an era when AI can complete complex tasks in a fraction of the time, clients will increasingly question the value of paying for hours of manual work. Forward-thinking firms are proactively addressing this challenge head-on, but those slow to adapt may soon find themselves at a competitive disadvantage, struggling to justify billable hours that AI can slash dramatically.

The good news? The technology is deployment-ready now. There's no need to wait for future breakthroughs or perfect solutions. The tools available today can transform your practice—if you're ready to embrace them. In a rapidly evolving landscape, fortune favors the bold.

How is your firm leveraging AI? What challenges or opportunities are you seeing? Connect with us on LinkedIn or Twitter to join the conversation and access exclusive AI resources. For personalized insights on implementing AI in your practice, visit advocacy-lab.com or contact us at hello@advocacy-lab.ai.

This article is part of Advocacy Lab's Deep Dive series on AI in legal practice. For more on the future of law, explore our suite of AI solutions and educational resources designed by lawyers, for lawyers.