Which Law Firms Use AI? Case Studies From BigLaw to Solo Practices

Still wondering whether AI use in law firms is real or just marketing noise? 

While many articles discuss legal technology trends in general, this guide profiles specific firms that have publicly shared their AI implementation stories. It discusses the tools they use and the measurable outcomes they share.

This article features firms of varying sizes using various AI platforms across multiple practice areas. Rather than relying on abstract trends, the examples below draw on documented case studies, public announcements, and firm-reported outcomes.

Note: AI use varies significantly across firms, practice areas, and jurisdictions. The examples here represent public disclosures and may not reflect the full scope of each firm's technology strategy.

Key Takeaways

• Firms of all sizes (from solo practices to AmLaw 100) actively use AI with documented success. 
• Common AI applications are in contract drafting and review (Spellbook), legal research (CoCounsel and Lexis+), and workflow automation (Harvey AI). 
• Firms report time savings, increased matter capacity, and improved work-life balance for attorneys without expanding headcount or outsourcing core work.

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Jason Wiener P.C.: Social Enterprise Law Firm Scaling with Spellbook

Jason Wiener P.C. is a Colorado law firm specializing in social enterprises and employee ownership. As a small, specialized firm, they needed to operate as efficiently as larger competitors while staying sharp in niche areas, such as benefit corporation governance.

Jason Wiener P.C. uses Spellbook for contract drafting and review in its transactional practice. The firm's work involves benefit corporation governance documents, impact investment agreements, and stakeholder-focused contracts. 

By using Spellbook to handle first-pass drafting and issue spotting in Microsoft Word, the firm increased capacity without diluting its specialized expertise. This is a recurring theme in legal AI case studies: AI helps boutique firms compete on efficiency by cutting due diligence costs for repeatable contract work.

Key Takeaway: Boutique and specialized practices can leverage AI integration to scale services without compromising expertise.

Alturas Capital Partners: Investment Firm Legal Team Using Spellbook

The corporate legal department at Alturas Capital Partners supports the investment firm's operations. In-house teams face a distinct challenge: they support growing portfolios without hiring additional lawyers, expanding outside counsel spend, or slowing down deal execution as volume increases.

The Alturas legal team uses Spellbook to draft and revise transaction documents, customize lease and investment clauses, and finalize redlines during active negotiations. 

By keeping complex drafting in-house, the team shortened commercial lease negotiations from weeks to days and reduced outside counsel spend by hundreds of thousands of dollars. More recently, Spellbook Associate supports multi-step review tasks, such as identifying inconsistencies between individual leases and master agreements.

Key Takeaway: In-house teams and corporate legal departments use AI to reduce outside counsel spend and increase deal velocity. Spellbook enables lean teams to punch above their weight.

Cunningham Legal: Solo Practitioner Competing with Spellbook

Solo practitioners face unique constraints. You compete against larger firms with deeper benches, manage client work as well as your legal practice, and work within strict time limits. Before AI, capacity was the binding constraint. There are only so many hours in a day.

A lawyer at Cunningham Legal adopted Spellbook to directly address these challenges. He uses it to accelerate contract drafting, enabling him to handle more clients. 

AI-powered risk identification improves operational efficiency in ways that go beyond speed. It can help catch potential issues during the initial review that might otherwise surface later as costly disputes or malpractice risks.

The result is improved work-life balance by eliminating repetitive tasks. This allows lawyers to accept more time-sensitive contract matters without hiring additional staff or extending turnaround times.

Key Takeaway: Firm size doesn't limit AI's impact. In fact, small firms and solo users can achieve the fastest ROI and the greatest competitive gains.

A&O Shearman: First BigLaw Firmwide Harvey Deployment

Allen & Overy broke ground in 2023 as the first BigLaw firm to deploy Harvey AI firmwide. Following its 2024 merger to become A&O Shearman, the firm solidified this global deployment across its workforce of 7,000+ employees. Their use cases include contract analysis, multilingual drafting, and regulatory horizon-scanning. What's notable about A&O Shearman's approach is their accountability framework: every AI output is audited by humans. 

Key Takeaway: Global firms can scale AI by pairing it with a rigorous 'human-in-the-loop' audit framework.

Paul Weiss: Custom Harvey AI Workflow Builder

Paul Weiss, an elite AmLaw 50 firm, partnered with Harvey to develop custom AI workflows using Harvey's workflow builder platform. This customization allows Paul Weiss to embed their proprietary methodologies and best practices into AI-assisted processes. The workflows are tailored to the firm's complex transactional and litigation matters. This approach delivers competitive advantages as the firm can feature its AI-powered workflows in client pitches as a differentiator.

The "Workflow Builder" isn't fully autonomous. It includes "response blocks" and "checkpoints" where a lawyer must review the AI’s output before the workflow moves to the next stage. Lawyers can build workflows without writing code, enabling automation to scale quickly across different practice groups.

Key Takeaway: Rather than adopting generic solutions, firms customize AI tools to match their unique practices and client needs. Custom workflows preserve competitive advantages while gaining efficiency.

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Latham & Watkins: First-of-Its-Kind AI Academy

Latham & Watkins, an AmLaw 10 firm and one of the highest-grossing firms globally, launched AI Academy, a firmwide education program covering AI tools, ethical implications, disclosure requirements, and best practices. By making the training mandatory and providing "billable credit" for time spent learning, they removed the primary barrier to AI adoption in BigLaw: the pressure to prioritize billable client work over professional development.

Latham’s model is unique in combining centralized education with practice-specific workshops. A litigator learns AI tools for deposition prep while a corporate lawyer learns AI for cap table analysis, preventing the training from feeling like a generic 'one-size-fits-all' IT seminar.

