There's a lot of hype and excitement regarding the use of AI in Biglaw. Harvey and Legora (mostly in Europe) seem to be leading the way for full-scale AI solutions, but Thomson Reuters, Lexis, and others have rolled out their own AI tools that augment their platforms. Harvey sits at an $8+ billion valuation, and Legora recently announced a $150 million Series C at a $1.8 billion evaluation. Importantly, several AmLaw 100 firms have signed on with these platforms. It seems that these aren't pilot programs anymore; they're becoming firm-wide implementations.

Here's what caught my attention though: despite all this investment, only about 20% of lawyers at major firms are regularly using their AI tools. This is an opportunity for those of us willing to experiment and learn.

What's Actually Changing in Our Daily Work

You've probably noticed that Lexis and Westlaw have been rolling out AI features pretty aggressively. What's interesting is how integrated these AI tools are becoming. Harvey users can now search both internal documents and external databases in one query.

The document review platforms are moving fast too. Relativity announced that by 2028, all new matters will need to use their cloud-based AI tools. Some of these platforms are hitting 96% accuracy rates in document review, which surprised me when I first saw those numbers (I'm still a bit skeptical).

AI is not going to revolutionize everything overnight, but I do think we're at an inflection point where learning these tools now, while they're still relatively new, could give you a real advantage. The firms that have committed to adoption are seeing utilization climb significantly, which suggests that once people start using these tools, they find them genuinely helpful.

The Reality: Challenges You Need to Know

Let's be clear-eyed about the current limitations:

Accuracy Concerns Remain Real

A 2024 benchmarking study revealed that Lexis+ AI produced incorrect information more than 17% of the time, while Westlaw's AI-Assisted Research hallucinated more than 33% of the time. Law librarians testing these platforms found that while all three major platforms (Lexis, Westlaw, Vincent AI) demonstrated competency in basic legal research, each showed distinct inconsistencies.

The Adoption Paradox

Even with the best intentions and significant investments, attorneys struggle to adopt new technology due to billable hour pressures. The early adopters, those "power users," represent a small percentage of attorneys in any firm.

But here's the key insight: Firms that have successfully integrated Harvey show utilization rates climbing from 33% to 69% within a year, with some reaching 93% by month 12. The firms that commit see exponential adoption.

Why This Matters for Lawyers (Especially Junior Associates)

Your Competitive Advantage

Here's what most people miss about legal AI: it doesn't require coding skills or technical expertise. It requires exactly what you already have: the ability to write clear, precise instructions and think through complex problems systematically. Prompting an AI effectively is essentially the same skill as drafting a clear research memo or explaining a complex issue to a client.

As a junior associate, you have something senior partners don't: the bandwidth to experiment and learn these tools while they're still emerging. You can take the time to figure out what works, develop best practices, and become your practice group's go-to person for AI implementation. That positioning matters more than you might think.

Your Strategic Playbook

1. Learn

The most important thing you can do right now is invest in learning how to implement AI in your workflow. Your firm probably offers more resources than you realize. Most firms have knowledge management and AI teams running regular trainings, and they're usually desperate for engaged participants who will actually use what they teach.

Don't stop with internal resources. If your firm uses Harvey, Lexis+ AI, or Westlaw's CoCounsel, reach out to their implementation teams. These vendors have dedicated client success people whose entire job is helping you get more value from their platforms. Schedule demos, ask for advanced training sessions, and push them to show you use cases specific to litigation. They want success stories to share with other clients, so they're often willing to spend significant time with motivated users.

The goal isn't to become a tech expert. It's to understand what these tools can and can't do, so you can spot opportunities to use them effectively in your practice. The more you experiment now, while expectations are still forming, the better positioned you'll be as these tools become standard.

2. Go Beyond Using ChatGPT as a Glorified Search Engine

Stop thinking of AI as a better search engine. Modern legal AI uses Retrieval Augmented Generation (RAG) technology that searches databases for relevant resources, then feeds both your prompt and identified resources to large language models. Understanding this architecture helps you craft better queries and know when to trust outputs. When you know the AI is pulling from actual case law databases rather than generating text from memory, you can write more specific queries that help the retrieval system find the right sources. You also know to be more confident in citations (which come from real retrieved documents) while remaining skeptical of any analysis that goes beyond what those sources actually say.

3. Focus on High-Value, Lower-Risk Applications

Start with these proven use cases:

  • Document Summaries: AI performs quite well at analyzing documents that you upload - you just need to be very specific with your instructions on what vantage of analysis you are seeking.
  • Administrative Work: Low risk and high value because admin tasks are annoying and associates usually can't bill that time. This could include time entries, annual reviews, conflict checks, and more.
  • Contract Analysis: Rapid comparison and extraction of key terms or clauses across document sets
  • Timelines: Automated timeline creation based on large sets of documents

4. Become the Bridge

Most attorneys struggle to adopt new technology and adapt to change due to billable pressures. Position yourself as the translator between the innovation team and the litigation floor. This isn't about becoming a programmer; it's about understanding capabilities and limitations well enough to guide practical implementation.

Practical Next Steps

This Week:

  1. Audit your firm's AI tools: You probably have access to more than you realize
  2. Pick one low-stakes project: Try AI-assisted research on a pro bono matter, internal memo, or administrative task
  3. Document what works and what doesn't: Build your own playbook

This Month:

  1. Connect with your innovation team: They're likely looking for attorneys willing to pilot new tools
  2. Run a comparison test: Take a recent research task and try it both traditionally and with AI assistance
  3. Share your findings: Write an internal memo or present at a practice group meeting

This Quarter:

  1. Develop a specialty: Become the go-to person for AI-assisted privilege review or contract analysis
  2. Track your metrics: Document time savings and accuracy improvements
  3. Build your reputation: Present your successes to leadership

The Bottom Line

As Harvey's CEO notes, many tasks junior associates do will get automated, but that doesn't mean their jobs will; it means they'll be different jobs. The question isn't whether AI will transform Biglaw litigation (it already is). The question is whether you'll be driving that transformation or watching from the sidelines.

The firms investing billions aren't doing it for marginal improvements. They see a fundamental shift in how legal work gets done. The associates who understand both the promise and the pitfalls of these tools, who can bridge the gap between technical capability and legal judgment, will find themselves uniquely valuable.

Start small, experiment deliberately, and remember: in a profession that bills by the hour, the person who can deliver better results in less time doesn't become less valuable. They become indispensable.

What's your take? Are you seeing AI adoption accelerate at your firm? What barriers are preventing wider adoption? Feel free to reach out and share your experiences.