The strategic rationale is clear: prepare the entire workforce for AI-augmented practice rather than leaving adoption to individual attorney discretion. This is deliberate change management that recognizes that technology adoption fails without proper training and cultural buy-in.

Key Takeaway: Successful AI adoption requires investment in training and change management, not just a technology purchase. Latham's Academy model shows how firms can systematically build AI capabilities across the entire organization.

Macfarlanes (UK): Custom "Amplify" AI Platform

Macfarlanes broke new ground in early 2025 by launching Amplify, a client-facing AI platform. While the firm achieved an internal adoption rate of over 80% for Harvey AI, Amplify represents a shift toward 'Legal-Product-as-a-Service.' It allows clients to access Macfarlanes' legal expertise through custom Harvey-powered workflows. For example, in-house teams can perform document interrogation and data extraction with the firm’s proprietary methodologies built in.

The platform combines Harvey's AI capabilities with Macfarlanes' institutional knowledge, creating a competitive advantage through proprietary AI implementation.

Key Takeaway: A specialist firm can use AI to create new revenue streams through building custom AI solutions on enterprise platforms. Macfarlanes shows how firms embed their expertise in AI tools rather than relying on generic capabilities.

Orrick, Herrington & Sutcliffe: Early CoCounsel Adopter

Orrick solidified its role as a legal tech pioneer through its foundational partnership with Casetext (now Thomson Reuters CoCounsel). As a lead beta tester and legal counsel to Casetext, Orrick integrated AI deep into its litigation and transactional practices. Beyond simple research, the firm uses 'agentic' AI workflows for high-volume document analysis. 

Their approach is defined by transparency; through their RegFi podcast and innovation events, they lead the industry dialogue on AI risk and ethical implementation, turning internal innovation into a distinct client-facing brand. 

Key Takeaway:  Orrick's willingness to beta-test new tools demonstrates a strategic approach to technology adoption and risk tolerance.

Wilson Sonsini Goodrich & Rosati: Proprietary "Neuron" AI System

Wilson Sonsini pioneered a 'firm-as-investor' model by partnering with Dioptra to launch Neuron, a proprietary technology platform. Unlike firms that simply license AI, Wilson Sonsini embedded its 60+ years of legal 'DNA' into custom agentic workflows that achieve a 92% accuracy rate in contract review. Most significantly, they have used this technology to move away from the billable hour, offering fixed-fee commercial contracting services. This transforms AI from a back-office efficiency tool into a client-facing revenue driver.

Key Takeaway: Tech-savvy firms can develop proprietary AI systems that serve both as internal efficiency tools and as client-facing products. Wilson Sonsini demonstrates that AI is a revenue generator, not just a cost-saver.

How AI Is Changing Law Firm Operations and Business Models

Regardless of differences in size and structure, several patterns emerge in how firms approach AI. None treats AI as autonomous or authoritative.

Across firm types and use cases, AI assists while lawyers decide. Firms avoid black-box automation, preferring systems where inputs and outputs remain transparent and reviewable.

AI also elevates junior attorney capabilities: juniors doing mid-level work and mids doing senior work helps shift firms away from strict hourly billing toward value-based pricing.

Tools that fit existing workflows, especially Word-native ones, see higher adoption rates. Firms report 10 to 40 percent increases in matter capacity per attorney and faster turnaround times (same-day rather than 2 to 3 days). 

The profiled case studies demonstrate measurable AI impact on revenue per attorney, improved realization rates, and fewer write-downs on routine work.

Why Spellbook is the Preferred Choice for Contract Work

Across the case studies, firms repeatedly chose Spellbook because it aligns with how transactional lawyers already work. Rather than forcing users to adopt new platforms or interfaces, lawyers draft, review, and redline without ever leaving Word. There's no learning curve. The balance of speed with accountability is why so many firms trust Spellbook for day-to-day contract work.

Spellbook also offers enterprise-grade security features that protect attorney-client privilege and confidentiality. These are critical concerns for any law firm considering AI adoption. 

Firms of all sizes, from solo practitioners to growing practices, successfully use Spellbook because it fits into existing workflows rather than requiring workflow redesign.

Join these firms and see why lawyers trust Spellbook for AI-powered contract work.

Frequently Asked Questions

What's the Typical Tmeline from AI Implementation to Seeing Results?

Most firms report increased lawyer productivity within the first 30 days. Full adoption and maximum efficiency are typically achieved in 60 to 90 days. ROI often appears within the first quarter, though timelines vary by firm size and change management. Larger firms with more structured rollouts may take longer to reach full utilization.

Do I Need to Be a Large Law Firm to Justify AI Investment?

No. Smaller firms often see faster ROI due to lower overhead. AI levels the playing field between small and large firms. A solo practitioner using Spellbook can compete on efficiency with a firm ten times their size.

Which Legal Practice Areas See the Most Significant Benefits from AI?

Transactional practices (contracts, M&A, real estate) can see immediate impact from AI drafting and review support. Litigation teams tend to benefit more from AI-assisted research and document analysis. In-house teams benefit from AI-enabled contract management and compliance work. Any high-volume document work is a good candidate.

How Do Law Firms Address Confidentiality and Privilege Concerns when Using AI?

Firms using Spellbook benefit from built-in security and private deployment environments. Firms using enterprise AI tools, such as Harvey and CoCounsel, have vendor agreements protecting confidentiality. The key is choosing enterprise-grade, legally compliant tools over free, public AI platforms. Proper vendor selection mitigates most risk.

What if My Partners Resist AI Adoption?

Show them this article: real firms getting real results. Many firms start with small pilots to demonstrate value. Focus on competitive necessity: clients increasingly expect AI-driven efficiencies, and early adopters gain a competitive advantage. Partner resistance often fades after they see documented results from peer firms.

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